Age Owner Branch data TLA Line data Source code
1 : : /*-------------------------------------------------------------------------
2 : : *
3 : : * nodeAgg.c
4 : : * Routines to handle aggregate nodes.
5 : : *
6 : : * ExecAgg normally evaluates each aggregate in the following steps:
7 : : *
8 : : * transvalue = initcond
9 : : * foreach input_tuple do
10 : : * transvalue = transfunc(transvalue, input_value(s))
11 : : * result = finalfunc(transvalue, direct_argument(s))
12 : : *
13 : : * If a finalfunc is not supplied then the result is just the ending
14 : : * value of transvalue.
15 : : *
16 : : * Other behaviors can be selected by the "aggsplit" mode, which exists
17 : : * to support partial aggregation. It is possible to:
18 : : * * Skip running the finalfunc, so that the output is always the
19 : : * final transvalue state.
20 : : * * Substitute the combinefunc for the transfunc, so that transvalue
21 : : * states (propagated up from a child partial-aggregation step) are merged
22 : : * rather than processing raw input rows. (The statements below about
23 : : * the transfunc apply equally to the combinefunc, when it's selected.)
24 : : * * Apply the serializefunc to the output values (this only makes sense
25 : : * when skipping the finalfunc, since the serializefunc works on the
26 : : * transvalue data type).
27 : : * * Apply the deserializefunc to the input values (this only makes sense
28 : : * when using the combinefunc, for similar reasons).
29 : : * It is the planner's responsibility to connect up Agg nodes using these
30 : : * alternate behaviors in a way that makes sense, with partial aggregation
31 : : * results being fed to nodes that expect them.
32 : : *
33 : : * If a normal aggregate call specifies DISTINCT or ORDER BY, we sort the
34 : : * input tuples and eliminate duplicates (if required) before performing
35 : : * the above-depicted process. (However, we don't do that for ordered-set
36 : : * aggregates; their "ORDER BY" inputs are ordinary aggregate arguments
37 : : * so far as this module is concerned.) Note that partial aggregation
38 : : * is not supported in these cases, since we couldn't ensure global
39 : : * ordering or distinctness of the inputs.
40 : : *
41 : : * If transfunc is marked "strict" in pg_proc and initcond is NULL,
42 : : * then the first non-NULL input_value is assigned directly to transvalue,
43 : : * and transfunc isn't applied until the second non-NULL input_value.
44 : : * The agg's first input type and transtype must be the same in this case!
45 : : *
46 : : * If transfunc is marked "strict" then NULL input_values are skipped,
47 : : * keeping the previous transvalue. If transfunc is not strict then it
48 : : * is called for every input tuple and must deal with NULL initcond
49 : : * or NULL input_values for itself.
50 : : *
51 : : * If finalfunc is marked "strict" then it is not called when the
52 : : * ending transvalue is NULL, instead a NULL result is created
53 : : * automatically (this is just the usual handling of strict functions,
54 : : * of course). A non-strict finalfunc can make its own choice of
55 : : * what to return for a NULL ending transvalue.
56 : : *
57 : : * Ordered-set aggregates are treated specially in one other way: we
58 : : * evaluate any "direct" arguments and pass them to the finalfunc along
59 : : * with the transition value.
60 : : *
61 : : * A finalfunc can have additional arguments beyond the transvalue and
62 : : * any "direct" arguments, corresponding to the input arguments of the
63 : : * aggregate. These are always just passed as NULL. Such arguments may be
64 : : * needed to allow resolution of a polymorphic aggregate's result type.
65 : : *
66 : : * We compute aggregate input expressions and run the transition functions
67 : : * in a temporary econtext (aggstate->tmpcontext). This is reset at least
68 : : * once per input tuple, so when the transvalue datatype is
69 : : * pass-by-reference, we have to be careful to copy it into a longer-lived
70 : : * memory context, and free the prior value to avoid memory leakage. We
71 : : * store transvalues in another set of econtexts, aggstate->aggcontexts
72 : : * (one per grouping set, see below), which are also used for the hashtable
73 : : * structures in AGG_HASHED mode. These econtexts are rescanned, not just
74 : : * reset, at group boundaries so that aggregate transition functions can
75 : : * register shutdown callbacks via AggRegisterCallback.
76 : : *
77 : : * The node's regular econtext (aggstate->ss.ps.ps_ExprContext) is used to
78 : : * run finalize functions and compute the output tuple; this context can be
79 : : * reset once per output tuple.
80 : : *
81 : : * The executor's AggState node is passed as the fmgr "context" value in
82 : : * all transfunc and finalfunc calls. It is not recommended that the
83 : : * transition functions look at the AggState node directly, but they can
84 : : * use AggCheckCallContext() to verify that they are being called by
85 : : * nodeAgg.c (and not as ordinary SQL functions). The main reason a
86 : : * transition function might want to know this is so that it can avoid
87 : : * palloc'ing a fixed-size pass-by-ref transition value on every call:
88 : : * it can instead just scribble on and return its left input. Ordinarily
89 : : * it is completely forbidden for functions to modify pass-by-ref inputs,
90 : : * but in the aggregate case we know the left input is either the initial
91 : : * transition value or a previous function result, and in either case its
92 : : * value need not be preserved. See int8inc() for an example. Notice that
93 : : * the EEOP_AGG_PLAIN_TRANS step is coded to avoid a data copy step when
94 : : * the previous transition value pointer is returned. It is also possible
95 : : * to avoid repeated data copying when the transition value is an expanded
96 : : * object: to do that, the transition function must take care to return
97 : : * an expanded object that is in a child context of the memory context
98 : : * returned by AggCheckCallContext(). Also, some transition functions want
99 : : * to store working state in addition to the nominal transition value; they
100 : : * can use the memory context returned by AggCheckCallContext() to do that.
101 : : *
102 : : * Note: AggCheckCallContext() is available as of PostgreSQL 9.0. The
103 : : * AggState is available as context in earlier releases (back to 8.1),
104 : : * but direct examination of the node is needed to use it before 9.0.
105 : : *
106 : : * As of 9.4, aggregate transition functions can also use AggGetAggref()
107 : : * to get hold of the Aggref expression node for their aggregate call.
108 : : * This is mainly intended for ordered-set aggregates, which are not
109 : : * supported as window functions. (A regular aggregate function would
110 : : * need some fallback logic to use this, since there's no Aggref node
111 : : * for a window function.)
112 : : *
113 : : * Grouping sets:
114 : : *
115 : : * A list of grouping sets which is structurally equivalent to a ROLLUP
116 : : * clause (e.g. (a,b,c), (a,b), (a)) can be processed in a single pass over
117 : : * ordered data. We do this by keeping a separate set of transition values
118 : : * for each grouping set being concurrently processed; for each input tuple
119 : : * we update them all, and on group boundaries we reset those states
120 : : * (starting at the front of the list) whose grouping values have changed
121 : : * (the list of grouping sets is ordered from most specific to least
122 : : * specific).
123 : : *
124 : : * Where more complex grouping sets are used, we break them down into
125 : : * "phases", where each phase has a different sort order (except phase 0
126 : : * which is reserved for hashing). During each phase but the last, the
127 : : * input tuples are additionally stored in a tuplesort which is keyed to the
128 : : * next phase's sort order; during each phase but the first, the input
129 : : * tuples are drawn from the previously sorted data. (The sorting of the
130 : : * data for the first phase is handled by the planner, as it might be
131 : : * satisfied by underlying nodes.)
132 : : *
133 : : * Hashing can be mixed with sorted grouping. To do this, we have an
134 : : * AGG_MIXED strategy that populates the hashtables during the first sorted
135 : : * phase, and switches to reading them out after completing all sort phases.
136 : : * We can also support AGG_HASHED with multiple hash tables and no sorting
137 : : * at all.
138 : : *
139 : : * From the perspective of aggregate transition and final functions, the
140 : : * only issue regarding grouping sets is this: a single call site (flinfo)
141 : : * of an aggregate function may be used for updating several different
142 : : * transition values in turn. So the function must not cache in the flinfo
143 : : * anything which logically belongs as part of the transition value (most
144 : : * importantly, the memory context in which the transition value exists).
145 : : * The support API functions (AggCheckCallContext, AggRegisterCallback) are
146 : : * sensitive to the grouping set for which the aggregate function is
147 : : * currently being called.
148 : : *
149 : : * Plan structure:
150 : : *
151 : : * What we get from the planner is actually one "real" Agg node which is
152 : : * part of the plan tree proper, but which optionally has an additional list
153 : : * of Agg nodes hung off the side via the "chain" field. This is because an
154 : : * Agg node happens to be a convenient representation of all the data we
155 : : * need for grouping sets.
156 : : *
157 : : * For many purposes, we treat the "real" node as if it were just the first
158 : : * node in the chain. The chain must be ordered such that hashed entries
159 : : * come before sorted/plain entries; the real node is marked AGG_MIXED if
160 : : * there are both types present (in which case the real node describes one
161 : : * of the hashed groupings, other AGG_HASHED nodes may optionally follow in
162 : : * the chain, followed in turn by AGG_SORTED or (one) AGG_PLAIN node). If
163 : : * the real node is marked AGG_HASHED or AGG_SORTED, then all the chained
164 : : * nodes must be of the same type; if it is AGG_PLAIN, there can be no
165 : : * chained nodes.
166 : : *
167 : : * We collect all hashed nodes into a single "phase", numbered 0, and create
168 : : * a sorted phase (numbered 1..n) for each AGG_SORTED or AGG_PLAIN node.
169 : : * Phase 0 is allocated even if there are no hashes, but remains unused in
170 : : * that case.
171 : : *
172 : : * AGG_HASHED nodes actually refer to only a single grouping set each,
173 : : * because for each hashed grouping we need a separate grpColIdx and
174 : : * numGroups estimate. AGG_SORTED nodes represent a "rollup", a list of
175 : : * grouping sets that share a sort order. Each AGG_SORTED node other than
176 : : * the first one has an associated Sort node which describes the sort order
177 : : * to be used; the first sorted node takes its input from the outer subtree,
178 : : * which the planner has already arranged to provide ordered data.
179 : : *
180 : : * Memory and ExprContext usage:
181 : : *
182 : : * Because we're accumulating aggregate values across input rows, we need to
183 : : * use more memory contexts than just simple input/output tuple contexts.
184 : : * In fact, for a rollup, we need a separate context for each grouping set
185 : : * so that we can reset the inner (finer-grained) aggregates on their group
186 : : * boundaries while continuing to accumulate values for outer
187 : : * (coarser-grained) groupings. On top of this, we might be simultaneously
188 : : * populating hashtables; however, we only need one context for all the
189 : : * hashtables.
190 : : *
191 : : * So we create an array, aggcontexts, with an ExprContext for each grouping
192 : : * set in the largest rollup that we're going to process, and use the
193 : : * per-tuple memory context of those ExprContexts to store the aggregate
194 : : * transition values. hashcontext is the single context created to support
195 : : * all hash tables.
196 : : *
197 : : * Spilling To Disk
198 : : *
199 : : * When performing hash aggregation, if the hash table memory exceeds the
200 : : * limit (see hash_agg_check_limits()), we enter "spill mode". In spill
201 : : * mode, we advance the transition states only for groups already in the
202 : : * hash table. For tuples that would need to create a new hash table
203 : : * entries (and initialize new transition states), we instead spill them to
204 : : * disk to be processed later. The tuples are spilled in a partitioned
205 : : * manner, so that subsequent batches are smaller and less likely to exceed
206 : : * hash_mem (if a batch does exceed hash_mem, it must be spilled
207 : : * recursively).
208 : : *
209 : : * Spilled data is written to logical tapes. These provide better control
210 : : * over memory usage, disk space, and the number of files than if we were
211 : : * to use a BufFile for each spill. We don't know the number of tapes needed
212 : : * at the start of the algorithm (because it can recurse), so a tape set is
213 : : * allocated at the beginning, and individual tapes are created as needed.
214 : : * As a particular tape is read, logtape.c recycles its disk space. When a
215 : : * tape is read to completion, it is destroyed entirely.
216 : : *
217 : : * Tapes' buffers can take up substantial memory when many tapes are open at
218 : : * once. We only need one tape open at a time in read mode (using a buffer
219 : : * that's a multiple of BLCKSZ); but we need one tape open in write mode (each
220 : : * requiring a buffer of size BLCKSZ) for each partition.
221 : : *
222 : : * Note that it's possible for transition states to start small but then
223 : : * grow very large; for instance in the case of ARRAY_AGG. In such cases,
224 : : * it's still possible to significantly exceed hash_mem. We try to avoid
225 : : * this situation by estimating what will fit in the available memory, and
226 : : * imposing a limit on the number of groups separately from the amount of
227 : : * memory consumed.
228 : : *
229 : : * Transition / Combine function invocation:
230 : : *
231 : : * For performance reasons transition functions, including combine
232 : : * functions, aren't invoked one-by-one from nodeAgg.c after computing
233 : : * arguments using the expression evaluation engine. Instead
234 : : * ExecBuildAggTrans() builds one large expression that does both argument
235 : : * evaluation and transition function invocation. That avoids performance
236 : : * issues due to repeated uses of expression evaluation, complications due
237 : : * to filter expressions having to be evaluated early, and allows to JIT
238 : : * the entire expression into one native function.
239 : : *
240 : : * Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group
241 : : * Portions Copyright (c) 1994, Regents of the University of California
242 : : *
243 : : * IDENTIFICATION
244 : : * src/backend/executor/nodeAgg.c
245 : : *
246 : : *-------------------------------------------------------------------------
247 : : */
248 : :
249 : : #include "postgres.h"
250 : :
251 : : #include "access/htup_details.h"
252 : : #include "access/parallel.h"
253 : : #include "catalog/objectaccess.h"
254 : : #include "catalog/pg_aggregate.h"
255 : : #include "catalog/pg_proc.h"
256 : : #include "catalog/pg_type.h"
257 : : #include "common/hashfn.h"
258 : : #include "executor/execExpr.h"
259 : : #include "executor/executor.h"
260 : : #include "executor/nodeAgg.h"
261 : : #include "lib/hyperloglog.h"
262 : : #include "miscadmin.h"
263 : : #include "nodes/nodeFuncs.h"
264 : : #include "optimizer/optimizer.h"
265 : : #include "parser/parse_agg.h"
266 : : #include "parser/parse_coerce.h"
267 : : #include "utils/acl.h"
268 : : #include "utils/builtins.h"
269 : : #include "utils/datum.h"
270 : : #include "utils/dynahash.h"
271 : : #include "utils/expandeddatum.h"
272 : : #include "utils/logtape.h"
273 : : #include "utils/lsyscache.h"
274 : : #include "utils/memutils.h"
275 : : #include "utils/syscache.h"
276 : : #include "utils/tuplesort.h"
277 : :
278 : : /*
279 : : * Control how many partitions are created when spilling HashAgg to
280 : : * disk.
281 : : *
282 : : * HASHAGG_PARTITION_FACTOR is multiplied by the estimated number of
283 : : * partitions needed such that each partition will fit in memory. The factor
284 : : * is set higher than one because there's not a high cost to having a few too
285 : : * many partitions, and it makes it less likely that a partition will need to
286 : : * be spilled recursively. Another benefit of having more, smaller partitions
287 : : * is that small hash tables may perform better than large ones due to memory
288 : : * caching effects.
289 : : *
290 : : * We also specify a min and max number of partitions per spill. Too few might
291 : : * mean a lot of wasted I/O from repeated spilling of the same tuples. Too
292 : : * many will result in lots of memory wasted buffering the spill files (which
293 : : * could instead be spent on a larger hash table).
294 : : */
295 : : #define HASHAGG_PARTITION_FACTOR 1.50
296 : : #define HASHAGG_MIN_PARTITIONS 4
297 : : #define HASHAGG_MAX_PARTITIONS 1024
298 : :
299 : : /*
300 : : * For reading from tapes, the buffer size must be a multiple of
301 : : * BLCKSZ. Larger values help when reading from multiple tapes concurrently,
302 : : * but that doesn't happen in HashAgg, so we simply use BLCKSZ. Writing to a
303 : : * tape always uses a buffer of size BLCKSZ.
304 : : */
305 : : #define HASHAGG_READ_BUFFER_SIZE BLCKSZ
306 : : #define HASHAGG_WRITE_BUFFER_SIZE BLCKSZ
307 : :
308 : : /*
309 : : * HyperLogLog is used for estimating the cardinality of the spilled tuples in
310 : : * a given partition. 5 bits corresponds to a size of about 32 bytes and a
311 : : * worst-case error of around 18%. That's effective enough to choose a
312 : : * reasonable number of partitions when recursing.
313 : : */
314 : : #define HASHAGG_HLL_BIT_WIDTH 5
315 : :
316 : : /*
317 : : * Estimate chunk overhead as a constant 16 bytes. XXX: should this be
318 : : * improved?
319 : : */
320 : : #define CHUNKHDRSZ 16
321 : :
322 : : /*
323 : : * Represents partitioned spill data for a single hashtable. Contains the
324 : : * necessary information to route tuples to the correct partition, and to
325 : : * transform the spilled data into new batches.
326 : : *
327 : : * The high bits are used for partition selection (when recursing, we ignore
328 : : * the bits that have already been used for partition selection at an earlier
329 : : * level).
330 : : */
331 : : typedef struct HashAggSpill
332 : : {
333 : : int npartitions; /* number of partitions */
334 : : LogicalTape **partitions; /* spill partition tapes */
335 : : int64 *ntuples; /* number of tuples in each partition */
336 : : uint32 mask; /* mask to find partition from hash value */
337 : : int shift; /* after masking, shift by this amount */
338 : : hyperLogLogState *hll_card; /* cardinality estimate for contents */
339 : : } HashAggSpill;
340 : :
341 : : /*
342 : : * Represents work to be done for one pass of hash aggregation (with only one
343 : : * grouping set).
344 : : *
345 : : * Also tracks the bits of the hash already used for partition selection by
346 : : * earlier iterations, so that this batch can use new bits. If all bits have
347 : : * already been used, no partitioning will be done (any spilled data will go
348 : : * to a single output tape).
349 : : */
350 : : typedef struct HashAggBatch
351 : : {
352 : : int setno; /* grouping set */
353 : : int used_bits; /* number of bits of hash already used */
354 : : LogicalTape *input_tape; /* input partition tape */
355 : : int64 input_tuples; /* number of tuples in this batch */
356 : : double input_card; /* estimated group cardinality */
357 : : } HashAggBatch;
358 : :
359 : : /* used to find referenced colnos */
360 : : typedef struct FindColsContext
361 : : {
362 : : bool is_aggref; /* is under an aggref */
363 : : Bitmapset *aggregated; /* column references under an aggref */
364 : : Bitmapset *unaggregated; /* other column references */
365 : : } FindColsContext;
366 : :
367 : : static void select_current_set(AggState *aggstate, int setno, bool is_hash);
368 : : static void initialize_phase(AggState *aggstate, int newphase);
369 : : static TupleTableSlot *fetch_input_tuple(AggState *aggstate);
370 : : static void initialize_aggregates(AggState *aggstate,
371 : : AggStatePerGroup *pergroups,
372 : : int numReset);
373 : : static void advance_transition_function(AggState *aggstate,
374 : : AggStatePerTrans pertrans,
375 : : AggStatePerGroup pergroupstate);
376 : : static void advance_aggregates(AggState *aggstate);
377 : : static void process_ordered_aggregate_single(AggState *aggstate,
378 : : AggStatePerTrans pertrans,
379 : : AggStatePerGroup pergroupstate);
380 : : static void process_ordered_aggregate_multi(AggState *aggstate,
381 : : AggStatePerTrans pertrans,
382 : : AggStatePerGroup pergroupstate);
383 : : static void finalize_aggregate(AggState *aggstate,
384 : : AggStatePerAgg peragg,
385 : : AggStatePerGroup pergroupstate,
386 : : Datum *resultVal, bool *resultIsNull);
387 : : static void finalize_partialaggregate(AggState *aggstate,
388 : : AggStatePerAgg peragg,
389 : : AggStatePerGroup pergroupstate,
390 : : Datum *resultVal, bool *resultIsNull);
391 : : static inline void prepare_hash_slot(AggStatePerHash perhash,
392 : : TupleTableSlot *inputslot,
393 : : TupleTableSlot *hashslot);
394 : : static void prepare_projection_slot(AggState *aggstate,
395 : : TupleTableSlot *slot,
396 : : int currentSet);
397 : : static void finalize_aggregates(AggState *aggstate,
398 : : AggStatePerAgg peraggs,
399 : : AggStatePerGroup pergroup);
400 : : static TupleTableSlot *project_aggregates(AggState *aggstate);
401 : : static void find_cols(AggState *aggstate, Bitmapset **aggregated,
402 : : Bitmapset **unaggregated);
403 : : static bool find_cols_walker(Node *node, FindColsContext *context);
404 : : static void build_hash_tables(AggState *aggstate);
405 : : static void build_hash_table(AggState *aggstate, int setno, long nbuckets);
406 : : static void hashagg_recompile_expressions(AggState *aggstate, bool minslot,
407 : : bool nullcheck);
408 : : static long hash_choose_num_buckets(double hashentrysize,
409 : : long ngroups, Size memory);
410 : : static int hash_choose_num_partitions(double input_groups,
411 : : double hashentrysize,
412 : : int used_bits,
413 : : int *log2_npartitions);
414 : : static void initialize_hash_entry(AggState *aggstate,
415 : : TupleHashTable hashtable,
416 : : TupleHashEntry entry);
417 : : static void lookup_hash_entries(AggState *aggstate);
418 : : static TupleTableSlot *agg_retrieve_direct(AggState *aggstate);
419 : : static void agg_fill_hash_table(AggState *aggstate);
420 : : static bool agg_refill_hash_table(AggState *aggstate);
421 : : static TupleTableSlot *agg_retrieve_hash_table(AggState *aggstate);
422 : : static TupleTableSlot *agg_retrieve_hash_table_in_memory(AggState *aggstate);
423 : : static void hash_agg_check_limits(AggState *aggstate);
424 : : static void hash_agg_enter_spill_mode(AggState *aggstate);
425 : : static void hash_agg_update_metrics(AggState *aggstate, bool from_tape,
426 : : int npartitions);
427 : : static void hashagg_finish_initial_spills(AggState *aggstate);
428 : : static void hashagg_reset_spill_state(AggState *aggstate);
429 : : static HashAggBatch *hashagg_batch_new(LogicalTape *input_tape, int setno,
430 : : int64 input_tuples, double input_card,
431 : : int used_bits);
432 : : static MinimalTuple hashagg_batch_read(HashAggBatch *batch, uint32 *hashp);
433 : : static void hashagg_spill_init(HashAggSpill *spill, LogicalTapeSet *tapeset,
434 : : int used_bits, double input_groups,
435 : : double hashentrysize);
436 : : static Size hashagg_spill_tuple(AggState *aggstate, HashAggSpill *spill,
437 : : TupleTableSlot *inputslot, uint32 hash);
438 : : static void hashagg_spill_finish(AggState *aggstate, HashAggSpill *spill,
439 : : int setno);
440 : : static Datum GetAggInitVal(Datum textInitVal, Oid transtype);
441 : : static void build_pertrans_for_aggref(AggStatePerTrans pertrans,
442 : : AggState *aggstate, EState *estate,
443 : : Aggref *aggref, Oid transfn_oid,
444 : : Oid aggtranstype, Oid aggserialfn,
445 : : Oid aggdeserialfn, Datum initValue,
446 : : bool initValueIsNull, Oid *inputTypes,
447 : : int numArguments);
448 : :
449 : :
450 : : /*
451 : : * Select the current grouping set; affects current_set and
452 : : * curaggcontext.
453 : : */
454 : : static void
2575 rhodiumtoad@postgres 455 :CBC 3166402 : select_current_set(AggState *aggstate, int setno, bool is_hash)
456 : : {
457 : : /*
458 : : * When changing this, also adapt ExecAggPlainTransByVal() and
459 : : * ExecAggPlainTransByRef().
460 : : */
461 [ + + ]: 3166402 : if (is_hash)
462 : 2837880 : aggstate->curaggcontext = aggstate->hashcontext;
463 : : else
464 : 328522 : aggstate->curaggcontext = aggstate->aggcontexts[setno];
465 : :
466 : 3166402 : aggstate->current_set = setno;
467 : 3166402 : }
468 : :
469 : : /*
470 : : * Switch to phase "newphase", which must either be 0 or 1 (to reset) or
471 : : * current_phase + 1. Juggle the tuplesorts accordingly.
472 : : *
473 : : * Phase 0 is for hashing, which we currently handle last in the AGG_MIXED
474 : : * case, so when entering phase 0, all we need to do is drop open sorts.
475 : : */
476 : : static void
3256 andres@anarazel.de 477 : 39654 : initialize_phase(AggState *aggstate, int newphase)
478 : : {
2575 rhodiumtoad@postgres 479 [ + + - + ]: 39654 : Assert(newphase <= 1 || newphase == aggstate->current_phase + 1);
480 : :
481 : : /*
482 : : * Whatever the previous state, we're now done with whatever input
483 : : * tuplesort was in use.
484 : : */
3256 andres@anarazel.de 485 [ + + ]: 39654 : if (aggstate->sort_in)
486 : : {
487 : 21 : tuplesort_end(aggstate->sort_in);
488 : 21 : aggstate->sort_in = NULL;
489 : : }
490 : :
2575 rhodiumtoad@postgres 491 [ + + ]: 39654 : if (newphase <= 1)
492 : : {
493 : : /*
494 : : * Discard any existing output tuplesort.
495 : : */
3256 andres@anarazel.de 496 [ + + ]: 39561 : if (aggstate->sort_out)
497 : : {
498 : 3 : tuplesort_end(aggstate->sort_out);
499 : 3 : aggstate->sort_out = NULL;
500 : : }
501 : : }
502 : : else
503 : : {
504 : : /*
505 : : * The old output tuplesort becomes the new input one, and this is the
506 : : * right time to actually sort it.
507 : : */
508 : 93 : aggstate->sort_in = aggstate->sort_out;
509 : 93 : aggstate->sort_out = NULL;
510 [ - + ]: 93 : Assert(aggstate->sort_in);
511 : 93 : tuplesort_performsort(aggstate->sort_in);
512 : : }
513 : :
514 : : /*
515 : : * If this isn't the last phase, we need to sort appropriately for the
516 : : * next phase in sequence.
517 : : */
2575 rhodiumtoad@postgres 518 [ + + + + ]: 39654 : if (newphase > 0 && newphase < aggstate->numphases - 1)
519 : : {
3249 bruce@momjian.us 520 : 117 : Sort *sortnode = aggstate->phases[newphase + 1].sortnode;
3256 andres@anarazel.de 521 : 117 : PlanState *outerNode = outerPlanState(aggstate);
522 : 117 : TupleDesc tupDesc = ExecGetResultType(outerNode);
523 : :
524 : 117 : aggstate->sort_out = tuplesort_begin_heap(tupDesc,
525 : : sortnode->numCols,
526 : : sortnode->sortColIdx,
527 : : sortnode->sortOperators,
528 : : sortnode->collations,
529 : : sortnode->nullsFirst,
530 : : work_mem,
531 : : NULL, TUPLESORT_NONE);
532 : : }
533 : :
534 : 39654 : aggstate->current_phase = newphase;
535 : 39654 : aggstate->phase = &aggstate->phases[newphase];
536 : 39654 : }
537 : :
538 : : /*
539 : : * Fetch a tuple from either the outer plan (for phase 1) or from the sorter
540 : : * populated by the previous phase. Copy it to the sorter for the next phase
541 : : * if any.
542 : : *
543 : : * Callers cannot rely on memory for tuple in returned slot remaining valid
544 : : * past any subsequently fetched tuple.
545 : : */
546 : : static TupleTableSlot *
547 : 12728155 : fetch_input_tuple(AggState *aggstate)
548 : : {
549 : : TupleTableSlot *slot;
550 : :
551 [ + + ]: 12728155 : if (aggstate->sort_in)
552 : : {
553 : : /* make sure we check for interrupts in either path through here */
2455 554 [ - + ]: 87441 : CHECK_FOR_INTERRUPTS();
2565 555 [ + + ]: 87441 : if (!tuplesort_gettupleslot(aggstate->sort_in, true, false,
556 : : aggstate->sort_slot, NULL))
3256 557 : 93 : return NULL;
558 : 87348 : slot = aggstate->sort_slot;
559 : : }
560 : : else
561 : 12640714 : slot = ExecProcNode(outerPlanState(aggstate));
562 : :
563 [ + + + + : 12728053 : if (!TupIsNull(slot) && aggstate->sort_out)
+ + ]
564 : 87348 : tuplesort_puttupleslot(aggstate->sort_out, slot);
565 : :
566 : 12728053 : return slot;
567 : : }
568 : :
569 : : /*
570 : : * (Re)Initialize an individual aggregate.
571 : : *
572 : : * This function handles only one grouping set, already set in
573 : : * aggstate->current_set.
574 : : *
575 : : * When called, CurrentMemoryContext should be the per-query context.
576 : : */
577 : : static void
3176 heikki.linnakangas@i 578 : 530376 : initialize_aggregate(AggState *aggstate, AggStatePerTrans pertrans,
579 : : AggStatePerGroup pergroupstate)
580 : : {
581 : : /*
582 : : * Start a fresh sort operation for each DISTINCT/ORDER BY aggregate.
583 : : */
621 drowley@postgresql.o 584 [ + + ]: 530376 : if (pertrans->aggsortrequired)
585 : : {
586 : : /*
587 : : * In case of rescan, maybe there could be an uncompleted sort
588 : : * operation? Clean it up if so.
589 : : */
3176 heikki.linnakangas@i 590 [ - + ]: 26914 : if (pertrans->sortstates[aggstate->current_set])
3176 heikki.linnakangas@i 591 :UBC 0 : tuplesort_end(pertrans->sortstates[aggstate->current_set]);
592 : :
593 : :
594 : : /*
595 : : * We use a plain Datum sorter when there's a single input column;
596 : : * otherwise sort the full tuple. (See comments for
597 : : * process_ordered_aggregate_single.)
598 : : */
3176 heikki.linnakangas@i 599 [ + + ]:CBC 26914 : if (pertrans->numInputs == 1)
600 : : {
2429 andres@anarazel.de 601 : 26878 : Form_pg_attribute attr = TupleDescAttr(pertrans->sortdesc, 0);
602 : :
3176 heikki.linnakangas@i 603 : 26878 : pertrans->sortstates[aggstate->current_set] =
2429 andres@anarazel.de 604 : 26878 : tuplesort_begin_datum(attr->atttypid,
3176 heikki.linnakangas@i 605 : 26878 : pertrans->sortOperators[0],
606 : 26878 : pertrans->sortCollations[0],
607 : 26878 : pertrans->sortNullsFirst[0],
608 : : work_mem, NULL, TUPLESORT_NONE);
609 : : }
610 : : else
611 : 36 : pertrans->sortstates[aggstate->current_set] =
2692 andres@anarazel.de 612 : 36 : tuplesort_begin_heap(pertrans->sortdesc,
613 : : pertrans->numSortCols,
614 : : pertrans->sortColIdx,
615 : : pertrans->sortOperators,
616 : : pertrans->sortCollations,
617 : : pertrans->sortNullsFirst,
618 : : work_mem, NULL, TUPLESORT_NONE);
619 : : }
620 : :
621 : : /*
622 : : * (Re)set transValue to the initial value.
623 : : *
624 : : * Note that when the initial value is pass-by-ref, we must copy it (into
625 : : * the aggcontext) since we will pfree the transValue later.
626 : : */
3176 heikki.linnakangas@i 627 [ + + ]: 530376 : if (pertrans->initValueIsNull)
628 : 264291 : pergroupstate->transValue = pertrans->initValue;
629 : : else
630 : : {
631 : : MemoryContext oldContext;
632 : :
1536 alvherre@alvh.no-ip. 633 : 266085 : oldContext = MemoryContextSwitchTo(aggstate->curaggcontext->ecxt_per_tuple_memory);
3176 heikki.linnakangas@i 634 : 532170 : pergroupstate->transValue = datumCopy(pertrans->initValue,
635 : 266085 : pertrans->transtypeByVal,
636 : 266085 : pertrans->transtypeLen);
3256 andres@anarazel.de 637 : 266085 : MemoryContextSwitchTo(oldContext);
638 : : }
3176 heikki.linnakangas@i 639 : 530376 : pergroupstate->transValueIsNull = pertrans->initValueIsNull;
640 : :
641 : : /*
642 : : * If the initial value for the transition state doesn't exist in the
643 : : * pg_aggregate table then we will let the first non-NULL value returned
644 : : * from the outer procNode become the initial value. (This is useful for
645 : : * aggregates like max() and min().) The noTransValue flag signals that we
646 : : * still need to do this.
647 : : */
648 : 530376 : pergroupstate->noTransValue = pertrans->initValueIsNull;
3256 andres@anarazel.de 649 : 530376 : }
650 : :
651 : : /*
652 : : * Initialize all aggregate transition states for a new group of input values.
653 : : *
654 : : * If there are multiple grouping sets, we initialize only the first numReset
655 : : * of them (the grouping sets are ordered so that the most specific one, which
656 : : * is reset most often, is first). As a convenience, if numReset is 0, we
657 : : * reinitialize all sets.
658 : : *
659 : : * NB: This cannot be used for hash aggregates, as for those the grouping set
660 : : * number has to be specified from further up.
661 : : *
662 : : * When called, CurrentMemoryContext should be the per-query context.
663 : : */
664 : : static void
665 : 147661 : initialize_aggregates(AggState *aggstate,
666 : : AggStatePerGroup *pergroups,
667 : : int numReset)
668 : : {
669 : : int transno;
3249 bruce@momjian.us 670 : 147661 : int numGroupingSets = Max(aggstate->phase->numsets, 1);
671 : 147661 : int setno = 0;
2575 rhodiumtoad@postgres 672 : 147661 : int numTrans = aggstate->numtrans;
3176 heikki.linnakangas@i 673 : 147661 : AggStatePerTrans transstates = aggstate->pertrans;
674 : :
2575 rhodiumtoad@postgres 675 [ - + ]: 147661 : if (numReset == 0)
3256 andres@anarazel.de 676 :UBC 0 : numReset = numGroupingSets;
677 : :
2294 andres@anarazel.de 678 [ + + ]:CBC 302400 : for (setno = 0; setno < numReset; setno++)
679 : : {
680 : 154739 : AggStatePerGroup pergroup = pergroups[setno];
681 : :
682 : 154739 : select_current_set(aggstate, setno, false);
683 : :
684 [ + + ]: 485414 : for (transno = 0; transno < numTrans; transno++)
685 : : {
686 : 330675 : AggStatePerTrans pertrans = &transstates[transno];
687 : 330675 : AggStatePerGroup pergroupstate = &pergroup[transno];
688 : :
689 : 330675 : initialize_aggregate(aggstate, pertrans, pergroupstate);
690 : : }
691 : : }
8889 tgl@sss.pgh.pa.us 692 : 147661 : }
693 : :
694 : : /*
695 : : * Given new input value(s), advance the transition function of one aggregate
696 : : * state within one grouping set only (already set in aggstate->current_set)
697 : : *
698 : : * The new values (and null flags) have been preloaded into argument positions
699 : : * 1 and up in pertrans->transfn_fcinfo, so that we needn't copy them again to
700 : : * pass to the transition function. We also expect that the static fields of
701 : : * the fcinfo are already initialized; that was done by ExecInitAgg().
702 : : *
703 : : * It doesn't matter which memory context this is called in.
704 : : */
705 : : static void
7830 706 : 362163 : advance_transition_function(AggState *aggstate,
707 : : AggStatePerTrans pertrans,
708 : : AggStatePerGroup pergroupstate)
709 : : {
1905 andres@anarazel.de 710 : 362163 : FunctionCallInfo fcinfo = pertrans->transfn_fcinfo;
711 : : MemoryContext oldContext;
712 : : Datum newVal;
713 : :
3176 heikki.linnakangas@i 714 [ + + ]: 362163 : if (pertrans->transfn.fn_strict)
715 : : {
716 : : /*
717 : : * For a strict transfn, nothing happens when there's a NULL input; we
718 : : * just keep the prior transValue.
719 : : */
720 : 112500 : int numTransInputs = pertrans->numTransInputs;
721 : : int i;
722 : :
3765 tgl@sss.pgh.pa.us 723 [ + + ]: 225000 : for (i = 1; i <= numTransInputs; i++)
724 : : {
1905 andres@anarazel.de 725 [ - + ]: 112500 : if (fcinfo->args[i].isnull)
6471 tgl@sss.pgh.pa.us 726 :UBC 0 : return;
727 : : }
7830 tgl@sss.pgh.pa.us 728 [ - + ]:CBC 112500 : if (pergroupstate->noTransValue)
729 : : {
730 : : /*
731 : : * transValue has not been initialized. This is the first non-NULL
732 : : * input value. We use it as the initial value for transValue. (We
733 : : * already checked that the agg's input type is binary-compatible
734 : : * with its transtype, so straight copy here is OK.)
735 : : *
736 : : * We must copy the datum into aggcontext if it is pass-by-ref. We
737 : : * do not need to pfree the old transValue, since it's NULL.
738 : : */
1536 alvherre@alvh.no-ip. 739 :UBC 0 : oldContext = MemoryContextSwitchTo(aggstate->curaggcontext->ecxt_per_tuple_memory);
1905 andres@anarazel.de 740 : 0 : pergroupstate->transValue = datumCopy(fcinfo->args[1].value,
3176 heikki.linnakangas@i 741 : 0 : pertrans->transtypeByVal,
742 : 0 : pertrans->transtypeLen);
7830 tgl@sss.pgh.pa.us 743 : 0 : pergroupstate->transValueIsNull = false;
744 : 0 : pergroupstate->noTransValue = false;
745 : 0 : MemoryContextSwitchTo(oldContext);
8672 746 : 0 : return;
747 : : }
7830 tgl@sss.pgh.pa.us 748 [ - + ]:CBC 112500 : if (pergroupstate->transValueIsNull)
749 : : {
750 : : /*
751 : : * Don't call a strict function with NULL inputs. Note it is
752 : : * possible to get here despite the above tests, if the transfn is
753 : : * strict *and* returned a NULL on a prior cycle. If that happens
754 : : * we will propagate the NULL all the way to the end.
755 : : */
8672 tgl@sss.pgh.pa.us 756 :UBC 0 : return;
757 : : }
758 : : }
759 : :
760 : : /* We run the transition functions in per-input-tuple memory context */
7830 tgl@sss.pgh.pa.us 761 :CBC 362163 : oldContext = MemoryContextSwitchTo(aggstate->tmpcontext->ecxt_per_tuple_memory);
762 : :
763 : : /* set up aggstate->curpertrans for AggGetAggref() */
3176 heikki.linnakangas@i 764 : 362163 : aggstate->curpertrans = pertrans;
765 : :
766 : : /*
767 : : * OK to call the transition function
768 : : */
1905 andres@anarazel.de 769 : 362163 : fcinfo->args[0].value = pergroupstate->transValue;
770 : 362163 : fcinfo->args[0].isnull = pergroupstate->transValueIsNull;
3749 tgl@sss.pgh.pa.us 771 : 362163 : fcinfo->isnull = false; /* just in case transfn doesn't set it */
772 : :
6471 773 : 362163 : newVal = FunctionCallInvoke(fcinfo);
774 : :
3176 heikki.linnakangas@i 775 : 362163 : aggstate->curpertrans = NULL;
776 : :
777 : : /*
778 : : * If pass-by-ref datatype, must copy the new value into aggcontext and
779 : : * free the prior transValue. But if transfn returned a pointer to its
780 : : * first input, we don't need to do anything.
781 : : *
782 : : * It's safe to compare newVal with pergroup->transValue without regard
783 : : * for either being NULL, because ExecAggCopyTransValue takes care to set
784 : : * transValue to 0 when NULL. Otherwise we could end up accidentally not
785 : : * reparenting, when the transValue has the same numerical value as
786 : : * newValue, despite being NULL. This is a somewhat hot path, making it
787 : : * undesirable to instead solve this with another branch for the common
788 : : * case of the transition function returning its (modified) input
789 : : * argument.
790 : : */
791 [ - + - - ]: 362163 : if (!pertrans->transtypeByVal &&
6756 bruce@momjian.us 792 :UBC 0 : DatumGetPointer(newVal) != DatumGetPointer(pergroupstate->transValue))
356 tgl@sss.pgh.pa.us 793 : 0 : newVal = ExecAggCopyTransValue(aggstate, pertrans,
794 : 0 : newVal, fcinfo->isnull,
795 : : pergroupstate->transValue,
796 : 0 : pergroupstate->transValueIsNull);
797 : :
7830 tgl@sss.pgh.pa.us 798 :CBC 362163 : pergroupstate->transValue = newVal;
6471 799 : 362163 : pergroupstate->transValueIsNull = fcinfo->isnull;
800 : :
7830 801 : 362163 : MemoryContextSwitchTo(oldContext);
802 : : }
803 : :
804 : : /*
805 : : * Advance each aggregate transition state for one input tuple. The input
806 : : * tuple has been stored in tmpcontext->ecxt_outertuple, so that it is
807 : : * accessible to ExecEvalExpr.
808 : : *
809 : : * We have two sets of transition states to handle: one for sorted aggregation
810 : : * and one for hashed; we do them both here, to avoid multiple evaluation of
811 : : * the inputs.
812 : : *
813 : : * When called, CurrentMemoryContext should be the per-query context.
814 : : */
815 : : static void
2287 andres@anarazel.de 816 : 12811266 : advance_aggregates(AggState *aggstate)
817 : : {
818 : : bool dummynull;
819 : :
820 : 12811266 : ExecEvalExprSwitchContext(aggstate->phase->evaltrans,
821 : : aggstate->tmpcontext,
822 : : &dummynull);
7830 tgl@sss.pgh.pa.us 823 : 12811233 : }
824 : :
825 : : /*
826 : : * Run the transition function for a DISTINCT or ORDER BY aggregate
827 : : * with only one input. This is called after we have completed
828 : : * entering all the input values into the sort object. We complete the
829 : : * sort, read out the values in sorted order, and run the transition
830 : : * function on each value (applying DISTINCT if appropriate).
831 : : *
832 : : * Note that the strictness of the transition function was checked when
833 : : * entering the values into the sort, so we don't check it again here;
834 : : * we just apply standard SQL DISTINCT logic.
835 : : *
836 : : * The one-input case is handled separately from the multi-input case
837 : : * for performance reasons: for single by-value inputs, such as the
838 : : * common case of count(distinct id), the tuplesort_getdatum code path
839 : : * is around 300% faster. (The speedup for by-reference types is less
840 : : * but still noticeable.)
841 : : *
842 : : * This function handles only one grouping set (already set in
843 : : * aggstate->current_set).
844 : : *
845 : : * When called, CurrentMemoryContext should be the per-query context.
846 : : */
847 : : static void
5234 848 : 26878 : process_ordered_aggregate_single(AggState *aggstate,
849 : : AggStatePerTrans pertrans,
850 : : AggStatePerGroup pergroupstate)
851 : : {
8677 852 : 26878 : Datum oldVal = (Datum) 0;
5161 bruce@momjian.us 853 : 26878 : bool oldIsNull = true;
8677 tgl@sss.pgh.pa.us 854 : 26878 : bool haveOldVal = false;
7830 855 : 26878 : MemoryContext workcontext = aggstate->tmpcontext->ecxt_per_tuple_memory;
856 : : MemoryContext oldContext;
3176 heikki.linnakangas@i 857 : 26878 : bool isDistinct = (pertrans->numDistinctCols > 0);
2979 rhaas@postgresql.org 858 : 26878 : Datum newAbbrevVal = (Datum) 0;
859 : 26878 : Datum oldAbbrevVal = (Datum) 0;
1905 andres@anarazel.de 860 : 26878 : FunctionCallInfo fcinfo = pertrans->transfn_fcinfo;
861 : : Datum *newVal;
862 : : bool *isNull;
863 : :
3176 heikki.linnakangas@i 864 [ - + ]: 26878 : Assert(pertrans->numDistinctCols < 2);
865 : :
866 : 26878 : tuplesort_performsort(pertrans->sortstates[aggstate->current_set]);
867 : :
868 : : /* Load the column into argument 1 (arg 0 will be transition value) */
1905 andres@anarazel.de 869 : 26878 : newVal = &fcinfo->args[1].value;
870 : 26878 : isNull = &fcinfo->args[1].isnull;
871 : :
872 : : /*
873 : : * Note: if input type is pass-by-ref, the datums returned by the sort are
874 : : * freshly palloc'd in the per-query context, so we must be careful to
875 : : * pfree them when they are no longer needed.
876 : : */
877 : :
3176 heikki.linnakangas@i 878 [ + + ]: 449070 : while (tuplesort_getdatum(pertrans->sortstates[aggstate->current_set],
879 : : true, false, newVal, isNull, &newAbbrevVal))
880 : : {
881 : : /*
882 : : * Clear and select the working context for evaluation of the equality
883 : : * function and transition function.
884 : : */
7830 tgl@sss.pgh.pa.us 885 : 422192 : MemoryContextReset(workcontext);
886 : 422192 : oldContext = MemoryContextSwitchTo(workcontext);
887 : :
888 : : /*
889 : : * If DISTINCT mode, and not distinct from prior, skip it.
890 : : */
5234 891 [ + + + + ]: 422192 : if (isDistinct &&
892 [ - + ]: 155161 : haveOldVal &&
5234 tgl@sss.pgh.pa.us 893 [ # # ]:UBC 0 : ((oldIsNull && *isNull) ||
5234 tgl@sss.pgh.pa.us 894 [ + - + - ]:CBC 155161 : (!oldIsNull && !*isNull &&
2979 rhaas@postgresql.org 895 [ + + + + ]: 302842 : oldAbbrevVal == newAbbrevVal &&
1850 peter@eisentraut.org 896 : 147681 : DatumGetBool(FunctionCall2Coll(&pertrans->equalfnOne,
897 : : pertrans->aggCollation,
898 : : oldVal, *newVal)))))
899 : : {
534 drowley@postgresql.o 900 : 60119 : MemoryContextSwitchTo(oldContext);
901 : 60119 : continue;
902 : : }
903 : : else
904 : : {
3176 heikki.linnakangas@i 905 : 362073 : advance_transition_function(aggstate, pertrans, pergroupstate);
906 : :
534 drowley@postgresql.o 907 : 362073 : MemoryContextSwitchTo(oldContext);
908 : :
909 : : /*
910 : : * Forget the old value, if any, and remember the new one for
911 : : * subsequent equality checks.
912 : : */
913 [ + + ]: 362073 : if (!pertrans->inputtypeByVal)
914 : : {
915 [ + + ]: 262644 : if (!oldIsNull)
916 : 262554 : pfree(DatumGetPointer(oldVal));
917 [ + + ]: 262644 : if (!*isNull)
918 : 262614 : oldVal = datumCopy(*newVal, pertrans->inputtypeByVal,
919 : 262614 : pertrans->inputtypeLen);
920 : : }
921 : : else
922 : 99429 : oldVal = *newVal;
2979 rhaas@postgresql.org 923 : 362073 : oldAbbrevVal = newAbbrevVal;
5234 tgl@sss.pgh.pa.us 924 : 362073 : oldIsNull = *isNull;
8889 925 : 362073 : haveOldVal = true;
926 : : }
927 : : }
928 : :
3176 heikki.linnakangas@i 929 [ + + + + ]: 26878 : if (!oldIsNull && !pertrans->inputtypeByVal)
8677 tgl@sss.pgh.pa.us 930 : 60 : pfree(DatumGetPointer(oldVal));
931 : :
3176 heikki.linnakangas@i 932 : 26878 : tuplesort_end(pertrans->sortstates[aggstate->current_set]);
933 : 26878 : pertrans->sortstates[aggstate->current_set] = NULL;
8677 tgl@sss.pgh.pa.us 934 : 26878 : }
935 : :
936 : : /*
937 : : * Run the transition function for a DISTINCT or ORDER BY aggregate
938 : : * with more than one input. This is called after we have completed
939 : : * entering all the input values into the sort object. We complete the
940 : : * sort, read out the values in sorted order, and run the transition
941 : : * function on each value (applying DISTINCT if appropriate).
942 : : *
943 : : * This function handles only one grouping set (already set in
944 : : * aggstate->current_set).
945 : : *
946 : : * When called, CurrentMemoryContext should be the per-query context.
947 : : */
948 : : static void
5234 949 : 36 : process_ordered_aggregate_multi(AggState *aggstate,
950 : : AggStatePerTrans pertrans,
951 : : AggStatePerGroup pergroupstate)
952 : : {
2250 andres@anarazel.de 953 : 36 : ExprContext *tmpcontext = aggstate->tmpcontext;
1905 954 : 36 : FunctionCallInfo fcinfo = pertrans->transfn_fcinfo;
2692 955 : 36 : TupleTableSlot *slot1 = pertrans->sortslot;
3176 heikki.linnakangas@i 956 : 36 : TupleTableSlot *slot2 = pertrans->uniqslot;
957 : 36 : int numTransInputs = pertrans->numTransInputs;
958 : 36 : int numDistinctCols = pertrans->numDistinctCols;
2979 rhaas@postgresql.org 959 : 36 : Datum newAbbrevVal = (Datum) 0;
960 : 36 : Datum oldAbbrevVal = (Datum) 0;
5161 bruce@momjian.us 961 : 36 : bool haveOldValue = false;
2250 andres@anarazel.de 962 : 36 : TupleTableSlot *save = aggstate->tmpcontext->ecxt_outertuple;
963 : : int i;
964 : :
3176 heikki.linnakangas@i 965 : 36 : tuplesort_performsort(pertrans->sortstates[aggstate->current_set]);
966 : :
5234 tgl@sss.pgh.pa.us 967 : 36 : ExecClearTuple(slot1);
968 [ - + ]: 36 : if (slot2)
5234 tgl@sss.pgh.pa.us 969 :UBC 0 : ExecClearTuple(slot2);
970 : :
3176 heikki.linnakangas@i 971 [ + + ]:CBC 126 : while (tuplesort_gettupleslot(pertrans->sortstates[aggstate->current_set],
972 : : true, true, slot1, &newAbbrevVal))
973 : : {
2455 andres@anarazel.de 974 [ - + ]: 90 : CHECK_FOR_INTERRUPTS();
975 : :
2250 976 : 90 : tmpcontext->ecxt_outertuple = slot1;
977 : 90 : tmpcontext->ecxt_innertuple = slot2;
978 : :
5234 tgl@sss.pgh.pa.us 979 [ - + ]: 90 : if (numDistinctCols == 0 ||
5234 tgl@sss.pgh.pa.us 980 [ # # ]:UBC 0 : !haveOldValue ||
2979 rhaas@postgresql.org 981 [ # # ]: 0 : newAbbrevVal != oldAbbrevVal ||
2250 andres@anarazel.de 982 [ # # ]: 0 : !ExecQual(pertrans->equalfnMulti, tmpcontext))
983 : : {
984 : : /*
985 : : * Extract the first numTransInputs columns as datums to pass to
986 : : * the transfn.
987 : : */
2250 andres@anarazel.de 988 :CBC 90 : slot_getsomeattrs(slot1, numTransInputs);
989 : :
990 : : /* Load values into fcinfo */
991 : : /* Start from 1, since the 0th arg will be the transition value */
3765 tgl@sss.pgh.pa.us 992 [ + + ]: 270 : for (i = 0; i < numTransInputs; i++)
993 : : {
1905 andres@anarazel.de 994 : 180 : fcinfo->args[i + 1].value = slot1->tts_values[i];
995 : 180 : fcinfo->args[i + 1].isnull = slot1->tts_isnull[i];
996 : : }
997 : :
3176 heikki.linnakangas@i 998 : 90 : advance_transition_function(aggstate, pertrans, pergroupstate);
999 : :
5234 tgl@sss.pgh.pa.us 1000 [ - + ]: 90 : if (numDistinctCols > 0)
1001 : : {
1002 : : /* swap the slot pointers to retain the current tuple */
5234 tgl@sss.pgh.pa.us 1003 :UBC 0 : TupleTableSlot *tmpslot = slot2;
1004 : :
1005 : 0 : slot2 = slot1;
1006 : 0 : slot1 = tmpslot;
1007 : : /* avoid ExecQual() calls by reusing abbreviated keys */
2979 rhaas@postgresql.org 1008 : 0 : oldAbbrevVal = newAbbrevVal;
5234 tgl@sss.pgh.pa.us 1009 : 0 : haveOldValue = true;
1010 : : }
1011 : : }
1012 : :
1013 : : /* Reset context each time */
2250 andres@anarazel.de 1014 :CBC 90 : ResetExprContext(tmpcontext);
1015 : :
5234 tgl@sss.pgh.pa.us 1016 : 90 : ExecClearTuple(slot1);
1017 : : }
1018 : :
1019 [ - + ]: 36 : if (slot2)
5234 tgl@sss.pgh.pa.us 1020 :UBC 0 : ExecClearTuple(slot2);
1021 : :
3176 heikki.linnakangas@i 1022 :CBC 36 : tuplesort_end(pertrans->sortstates[aggstate->current_set]);
1023 : 36 : pertrans->sortstates[aggstate->current_set] = NULL;
1024 : :
1025 : : /* restore previous slot, potentially in use for grouping sets */
2250 andres@anarazel.de 1026 : 36 : tmpcontext->ecxt_outertuple = save;
5234 tgl@sss.pgh.pa.us 1027 : 36 : }
1028 : :
1029 : : /*
1030 : : * Compute the final value of one aggregate.
1031 : : *
1032 : : * This function handles only one grouping set (already set in
1033 : : * aggstate->current_set).
1034 : : *
1035 : : * The finalfn will be run, and the result delivered, in the
1036 : : * output-tuple context; caller's CurrentMemoryContext does not matter.
1037 : : * (But note that in some cases, such as when there is no finalfn, the
1038 : : * result might be a pointer to or into the agg's transition value.)
1039 : : *
1040 : : * The finalfn uses the state as set in the transno. This also might be
1041 : : * being used by another aggregate function, so it's important that we do
1042 : : * nothing destructive here. Moreover, the aggregate's final value might
1043 : : * get used in multiple places, so we mustn't return a R/W expanded datum.
1044 : : */
1045 : : static void
7830 1046 : 524181 : finalize_aggregate(AggState *aggstate,
1047 : : AggStatePerAgg peragg,
1048 : : AggStatePerGroup pergroupstate,
1049 : : Datum *resultVal, bool *resultIsNull)
1050 : : {
1905 andres@anarazel.de 1051 : 524181 : LOCAL_FCINFO(fcinfo, FUNC_MAX_ARGS);
3765 tgl@sss.pgh.pa.us 1052 : 524181 : bool anynull = false;
1053 : : MemoryContext oldContext;
1054 : : int i;
1055 : : ListCell *lc;
3176 heikki.linnakangas@i 1056 : 524181 : AggStatePerTrans pertrans = &aggstate->pertrans[peragg->transno];
1057 : :
7801 tgl@sss.pgh.pa.us 1058 : 524181 : oldContext = MemoryContextSwitchTo(aggstate->ss.ps.ps_ExprContext->ecxt_per_tuple_memory);
1059 : :
1060 : : /*
1061 : : * Evaluate any direct arguments. We do this even if there's no finalfn
1062 : : * (which is unlikely anyway), so that side-effects happen as expected.
1063 : : * The direct arguments go into arg positions 1 and up, leaving position 0
1064 : : * for the transition state value.
1065 : : */
3765 1066 : 524181 : i = 1;
2372 1067 [ + + + + : 524668 : foreach(lc, peragg->aggdirectargs)
+ + ]
1068 : : {
3765 1069 : 487 : ExprState *expr = (ExprState *) lfirst(lc);
1070 : :
1905 andres@anarazel.de 1071 : 487 : fcinfo->args[i].value = ExecEvalExpr(expr,
1072 : : aggstate->ss.ps.ps_ExprContext,
1073 : : &fcinfo->args[i].isnull);
1074 : 487 : anynull |= fcinfo->args[i].isnull;
3765 tgl@sss.pgh.pa.us 1075 : 487 : i++;
1076 : : }
1077 : :
1078 : : /*
1079 : : * Apply the agg's finalfn if one is provided, else return transValue.
1080 : : */
3176 heikki.linnakangas@i 1081 [ + + ]: 524181 : if (OidIsValid(peragg->finalfn_oid))
1082 : : {
1083 : 136223 : int numFinalArgs = peragg->numFinalArgs;
1084 : :
1085 : : /* set up aggstate->curperagg for AggGetAggref() */
2376 tgl@sss.pgh.pa.us 1086 : 136223 : aggstate->curperagg = peragg;
1087 : :
1905 andres@anarazel.de 1088 : 136223 : InitFunctionCallInfoData(*fcinfo, &peragg->finalfn,
1089 : : numFinalArgs,
1090 : : pertrans->aggCollation,
1091 : : (void *) aggstate, NULL);
1092 : :
1093 : : /* Fill in the transition state value */
1094 : 136223 : fcinfo->args[0].value =
1095 [ + + + + ]: 136223 : MakeExpandedObjectReadOnly(pergroupstate->transValue,
1096 : : pergroupstate->transValueIsNull,
1097 : : pertrans->transtypeLen);
1098 : 136223 : fcinfo->args[0].isnull = pergroupstate->transValueIsNull;
3765 tgl@sss.pgh.pa.us 1099 : 136223 : anynull |= pergroupstate->transValueIsNull;
1100 : :
1101 : : /* Fill any remaining argument positions with nulls */
3644 1102 [ + + ]: 179828 : for (; i < numFinalArgs; i++)
1103 : : {
1905 andres@anarazel.de 1104 : 43605 : fcinfo->args[i].value = (Datum) 0;
1105 : 43605 : fcinfo->args[i].isnull = true;
3765 tgl@sss.pgh.pa.us 1106 : 43605 : anynull = true;
1107 : : }
1108 : :
1905 andres@anarazel.de 1109 [ + + - + ]: 136223 : if (fcinfo->flinfo->fn_strict && anynull)
1110 : : {
1111 : : /* don't call a strict function with NULL inputs */
8722 tgl@sss.pgh.pa.us 1112 :UBC 0 : *resultVal = (Datum) 0;
1113 : 0 : *resultIsNull = true;
1114 : : }
1115 : : else
1116 : : {
1117 : : Datum result;
1118 : :
364 tgl@sss.pgh.pa.us 1119 :CBC 136223 : result = FunctionCallInvoke(fcinfo);
1905 andres@anarazel.de 1120 : 136217 : *resultIsNull = fcinfo->isnull;
364 tgl@sss.pgh.pa.us 1121 [ + + + + ]: 136217 : *resultVal = MakeExpandedObjectReadOnly(result,
1122 : : fcinfo->isnull,
1123 : : peragg->resulttypeLen);
1124 : : }
2376 1125 : 136217 : aggstate->curperagg = NULL;
1126 : : }
1127 : : else
1128 : : {
556 1129 : 387958 : *resultVal =
1130 [ + + + + ]: 387958 : MakeExpandedObjectReadOnly(pergroupstate->transValue,
1131 : : pergroupstate->transValueIsNull,
1132 : : pertrans->transtypeLen);
7830 1133 : 387958 : *resultIsNull = pergroupstate->transValueIsNull;
1134 : : }
1135 : :
1136 : 524175 : MemoryContextSwitchTo(oldContext);
8889 1137 : 524175 : }
1138 : :
1139 : : /*
1140 : : * Compute the output value of one partial aggregate.
1141 : : *
1142 : : * The serialization function will be run, and the result delivered, in the
1143 : : * output-tuple context; caller's CurrentMemoryContext does not matter.
1144 : : */
1145 : : static void
2938 rhaas@postgresql.org 1146 : 8023 : finalize_partialaggregate(AggState *aggstate,
1147 : : AggStatePerAgg peragg,
1148 : : AggStatePerGroup pergroupstate,
1149 : : Datum *resultVal, bool *resultIsNull)
1150 : : {
2866 1151 : 8023 : AggStatePerTrans pertrans = &aggstate->pertrans[peragg->transno];
1152 : : MemoryContext oldContext;
1153 : :
2938 1154 : 8023 : oldContext = MemoryContextSwitchTo(aggstate->ss.ps.ps_ExprContext->ecxt_per_tuple_memory);
1155 : :
1156 : : /*
1157 : : * serialfn_oid will be set if we must serialize the transvalue before
1158 : : * returning it
1159 : : */
1160 [ + + ]: 8023 : if (OidIsValid(pertrans->serialfn_oid))
1161 : : {
1162 : : /* Don't call a strict serialization function with NULL input. */
1163 [ + - + + ]: 333 : if (pertrans->serialfn.fn_strict && pergroupstate->transValueIsNull)
1164 : : {
1165 : 24 : *resultVal = (Datum) 0;
1166 : 24 : *resultIsNull = true;
1167 : : }
1168 : : else
1169 : : {
1905 andres@anarazel.de 1170 : 309 : FunctionCallInfo fcinfo = pertrans->serialfn_fcinfo;
1171 : : Datum result;
1172 : :
1173 : 309 : fcinfo->args[0].value =
1174 [ + - + - ]: 309 : MakeExpandedObjectReadOnly(pergroupstate->transValue,
1175 : : pergroupstate->transValueIsNull,
1176 : : pertrans->transtypeLen);
1177 : 309 : fcinfo->args[0].isnull = pergroupstate->transValueIsNull;
1454 tgl@sss.pgh.pa.us 1178 : 309 : fcinfo->isnull = false;
1179 : :
364 1180 : 309 : result = FunctionCallInvoke(fcinfo);
2938 rhaas@postgresql.org 1181 : 309 : *resultIsNull = fcinfo->isnull;
364 tgl@sss.pgh.pa.us 1182 [ + - + - ]: 309 : *resultVal = MakeExpandedObjectReadOnly(result,
1183 : : fcinfo->isnull,
1184 : : peragg->resulttypeLen);
1185 : : }
1186 : : }
1187 : : else
1188 : : {
556 1189 : 7690 : *resultVal =
1190 [ + + + + ]: 7690 : MakeExpandedObjectReadOnly(pergroupstate->transValue,
1191 : : pergroupstate->transValueIsNull,
1192 : : pertrans->transtypeLen);
2938 rhaas@postgresql.org 1193 : 7690 : *resultIsNull = pergroupstate->transValueIsNull;
1194 : : }
1195 : :
1196 : 8023 : MemoryContextSwitchTo(oldContext);
1197 : 8023 : }
1198 : :
1199 : : /*
1200 : : * Extract the attributes that make up the grouping key into the
1201 : : * hashslot. This is necessary to compute the hash or perform a lookup.
1202 : : */
1203 : : static inline void
1358 jdavis@postgresql.or 1204 : 3093261 : prepare_hash_slot(AggStatePerHash perhash,
1205 : : TupleTableSlot *inputslot,
1206 : : TupleTableSlot *hashslot)
1207 : : {
1208 : : int i;
1209 : :
1210 : : /* transfer just the needed columns into hashslot */
1516 1211 : 3093261 : slot_getsomeattrs(inputslot, perhash->largestGrpColIdx);
1212 : 3093261 : ExecClearTuple(hashslot);
1213 : :
1214 [ + + ]: 7673964 : for (i = 0; i < perhash->numhashGrpCols; i++)
1215 : : {
1216 : 4580703 : int varNumber = perhash->hashGrpColIdxInput[i] - 1;
1217 : :
1218 : 4580703 : hashslot->tts_values[i] = inputslot->tts_values[varNumber];
1219 : 4580703 : hashslot->tts_isnull[i] = inputslot->tts_isnull[varNumber];
1220 : : }
1221 : 3093261 : ExecStoreVirtualTuple(hashslot);
1222 : 3093261 : }
1223 : :
1224 : : /*
1225 : : * Prepare to finalize and project based on the specified representative tuple
1226 : : * slot and grouping set.
1227 : : *
1228 : : * In the specified tuple slot, force to null all attributes that should be
1229 : : * read as null in the context of the current grouping set. Also stash the
1230 : : * current group bitmap where GroupingExpr can get at it.
1231 : : *
1232 : : * This relies on three conditions:
1233 : : *
1234 : : * 1) Nothing is ever going to try and extract the whole tuple from this slot,
1235 : : * only reference it in evaluations, which will only access individual
1236 : : * attributes.
1237 : : *
1238 : : * 2) No system columns are going to need to be nulled. (If a system column is
1239 : : * referenced in a group clause, it is actually projected in the outer plan
1240 : : * tlist.)
1241 : : *
1242 : : * 3) Within a given phase, we never need to recover the value of an attribute
1243 : : * once it has been set to null.
1244 : : *
1245 : : * Poking into the slot this way is a bit ugly, but the consensus is that the
1246 : : * alternative was worse.
1247 : : */
1248 : : static void
3256 andres@anarazel.de 1249 : 427429 : prepare_projection_slot(AggState *aggstate, TupleTableSlot *slot, int currentSet)
1250 : : {
1251 [ + + ]: 427429 : if (aggstate->phase->grouped_cols)
1252 : : {
3249 bruce@momjian.us 1253 : 287378 : Bitmapset *grouped_cols = aggstate->phase->grouped_cols[currentSet];
1254 : :
3256 andres@anarazel.de 1255 : 287378 : aggstate->grouped_cols = grouped_cols;
1256 : :
2008 1257 [ + + ]: 287378 : if (TTS_EMPTY(slot))
1258 : : {
1259 : : /*
1260 : : * Force all values to be NULL if working on an empty input tuple
1261 : : * (i.e. an empty grouping set for which no input rows were
1262 : : * supplied).
1263 : : */
3256 1264 : 24 : ExecStoreAllNullTuple(slot);
1265 : : }
1266 [ + + ]: 287354 : else if (aggstate->all_grouped_cols)
1267 : : {
1268 : : ListCell *lc;
1269 : :
1270 : : /* all_grouped_cols is arranged in desc order */
1271 : 287330 : slot_getsomeattrs(slot, linitial_int(aggstate->all_grouped_cols));
1272 : :
1273 [ + - + + : 843539 : foreach(lc, aggstate->all_grouped_cols)
+ + ]
1274 : : {
3249 bruce@momjian.us 1275 : 556209 : int attnum = lfirst_int(lc);
1276 : :
3256 andres@anarazel.de 1277 [ + + ]: 556209 : if (!bms_is_member(attnum, grouped_cols))
1278 : 28673 : slot->tts_isnull[attnum - 1] = true;
1279 : : }
1280 : : }
1281 : : }
1282 : 427429 : }
1283 : :
1284 : : /*
1285 : : * Compute the final value of all aggregates for one group.
1286 : : *
1287 : : * This function handles only one grouping set at a time, which the caller must
1288 : : * have selected. It's also the caller's responsibility to adjust the supplied
1289 : : * pergroup parameter to point to the current set's transvalues.
1290 : : *
1291 : : * Results are stored in the output econtext aggvalues/aggnulls.
1292 : : */
1293 : : static void
1294 : 427429 : finalize_aggregates(AggState *aggstate,
1295 : : AggStatePerAgg peraggs,
1296 : : AggStatePerGroup pergroup)
1297 : : {
1298 : 427429 : ExprContext *econtext = aggstate->ss.ps.ps_ExprContext;
1299 : 427429 : Datum *aggvalues = econtext->ecxt_aggvalues;
1300 : 427429 : bool *aggnulls = econtext->ecxt_aggnulls;
1301 : : int aggno;
1302 : :
1303 : : /*
1304 : : * If there were any DISTINCT and/or ORDER BY aggregates, sort their
1305 : : * inputs and run the transition functions.
1306 : : */
599 drowley@postgresql.o 1307 [ + + ]: 959504 : for (int transno = 0; transno < aggstate->numtrans; transno++)
1308 : : {
3176 heikki.linnakangas@i 1309 : 532075 : AggStatePerTrans pertrans = &aggstate->pertrans[transno];
1310 : : AggStatePerGroup pergroupstate;
1311 : :
2575 rhodiumtoad@postgres 1312 : 532075 : pergroupstate = &pergroup[transno];
1313 : :
621 drowley@postgresql.o 1314 [ + + ]: 532075 : if (pertrans->aggsortrequired)
1315 : : {
2575 rhodiumtoad@postgres 1316 [ + - - + ]: 26914 : Assert(aggstate->aggstrategy != AGG_HASHED &&
1317 : : aggstate->aggstrategy != AGG_MIXED);
1318 : :
3176 heikki.linnakangas@i 1319 [ + + ]: 26914 : if (pertrans->numInputs == 1)
3256 andres@anarazel.de 1320 : 26878 : process_ordered_aggregate_single(aggstate,
1321 : : pertrans,
1322 : : pergroupstate);
1323 : : else
1324 : 36 : process_ordered_aggregate_multi(aggstate,
1325 : : pertrans,
1326 : : pergroupstate);
1327 : : }
621 drowley@postgresql.o 1328 [ + + + + ]: 505161 : else if (pertrans->numDistinctCols > 0 && pertrans->haslast)
1329 : : {
1330 : 9174 : pertrans->haslast = false;
1331 : :
1332 [ + + ]: 9174 : if (pertrans->numDistinctCols == 1)
1333 : : {
1334 [ + + + + ]: 9126 : if (!pertrans->inputtypeByVal && !pertrans->lastisnull)
1335 : 125 : pfree(DatumGetPointer(pertrans->lastdatum));
1336 : :
1337 : 9126 : pertrans->lastisnull = false;
1338 : 9126 : pertrans->lastdatum = (Datum) 0;
1339 : : }
1340 : : else
1341 : 48 : ExecClearTuple(pertrans->uniqslot);
1342 : : }
1343 : : }
1344 : :
1345 : : /*
1346 : : * Run the final functions.
1347 : : */
2672 heikki.linnakangas@i 1348 [ + + ]: 959627 : for (aggno = 0; aggno < aggstate->numaggs; aggno++)
1349 : : {
1350 : 532204 : AggStatePerAgg peragg = &peraggs[aggno];
1351 : 532204 : int transno = peragg->transno;
1352 : : AggStatePerGroup pergroupstate;
1353 : :
2575 rhodiumtoad@postgres 1354 : 532204 : pergroupstate = &pergroup[transno];
1355 : :
2849 tgl@sss.pgh.pa.us 1356 [ + + ]: 532204 : if (DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit))
2938 rhaas@postgresql.org 1357 : 8023 : finalize_partialaggregate(aggstate, peragg, pergroupstate,
1358 : 8023 : &aggvalues[aggno], &aggnulls[aggno]);
1359 : : else
2849 tgl@sss.pgh.pa.us 1360 : 524181 : finalize_aggregate(aggstate, peragg, pergroupstate,
1361 : 524181 : &aggvalues[aggno], &aggnulls[aggno]);
1362 : : }
3256 andres@anarazel.de 1363 : 427423 : }
1364 : :
1365 : : /*
1366 : : * Project the result of a group (whose aggs have already been calculated by
1367 : : * finalize_aggregates). Returns the result slot, or NULL if no row is
1368 : : * projected (suppressed by qual).
1369 : : */
1370 : : static TupleTableSlot *
1371 : 427423 : project_aggregates(AggState *aggstate)
1372 : : {
1373 : 427423 : ExprContext *econtext = aggstate->ss.ps.ps_ExprContext;
1374 : :
1375 : : /*
1376 : : * Check the qual (HAVING clause); if the group does not match, ignore it.
1377 : : */
2588 1378 [ + + ]: 427423 : if (ExecQual(aggstate->ss.ps.qual, econtext))
1379 : : {
1380 : : /*
1381 : : * Form and return projection tuple using the aggregate results and
1382 : : * the representative input tuple.
1383 : : */
2642 1384 : 374139 : return ExecProject(aggstate->ss.ps.ps_ProjInfo);
1385 : : }
1386 : : else
3256 1387 [ - + ]: 53284 : InstrCountFiltered1(aggstate, 1);
1388 : :
1389 : 53284 : return NULL;
1390 : : }
1391 : :
1392 : : /*
1393 : : * Find input-tuple columns that are needed, dividing them into
1394 : : * aggregated and unaggregated sets.
1395 : : */
1396 : : static void
1372 jdavis@postgresql.or 1397 : 2570 : find_cols(AggState *aggstate, Bitmapset **aggregated, Bitmapset **unaggregated)
1398 : : {
1068 tgl@sss.pgh.pa.us 1399 : 2570 : Agg *agg = (Agg *) aggstate->ss.ps.plan;
1400 : : FindColsContext context;
1401 : :
1372 jdavis@postgresql.or 1402 : 2570 : context.is_aggref = false;
1403 : 2570 : context.aggregated = NULL;
1404 : 2570 : context.unaggregated = NULL;
1405 : :
1406 : : /* Examine tlist and quals */
1407 : 2570 : (void) find_cols_walker((Node *) agg->plan.targetlist, &context);
1408 : 2570 : (void) find_cols_walker((Node *) agg->plan.qual, &context);
1409 : :
1410 : : /* In some cases, grouping columns will not appear in the tlist */
1165 tgl@sss.pgh.pa.us 1411 [ + + ]: 6606 : for (int i = 0; i < agg->numCols; i++)
1412 : 4036 : context.unaggregated = bms_add_member(context.unaggregated,
1413 : 4036 : agg->grpColIdx[i]);
1414 : :
1372 jdavis@postgresql.or 1415 : 2570 : *aggregated = context.aggregated;
1416 : 2570 : *unaggregated = context.unaggregated;
6500 tgl@sss.pgh.pa.us 1417 : 2570 : }
1418 : :
1419 : : static bool
1372 jdavis@postgresql.or 1420 : 31587 : find_cols_walker(Node *node, FindColsContext *context)
1421 : : {
6500 tgl@sss.pgh.pa.us 1422 [ + + ]: 31587 : if (node == NULL)
1423 : 5587 : return false;
1424 [ + + ]: 26000 : if (IsA(node, Var))
1425 : : {
1426 : 6778 : Var *var = (Var *) node;
1427 : :
1428 : : /* setrefs.c should have set the varno to OUTER_VAR */
4569 1429 [ - + ]: 6778 : Assert(var->varno == OUTER_VAR);
6500 1430 [ - + ]: 6778 : Assert(var->varlevelsup == 0);
1372 jdavis@postgresql.or 1431 [ + + ]: 6778 : if (context->is_aggref)
1432 : 2185 : context->aggregated = bms_add_member(context->aggregated,
1433 : 2185 : var->varattno);
1434 : : else
1435 : 4593 : context->unaggregated = bms_add_member(context->unaggregated,
1436 : 4593 : var->varattno);
6500 tgl@sss.pgh.pa.us 1437 : 6778 : return false;
1438 : : }
1372 jdavis@postgresql.or 1439 [ + + ]: 19222 : if (IsA(node, Aggref))
1440 : : {
1441 [ - + ]: 3279 : Assert(!context->is_aggref);
1442 : 3279 : context->is_aggref = true;
1443 : 3279 : expression_tree_walker(node, find_cols_walker, (void *) context);
1444 : 3279 : context->is_aggref = false;
6500 tgl@sss.pgh.pa.us 1445 : 3279 : return false;
1446 : : }
1372 jdavis@postgresql.or 1447 : 15943 : return expression_tree_walker(node, find_cols_walker,
1448 : : (void *) context);
1449 : : }
1450 : :
1451 : : /*
1452 : : * (Re-)initialize the hash table(s) to empty.
1453 : : *
1454 : : * To implement hashed aggregation, we need a hashtable that stores a
1455 : : * representative tuple and an array of AggStatePerGroup structs for each
1456 : : * distinct set of GROUP BY column values. We compute the hash key from the
1457 : : * GROUP BY columns. The per-group data is allocated in lookup_hash_entry(),
1458 : : * for each entry.
1459 : : *
1460 : : * We have a separate hashtable and associated perhash data structure for each
1461 : : * grouping set for which we're doing hashing.
1462 : : *
1463 : : * The contents of the hash tables always live in the hashcontext's per-tuple
1464 : : * memory context (there is only one of these for all tables together, since
1465 : : * they are all reset at the same time).
1466 : : */
1467 : : static void
1516 1468 : 2046 : build_hash_tables(AggState *aggstate)
1469 : : {
1470 : : int setno;
1471 : :
1472 [ + + ]: 4234 : for (setno = 0; setno < aggstate->num_hashes; ++setno)
1473 : : {
1474 : 2188 : AggStatePerHash perhash = &aggstate->perhash[setno];
1475 : : long nbuckets;
1476 : : Size memory;
1477 : :
1488 1478 [ + + ]: 2188 : if (perhash->hashtable != NULL)
1479 : : {
1480 : 69 : ResetTupleHashTable(perhash->hashtable);
1481 : 69 : continue;
1482 : : }
1483 : :
2575 rhodiumtoad@postgres 1484 [ - + ]: 2119 : Assert(perhash->aggnode->numGroups > 0);
1485 : :
1488 jdavis@postgresql.or 1486 : 2119 : memory = aggstate->hash_mem_limit / aggstate->num_hashes;
1487 : :
1488 : : /* choose reasonable number of buckets per hashtable */
1431 tgl@sss.pgh.pa.us 1489 : 2119 : nbuckets = hash_choose_num_buckets(aggstate->hashentrysize,
1490 : 2119 : perhash->aggnode->numGroups,
1491 : : memory);
1492 : :
1488 jdavis@postgresql.or 1493 : 2119 : build_hash_table(aggstate, setno, nbuckets);
1494 : : }
1495 : :
1496 : 2046 : aggstate->hash_ngroups_current = 0;
5659 neilc@samurai.com 1497 : 2046 : }
1498 : :
1499 : : /*
1500 : : * Build a single hashtable for this grouping set.
1501 : : */
1502 : : static void
1516 jdavis@postgresql.or 1503 : 2119 : build_hash_table(AggState *aggstate, int setno, long nbuckets)
1504 : : {
1505 : 2119 : AggStatePerHash perhash = &aggstate->perhash[setno];
1431 tgl@sss.pgh.pa.us 1506 : 2119 : MemoryContext metacxt = aggstate->hash_metacxt;
1507 : 2119 : MemoryContext hashcxt = aggstate->hashcontext->ecxt_per_tuple_memory;
1508 : 2119 : MemoryContext tmpcxt = aggstate->tmpcontext->ecxt_per_tuple_memory;
1509 : : Size additionalsize;
1510 : :
1516 jdavis@postgresql.or 1511 [ + + - + ]: 2119 : Assert(aggstate->aggstrategy == AGG_HASHED ||
1512 : : aggstate->aggstrategy == AGG_MIXED);
1513 : :
1514 : : /*
1515 : : * Used to make sure initial hash table allocation does not exceed
1516 : : * hash_mem. Note that the estimate does not include space for
1517 : : * pass-by-reference transition data values, nor for the representative
1518 : : * tuple of each group.
1519 : : */
1520 : 2119 : additionalsize = aggstate->numtrans * sizeof(AggStatePerGroupData);
1521 : :
1431 tgl@sss.pgh.pa.us 1522 : 4238 : perhash->hashtable = BuildTupleHashTableExt(&aggstate->ss.ps,
1523 : 2119 : perhash->hashslot->tts_tupleDescriptor,
1524 : : perhash->numCols,
1525 : : perhash->hashGrpColIdxHash,
1526 : 2119 : perhash->eqfuncoids,
1527 : : perhash->hashfunctions,
1528 : 2119 : perhash->aggnode->grpCollations,
1529 : : nbuckets,
1530 : : additionalsize,
1531 : : metacxt,
1532 : : hashcxt,
1533 : : tmpcxt,
1534 : 2119 : DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit));
1516 jdavis@postgresql.or 1535 : 2119 : }
1536 : :
1537 : : /*
1538 : : * Compute columns that actually need to be stored in hashtable entries. The
1539 : : * incoming tuples from the child plan node will contain grouping columns,
1540 : : * other columns referenced in our targetlist and qual, columns used to
1541 : : * compute the aggregate functions, and perhaps just junk columns we don't use
1542 : : * at all. Only columns of the first two types need to be stored in the
1543 : : * hashtable, and getting rid of the others can make the table entries
1544 : : * significantly smaller. The hashtable only contains the relevant columns,
1545 : : * and is packed/unpacked in lookup_hash_entry() / agg_retrieve_hash_table()
1546 : : * into the format of the normal input descriptor.
1547 : : *
1548 : : * Additional columns, in addition to the columns grouped by, come from two
1549 : : * sources: Firstly functionally dependent columns that we don't need to group
1550 : : * by themselves, and secondly ctids for row-marks.
1551 : : *
1552 : : * To eliminate duplicates, we build a bitmapset of the needed columns, and
1553 : : * then build an array of the columns included in the hashtable. We might
1554 : : * still have duplicates if the passed-in grpColIdx has them, which can happen
1555 : : * in edge cases from semijoins/distinct; these can't always be removed,
1556 : : * because it's not certain that the duplicate cols will be using the same
1557 : : * hash function.
1558 : : *
1559 : : * Note that the array is preserved over ExecReScanAgg, so we allocate it in
1560 : : * the per-query context (unlike the hash table itself).
1561 : : */
1562 : : static void
5659 neilc@samurai.com 1563 : 2570 : find_hash_columns(AggState *aggstate)
1564 : : {
1565 : : Bitmapset *base_colnos;
1566 : : Bitmapset *aggregated_colnos;
1372 jdavis@postgresql.or 1567 : 2570 : TupleDesc scanDesc = aggstate->ss.ss_ScanTupleSlot->tts_tupleDescriptor;
2692 andres@anarazel.de 1568 : 2570 : List *outerTlist = outerPlanState(aggstate)->plan->targetlist;
2575 rhodiumtoad@postgres 1569 : 2570 : int numHashes = aggstate->num_hashes;
2250 andres@anarazel.de 1570 : 2570 : EState *estate = aggstate->ss.ps.state;
1571 : : int j;
1572 : :
1573 : : /* Find Vars that will be needed in tlist and qual */
1372 jdavis@postgresql.or 1574 : 2570 : find_cols(aggstate, &aggregated_colnos, &base_colnos);
1575 : 2570 : aggstate->colnos_needed = bms_union(base_colnos, aggregated_colnos);
1576 : 2570 : aggstate->max_colno_needed = 0;
1577 : 2570 : aggstate->all_cols_needed = true;
1578 : :
1579 [ + + ]: 11209 : for (int i = 0; i < scanDesc->natts; i++)
1580 : : {
1068 tgl@sss.pgh.pa.us 1581 : 8639 : int colno = i + 1;
1582 : :
1372 jdavis@postgresql.or 1583 [ + + ]: 8639 : if (bms_is_member(colno, aggstate->colnos_needed))
1584 : 5644 : aggstate->max_colno_needed = colno;
1585 : : else
1586 : 2995 : aggstate->all_cols_needed = false;
1587 : : }
1588 : :
2575 rhodiumtoad@postgres 1589 [ + + ]: 5337 : for (j = 0; j < numHashes; ++j)
1590 : : {
1591 : 2767 : AggStatePerHash perhash = &aggstate->perhash[j];
1592 : 2767 : Bitmapset *colnos = bms_copy(base_colnos);
1593 : 2767 : AttrNumber *grpColIdx = perhash->aggnode->grpColIdx;
1594 : 2767 : List *hashTlist = NIL;
1595 : : TupleDesc hashDesc;
1596 : : int maxCols;
1597 : : int i;
1598 : :
1599 : 2767 : perhash->largestGrpColIdx = 0;
1600 : :
1601 : : /*
1602 : : * If we're doing grouping sets, then some Vars might be referenced in
1603 : : * tlist/qual for the benefit of other grouping sets, but not needed
1604 : : * when hashing; i.e. prepare_projection_slot will null them out, so
1605 : : * there'd be no point storing them. Use prepare_projection_slot's
1606 : : * logic to determine which.
1607 : : */
1608 [ + - ]: 2767 : if (aggstate->phases[0].grouped_cols)
1609 : : {
1610 : 2767 : Bitmapset *grouped_cols = aggstate->phases[0].grouped_cols[j];
1611 : : ListCell *lc;
1612 : :
1613 [ + - + + : 7555 : foreach(lc, aggstate->all_grouped_cols)
+ + ]
1614 : : {
1615 : 4788 : int attnum = lfirst_int(lc);
1616 : :
1617 [ + + ]: 4788 : if (!bms_is_member(attnum, grouped_cols))
1618 : 504 : colnos = bms_del_member(colnos, attnum);
1619 : : }
1620 : : }
1621 : :
1622 : : /*
1623 : : * Compute maximum number of input columns accounting for possible
1624 : : * duplications in the grpColIdx array, which can happen in some edge
1625 : : * cases where HashAggregate was generated as part of a semijoin or a
1626 : : * DISTINCT.
1627 : : */
1788 1628 : 2767 : maxCols = bms_num_members(colnos) + perhash->numCols;
1629 : :
2575 1630 : 2767 : perhash->hashGrpColIdxInput =
1788 1631 : 2767 : palloc(maxCols * sizeof(AttrNumber));
2575 1632 : 2767 : perhash->hashGrpColIdxHash =
1633 : 2767 : palloc(perhash->numCols * sizeof(AttrNumber));
1634 : :
1635 : : /* Add all the grouping columns to colnos */
1788 1636 [ + + ]: 7054 : for (i = 0; i < perhash->numCols; i++)
1637 : 4287 : colnos = bms_add_member(colnos, grpColIdx[i]);
1638 : :
1639 : : /*
1640 : : * First build mapping for columns directly hashed. These are the
1641 : : * first, because they'll be accessed when computing hash values and
1642 : : * comparing tuples for exact matches. We also build simple mapping
1643 : : * for execGrouping, so it knows where to find the to-be-hashed /
1644 : : * compared columns in the input.
1645 : : */
2575 1646 [ + + ]: 7054 : for (i = 0; i < perhash->numCols; i++)
1647 : : {
1648 : 4287 : perhash->hashGrpColIdxInput[i] = grpColIdx[i];
1649 : 4287 : perhash->hashGrpColIdxHash[i] = i + 1;
1650 : 4287 : perhash->numhashGrpCols++;
1651 : : /* delete already mapped columns */
409 tgl@sss.pgh.pa.us 1652 : 4287 : colnos = bms_del_member(colnos, grpColIdx[i]);
1653 : : }
1654 : :
1655 : : /* and add the remaining columns */
1656 : 2767 : i = -1;
1657 [ + + ]: 3086 : while ((i = bms_next_member(colnos, i)) >= 0)
1658 : : {
2575 rhodiumtoad@postgres 1659 : 319 : perhash->hashGrpColIdxInput[perhash->numhashGrpCols] = i;
1660 : 319 : perhash->numhashGrpCols++;
1661 : : }
1662 : :
1663 : : /* and build a tuple descriptor for the hashtable */
1664 [ + + ]: 7373 : for (i = 0; i < perhash->numhashGrpCols; i++)
1665 : : {
1666 : 4606 : int varNumber = perhash->hashGrpColIdxInput[i] - 1;
1667 : :
1668 : 4606 : hashTlist = lappend(hashTlist, list_nth(outerTlist, varNumber));
1669 : 4606 : perhash->largestGrpColIdx =
1670 : 4606 : Max(varNumber + 1, perhash->largestGrpColIdx);
1671 : : }
1672 : :
1972 andres@anarazel.de 1673 : 2767 : hashDesc = ExecTypeFromTL(hashTlist);
1674 : :
2250 1675 : 2767 : execTuplesHashPrepare(perhash->numCols,
1676 : 2767 : perhash->aggnode->grpOperators,
1677 : : &perhash->eqfuncoids,
1678 : : &perhash->hashfunctions);
2249 1679 : 2767 : perhash->hashslot =
1977 1680 : 2767 : ExecAllocTableSlot(&estate->es_tupleTable, hashDesc,
1681 : : &TTSOpsMinimalTuple);
1682 : :
2575 rhodiumtoad@postgres 1683 : 2767 : list_free(hashTlist);
1684 : 2767 : bms_free(colnos);
1685 : : }
1686 : :
1687 : 2570 : bms_free(base_colnos);
7830 tgl@sss.pgh.pa.us 1688 : 2570 : }
1689 : :
1690 : : /*
1691 : : * Estimate per-hash-table-entry overhead.
1692 : : */
1693 : : Size
1472 jdavis@postgresql.or 1694 : 12522 : hash_agg_entry_size(int numTrans, Size tupleWidth, Size transitionSpace)
1695 : : {
1696 : : Size tupleChunkSize;
1697 : : Size pergroupChunkSize;
1698 : : Size transitionChunkSize;
1431 tgl@sss.pgh.pa.us 1699 : 12522 : Size tupleSize = (MAXALIGN(SizeofMinimalTupleHeader) +
1700 : : tupleWidth);
1701 : 12522 : Size pergroupSize = numTrans * sizeof(AggStatePerGroupData);
1702 : :
1472 jdavis@postgresql.or 1703 : 12522 : tupleChunkSize = CHUNKHDRSZ + tupleSize;
1704 : :
1705 [ + + ]: 12522 : if (pergroupSize > 0)
1706 : 5161 : pergroupChunkSize = CHUNKHDRSZ + pergroupSize;
1707 : : else
1708 : 7361 : pergroupChunkSize = 0;
1709 : :
1710 [ + + ]: 12522 : if (transitionSpace > 0)
1711 : 2366 : transitionChunkSize = CHUNKHDRSZ + transitionSpace;
1712 : : else
1713 : 10156 : transitionChunkSize = 0;
1714 : :
1715 : : return
1716 : : sizeof(TupleHashEntryData) +
1717 : 12522 : tupleChunkSize +
1718 : 12522 : pergroupChunkSize +
1719 : : transitionChunkSize;
1720 : : }
1721 : :
1722 : : /*
1723 : : * hashagg_recompile_expressions()
1724 : : *
1725 : : * Identifies the right phase, compiles the right expression given the
1726 : : * arguments, and then sets phase->evalfunc to that expression.
1727 : : *
1728 : : * Different versions of the compiled expression are needed depending on
1729 : : * whether hash aggregation has spilled or not, and whether it's reading from
1730 : : * the outer plan or a tape. Before spilling to disk, the expression reads
1731 : : * from the outer plan and does not need to perform a NULL check. After
1732 : : * HashAgg begins to spill, new groups will not be created in the hash table,
1733 : : * and the AggStatePerGroup array may be NULL; therefore we need to add a null
1734 : : * pointer check to the expression. Then, when reading spilled data from a
1735 : : * tape, we change the outer slot type to be a fixed minimal tuple slot.
1736 : : *
1737 : : * It would be wasteful to recompile every time, so cache the compiled
1738 : : * expressions in the AggStatePerPhase, and reuse when appropriate.
1739 : : */
1740 : : static void
1488 1741 : 26781 : hashagg_recompile_expressions(AggState *aggstate, bool minslot, bool nullcheck)
1742 : : {
1743 : : AggStatePerPhase phase;
1431 tgl@sss.pgh.pa.us 1744 : 26781 : int i = minslot ? 1 : 0;
1745 : 26781 : int j = nullcheck ? 1 : 0;
1746 : :
1488 jdavis@postgresql.or 1747 [ + + - + ]: 26781 : Assert(aggstate->aggstrategy == AGG_HASHED ||
1748 : : aggstate->aggstrategy == AGG_MIXED);
1749 : :
1750 [ + + ]: 26781 : if (aggstate->aggstrategy == AGG_HASHED)
1751 : 495 : phase = &aggstate->phases[0];
1752 : : else /* AGG_MIXED */
1753 : 26286 : phase = &aggstate->phases[1];
1754 : :
1755 [ + + ]: 26781 : if (phase->evaltrans_cache[i][j] == NULL)
1756 : : {
1431 tgl@sss.pgh.pa.us 1757 : 48 : const TupleTableSlotOps *outerops = aggstate->ss.ps.outerops;
1758 : 48 : bool outerfixed = aggstate->ss.ps.outeropsfixed;
1759 : 48 : bool dohash = true;
1205 jdavis@postgresql.or 1760 : 48 : bool dosort = false;
1761 : :
1762 : : /*
1763 : : * If minslot is true, that means we are processing a spilled batch
1764 : : * (inside agg_refill_hash_table()), and we must not advance the
1765 : : * sorted grouping sets.
1766 : : */
1767 [ + + + + ]: 48 : if (aggstate->aggstrategy == AGG_MIXED && !minslot)
1768 : 6 : dosort = true;
1769 : :
1770 : : /* temporarily change the outerops while compiling the expression */
1488 1771 [ + + ]: 48 : if (minslot)
1772 : : {
1773 : 24 : aggstate->ss.ps.outerops = &TTSOpsMinimalTuple;
1774 : 24 : aggstate->ss.ps.outeropsfixed = true;
1775 : : }
1776 : :
1431 tgl@sss.pgh.pa.us 1777 : 48 : phase->evaltrans_cache[i][j] = ExecBuildAggTrans(aggstate, phase,
1778 : : dosort, dohash,
1779 : : nullcheck);
1780 : :
1781 : : /* change back */
1488 jdavis@postgresql.or 1782 : 48 : aggstate->ss.ps.outerops = outerops;
1783 : 48 : aggstate->ss.ps.outeropsfixed = outerfixed;
1784 : : }
1785 : :
1786 : 26781 : phase->evaltrans = phase->evaltrans_cache[i][j];
1787 : 26781 : }
1788 : :
1789 : : /*
1790 : : * Set limits that trigger spilling to avoid exceeding hash_mem. Consider the
1791 : : * number of partitions we expect to create (if we do spill).
1792 : : *
1793 : : * There are two limits: a memory limit, and also an ngroups limit. The
1794 : : * ngroups limit becomes important when we expect transition values to grow
1795 : : * substantially larger than the initial value.
1796 : : */
1797 : : void
1356 1798 : 25039 : hash_agg_set_limits(double hashentrysize, double input_groups, int used_bits,
1799 : : Size *mem_limit, uint64 *ngroups_limit,
1800 : : int *num_partitions)
1801 : : {
1802 : : int npartitions;
1803 : : Size partition_mem;
994 tgl@sss.pgh.pa.us 1804 : 25039 : Size hash_mem_limit = get_hash_memory_limit();
1805 : :
1806 : : /* if not expected to spill, use all of hash_mem */
1807 [ + + ]: 25039 : if (input_groups * hashentrysize <= hash_mem_limit)
1808 : : {
1478 jdavis@postgresql.or 1809 [ + + ]: 23824 : if (num_partitions != NULL)
1810 : 11488 : *num_partitions = 0;
994 tgl@sss.pgh.pa.us 1811 : 23824 : *mem_limit = hash_mem_limit;
1812 : 23824 : *ngroups_limit = hash_mem_limit / hashentrysize;
1488 jdavis@postgresql.or 1813 : 23824 : return;
1814 : : }
1815 : :
1816 : : /*
1817 : : * Calculate expected memory requirements for spilling, which is the size
1818 : : * of the buffers needed for all the tapes that need to be open at once.
1819 : : * Then, subtract that from the memory available for holding hash tables.
1820 : : */
1821 : 1215 : npartitions = hash_choose_num_partitions(input_groups,
1822 : : hashentrysize,
1823 : : used_bits,
1824 : : NULL);
1825 [ + + ]: 1215 : if (num_partitions != NULL)
1826 : 45 : *num_partitions = npartitions;
1827 : :
1828 : 1215 : partition_mem =
1829 : 1215 : HASHAGG_READ_BUFFER_SIZE +
1830 : : HASHAGG_WRITE_BUFFER_SIZE * npartitions;
1831 : :
1832 : : /*
1833 : : * Don't set the limit below 3/4 of hash_mem. In that case, we are at the
1834 : : * minimum number of partitions, so we aren't going to dramatically exceed
1835 : : * work mem anyway.
1836 : : */
994 tgl@sss.pgh.pa.us 1837 [ - + ]: 1215 : if (hash_mem_limit > 4 * partition_mem)
994 tgl@sss.pgh.pa.us 1838 :UBC 0 : *mem_limit = hash_mem_limit - partition_mem;
1839 : : else
994 tgl@sss.pgh.pa.us 1840 :CBC 1215 : *mem_limit = hash_mem_limit * 0.75;
1841 : :
1488 jdavis@postgresql.or 1842 [ + - ]: 1215 : if (*mem_limit > hashentrysize)
1843 : 1215 : *ngroups_limit = *mem_limit / hashentrysize;
1844 : : else
1488 jdavis@postgresql.or 1845 :UBC 0 : *ngroups_limit = 1;
1846 : : }
1847 : :
1848 : : /*
1849 : : * hash_agg_check_limits
1850 : : *
1851 : : * After adding a new group to the hash table, check whether we need to enter
1852 : : * spill mode. Allocations may happen without adding new groups (for instance,
1853 : : * if the transition state size grows), so this check is imperfect.
1854 : : */
1855 : : static void
1488 jdavis@postgresql.or 1856 :CBC 212238 : hash_agg_check_limits(AggState *aggstate)
1857 : : {
1431 tgl@sss.pgh.pa.us 1858 : 212238 : uint64 ngroups = aggstate->hash_ngroups_current;
1859 : 212238 : Size meta_mem = MemoryContextMemAllocated(aggstate->hash_metacxt,
1860 : : true);
1356 pg@bowt.ie 1861 : 212238 : Size hashkey_mem = MemoryContextMemAllocated(aggstate->hashcontext->ecxt_per_tuple_memory,
1862 : : true);
1863 : :
1864 : : /*
1865 : : * Don't spill unless there's at least one group in the hash table so we
1866 : : * can be sure to make progress even in edge cases.
1867 : : */
1488 jdavis@postgresql.or 1868 [ + - ]: 212238 : if (aggstate->hash_ngroups_current > 0 &&
1356 pg@bowt.ie 1869 [ + + ]: 212238 : (meta_mem + hashkey_mem > aggstate->hash_mem_limit ||
1488 jdavis@postgresql.or 1870 [ + + ]: 199020 : ngroups > aggstate->hash_ngroups_limit))
1871 : : {
1872 : 13236 : hash_agg_enter_spill_mode(aggstate);
1873 : : }
1874 : 212238 : }
1875 : :
1876 : : /*
1877 : : * Enter "spill mode", meaning that no new groups are added to any of the hash
1878 : : * tables. Tuples that would create a new group are instead spilled, and
1879 : : * processed later.
1880 : : */
1881 : : static void
1882 : 13236 : hash_agg_enter_spill_mode(AggState *aggstate)
1883 : : {
1884 : 13236 : aggstate->hash_spill_mode = true;
1885 : 13236 : hashagg_recompile_expressions(aggstate, aggstate->table_filled, true);
1886 : :
1887 [ + + ]: 13236 : if (!aggstate->hash_ever_spilled)
1888 : : {
909 heikki.linnakangas@i 1889 [ - + ]: 33 : Assert(aggstate->hash_tapeset == NULL);
1488 jdavis@postgresql.or 1890 [ - + ]: 33 : Assert(aggstate->hash_spills == NULL);
1891 : :
1892 : 33 : aggstate->hash_ever_spilled = true;
1893 : :
909 heikki.linnakangas@i 1894 : 33 : aggstate->hash_tapeset = LogicalTapeSetCreate(true, NULL, -1);
1895 : :
1431 tgl@sss.pgh.pa.us 1896 : 33 : aggstate->hash_spills = palloc(sizeof(HashAggSpill) * aggstate->num_hashes);
1897 : :
1488 jdavis@postgresql.or 1898 [ + + ]: 96 : for (int setno = 0; setno < aggstate->num_hashes; setno++)
1899 : : {
1431 tgl@sss.pgh.pa.us 1900 : 63 : AggStatePerHash perhash = &aggstate->perhash[setno];
1901 : 63 : HashAggSpill *spill = &aggstate->hash_spills[setno];
1902 : :
909 heikki.linnakangas@i 1903 : 63 : hashagg_spill_init(spill, aggstate->hash_tapeset, 0,
1488 jdavis@postgresql.or 1904 : 63 : perhash->aggnode->numGroups,
1905 : : aggstate->hashentrysize);
1906 : : }
1907 : : }
1908 : 13236 : }
1909 : :
1910 : : /*
1911 : : * Update metrics after filling the hash table.
1912 : : *
1913 : : * If reading from the outer plan, from_tape should be false; if reading from
1914 : : * another tape, from_tape should be true.
1915 : : */
1916 : : static void
1917 : 15449 : hash_agg_update_metrics(AggState *aggstate, bool from_tape, int npartitions)
1918 : : {
1919 : : Size meta_mem;
1920 : : Size hashkey_mem;
1921 : : Size buffer_mem;
1922 : : Size total_mem;
1923 : :
1924 [ + + ]: 15449 : if (aggstate->aggstrategy != AGG_MIXED &&
1925 [ - + ]: 2255 : aggstate->aggstrategy != AGG_HASHED)
1488 jdavis@postgresql.or 1926 :UBC 0 : return;
1927 : :
1928 : : /* memory for the hash table itself */
1488 jdavis@postgresql.or 1929 :CBC 15449 : meta_mem = MemoryContextMemAllocated(aggstate->hash_metacxt, true);
1930 : :
1931 : : /* memory for the group keys and transition states */
1367 pg@bowt.ie 1932 : 15449 : hashkey_mem = MemoryContextMemAllocated(aggstate->hashcontext->ecxt_per_tuple_memory, true);
1933 : :
1934 : : /* memory for read/write tape buffers, if spilled */
1488 jdavis@postgresql.or 1935 : 15449 : buffer_mem = npartitions * HASHAGG_WRITE_BUFFER_SIZE;
1936 [ + + ]: 15449 : if (from_tape)
1937 : 13506 : buffer_mem += HASHAGG_READ_BUFFER_SIZE;
1938 : :
1939 : : /* update peak mem */
1367 pg@bowt.ie 1940 : 15449 : total_mem = meta_mem + hashkey_mem + buffer_mem;
1488 jdavis@postgresql.or 1941 [ + + ]: 15449 : if (total_mem > aggstate->hash_mem_peak)
1942 : 1922 : aggstate->hash_mem_peak = total_mem;
1943 : :
1944 : : /* update disk usage */
909 heikki.linnakangas@i 1945 [ + + ]: 15449 : if (aggstate->hash_tapeset != NULL)
1946 : : {
1947 : 13539 : uint64 disk_used = LogicalTapeSetBlocks(aggstate->hash_tapeset) * (BLCKSZ / 1024);
1948 : :
1488 jdavis@postgresql.or 1949 [ + + ]: 13539 : if (aggstate->hash_disk_used < disk_used)
1950 : 30 : aggstate->hash_disk_used = disk_used;
1951 : : }
1952 : :
1953 : : /* update hashentrysize estimate based on contents */
1954 [ + + ]: 15449 : if (aggstate->hash_ngroups_current > 0)
1955 : : {
1956 : 15389 : aggstate->hashentrysize =
1483 1957 : 15389 : sizeof(TupleHashEntryData) +
1367 pg@bowt.ie 1958 : 15389 : (hashkey_mem / (double) aggstate->hash_ngroups_current);
1959 : : }
1960 : : }
1961 : :
1962 : : /*
1963 : : * Choose a reasonable number of buckets for the initial hash table size.
1964 : : */
1965 : : static long
1488 jdavis@postgresql.or 1966 : 2119 : hash_choose_num_buckets(double hashentrysize, long ngroups, Size memory)
1967 : : {
1968 : : long max_nbuckets;
1431 tgl@sss.pgh.pa.us 1969 : 2119 : long nbuckets = ngroups;
1970 : :
1488 jdavis@postgresql.or 1971 : 2119 : max_nbuckets = memory / hashentrysize;
1972 : :
1973 : : /*
1974 : : * Underestimating is better than overestimating. Too many buckets crowd
1975 : : * out space for group keys and transition state values.
1976 : : */
1483 1977 : 2119 : max_nbuckets >>= 1;
1978 : :
1488 1979 [ + + ]: 2119 : if (nbuckets > max_nbuckets)
1980 : 36 : nbuckets = max_nbuckets;
1981 : :
1406 1982 : 2119 : return Max(nbuckets, 1);
1983 : : }
1984 : :
1985 : : /*
1986 : : * Determine the number of partitions to create when spilling, which will
1987 : : * always be a power of two. If log2_npartitions is non-NULL, set
1988 : : * *log2_npartitions to the log2() of the number of partitions.
1989 : : */
1990 : : static int
1356 1991 : 7533 : hash_choose_num_partitions(double input_groups, double hashentrysize,
1992 : : int used_bits, int *log2_npartitions)
1993 : : {
994 tgl@sss.pgh.pa.us 1994 : 7533 : Size hash_mem_limit = get_hash_memory_limit();
1995 : : double partition_limit;
1996 : : double mem_wanted;
1997 : : double dpartitions;
1998 : : int npartitions;
1999 : : int partition_bits;
2000 : :
2001 : : /*
2002 : : * Avoid creating so many partitions that the memory requirements of the
2003 : : * open partition files are greater than 1/4 of hash_mem.
2004 : : */
1488 jdavis@postgresql.or 2005 : 7533 : partition_limit =
994 tgl@sss.pgh.pa.us 2006 : 7533 : (hash_mem_limit * 0.25 - HASHAGG_READ_BUFFER_SIZE) /
2007 : : HASHAGG_WRITE_BUFFER_SIZE;
2008 : :
1488 jdavis@postgresql.or 2009 : 7533 : mem_wanted = HASHAGG_PARTITION_FACTOR * input_groups * hashentrysize;
2010 : :
2011 : : /* make enough partitions so that each one is likely to fit in memory */
994 tgl@sss.pgh.pa.us 2012 : 7533 : dpartitions = 1 + (mem_wanted / hash_mem_limit);
2013 : :
2014 [ + + ]: 7533 : if (dpartitions > partition_limit)
2015 : 7512 : dpartitions = partition_limit;
2016 : :
2017 [ + - ]: 7533 : if (dpartitions < HASHAGG_MIN_PARTITIONS)
2018 : 7533 : dpartitions = HASHAGG_MIN_PARTITIONS;
2019 [ - + ]: 7533 : if (dpartitions > HASHAGG_MAX_PARTITIONS)
994 tgl@sss.pgh.pa.us 2020 :UBC 0 : dpartitions = HASHAGG_MAX_PARTITIONS;
2021 : :
2022 : : /* HASHAGG_MAX_PARTITIONS limit makes this safe */
994 tgl@sss.pgh.pa.us 2023 :CBC 7533 : npartitions = (int) dpartitions;
2024 : :
2025 : : /* ceil(log2(npartitions)) */
1488 jdavis@postgresql.or 2026 : 7533 : partition_bits = my_log2(npartitions);
2027 : :
2028 : : /* make sure that we don't exhaust the hash bits */
2029 [ - + ]: 7533 : if (partition_bits + used_bits >= 32)
1488 jdavis@postgresql.or 2030 :UBC 0 : partition_bits = 32 - used_bits;
2031 : :
1488 jdavis@postgresql.or 2032 [ + + ]:CBC 7533 : if (log2_npartitions != NULL)
2033 : 6318 : *log2_npartitions = partition_bits;
2034 : :
2035 : : /* number of partitions will be a power of two */
994 tgl@sss.pgh.pa.us 2036 : 7533 : npartitions = 1 << partition_bits;
2037 : :
1488 jdavis@postgresql.or 2038 : 7533 : return npartitions;
2039 : : }
2040 : :
2041 : : /*
2042 : : * Initialize a freshly-created TupleHashEntry.
2043 : : */
2044 : : static void
1358 2045 : 212238 : initialize_hash_entry(AggState *aggstate, TupleHashTable hashtable,
2046 : : TupleHashEntry entry)
2047 : : {
2048 : : AggStatePerGroup pergroup;
2049 : : int transno;
2050 : :
2051 : 212238 : aggstate->hash_ngroups_current++;
2052 : 212238 : hash_agg_check_limits(aggstate);
2053 : :
2054 : : /* no need to allocate or initialize per-group state */
2055 [ + + ]: 212238 : if (aggstate->numtrans == 0)
2056 : 86312 : return;
2057 : :
2058 : : pergroup = (AggStatePerGroup)
2059 : 125926 : MemoryContextAlloc(hashtable->tablecxt,
2060 : 125926 : sizeof(AggStatePerGroupData) * aggstate->numtrans);
2061 : :
2062 : 125926 : entry->additional = pergroup;
2063 : :
2064 : : /*
2065 : : * Initialize aggregates for new tuple group, lookup_hash_entries()
2066 : : * already has selected the relevant grouping set.
2067 : : */
2068 [ + + ]: 325627 : for (transno = 0; transno < aggstate->numtrans; transno++)
2069 : : {
2070 : 199701 : AggStatePerTrans pertrans = &aggstate->pertrans[transno];
2071 : 199701 : AggStatePerGroup pergroupstate = &pergroup[transno];
2072 : :
2073 : 199701 : initialize_aggregate(aggstate, pertrans, pergroupstate);
2074 : : }
2075 : : }
2076 : :
2077 : : /*
2078 : : * Look up hash entries for the current tuple in all hashed grouping sets.
2079 : : *
2080 : : * Be aware that lookup_hash_entry can reset the tmpcontext.
2081 : : *
2082 : : * Some entries may be left NULL if we are in "spill mode". The same tuple
2083 : : * will belong to different groups for each grouping set, so may match a group
2084 : : * already in memory for one set and match a group not in memory for another
2085 : : * set. When in "spill mode", the tuple will be spilled for each grouping set
2086 : : * where it doesn't match a group in memory.
2087 : : *
2088 : : * NB: It's possible to spill the same tuple for several different grouping
2089 : : * sets. This may seem wasteful, but it's actually a trade-off: if we spill
2090 : : * the tuple multiple times for multiple grouping sets, it can be partitioned
2091 : : * for each grouping set, making the refilling of the hash table very
2092 : : * efficient.
2093 : : */
2094 : : static void
2575 rhodiumtoad@postgres 2095 : 2688679 : lookup_hash_entries(AggState *aggstate)
2096 : : {
2097 : 2688679 : AggStatePerGroup *pergroup = aggstate->hash_pergroup;
1358 jdavis@postgresql.or 2098 : 2688679 : TupleTableSlot *outerslot = aggstate->tmpcontext->ecxt_outertuple;
2099 : : int setno;
2100 : :
1488 2101 [ + + ]: 5444506 : for (setno = 0; setno < aggstate->num_hashes; setno++)
2102 : : {
1431 tgl@sss.pgh.pa.us 2103 : 2755827 : AggStatePerHash perhash = &aggstate->perhash[setno];
1358 jdavis@postgresql.or 2104 : 2755827 : TupleHashTable hashtable = perhash->hashtable;
2105 : 2755827 : TupleTableSlot *hashslot = perhash->hashslot;
2106 : : TupleHashEntry entry;
2107 : : uint32 hash;
2108 : 2755827 : bool isnew = false;
2109 : : bool *p_isnew;
2110 : :
2111 : : /* if hash table already spilled, don't create new entries */
2112 [ + + ]: 2755827 : p_isnew = aggstate->hash_spill_mode ? NULL : &isnew;
2113 : :
2575 rhodiumtoad@postgres 2114 : 2755827 : select_current_set(aggstate, setno, true);
1358 jdavis@postgresql.or 2115 : 2755827 : prepare_hash_slot(perhash,
2116 : : outerslot,
2117 : : hashslot);
2118 : :
2119 : 2755827 : entry = LookupTupleHashEntry(hashtable, hashslot,
2120 : : p_isnew, &hash);
2121 : :
2122 [ + + ]: 2755827 : if (entry != NULL)
2123 : : {
2124 [ + + ]: 2639409 : if (isnew)
2125 : 164124 : initialize_hash_entry(aggstate, hashtable, entry);
2126 : 2639409 : pergroup[setno] = entry->additional;
2127 : : }
2128 : : else
2129 : : {
1431 tgl@sss.pgh.pa.us 2130 : 116418 : HashAggSpill *spill = &aggstate->hash_spills[setno];
2131 : 116418 : TupleTableSlot *slot = aggstate->tmpcontext->ecxt_outertuple;
2132 : :
1488 jdavis@postgresql.or 2133 [ - + ]: 116418 : if (spill->partitions == NULL)
909 heikki.linnakangas@i 2134 :UBC 0 : hashagg_spill_init(spill, aggstate->hash_tapeset, 0,
1488 jdavis@postgresql.or 2135 : 0 : perhash->aggnode->numGroups,
2136 : : aggstate->hashentrysize);
2137 : :
1372 jdavis@postgresql.or 2138 :CBC 116418 : hashagg_spill_tuple(aggstate, spill, slot, hash);
1358 2139 : 116418 : pergroup[setno] = NULL;
2140 : : }
2141 : : }
2575 rhodiumtoad@postgres 2142 : 2688679 : }
2143 : :
2144 : : /*
2145 : : * ExecAgg -
2146 : : *
2147 : : * ExecAgg receives tuples from its outer subplan and aggregates over
2148 : : * the appropriate attribute for each aggregate function use (Aggref
2149 : : * node) appearing in the targetlist or qual of the node. The number
2150 : : * of tuples to aggregate over depends on whether grouped or plain
2151 : : * aggregation is selected. In grouped aggregation, we produce a result
2152 : : * row for each group; in plain aggregation there's a single result row
2153 : : * for the whole query. In either case, the value of each aggregate is
2154 : : * stored in the expression context to be used when ExecProject evaluates
2155 : : * the result tuple.
2156 : : */
2157 : : static TupleTableSlot *
2463 andres@anarazel.de 2158 : 405579 : ExecAgg(PlanState *pstate)
2159 : : {
2160 : 405579 : AggState *node = castNode(AggState, pstate);
2575 rhodiumtoad@postgres 2161 : 405579 : TupleTableSlot *result = NULL;
2162 : :
2455 andres@anarazel.de 2163 [ + + ]: 405579 : CHECK_FOR_INTERRUPTS();
2164 : :
3256 2165 [ + + ]: 405579 : if (!node->agg_done)
2166 : : {
2167 : : /* Dispatch based on strategy */
2575 rhodiumtoad@postgres 2168 [ + + + - ]: 377016 : switch (node->phase->aggstrategy)
2169 : : {
3256 andres@anarazel.de 2170 : 243594 : case AGG_HASHED:
2171 [ + + ]: 243594 : if (!node->table_filled)
2172 : 1880 : agg_fill_hash_table(node);
2173 : : /* FALLTHROUGH */
2174 : : case AGG_MIXED:
2175 : 257266 : result = agg_retrieve_hash_table(node);
2176 : 257266 : break;
2575 rhodiumtoad@postgres 2177 : 119750 : case AGG_PLAIN:
2178 : : case AGG_SORTED:
3256 andres@anarazel.de 2179 : 119750 : result = agg_retrieve_direct(node);
2180 : 119702 : break;
2181 : : }
2182 : :
2183 [ + + + - ]: 376968 : if (!TupIsNull(result))
2184 : 374139 : return result;
2185 : : }
2186 : :
2187 : 31392 : return NULL;
2188 : : }
2189 : :
2190 : : /*
2191 : : * ExecAgg for non-hashed case
2192 : : */
2193 : : static TupleTableSlot *
7801 tgl@sss.pgh.pa.us 2194 : 119750 : agg_retrieve_direct(AggState *aggstate)
2195 : : {
3256 andres@anarazel.de 2196 : 119750 : Agg *node = aggstate->phase->aggnode;
2197 : : ExprContext *econtext;
2198 : : ExprContext *tmpcontext;
2199 : : AggStatePerAgg peragg;
2200 : : AggStatePerGroup *pergroups;
2201 : : TupleTableSlot *outerslot;
2202 : : TupleTableSlot *firstSlot;
2203 : : TupleTableSlot *result;
2204 : 119750 : bool hasGroupingSets = aggstate->phase->numsets > 0;
2205 : 119750 : int numGroupingSets = Max(aggstate->phase->numsets, 1);
2206 : : int currentSet;
2207 : : int nextSetSize;
2208 : : int numReset;
2209 : : int i;
2210 : :
2211 : : /*
2212 : : * get state info from node
2213 : : *
2214 : : * econtext is the per-output-tuple expression context
2215 : : *
2216 : : * tmpcontext is the per-input-tuple expression context
2217 : : */
7801 tgl@sss.pgh.pa.us 2218 : 119750 : econtext = aggstate->ss.ps.ps_ExprContext;
7830 2219 : 119750 : tmpcontext = aggstate->tmpcontext;
2220 : :
8967 2221 : 119750 : peragg = aggstate->peragg;
2294 andres@anarazel.de 2222 : 119750 : pergroups = aggstate->pergroups;
7801 tgl@sss.pgh.pa.us 2223 : 119750 : firstSlot = aggstate->ss.ss_ScanTupleSlot;
2224 : :
2225 : : /*
2226 : : * We loop retrieving groups until we find one matching
2227 : : * aggstate->ss.ps.qual
2228 : : *
2229 : : * For grouping sets, we have the invariant that aggstate->projected_set
2230 : : * is either -1 (initial call) or the index (starting from 0) in
2231 : : * gset_lengths for the group we just completed (either by projecting a
2232 : : * row or by discarding it in the qual).
2233 : : */
7218 2234 [ + + ]: 155227 : while (!aggstate->agg_done)
2235 : : {
2236 : : /*
2237 : : * Clear the per-output-tuple context for each group, as well as
2238 : : * aggcontext (which contains any pass-by-ref transvalues of the old
2239 : : * group). Some aggregate functions store working state in child
2240 : : * contexts; those now get reset automatically without us needing to
2241 : : * do anything special.
2242 : : *
2243 : : * We use ReScanExprContext not just ResetExprContext because we want
2244 : : * any registered shutdown callbacks to be called. That allows
2245 : : * aggregate functions to ensure they've cleaned up any non-memory
2246 : : * resources.
2247 : : */
3256 andres@anarazel.de 2248 : 155028 : ReScanExprContext(econtext);
2249 : :
2250 : : /*
2251 : : * Determine how many grouping sets need to be reset at this boundary.
2252 : : */
2253 [ + + ]: 155028 : if (aggstate->projected_set >= 0 &&
2254 [ + + ]: 123661 : aggstate->projected_set < numGroupingSets)
2255 : 123658 : numReset = aggstate->projected_set + 1;
2256 : : else
2257 : 31370 : numReset = numGroupingSets;
2258 : :
2259 : : /*
2260 : : * numReset can change on a phase boundary, but that's OK; we want to
2261 : : * reset the contexts used in _this_ phase, and later, after possibly
2262 : : * changing phase, initialize the right number of aggregates for the
2263 : : * _new_ phase.
2264 : : */
2265 : :
2266 [ + + ]: 321177 : for (i = 0; i < numReset; i++)
2267 : : {
2268 : 166149 : ReScanExprContext(aggstate->aggcontexts[i]);
2269 : : }
2270 : :
2271 : : /*
2272 : : * Check if input is complete and there are no more groups to project
2273 : : * in this phase; move to next phase or mark as done.
2274 : : */
2275 [ + + ]: 155028 : if (aggstate->input_done == true &&
2276 [ + + ]: 762 : aggstate->projected_set >= (numGroupingSets - 1))
2277 : : {
2278 [ + + ]: 360 : if (aggstate->current_phase < aggstate->numphases - 1)
2279 : : {
2280 : 93 : initialize_phase(aggstate, aggstate->current_phase + 1);
2281 : 93 : aggstate->input_done = false;
2282 : 93 : aggstate->projected_set = -1;
2283 : 93 : numGroupingSets = Max(aggstate->phase->numsets, 1);
2284 : 93 : node = aggstate->phase->aggnode;
2285 : 93 : numReset = numGroupingSets;
2286 : : }
2575 rhodiumtoad@postgres 2287 [ + + ]: 267 : else if (aggstate->aggstrategy == AGG_MIXED)
2288 : : {
2289 : : /*
2290 : : * Mixed mode; we've output all the grouped stuff and have
2291 : : * full hashtables, so switch to outputting those.
2292 : : */
2293 : 69 : initialize_phase(aggstate, 0);
2294 : 69 : aggstate->table_filled = true;
2295 : 69 : ResetTupleHashIterator(aggstate->perhash[0].hashtable,
2296 : : &aggstate->perhash[0].hashiter);
2297 : 69 : select_current_set(aggstate, 0, true);
2298 : 69 : return agg_retrieve_hash_table(aggstate);
2299 : : }
2300 : : else
2301 : : {
7830 tgl@sss.pgh.pa.us 2302 : 198 : aggstate->agg_done = true;
3256 andres@anarazel.de 2303 : 198 : break;
2304 : : }
2305 : : }
2306 : :
2307 : : /*
2308 : : * Get the number of columns in the next grouping set after the last
2309 : : * projected one (if any). This is the number of columns to compare to
2310 : : * see if we reached the boundary of that set too.
2311 : : */
2312 [ + + ]: 154761 : if (aggstate->projected_set >= 0 &&
2313 [ + + ]: 123301 : aggstate->projected_set < (numGroupingSets - 1))
2314 : 13638 : nextSetSize = aggstate->phase->gset_lengths[aggstate->projected_set + 1];
2315 : : else
2316 : 141123 : nextSetSize = 0;
2317 : :
2318 : : /*----------
2319 : : * If a subgroup for the current grouping set is present, project it.
2320 : : *
2321 : : * We have a new group if:
2322 : : * - we're out of input but haven't projected all grouping sets
2323 : : * (checked above)
2324 : : * OR
2325 : : * - we already projected a row that wasn't from the last grouping
2326 : : * set
2327 : : * AND
2328 : : * - the next grouping set has at least one grouping column (since
2329 : : * empty grouping sets project only once input is exhausted)
2330 : : * AND
2331 : : * - the previous and pending rows differ on the grouping columns
2332 : : * of the next grouping set
2333 : : *----------
2334 : : */
2250 2335 : 154761 : tmpcontext->ecxt_innertuple = econtext->ecxt_outertuple;
3256 2336 [ + + ]: 154761 : if (aggstate->input_done ||
2575 rhodiumtoad@postgres 2337 [ + + ]: 154359 : (node->aggstrategy != AGG_PLAIN &&
3256 andres@anarazel.de 2338 [ + + ]: 123732 : aggstate->projected_set != -1 &&
2339 [ + + + + ]: 122899 : aggstate->projected_set < (numGroupingSets - 1) &&
2340 : 9970 : nextSetSize > 0 &&
2250 2341 [ + + ]: 9970 : !ExecQualAndReset(aggstate->phase->eqfunctions[nextSetSize - 1],
2342 : : tmpcontext)))
2343 : : {
3256 2344 : 7069 : aggstate->projected_set += 1;
2345 : :
2346 [ - + ]: 7069 : Assert(aggstate->projected_set < numGroupingSets);
2347 [ + + - + ]: 7069 : Assert(nextSetSize > 0 || aggstate->input_done);
2348 : : }
2349 : : else
2350 : : {
2351 : : /*
2352 : : * We no longer care what group we just projected, the next
2353 : : * projection will always be the first (or only) grouping set
2354 : : * (unless the input proves to be empty).
2355 : : */
2356 : 147692 : aggstate->projected_set = 0;
2357 : :
2358 : : /*
2359 : : * If we don't already have the first tuple of the new group,
2360 : : * fetch it from the outer plan.
2361 : : */
2362 [ + + ]: 147692 : if (aggstate->grp_firstTuple == NULL)
2363 : : {
2364 : 31460 : outerslot = fetch_input_tuple(aggstate);
2365 [ + + + + ]: 31451 : if (!TupIsNull(outerslot))
2366 : : {
2367 : : /*
2368 : : * Make a copy of the first input tuple; we will use this
2369 : : * for comparisons (in group mode) and for projection.
2370 : : */
1976 2371 : 25872 : aggstate->grp_firstTuple = ExecCopySlotHeapTuple(outerslot);
2372 : : }
2373 : : else
2374 : : {
2375 : : /* outer plan produced no tuples at all */
3256 2376 [ + + ]: 5579 : if (hasGroupingSets)
2377 : : {
2378 : : /*
2379 : : * If there was no input at all, we need to project
2380 : : * rows only if there are grouping sets of size 0.
2381 : : * Note that this implies that there can't be any
2382 : : * references to ungrouped Vars, which would otherwise
2383 : : * cause issues with the empty output slot.
2384 : : *
2385 : : * XXX: This is no longer true, we currently deal with
2386 : : * this in finalize_aggregates().
2387 : : */
2388 : 27 : aggstate->input_done = true;
2389 : :
2390 [ + + ]: 39 : while (aggstate->phase->gset_lengths[aggstate->projected_set] > 0)
2391 : : {
2392 : 15 : aggstate->projected_set += 1;
2393 [ + + ]: 15 : if (aggstate->projected_set >= numGroupingSets)
2394 : : {
2395 : : /*
2396 : : * We can't set agg_done here because we might
2397 : : * have more phases to do, even though the
2398 : : * input is empty. So we need to restart the
2399 : : * whole outer loop.
2400 : : */
2401 : 3 : break;
2402 : : }
2403 : : }
2404 : :
2405 [ + + ]: 27 : if (aggstate->projected_set >= numGroupingSets)
2406 : 3 : continue;
2407 : : }
2408 : : else
2409 : : {
2410 : 5552 : aggstate->agg_done = true;
2411 : : /* If we are grouping, we should produce no tuples too */
2412 [ + + ]: 5552 : if (node->aggstrategy != AGG_PLAIN)
2413 : 19 : return NULL;
2414 : : }
2415 : : }
2416 : : }
2417 : :
2418 : : /*
2419 : : * Initialize working state for a new input tuple group.
2420 : : */
2294 2421 : 147661 : initialize_aggregates(aggstate, pergroups, numReset);
2422 : :
3256 2423 [ + + ]: 147661 : if (aggstate->grp_firstTuple != NULL)
2424 : : {
2425 : : /*
2426 : : * Store the copied first input tuple in the tuple table slot
2427 : : * reserved for it. The tuple will be deleted when it is
2428 : : * cleared from the slot.
2429 : : */
1976 2430 : 142104 : ExecForceStoreHeapTuple(aggstate->grp_firstTuple,
2431 : : firstSlot, true);
2489 tgl@sss.pgh.pa.us 2432 : 142104 : aggstate->grp_firstTuple = NULL; /* don't keep two pointers */
2433 : :
2434 : : /* set up for first advance_aggregates call */
3256 andres@anarazel.de 2435 : 142104 : tmpcontext->ecxt_outertuple = firstSlot;
2436 : :
2437 : : /*
2438 : : * Process each outer-plan tuple, and then fetch the next one,
2439 : : * until we exhaust the outer plan or cross a group boundary.
2440 : : */
2441 : : for (;;)
2442 : : {
2443 : : /*
2444 : : * During phase 1 only of a mixed agg, we need to update
2445 : : * hashtables as well in advance_aggregates.
2446 : : */
2575 rhodiumtoad@postgres 2447 [ + + ]: 10025191 : if (aggstate->aggstrategy == AGG_MIXED &&
2448 [ + - ]: 19022 : aggstate->current_phase == 1)
2449 : : {
2287 andres@anarazel.de 2450 : 19022 : lookup_hash_entries(aggstate);
2451 : : }
2452 : :
2453 : : /* Advance the aggregates (or combine functions) */
2454 : 10025191 : advance_aggregates(aggstate);
2455 : :
2456 : : /* Reset per-input-tuple context after each tuple */
3256 2457 : 10025158 : ResetExprContext(tmpcontext);
2458 : :
2459 : 10025158 : outerslot = fetch_input_tuple(aggstate);
2460 [ + + + + ]: 10025158 : if (TupIsNull(outerslot))
2461 : : {
2462 : : /* no more outer-plan tuples available */
2463 : :
2464 : : /* if we built hash tables, finalize any spills */
1488 jdavis@postgresql.or 2465 [ + + ]: 25836 : if (aggstate->aggstrategy == AGG_MIXED &&
2466 [ + - ]: 63 : aggstate->current_phase == 1)
2467 : 63 : hashagg_finish_initial_spills(aggstate);
2468 : :
3256 andres@anarazel.de 2469 [ + + ]: 25836 : if (hasGroupingSets)
2470 : : {
2471 : 333 : aggstate->input_done = true;
2472 : 333 : break;
2473 : : }
2474 : : else
2475 : : {
2476 : 25503 : aggstate->agg_done = true;
2477 : 25503 : break;
2478 : : }
2479 : : }
2480 : : /* set up for next advance_aggregates call */
2481 : 9999322 : tmpcontext->ecxt_outertuple = outerslot;
2482 : :
2483 : : /*
2484 : : * If we are grouping, check whether we've crossed a group
2485 : : * boundary.
2486 : : */
452 tgl@sss.pgh.pa.us 2487 [ + + + + ]: 9999322 : if (node->aggstrategy != AGG_PLAIN && node->numCols > 0)
2488 : : {
2250 andres@anarazel.de 2489 : 906576 : tmpcontext->ecxt_innertuple = firstSlot;
2490 [ + + ]: 906576 : if (!ExecQual(aggstate->phase->eqfunctions[node->numCols - 1],
2491 : : tmpcontext))
2492 : : {
1976 2493 : 116235 : aggstate->grp_firstTuple = ExecCopySlotHeapTuple(outerslot);
3256 2494 : 116235 : break;
2495 : : }
2496 : : }
2497 : : }
2498 : : }
2499 : :
2500 : : /*
2501 : : * Use the representative input tuple for any references to
2502 : : * non-aggregated input columns in aggregate direct args, the node
2503 : : * qual, and the tlist. (If we are not grouping, and there are no
2504 : : * input rows at all, we will come here with an empty firstSlot
2505 : : * ... but if not grouping, there can't be any references to
2506 : : * non-aggregated input columns, so no problem.)
2507 : : */
2508 : 147628 : econtext->ecxt_outertuple = firstSlot;
2509 : : }
2510 : :
2511 [ - + ]: 154697 : Assert(aggstate->projected_set >= 0);
2512 : :
2513 : 154697 : currentSet = aggstate->projected_set;
2514 : :
2515 : 154697 : prepare_projection_slot(aggstate, econtext->ecxt_outertuple, currentSet);
2516 : :
2575 rhodiumtoad@postgres 2517 : 154697 : select_current_set(aggstate, currentSet, false);
2518 : :
2519 : 154697 : finalize_aggregates(aggstate,
2520 : : peragg,
2294 andres@anarazel.de 2521 : 154697 : pergroups[currentSet]);
2522 : :
2523 : : /*
2524 : : * If there's no row to project right now, we must continue rather
2525 : : * than returning a null since there might be more groups.
2526 : : */
3256 2527 : 154691 : result = project_aggregates(aggstate);
2528 [ + + ]: 154691 : if (result)
2529 : 119217 : return result;
2530 : : }
2531 : :
2532 : : /* No more groups */
7218 tgl@sss.pgh.pa.us 2533 : 397 : return NULL;
2534 : : }
2535 : :
2536 : : /*
2537 : : * ExecAgg for hashed case: read input and build hash table
2538 : : */
2539 : : static void
7801 2540 : 1880 : agg_fill_hash_table(AggState *aggstate)
2541 : : {
2542 : : TupleTableSlot *outerslot;
2575 rhodiumtoad@postgres 2543 : 1880 : ExprContext *tmpcontext = aggstate->tmpcontext;
2544 : :
2545 : : /*
2546 : : * Process each outer-plan tuple, and then fetch the next one, until we
2547 : : * exhaust the outer plan.
2548 : : */
2549 : : for (;;)
2550 : : {
3256 andres@anarazel.de 2551 : 2671537 : outerslot = fetch_input_tuple(aggstate);
7830 tgl@sss.pgh.pa.us 2552 [ + + + + ]: 2671537 : if (TupIsNull(outerslot))
2553 : : break;
2554 : :
2555 : : /* set up for lookup_hash_entries and advance_aggregates */
6261 2556 : 2669657 : tmpcontext->ecxt_outertuple = outerslot;
2557 : :
2558 : : /* Find or build hashtable entries */
2287 andres@anarazel.de 2559 : 2669657 : lookup_hash_entries(aggstate);
2560 : :
2561 : : /* Advance the aggregates (or combine functions) */
2562 : 2669657 : advance_aggregates(aggstate);
2563 : :
2564 : : /*
2565 : : * Reset per-input-tuple context after each tuple, but note that the
2566 : : * hash lookups do this too
2567 : : */
2575 rhodiumtoad@postgres 2568 : 2669657 : ResetExprContext(aggstate->tmpcontext);
2569 : : }
2570 : :
2571 : : /* finalize spills, if any */
1488 jdavis@postgresql.or 2572 : 1880 : hashagg_finish_initial_spills(aggstate);
2573 : :
7830 tgl@sss.pgh.pa.us 2574 : 1880 : aggstate->table_filled = true;
2575 : : /* Initialize to walk the first hash table */
2575 rhodiumtoad@postgres 2576 : 1880 : select_current_set(aggstate, 0, true);
2577 : 1880 : ResetTupleHashIterator(aggstate->perhash[0].hashtable,
2578 : : &aggstate->perhash[0].hashiter);
7830 tgl@sss.pgh.pa.us 2579 : 1880 : }
2580 : :
2581 : : /*
2582 : : * If any data was spilled during hash aggregation, reset the hash table and
2583 : : * reprocess one batch of spilled data. After reprocessing a batch, the hash
2584 : : * table will again contain data, ready to be consumed by
2585 : : * agg_retrieve_hash_table_in_memory().
2586 : : *
2587 : : * Should only be called after all in memory hash table entries have been
2588 : : * finalized and emitted.
2589 : : *
2590 : : * Return false when input is exhausted and there's no more work to be done;
2591 : : * otherwise return true.
2592 : : */
2593 : : static bool
1488 jdavis@postgresql.or 2594 : 15919 : agg_refill_hash_table(AggState *aggstate)
2595 : : {
2596 : : HashAggBatch *batch;
2597 : : AggStatePerHash perhash;
2598 : : HashAggSpill spill;
909 heikki.linnakangas@i 2599 : 15919 : LogicalTapeSet *tapeset = aggstate->hash_tapeset;
1431 tgl@sss.pgh.pa.us 2600 : 15919 : bool spill_initialized = false;
2601 : :
1488 jdavis@postgresql.or 2602 [ + + ]: 15919 : if (aggstate->hash_batches == NIL)
2603 : 2413 : return false;
2604 : :
2605 : : /* hash_batches is a stack, with the top item at the end of the list */
895 tgl@sss.pgh.pa.us 2606 : 13506 : batch = llast(aggstate->hash_batches);
2607 : 13506 : aggstate->hash_batches = list_delete_last(aggstate->hash_batches);
2608 : :
1356 jdavis@postgresql.or 2609 : 13506 : hash_agg_set_limits(aggstate->hashentrysize, batch->input_card,
2610 : : batch->used_bits, &aggstate->hash_mem_limit,
2611 : : &aggstate->hash_ngroups_limit, NULL);
2612 : :
2613 : : /*
2614 : : * Each batch only processes one grouping set; set the rest to NULL so
2615 : : * that advance_aggregates() knows to ignore them. We don't touch
2616 : : * pergroups for sorted grouping sets here, because they will be needed if
2617 : : * we rescan later. The expressions for sorted grouping sets will not be
2618 : : * evaluated after we recompile anyway.
2619 : : */
1205 2620 [ + - + - : 103782 : MemSet(aggstate->hash_pergroup, 0,
+ - + - +
+ ]
2621 : : sizeof(AggStatePerGroup) * aggstate->num_hashes);
2622 : :
2623 : : /* free memory and reset hash tables */
1488 2624 : 13506 : ReScanExprContext(aggstate->hashcontext);
2625 [ + + ]: 103782 : for (int setno = 0; setno < aggstate->num_hashes; setno++)
2626 : 90276 : ResetTupleHashTable(aggstate->perhash[setno].hashtable);
2627 : :
2628 : 13506 : aggstate->hash_ngroups_current = 0;
2629 : :
2630 : : /*
2631 : : * In AGG_MIXED mode, hash aggregation happens in phase 1 and the output
2632 : : * happens in phase 0. So, we switch to phase 1 when processing a batch,
2633 : : * and back to phase 0 after the batch is done.
2634 : : */
2635 [ - + ]: 13506 : Assert(aggstate->current_phase == 0);
2636 [ + + ]: 13506 : if (aggstate->phase->aggstrategy == AGG_MIXED)
2637 : : {
2638 : 13131 : aggstate->current_phase = 1;
2639 : 13131 : aggstate->phase = &aggstate->phases[aggstate->current_phase];
2640 : : }
2641 : :
2642 : 13506 : select_current_set(aggstate, batch->setno, true);
2643 : :
1358 2644 : 13506 : perhash = &aggstate->perhash[aggstate->current_set];
2645 : :
2646 : : /*
2647 : : * Spilled tuples are always read back as MinimalTuples, which may be
2648 : : * different from the outer plan, so recompile the aggregate expressions.
2649 : : *
2650 : : * We still need the NULL check, because we are only processing one
2651 : : * grouping set at a time and the rest will be NULL.
2652 : : */
1488 2653 : 13506 : hashagg_recompile_expressions(aggstate, true, true);
2654 : :
2655 : : for (;;)
1431 tgl@sss.pgh.pa.us 2656 : 337434 : {
1358 jdavis@postgresql.or 2657 : 350940 : TupleTableSlot *spillslot = aggstate->hash_spill_rslot;
2658 : 350940 : TupleTableSlot *hashslot = perhash->hashslot;
2659 : : TupleHashEntry entry;
2660 : : MinimalTuple tuple;
2661 : : uint32 hash;
2662 : 350940 : bool isnew = false;
2663 [ + + ]: 350940 : bool *p_isnew = aggstate->hash_spill_mode ? NULL : &isnew;
2664 : :
1488 2665 [ - + ]: 350940 : CHECK_FOR_INTERRUPTS();
2666 : :
2667 : 350940 : tuple = hashagg_batch_read(batch, &hash);
2668 [ + + ]: 350940 : if (tuple == NULL)
2669 : 13506 : break;
2670 : :
1358 2671 : 337434 : ExecStoreMinimalTuple(tuple, spillslot, true);
2672 : 337434 : aggstate->tmpcontext->ecxt_outertuple = spillslot;
2673 : :
2674 : 337434 : prepare_hash_slot(perhash,
2675 : 337434 : aggstate->tmpcontext->ecxt_outertuple,
2676 : : hashslot);
702 alvherre@alvh.no-ip. 2677 : 337434 : entry = LookupTupleHashEntryHash(perhash->hashtable, hashslot,
2678 : : p_isnew, hash);
2679 : :
1358 jdavis@postgresql.or 2680 [ + + ]: 337434 : if (entry != NULL)
2681 : : {
2682 [ + + ]: 116418 : if (isnew)
2683 : 48114 : initialize_hash_entry(aggstate, perhash->hashtable, entry);
2684 : 116418 : aggstate->hash_pergroup[batch->setno] = entry->additional;
1488 2685 : 116418 : advance_aggregates(aggstate);
2686 : : }
2687 : : else
2688 : : {
2689 [ + + ]: 221016 : if (!spill_initialized)
2690 : : {
2691 : : /*
2692 : : * Avoid initializing the spill until we actually need it so
2693 : : * that we don't assign tapes that will never be used.
2694 : : */
2695 : 6255 : spill_initialized = true;
909 heikki.linnakangas@i 2696 : 6255 : hashagg_spill_init(&spill, tapeset, batch->used_bits,
2697 : : batch->input_card, aggstate->hashentrysize);
2698 : : }
2699 : : /* no memory for a new group, spill */
1358 jdavis@postgresql.or 2700 : 221016 : hashagg_spill_tuple(aggstate, &spill, spillslot, hash);
2701 : :
2702 : 221016 : aggstate->hash_pergroup[batch->setno] = NULL;
2703 : : }
2704 : :
2705 : : /*
2706 : : * Reset per-input-tuple context after each tuple, but note that the
2707 : : * hash lookups do this too
2708 : : */
1488 2709 : 337434 : ResetExprContext(aggstate->tmpcontext);
2710 : : }
2711 : :
909 heikki.linnakangas@i 2712 : 13506 : LogicalTapeClose(batch->input_tape);
2713 : :
2714 : : /* change back to phase 0 */
1488 jdavis@postgresql.or 2715 : 13506 : aggstate->current_phase = 0;
2716 : 13506 : aggstate->phase = &aggstate->phases[aggstate->current_phase];
2717 : :
2718 [ + + ]: 13506 : if (spill_initialized)
2719 : : {
2720 : 6255 : hashagg_spill_finish(aggstate, &spill, batch->setno);
1307 2721 : 6255 : hash_agg_update_metrics(aggstate, true, spill.npartitions);
2722 : : }
2723 : : else
1488 2724 : 7251 : hash_agg_update_metrics(aggstate, true, 0);
2725 : :
2726 : 13506 : aggstate->hash_spill_mode = false;
2727 : :
2728 : : /* prepare to walk the first hash table */
2729 : 13506 : select_current_set(aggstate, batch->setno, true);
2730 : 13506 : ResetTupleHashIterator(aggstate->perhash[batch->setno].hashtable,
2731 : : &aggstate->perhash[batch->setno].hashiter);
2732 : :
2733 : 13506 : pfree(batch);
2734 : :
2735 : 13506 : return true;
2736 : : }
2737 : :
2738 : : /*
2739 : : * ExecAgg for hashed case: retrieving groups from hash table
2740 : : *
2741 : : * After exhausting in-memory tuples, also try refilling the hash table using
2742 : : * previously-spilled tuples. Only returns NULL after all in-memory and
2743 : : * spilled tuples are exhausted.
2744 : : */
2745 : : static TupleTableSlot *
7801 tgl@sss.pgh.pa.us 2746 : 257335 : agg_retrieve_hash_table(AggState *aggstate)
2747 : : {
1488 jdavis@postgresql.or 2748 : 257335 : TupleTableSlot *result = NULL;
2749 : :
2750 [ + + ]: 525763 : while (result == NULL)
2751 : : {
2752 : 270841 : result = agg_retrieve_hash_table_in_memory(aggstate);
2753 [ + + ]: 270841 : if (result == NULL)
2754 : : {
2755 [ + + ]: 15919 : if (!agg_refill_hash_table(aggstate))
2756 : : {
2757 : 2413 : aggstate->agg_done = true;
2758 : 2413 : break;
2759 : : }
2760 : : }
2761 : : }
2762 : :
2763 : 257335 : return result;
2764 : : }
2765 : :
2766 : : /*
2767 : : * Retrieve the groups from the in-memory hash tables without considering any
2768 : : * spilled tuples.
2769 : : */
2770 : : static TupleTableSlot *
2771 : 270841 : agg_retrieve_hash_table_in_memory(AggState *aggstate)
2772 : : {
2773 : : ExprContext *econtext;
2774 : : AggStatePerAgg peragg;
2775 : : AggStatePerGroup pergroup;
2776 : : TupleHashEntryData *entry;
2777 : : TupleTableSlot *firstSlot;
2778 : : TupleTableSlot *result;
2779 : : AggStatePerHash perhash;
2780 : :
2781 : : /*
2782 : : * get state info from node.
2783 : : *
2784 : : * econtext is the per-output-tuple expression context.
2785 : : */
7801 tgl@sss.pgh.pa.us 2786 : 270841 : econtext = aggstate->ss.ps.ps_ExprContext;
7830 2787 : 270841 : peragg = aggstate->peragg;
7801 2788 : 270841 : firstSlot = aggstate->ss.ss_ScanTupleSlot;
2789 : :
2790 : : /*
2791 : : * Note that perhash (and therefore anything accessed through it) can
2792 : : * change inside the loop, as we change between grouping sets.
2793 : : */
2575 rhodiumtoad@postgres 2794 : 270841 : perhash = &aggstate->perhash[aggstate->current_set];
2795 : :
2796 : : /*
2797 : : * We loop retrieving groups until we find one satisfying
2798 : : * aggstate->ss.ps.qual
2799 : : */
2800 : : for (;;)
7830 tgl@sss.pgh.pa.us 2801 : 67926 : {
2575 rhodiumtoad@postgres 2802 : 338767 : TupleTableSlot *hashslot = perhash->hashslot;
2803 : : int i;
2804 : :
2455 andres@anarazel.de 2805 [ + + ]: 338767 : CHECK_FOR_INTERRUPTS();
2806 : :
2807 : : /*
2808 : : * Find the next entry in the hash table
2809 : : */
2575 rhodiumtoad@postgres 2810 : 338767 : entry = ScanTupleHashTable(perhash->hashtable, &perhash->hashiter);
7765 tgl@sss.pgh.pa.us 2811 [ + + ]: 338767 : if (entry == NULL)
2812 : : {
2575 rhodiumtoad@postgres 2813 : 66035 : int nextset = aggstate->current_set + 1;
2814 : :
2815 [ + + ]: 66035 : if (nextset < aggstate->num_hashes)
2816 : : {
2817 : : /*
2818 : : * Switch to next grouping set, reinitialize, and restart the
2819 : : * loop.
2820 : : */
2821 : 50116 : select_current_set(aggstate, nextset, true);
2822 : :
2823 : 50116 : perhash = &aggstate->perhash[aggstate->current_set];
2824 : :
2825 : 50116 : ResetTupleHashIterator(perhash->hashtable, &perhash->hashiter);
2826 : :
2827 : 50116 : continue;
2828 : : }
2829 : : else
2830 : : {
2831 : 15919 : return NULL;
2832 : : }
2833 : : }
2834 : :
2835 : : /*
2836 : : * Clear the per-output-tuple context for each group
2837 : : *
2838 : : * We intentionally don't use ReScanExprContext here; if any aggs have
2839 : : * registered shutdown callbacks, they mustn't be called yet, since we
2840 : : * might not be done with that agg.
2841 : : */
7830 tgl@sss.pgh.pa.us 2842 : 272732 : ResetExprContext(econtext);
2843 : :
2844 : : /*
2845 : : * Transform representative tuple back into one with the right
2846 : : * columns.
2847 : : */
2692 andres@anarazel.de 2848 : 272732 : ExecStoreMinimalTuple(entry->firstTuple, hashslot, false);
2849 : 272732 : slot_getallattrs(hashslot);
2850 : :
2851 : 272732 : ExecClearTuple(firstSlot);
2852 : 272732 : memset(firstSlot->tts_isnull, true,
2853 : 272732 : firstSlot->tts_tupleDescriptor->natts * sizeof(bool));
2854 : :
2575 rhodiumtoad@postgres 2855 [ + + ]: 842247 : for (i = 0; i < perhash->numhashGrpCols; i++)
2856 : : {
2857 : 569515 : int varNumber = perhash->hashGrpColIdxInput[i] - 1;
2858 : :
2692 andres@anarazel.de 2859 : 569515 : firstSlot->tts_values[varNumber] = hashslot->tts_values[i];
2860 : 569515 : firstSlot->tts_isnull[varNumber] = hashslot->tts_isnull[i];
2861 : : }
2862 : 272732 : ExecStoreVirtualTuple(firstSlot);
2863 : :
2739 2864 : 272732 : pergroup = (AggStatePerGroup) entry->additional;
2865 : :
2866 : : /*
2867 : : * Use the representative input tuple for any references to
2868 : : * non-aggregated input columns in the qual and tlist.
2869 : : */
6261 tgl@sss.pgh.pa.us 2870 : 272732 : econtext->ecxt_outertuple = firstSlot;
2871 : :
2575 rhodiumtoad@postgres 2872 : 272732 : prepare_projection_slot(aggstate,
2873 : : econtext->ecxt_outertuple,
2874 : : aggstate->current_set);
2875 : :
2876 : 272732 : finalize_aggregates(aggstate, peragg, pergroup);
2877 : :
3256 andres@anarazel.de 2878 : 272732 : result = project_aggregates(aggstate);
2879 [ + + ]: 272732 : if (result)
2880 : 254922 : return result;
2881 : : }
2882 : :
2883 : : /* No more groups */
2884 : : return NULL;
2885 : : }
2886 : :
2887 : : /*
2888 : : * hashagg_spill_init
2889 : : *
2890 : : * Called after we determined that spilling is necessary. Chooses the number
2891 : : * of partitions to create, and initializes them.
2892 : : */
2893 : : static void
909 heikki.linnakangas@i 2894 : 6318 : hashagg_spill_init(HashAggSpill *spill, LogicalTapeSet *tapeset, int used_bits,
2895 : : double input_groups, double hashentrysize)
2896 : : {
2897 : : int npartitions;
2898 : : int partition_bits;
2899 : :
1431 tgl@sss.pgh.pa.us 2900 : 6318 : npartitions = hash_choose_num_partitions(input_groups, hashentrysize,
2901 : : used_bits, &partition_bits);
2902 : :
909 heikki.linnakangas@i 2903 : 6318 : spill->partitions = palloc0(sizeof(LogicalTape *) * npartitions);
1488 jdavis@postgresql.or 2904 : 6318 : spill->ntuples = palloc0(sizeof(int64) * npartitions);
1356 2905 : 6318 : spill->hll_card = palloc0(sizeof(hyperLogLogState) * npartitions);
2906 : :
909 heikki.linnakangas@i 2907 [ + + ]: 31590 : for (int i = 0; i < npartitions; i++)
2908 : 25272 : spill->partitions[i] = LogicalTapeCreate(tapeset);
2909 : :
1488 jdavis@postgresql.or 2910 : 6318 : spill->shift = 32 - used_bits - partition_bits;
2911 : 6318 : spill->mask = (npartitions - 1) << spill->shift;
2912 : 6318 : spill->npartitions = npartitions;
2913 : :
1356 2914 [ + + ]: 31590 : for (int i = 0; i < npartitions; i++)
2915 : 25272 : initHyperLogLog(&spill->hll_card[i], HASHAGG_HLL_BIT_WIDTH);
1488 2916 : 6318 : }
2917 : :
2918 : : /*
2919 : : * hashagg_spill_tuple
2920 : : *
2921 : : * No room for new groups in the hash table. Save for later in the appropriate
2922 : : * partition.
2923 : : */
2924 : : static Size
1372 2925 : 337434 : hashagg_spill_tuple(AggState *aggstate, HashAggSpill *spill,
2926 : : TupleTableSlot *inputslot, uint32 hash)
2927 : : {
2928 : : TupleTableSlot *spillslot;
2929 : : int partition;
2930 : : MinimalTuple tuple;
2931 : : LogicalTape *tape;
1431 tgl@sss.pgh.pa.us 2932 : 337434 : int total_written = 0;
2933 : : bool shouldFree;
2934 : :
1488 jdavis@postgresql.or 2935 [ - + ]: 337434 : Assert(spill->partitions != NULL);
2936 : :
2937 : : /* spill only attributes that we actually need */
1372 2938 [ + + ]: 337434 : if (!aggstate->all_cols_needed)
2939 : : {
2940 : 2454 : spillslot = aggstate->hash_spill_wslot;
2941 : 2454 : slot_getsomeattrs(inputslot, aggstate->max_colno_needed);
2942 : 2454 : ExecClearTuple(spillslot);
2943 [ + + ]: 7362 : for (int i = 0; i < spillslot->tts_tupleDescriptor->natts; i++)
2944 : : {
2945 [ + + ]: 4908 : if (bms_is_member(i + 1, aggstate->colnos_needed))
2946 : : {
2947 : 2454 : spillslot->tts_values[i] = inputslot->tts_values[i];
2948 : 2454 : spillslot->tts_isnull[i] = inputslot->tts_isnull[i];
2949 : : }
2950 : : else
2951 : 2454 : spillslot->tts_isnull[i] = true;
2952 : : }
2953 : 2454 : ExecStoreVirtualTuple(spillslot);
2954 : : }
2955 : : else
2956 : 334980 : spillslot = inputslot;
2957 : :
2958 : 337434 : tuple = ExecFetchSlotMinimalTuple(spillslot, &shouldFree);
2959 : :
1488 2960 : 337434 : partition = (hash & spill->mask) >> spill->shift;
2961 : 337434 : spill->ntuples[partition]++;
2962 : :
2963 : : /*
2964 : : * All hash values destined for a given partition have some bits in
2965 : : * common, which causes bad HLL cardinality estimates. Hash the hash to
2966 : : * get a more uniform distribution.
2967 : : */
1356 2968 : 337434 : addHyperLogLog(&spill->hll_card[partition], hash_bytes_uint32(hash));
2969 : :
909 heikki.linnakangas@i 2970 : 337434 : tape = spill->partitions[partition];
2971 : :
471 peter@eisentraut.org 2972 : 337434 : LogicalTapeWrite(tape, &hash, sizeof(uint32));
1488 jdavis@postgresql.or 2973 : 337434 : total_written += sizeof(uint32);
2974 : :
471 peter@eisentraut.org 2975 : 337434 : LogicalTapeWrite(tape, tuple, tuple->t_len);
1488 jdavis@postgresql.or 2976 : 337434 : total_written += tuple->t_len;
2977 : :
2978 [ + + ]: 337434 : if (shouldFree)
2979 : 116418 : pfree(tuple);
2980 : :
2981 : 337434 : return total_written;
2982 : : }
2983 : :
2984 : : /*
2985 : : * hashagg_batch_new
2986 : : *
2987 : : * Construct a HashAggBatch item, which represents one iteration of HashAgg to
2988 : : * be done.
2989 : : */
2990 : : static HashAggBatch *
909 heikki.linnakangas@i 2991 : 13506 : hashagg_batch_new(LogicalTape *input_tape, int setno,
2992 : : int64 input_tuples, double input_card, int used_bits)
2993 : : {
1488 jdavis@postgresql.or 2994 : 13506 : HashAggBatch *batch = palloc0(sizeof(HashAggBatch));
2995 : :
2996 : 13506 : batch->setno = setno;
2997 : 13506 : batch->used_bits = used_bits;
909 heikki.linnakangas@i 2998 : 13506 : batch->input_tape = input_tape;
1488 jdavis@postgresql.or 2999 : 13506 : batch->input_tuples = input_tuples;
1356 3000 : 13506 : batch->input_card = input_card;
3001 : :
1488 3002 : 13506 : return batch;
3003 : : }
3004 : :
3005 : : /*
3006 : : * hashagg_batch_read
3007 : : * read the next tuple from a batch's tape. Return NULL if no more.
3008 : : */
3009 : : static MinimalTuple
3010 : 350940 : hashagg_batch_read(HashAggBatch *batch, uint32 *hashp)
3011 : : {
909 heikki.linnakangas@i 3012 : 350940 : LogicalTape *tape = batch->input_tape;
3013 : : MinimalTuple tuple;
3014 : : uint32 t_len;
3015 : : size_t nread;
3016 : : uint32 hash;
3017 : :
3018 : 350940 : nread = LogicalTapeRead(tape, &hash, sizeof(uint32));
1488 jdavis@postgresql.or 3019 [ + + ]: 350940 : if (nread == 0)
3020 : 13506 : return NULL;
3021 [ - + ]: 337434 : if (nread != sizeof(uint32))
1488 jdavis@postgresql.or 3022 [ # # ]:UBC 0 : ereport(ERROR,
3023 : : (errcode_for_file_access(),
3024 : : errmsg_internal("unexpected EOF for tape %p: requested %zu bytes, read %zu bytes",
3025 : : tape, sizeof(uint32), nread)));
1488 jdavis@postgresql.or 3026 [ + - ]:CBC 337434 : if (hashp != NULL)
3027 : 337434 : *hashp = hash;
3028 : :
909 heikki.linnakangas@i 3029 : 337434 : nread = LogicalTapeRead(tape, &t_len, sizeof(t_len));
1488 jdavis@postgresql.or 3030 [ - + ]: 337434 : if (nread != sizeof(uint32))
1488 jdavis@postgresql.or 3031 [ # # ]:UBC 0 : ereport(ERROR,
3032 : : (errcode_for_file_access(),
3033 : : errmsg_internal("unexpected EOF for tape %p: requested %zu bytes, read %zu bytes",
3034 : : tape, sizeof(uint32), nread)));
3035 : :
1488 jdavis@postgresql.or 3036 :CBC 337434 : tuple = (MinimalTuple) palloc(t_len);
3037 : 337434 : tuple->t_len = t_len;
3038 : :
909 heikki.linnakangas@i 3039 : 337434 : nread = LogicalTapeRead(tape,
3040 : : (char *) tuple + sizeof(uint32),
3041 : : t_len - sizeof(uint32));
1488 jdavis@postgresql.or 3042 [ - + ]: 337434 : if (nread != t_len - sizeof(uint32))
1488 jdavis@postgresql.or 3043 [ # # ]:UBC 0 : ereport(ERROR,
3044 : : (errcode_for_file_access(),
3045 : : errmsg_internal("unexpected EOF for tape %p: requested %zu bytes, read %zu bytes",
3046 : : tape, t_len - sizeof(uint32), nread)));
3047 : :
1488 jdavis@postgresql.or 3048 :CBC 337434 : return tuple;
3049 : : }
3050 : :
3051 : : /*
3052 : : * hashagg_finish_initial_spills
3053 : : *
3054 : : * After a HashAggBatch has been processed, it may have spilled tuples to
3055 : : * disk. If so, turn the spilled partitions into new batches that must later
3056 : : * be executed.
3057 : : */
3058 : : static void
3059 : 1943 : hashagg_finish_initial_spills(AggState *aggstate)
3060 : : {
3061 : : int setno;
1431 tgl@sss.pgh.pa.us 3062 : 1943 : int total_npartitions = 0;
3063 : :
1488 jdavis@postgresql.or 3064 [ + + ]: 1943 : if (aggstate->hash_spills != NULL)
3065 : : {
3066 [ + + ]: 96 : for (setno = 0; setno < aggstate->num_hashes; setno++)
3067 : : {
3068 : 63 : HashAggSpill *spill = &aggstate->hash_spills[setno];
3069 : :
3070 : 63 : total_npartitions += spill->npartitions;
3071 : 63 : hashagg_spill_finish(aggstate, spill, setno);
3072 : : }
3073 : :
3074 : : /*
3075 : : * We're not processing tuples from outer plan any more; only
3076 : : * processing batches of spilled tuples. The initial spill structures
3077 : : * are no longer needed.
3078 : : */
3079 : 33 : pfree(aggstate->hash_spills);
3080 : 33 : aggstate->hash_spills = NULL;
3081 : : }
3082 : :
3083 : 1943 : hash_agg_update_metrics(aggstate, false, total_npartitions);
3084 : 1943 : aggstate->hash_spill_mode = false;
3085 : 1943 : }
3086 : :
3087 : : /*
3088 : : * hashagg_spill_finish
3089 : : *
3090 : : * Transform spill partitions into new batches.
3091 : : */
3092 : : static void
3093 : 6318 : hashagg_spill_finish(AggState *aggstate, HashAggSpill *spill, int setno)
3094 : : {
3095 : : int i;
1431 tgl@sss.pgh.pa.us 3096 : 6318 : int used_bits = 32 - spill->shift;
3097 : :
1488 jdavis@postgresql.or 3098 [ - + ]: 6318 : if (spill->npartitions == 0)
1431 tgl@sss.pgh.pa.us 3099 :UBC 0 : return; /* didn't spill */
3100 : :
1488 jdavis@postgresql.or 3101 [ + + ]:CBC 31590 : for (i = 0; i < spill->npartitions; i++)
3102 : : {
909 heikki.linnakangas@i 3103 : 25272 : LogicalTape *tape = spill->partitions[i];
3104 : : HashAggBatch *new_batch;
3105 : : double cardinality;
3106 : :
3107 : : /* if the partition is empty, don't create a new batch of work */
1488 jdavis@postgresql.or 3108 [ + + ]: 25272 : if (spill->ntuples[i] == 0)
3109 : 11766 : continue;
3110 : :
1356 3111 : 13506 : cardinality = estimateHyperLogLog(&spill->hll_card[i]);
3112 : 13506 : freeHyperLogLog(&spill->hll_card[i]);
3113 : :
3114 : : /* rewinding frees the buffer while not in use */
909 heikki.linnakangas@i 3115 : 13506 : LogicalTapeRewindForRead(tape, HASHAGG_READ_BUFFER_SIZE);
3116 : :
3117 : 13506 : new_batch = hashagg_batch_new(tape, setno,
1307 jdavis@postgresql.or 3118 : 13506 : spill->ntuples[i], cardinality,
3119 : : used_bits);
895 tgl@sss.pgh.pa.us 3120 : 13506 : aggstate->hash_batches = lappend(aggstate->hash_batches, new_batch);
1488 jdavis@postgresql.or 3121 : 13506 : aggstate->hash_batches_used++;
3122 : : }
3123 : :
3124 : 6318 : pfree(spill->ntuples);
1356 3125 : 6318 : pfree(spill->hll_card);
1488 3126 : 6318 : pfree(spill->partitions);
3127 : : }
3128 : :
3129 : : /*
3130 : : * Free resources related to a spilled HashAgg.
3131 : : */
3132 : : static void
3133 : 21541 : hashagg_reset_spill_state(AggState *aggstate)
3134 : : {
3135 : : /* free spills from initial pass */
3136 [ - + ]: 21541 : if (aggstate->hash_spills != NULL)
3137 : : {
3138 : : int setno;
3139 : :
1488 jdavis@postgresql.or 3140 [ # # ]:UBC 0 : for (setno = 0; setno < aggstate->num_hashes; setno++)
3141 : : {
3142 : 0 : HashAggSpill *spill = &aggstate->hash_spills[setno];
3143 : :
3144 : 0 : pfree(spill->ntuples);
3145 : 0 : pfree(spill->partitions);
3146 : : }
3147 : 0 : pfree(aggstate->hash_spills);
3148 : 0 : aggstate->hash_spills = NULL;
3149 : : }
3150 : :
3151 : : /* free batches */
895 tgl@sss.pgh.pa.us 3152 :CBC 21541 : list_free_deep(aggstate->hash_batches);
1488 jdavis@postgresql.or 3153 : 21541 : aggstate->hash_batches = NIL;
3154 : :
3155 : : /* close tape set */
909 heikki.linnakangas@i 3156 [ + + ]: 21541 : if (aggstate->hash_tapeset != NULL)
3157 : : {
3158 : 33 : LogicalTapeSetClose(aggstate->hash_tapeset);
3159 : 33 : aggstate->hash_tapeset = NULL;
3160 : : }
1488 jdavis@postgresql.or 3161 : 21541 : }
3162 : :
3163 : :
3164 : : /* -----------------
3165 : : * ExecInitAgg
3166 : : *
3167 : : * Creates the run-time information for the agg node produced by the
3168 : : * planner and initializes its outer subtree.
3169 : : *
3170 : : * -----------------
3171 : : */
3172 : : AggState *
6620 tgl@sss.pgh.pa.us 3173 : 21558 : ExecInitAgg(Agg *node, EState *estate, int eflags)
3174 : : {
3175 : : AggState *aggstate;
3176 : : AggStatePerAgg peraggs;
3177 : : AggStatePerTrans pertransstates;
3178 : : AggStatePerGroup *pergroups;
3179 : : Plan *outerPlan;
3180 : : ExprContext *econtext;
3181 : : TupleDesc scanDesc;
3182 : : int max_aggno;
3183 : : int max_transno;
3184 : : int numaggrefs;
3185 : : int numaggs;
3186 : : int numtrans;
3187 : : int phase;
3188 : : int phaseidx;
3189 : : ListCell *l;
3256 andres@anarazel.de 3190 : 21558 : Bitmapset *all_grouped_cols = NULL;
3191 : 21558 : int numGroupingSets = 1;
3192 : : int numPhases;
3193 : : int numHashes;
3194 : 21558 : int i = 0;
3195 : 21558 : int j = 0;
2575 rhodiumtoad@postgres 3196 [ + + ]: 40644 : bool use_hashing = (node->aggstrategy == AGG_HASHED ||
3197 [ + + ]: 19086 : node->aggstrategy == AGG_MIXED);
3198 : :
3199 : : /* check for unsupported flags */
6620 tgl@sss.pgh.pa.us 3200 [ - + ]: 21558 : Assert(!(eflags & (EXEC_FLAG_BACKWARD | EXEC_FLAG_MARK)));
3201 : :
3202 : : /*
3203 : : * create state structure
3204 : : */
9716 bruce@momjian.us 3205 : 21558 : aggstate = makeNode(AggState);
7801 tgl@sss.pgh.pa.us 3206 : 21558 : aggstate->ss.ps.plan = (Plan *) node;
3207 : 21558 : aggstate->ss.ps.state = estate;
2463 andres@anarazel.de 3208 : 21558 : aggstate->ss.ps.ExecProcNode = ExecAgg;
3209 : :
7801 tgl@sss.pgh.pa.us 3210 : 21558 : aggstate->aggs = NIL;
3211 : 21558 : aggstate->numaggs = 0;
3176 heikki.linnakangas@i 3212 : 21558 : aggstate->numtrans = 0;
2575 rhodiumtoad@postgres 3213 : 21558 : aggstate->aggstrategy = node->aggstrategy;
2849 tgl@sss.pgh.pa.us 3214 : 21558 : aggstate->aggsplit = node->aggsplit;
3256 andres@anarazel.de 3215 : 21558 : aggstate->maxsets = 0;
3216 : 21558 : aggstate->projected_set = -1;
3217 : 21558 : aggstate->current_set = 0;
7830 tgl@sss.pgh.pa.us 3218 : 21558 : aggstate->peragg = NULL;
3176 heikki.linnakangas@i 3219 : 21558 : aggstate->pertrans = NULL;
2376 tgl@sss.pgh.pa.us 3220 : 21558 : aggstate->curperagg = NULL;
3176 heikki.linnakangas@i 3221 : 21558 : aggstate->curpertrans = NULL;
3256 andres@anarazel.de 3222 : 21558 : aggstate->input_done = false;
2849 tgl@sss.pgh.pa.us 3223 : 21558 : aggstate->agg_done = false;
2294 andres@anarazel.de 3224 : 21558 : aggstate->pergroups = NULL;
7830 tgl@sss.pgh.pa.us 3225 : 21558 : aggstate->grp_firstTuple = NULL;
3256 andres@anarazel.de 3226 : 21558 : aggstate->sort_in = NULL;
3227 : 21558 : aggstate->sort_out = NULL;
3228 : :
3229 : : /*
3230 : : * phases[0] always exists, but is dummy in sorted/plain mode
3231 : : */
2575 rhodiumtoad@postgres 3232 [ + + ]: 21558 : numPhases = (use_hashing ? 1 : 2);
3233 : 21558 : numHashes = (use_hashing ? 1 : 0);
3234 : :
3235 : : /*
3236 : : * Calculate the maximum number of grouping sets in any phase; this
3237 : : * determines the size of some allocations. Also calculate the number of
3238 : : * phases, since all hashed/mixed nodes contribute to only a single phase.
3239 : : */
3256 andres@anarazel.de 3240 [ + + ]: 21558 : if (node->groupingSets)
3241 : : {
3242 : 358 : numGroupingSets = list_length(node->groupingSets);
3243 : :
3244 [ + + + + : 767 : foreach(l, node->chain)
+ + ]
3245 : : {
3249 bruce@momjian.us 3246 : 409 : Agg *agg = lfirst(l);
3247 : :
3256 andres@anarazel.de 3248 [ + + ]: 409 : numGroupingSets = Max(numGroupingSets,
3249 : : list_length(agg->groupingSets));
3250 : :
3251 : : /*
3252 : : * additional AGG_HASHED aggs become part of phase 0, but all
3253 : : * others add an extra phase.
3254 : : */
2575 rhodiumtoad@postgres 3255 [ + + ]: 409 : if (agg->aggstrategy != AGG_HASHED)
3256 : 212 : ++numPhases;
3257 : : else
3258 : 197 : ++numHashes;
3259 : : }
3260 : : }
3261 : :
3256 andres@anarazel.de 3262 : 21558 : aggstate->maxsets = numGroupingSets;
2575 rhodiumtoad@postgres 3263 : 21558 : aggstate->numphases = numPhases;
3264 : :
3256 andres@anarazel.de 3265 : 21558 : aggstate->aggcontexts = (ExprContext **)
3266 : 21558 : palloc0(sizeof(ExprContext *) * numGroupingSets);
3267 : :
3268 : : /*
3269 : : * Create expression contexts. We need three or more, one for
3270 : : * per-input-tuple processing, one for per-output-tuple processing, one
3271 : : * for all the hashtables, and one for each grouping set. The per-tuple
3272 : : * memory context of the per-grouping-set ExprContexts (aggcontexts)
3273 : : * replaces the standalone memory context formerly used to hold transition
3274 : : * values. We cheat a little by using ExecAssignExprContext() to build
3275 : : * all of them.
3276 : : *
3277 : : * NOTE: the details of what is stored in aggcontexts and what is stored
3278 : : * in the regular per-query memory context are driven by a simple
3279 : : * decision: we want to reset the aggcontext at group boundaries (if not
3280 : : * hashing) and in ExecReScanAgg to recover no-longer-wanted space.
3281 : : */
3282 : 21558 : ExecAssignExprContext(estate, &aggstate->ss.ps);
3283 : 21558 : aggstate->tmpcontext = aggstate->ss.ps.ps_ExprContext;
3284 : :
3285 [ + + ]: 43530 : for (i = 0; i < numGroupingSets; ++i)
3286 : : {
3287 : 21972 : ExecAssignExprContext(estate, &aggstate->ss.ps);
3288 : 21972 : aggstate->aggcontexts[i] = aggstate->ss.ps.ps_ExprContext;
3289 : : }
3290 : :
2575 rhodiumtoad@postgres 3291 [ + + ]: 21558 : if (use_hashing)
1468 jdavis@postgresql.or 3292 : 2570 : aggstate->hashcontext = CreateWorkExprContext(estate);
3293 : :
3256 andres@anarazel.de 3294 : 21558 : ExecAssignExprContext(estate, &aggstate->ss.ps);
3295 : :
3296 : : /*
3297 : : * Initialize child nodes.
3298 : : *
3299 : : * If we are doing a hashed aggregation then the child plan does not need
3300 : : * to handle REWIND efficiently; see ExecReScanAgg.
3301 : : */
6620 tgl@sss.pgh.pa.us 3302 [ + + ]: 21558 : if (node->aggstrategy == AGG_HASHED)
3303 : 2472 : eflags &= ~EXEC_FLAG_REWIND;
7801 3304 : 21558 : outerPlan = outerPlan(node);
6620 3305 : 21558 : outerPlanState(aggstate) = ExecInitNode(outerPlan, estate, eflags);
3306 : :
3307 : : /*
3308 : : * initialize source tuple type.
3309 : : */
1725 andres@anarazel.de 3310 : 21558 : aggstate->ss.ps.outerops =
3311 : 21558 : ExecGetResultSlotOps(outerPlanState(&aggstate->ss),
3312 : : &aggstate->ss.ps.outeropsfixed);
3313 : 21558 : aggstate->ss.ps.outeropsset = true;
3314 : :
1977 3315 : 21558 : ExecCreateScanSlotFromOuterPlan(estate, &aggstate->ss,
3316 : : aggstate->ss.ps.outerops);
2250 3317 : 21558 : scanDesc = aggstate->ss.ss_ScanTupleSlot->tts_tupleDescriptor;
3318 : :
3319 : : /*
3320 : : * If there are more than two phases (including a potential dummy phase
3321 : : * 0), input will be resorted using tuplesort. Need a slot for that.
3322 : : */
1725 3323 [ + + ]: 21558 : if (numPhases > 2)
3324 : : {
1977 3325 : 93 : aggstate->sort_slot = ExecInitExtraTupleSlot(estate, scanDesc,
3326 : : &TTSOpsMinimalTuple);
3327 : :
3328 : : /*
3329 : : * The output of the tuplesort, and the output from the outer child
3330 : : * might not use the same type of slot. In most cases the child will
3331 : : * be a Sort, and thus return a TTSOpsMinimalTuple type slot - but the
3332 : : * input can also be presorted due an index, in which case it could be
3333 : : * a different type of slot.
3334 : : *
3335 : : * XXX: For efficiency it would be good to instead/additionally
3336 : : * generate expressions with corresponding settings of outerops* for
3337 : : * the individual phases - deforming is often a bottleneck for
3338 : : * aggregations with lots of rows per group. If there's multiple
3339 : : * sorts, we know that all but the first use TTSOpsMinimalTuple (via
3340 : : * the nodeAgg.c internal tuplesort).
3341 : : */
1725 3342 [ + - ]: 93 : if (aggstate->ss.ps.outeropsfixed &&
3343 [ + + ]: 93 : aggstate->ss.ps.outerops != &TTSOpsMinimalTuple)
3344 : 12 : aggstate->ss.ps.outeropsfixed = false;
3345 : : }
3346 : :
3347 : : /*
3348 : : * Initialize result type, slot and projection.
3349 : : */
1977 3350 : 21558 : ExecInitResultTupleSlotTL(&aggstate->ss.ps, &TTSOpsVirtual);
6281 tgl@sss.pgh.pa.us 3351 : 21558 : ExecAssignProjectionInfo(&aggstate->ss.ps, NULL);
3352 : :
3353 : : /*
3354 : : * initialize child expressions
3355 : : *
3356 : : * We expect the parser to have checked that no aggs contain other agg
3357 : : * calls in their arguments (and just to be sure, we verify it again while
3358 : : * initializing the plan node). This would make no sense under SQL
3359 : : * semantics, and it's forbidden by the spec. Because it is true, we
3360 : : * don't need to worry about evaluating the aggs in any particular order.
3361 : : *
3362 : : * Note: execExpr.c finds Aggrefs for us, and adds them to aggstate->aggs.
3363 : : * Aggrefs in the qual are found here; Aggrefs in the targetlist are found
3364 : : * during ExecAssignProjectionInfo, above.
3365 : : */
2249 andres@anarazel.de 3366 : 21558 : aggstate->ss.ps.qual =
3367 : 21558 : ExecInitQual(node->plan.qual, (PlanState *) aggstate);
3368 : :
3369 : : /*
3370 : : * We should now have found all Aggrefs in the targetlist and quals.
3371 : : */
1237 heikki.linnakangas@i 3372 : 21558 : numaggrefs = list_length(aggstate->aggs);
3373 : 21558 : max_aggno = -1;
3374 : 21558 : max_transno = -1;
3375 [ + + + + : 45909 : foreach(l, aggstate->aggs)
+ + ]
3376 : : {
3377 : 24351 : Aggref *aggref = (Aggref *) lfirst(l);
3378 : :
3379 : 24351 : max_aggno = Max(max_aggno, aggref->aggno);
3380 : 24351 : max_transno = Max(max_transno, aggref->aggtransno);
3381 : : }
3382 : 21558 : numaggs = max_aggno + 1;
3383 : 21558 : numtrans = max_transno + 1;
3384 : :
3385 : : /*
3386 : : * For each phase, prepare grouping set data and fmgr lookup data for
3387 : : * compare functions. Accumulate all_grouped_cols in passing.
3388 : : */
3256 andres@anarazel.de 3389 : 21558 : aggstate->phases = palloc0(numPhases * sizeof(AggStatePerPhaseData));
3390 : :
2575 rhodiumtoad@postgres 3391 : 21558 : aggstate->num_hashes = numHashes;
3392 [ + + ]: 21558 : if (numHashes)
3393 : : {
3394 : 2570 : aggstate->perhash = palloc0(sizeof(AggStatePerHashData) * numHashes);
3395 : 2570 : aggstate->phases[0].numsets = 0;
3396 : 2570 : aggstate->phases[0].gset_lengths = palloc(numHashes * sizeof(int));
3397 : 2570 : aggstate->phases[0].grouped_cols = palloc(numHashes * sizeof(Bitmapset *));
3398 : : }
3399 : :
3400 : 21558 : phase = 0;
3401 [ + + ]: 43525 : for (phaseidx = 0; phaseidx <= list_length(node->chain); ++phaseidx)
3402 : : {
3403 : : Agg *aggnode;
3404 : : Sort *sortnode;
3405 : :
3406 [ + + ]: 21967 : if (phaseidx > 0)
3407 : : {
2561 tgl@sss.pgh.pa.us 3408 : 409 : aggnode = list_nth_node(Agg, node->chain, phaseidx - 1);
647 3409 : 409 : sortnode = castNode(Sort, outerPlan(aggnode));
3410 : : }
3411 : : else
3412 : : {
3256 andres@anarazel.de 3413 : 21558 : aggnode = node;
3414 : 21558 : sortnode = NULL;
3415 : : }
3416 : :
2575 rhodiumtoad@postgres 3417 [ + + - + ]: 21967 : Assert(phase <= 1 || sortnode);
3418 : :
3419 [ + + ]: 21967 : if (aggnode->aggstrategy == AGG_HASHED
3420 [ + + ]: 19298 : || aggnode->aggstrategy == AGG_MIXED)
3256 andres@anarazel.de 3421 : 2767 : {
2575 rhodiumtoad@postgres 3422 : 2767 : AggStatePerPhase phasedata = &aggstate->phases[0];
3423 : : AggStatePerHash perhash;
3424 : 2767 : Bitmapset *cols = NULL;
3425 : :
3426 [ - + ]: 2767 : Assert(phase == 0);
3427 : 2767 : i = phasedata->numsets++;
3428 : 2767 : perhash = &aggstate->perhash[i];
3429 : :
3430 : : /* phase 0 always points to the "real" Agg in the hash case */
3431 : 2767 : phasedata->aggnode = node;
3432 : 2767 : phasedata->aggstrategy = node->aggstrategy;
3433 : :
3434 : : /* but the actual Agg node representing this hash is saved here */
3435 : 2767 : perhash->aggnode = aggnode;
3436 : :
3437 : 2767 : phasedata->gset_lengths[i] = perhash->numCols = aggnode->numCols;
3438 : :
3439 [ + + ]: 7054 : for (j = 0; j < aggnode->numCols; ++j)
3440 : 4287 : cols = bms_add_member(cols, aggnode->grpColIdx[j]);
3441 : :
3442 : 2767 : phasedata->grouped_cols[i] = cols;
3443 : :
3444 : 2767 : all_grouped_cols = bms_add_members(all_grouped_cols, cols);
3445 : 2767 : continue;
3446 : : }
3447 : : else
3448 : : {
3449 : 19200 : AggStatePerPhase phasedata = &aggstate->phases[++phase];
3450 : : int num_sets;
3451 : :
3452 : 19200 : phasedata->numsets = num_sets = list_length(aggnode->groupingSets);
3453 : :
3454 [ + + ]: 19200 : if (num_sets)
3455 : : {
3456 : 431 : phasedata->gset_lengths = palloc(num_sets * sizeof(int));
3457 : 431 : phasedata->grouped_cols = palloc(num_sets * sizeof(Bitmapset *));
3458 : :
3459 : 431 : i = 0;
3460 [ + - + + : 1312 : foreach(l, aggnode->groupingSets)
+ + ]
3461 : : {
3462 : 881 : int current_length = list_length(lfirst(l));
3463 : 881 : Bitmapset *cols = NULL;
3464 : :
3465 : : /* planner forces this to be correct */
3466 [ + + ]: 1749 : for (j = 0; j < current_length; ++j)
3467 : 868 : cols = bms_add_member(cols, aggnode->grpColIdx[j]);
3468 : :
3469 : 881 : phasedata->grouped_cols[i] = cols;
3470 : 881 : phasedata->gset_lengths[i] = current_length;
3471 : :
3472 : 881 : ++i;
3473 : : }
3474 : :
3475 : 431 : all_grouped_cols = bms_add_members(all_grouped_cols,
2489 tgl@sss.pgh.pa.us 3476 : 431 : phasedata->grouped_cols[0]);
3477 : : }
3478 : : else
3479 : : {
2575 rhodiumtoad@postgres 3480 [ - + ]: 18769 : Assert(phaseidx == 0);
3481 : :
3482 : 18769 : phasedata->gset_lengths = NULL;
3483 : 18769 : phasedata->grouped_cols = NULL;
3484 : : }
3485 : :
3486 : : /*
3487 : : * If we are grouping, precompute fmgr lookup data for inner loop.
3488 : : */
3489 [ + + ]: 19200 : if (aggnode->aggstrategy == AGG_SORTED)
3490 : : {
3491 : : /*
3492 : : * Build a separate function for each subset of columns that
3493 : : * need to be compared.
3494 : : */
3495 : 1109 : phasedata->eqfunctions =
2250 andres@anarazel.de 3496 : 1109 : (ExprState **) palloc0(aggnode->numCols * sizeof(ExprState *));
3497 : :
3498 : : /* for each grouping set */
557 drowley@postgresql.o 3499 [ + + ]: 1869 : for (int k = 0; k < phasedata->numsets; k++)
3500 : : {
3501 : 760 : int length = phasedata->gset_lengths[k];
3502 : :
3503 : : /* nothing to do for empty grouping set */
468 tgl@sss.pgh.pa.us 3504 [ + + ]: 760 : if (length == 0)
3505 : 163 : continue;
3506 : :
3507 : : /* if we already had one of this length, it'll do */
2250 andres@anarazel.de 3508 [ + + ]: 597 : if (phasedata->eqfunctions[length - 1] != NULL)
3509 : 69 : continue;
3510 : :
3511 : 528 : phasedata->eqfunctions[length - 1] =
3512 : 528 : execTuplesMatchPrepare(scanDesc,
3513 : : length,
3514 : 528 : aggnode->grpColIdx,
3515 : 528 : aggnode->grpOperators,
1850 peter@eisentraut.org 3516 : 528 : aggnode->grpCollations,
3517 : : (PlanState *) aggstate);
3518 : : }
3519 : :
3520 : : /* and for all grouped columns, unless already computed */
452 tgl@sss.pgh.pa.us 3521 [ + + ]: 1109 : if (aggnode->numCols > 0 &&
3522 [ + + ]: 1062 : phasedata->eqfunctions[aggnode->numCols - 1] == NULL)
3523 : : {
2250 andres@anarazel.de 3524 : 716 : phasedata->eqfunctions[aggnode->numCols - 1] =
3525 : 716 : execTuplesMatchPrepare(scanDesc,
3526 : : aggnode->numCols,
3527 : 716 : aggnode->grpColIdx,
3528 : 716 : aggnode->grpOperators,
1850 peter@eisentraut.org 3529 : 716 : aggnode->grpCollations,
3530 : : (PlanState *) aggstate);
3531 : : }
3532 : : }
3533 : :
2575 rhodiumtoad@postgres 3534 : 19200 : phasedata->aggnode = aggnode;
3535 : 19200 : phasedata->aggstrategy = aggnode->aggstrategy;
3536 : 19200 : phasedata->sortnode = sortnode;
3537 : : }
3538 : : }
3539 : :
3540 : : /*
3541 : : * Convert all_grouped_cols to a descending-order list.
3542 : : */
3256 andres@anarazel.de 3543 : 21558 : i = -1;
3544 [ + + ]: 26122 : while ((i = bms_next_member(all_grouped_cols, i)) >= 0)
3545 : 4564 : aggstate->all_grouped_cols = lcons_int(i, aggstate->all_grouped_cols);
3546 : :
3547 : : /*
3548 : : * Set up aggregate-result storage in the output expr context, and also
3549 : : * allocate my private per-agg working storage
3550 : : */
7801 tgl@sss.pgh.pa.us 3551 : 21558 : econtext = aggstate->ss.ps.ps_ExprContext;
7823 bruce@momjian.us 3552 : 21558 : econtext->ecxt_aggvalues = (Datum *) palloc0(sizeof(Datum) * numaggs);
3553 : 21558 : econtext->ecxt_aggnulls = (bool *) palloc0(sizeof(bool) * numaggs);
3554 : :
3176 heikki.linnakangas@i 3555 : 21558 : peraggs = (AggStatePerAgg) palloc0(sizeof(AggStatePerAggData) * numaggs);
1237 3556 : 21558 : pertransstates = (AggStatePerTrans) palloc0(sizeof(AggStatePerTransData) * numtrans);
3557 : :
3176 3558 : 21558 : aggstate->peragg = peraggs;
3559 : 21558 : aggstate->pertrans = pertransstates;
3560 : :
3561 : :
2287 andres@anarazel.de 3562 : 21558 : aggstate->all_pergroups =
3563 : 21558 : (AggStatePerGroup *) palloc0(sizeof(AggStatePerGroup)
3564 : 21558 : * (numGroupingSets + numHashes));
3565 : 21558 : pergroups = aggstate->all_pergroups;
3566 : :
3567 [ + + ]: 21558 : if (node->aggstrategy != AGG_HASHED)
3568 : : {
3569 [ + + ]: 38586 : for (i = 0; i < numGroupingSets; i++)
3570 : : {
3571 : 19500 : pergroups[i] = (AggStatePerGroup) palloc0(sizeof(AggStatePerGroupData)
3572 : : * numaggs);
3573 : : }
3574 : :
3575 : 19086 : aggstate->pergroups = pergroups;
3576 : 19086 : pergroups += numGroupingSets;
3577 : : }
3578 : :
3579 : : /*
3580 : : * Hashing can only appear in the initial phase.
3581 : : */
2575 rhodiumtoad@postgres 3582 [ + + ]: 21558 : if (use_hashing)
3583 : : {
1431 tgl@sss.pgh.pa.us 3584 : 2570 : Plan *outerplan = outerPlan(node);
3585 : 2570 : uint64 totalGroups = 0;
3586 : :
3587 : 2570 : aggstate->hash_metacxt = AllocSetContextCreate(aggstate->ss.ps.state->es_query_cxt,
3588 : : "HashAgg meta context",
3589 : : ALLOCSET_DEFAULT_SIZES);
1372 jdavis@postgresql.or 3590 : 2570 : aggstate->hash_spill_rslot = ExecInitExtraTupleSlot(estate, scanDesc,
3591 : : &TTSOpsMinimalTuple);
3592 : 2570 : aggstate->hash_spill_wslot = ExecInitExtraTupleSlot(estate, scanDesc,
3593 : : &TTSOpsVirtual);
3594 : :
3595 : : /* this is an array of pointers, not structures */
2287 andres@anarazel.de 3596 : 2570 : aggstate->hash_pergroup = pergroups;
3597 : :
1431 tgl@sss.pgh.pa.us 3598 : 5140 : aggstate->hashentrysize = hash_agg_entry_size(aggstate->numtrans,
3599 : 2570 : outerplan->plan_width,
3600 : : node->transitionSpace);
3601 : :
3602 : : /*
3603 : : * Consider all of the grouping sets together when setting the limits
3604 : : * and estimating the number of partitions. This can be inaccurate
3605 : : * when there is more than one grouping set, but should still be
3606 : : * reasonable.
3607 : : */
557 drowley@postgresql.o 3608 [ + + ]: 5337 : for (int k = 0; k < aggstate->num_hashes; k++)
3609 : 2767 : totalGroups += aggstate->perhash[k].aggnode->numGroups;
3610 : :
1488 jdavis@postgresql.or 3611 : 2570 : hash_agg_set_limits(aggstate->hashentrysize, totalGroups, 0,
3612 : : &aggstate->hash_mem_limit,
3613 : : &aggstate->hash_ngroups_limit,
3614 : : &aggstate->hash_planned_partitions);
2575 rhodiumtoad@postgres 3615 : 2570 : find_hash_columns(aggstate);
3616 : :
3617 : : /* Skip massive memory allocation if we are just doing EXPLAIN */
1243 heikki.linnakangas@i 3618 [ + + ]: 2570 : if (!(eflags & EXEC_FLAG_EXPLAIN_ONLY))
3619 : 2007 : build_hash_tables(aggstate);
3620 : :
7830 tgl@sss.pgh.pa.us 3621 : 2570 : aggstate->table_filled = false;
3622 : :
3623 : : /* Initialize this to 1, meaning nothing spilled, yet */
1355 drowley@postgresql.o 3624 : 2570 : aggstate->hash_batches_used = 1;
3625 : : }
3626 : :
3627 : : /*
3628 : : * Initialize current phase-dependent values to initial phase. The initial
3629 : : * phase is 1 (first sort pass) for all strategies that use sorting (if
3630 : : * hashing is being done too, then phase 0 is processed last); but if only
3631 : : * hashing is being done, then phase 0 is all there is.
3632 : : */
2575 rhodiumtoad@postgres 3633 [ + + ]: 21558 : if (node->aggstrategy == AGG_HASHED)
3634 : : {
3635 : 2472 : aggstate->current_phase = 0;
3636 : 2472 : initialize_phase(aggstate, 0);
3637 : 2472 : select_current_set(aggstate, 0, true);
3638 : : }
3639 : : else
3640 : : {
3641 : 19086 : aggstate->current_phase = 1;
3642 : 19086 : initialize_phase(aggstate, 1);
3643 : 19086 : select_current_set(aggstate, 0, false);
3644 : : }
3645 : :
3646 : : /*
3647 : : * Perform lookups of aggregate function info, and initialize the
3648 : : * unchanging fields of the per-agg and per-trans data.
3649 : : */
7263 neilc@samurai.com 3650 [ + + + + : 45906 : foreach(l, aggstate->aggs)
+ + ]
3651 : : {
1237 heikki.linnakangas@i 3652 : 24351 : Aggref *aggref = lfirst(l);
3653 : : AggStatePerAgg peragg;
3654 : : AggStatePerTrans pertrans;
3655 : : Oid aggTransFnInputTypes[FUNC_MAX_ARGS];
3656 : : int numAggTransFnArgs;
3657 : : int numDirectArgs;
3658 : : HeapTuple aggTuple;
3659 : : Form_pg_aggregate aggform;
3660 : : AclResult aclresult;
3661 : : Oid finalfn_oid;
3662 : : Oid serialfn_oid,
3663 : : deserialfn_oid;
3664 : : Oid aggOwner;
3665 : : Expr *finalfnexpr;
3666 : : Oid aggtranstype;
3667 : :
3668 : : /* Planner should have assigned aggregate to correct level */
7618 tgl@sss.pgh.pa.us 3669 [ - + ]: 24351 : Assert(aggref->agglevelsup == 0);
3670 : : /* ... and the split mode should match */
2849 3671 [ - + ]: 24351 : Assert(aggref->aggsplit == aggstate->aggsplit);
3672 : :
1237 heikki.linnakangas@i 3673 : 24351 : peragg = &peraggs[aggref->aggno];
3674 : :
3675 : : /* Check if we initialized the state for this aggregate already. */
3676 [ + + ]: 24351 : if (peragg->aggref != NULL)
7740 tgl@sss.pgh.pa.us 3677 : 224 : continue;
3678 : :
3176 heikki.linnakangas@i 3679 : 24127 : peragg->aggref = aggref;
1237 3680 : 24127 : peragg->transno = aggref->aggtransno;
3681 : :
3682 : : /* Fetch the pg_aggregate row */
5173 rhaas@postgresql.org 3683 : 24127 : aggTuple = SearchSysCache1(AGGFNOID,
3684 : : ObjectIdGetDatum(aggref->aggfnoid));
8967 tgl@sss.pgh.pa.us 3685 [ - + ]: 24127 : if (!HeapTupleIsValid(aggTuple))
7573 tgl@sss.pgh.pa.us 3686 [ # # ]:UBC 0 : elog(ERROR, "cache lookup failed for aggregate %u",
3687 : : aggref->aggfnoid);
8967 tgl@sss.pgh.pa.us 3688 :CBC 24127 : aggform = (Form_pg_aggregate) GETSTRUCT(aggTuple);
3689 : :
3690 : : /* Check permission to call aggregate function */
518 peter@eisentraut.org 3691 : 24127 : aclresult = object_aclcheck(ProcedureRelationId, aggref->aggfnoid, GetUserId(),
3692 : : ACL_EXECUTE);
8021 tgl@sss.pgh.pa.us 3693 [ + + ]: 24127 : if (aclresult != ACLCHECK_OK)
2325 peter_e@gmx.net 3694 : 3 : aclcheck_error(aclresult, OBJECT_AGGREGATE,
7562 tgl@sss.pgh.pa.us 3695 : 3 : get_func_name(aggref->aggfnoid));
4020 rhaas@postgresql.org 3696 [ - + ]: 24124 : InvokeFunctionExecuteHook(aggref->aggfnoid);
3697 : :
3698 : : /* planner recorded transition state type in the Aggref itself */
2858 tgl@sss.pgh.pa.us 3699 : 24124 : aggtranstype = aggref->aggtranstype;
3700 [ - + ]: 24124 : Assert(OidIsValid(aggtranstype));
3701 : :
3702 : : /* Final function only required if we're finalizing the aggregates */
2849 3703 [ + + ]: 24124 : if (DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit))
3007 rhaas@postgresql.org 3704 : 2128 : peragg->finalfn_oid = finalfn_oid = InvalidOid;
3705 : : else
2849 tgl@sss.pgh.pa.us 3706 : 21996 : peragg->finalfn_oid = finalfn_oid = aggform->aggfinalfn;
3707 : :
2938 rhaas@postgresql.org 3708 : 24124 : serialfn_oid = InvalidOid;
3709 : 24124 : deserialfn_oid = InvalidOid;
3710 : :
3711 : : /*
3712 : : * Check if serialization/deserialization is required. We only do it
3713 : : * for aggregates that have transtype INTERNAL.
3714 : : */
2849 tgl@sss.pgh.pa.us 3715 [ + + ]: 24124 : if (aggtranstype == INTERNALOID)
3716 : : {
3717 : : /*
3718 : : * The planner should only have generated a serialize agg node if
3719 : : * every aggregate with an INTERNAL state has a serialization
3720 : : * function. Verify that.
3721 : : */
3722 [ + + ]: 10392 : if (DO_AGGSPLIT_SERIALIZE(aggstate->aggsplit))
3723 : : {
3724 : : /* serialization only valid when not running finalfn */
3725 [ - + ]: 168 : Assert(DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit));
3726 : :
3727 [ - + ]: 168 : if (!OidIsValid(aggform->aggserialfn))
2849 tgl@sss.pgh.pa.us 3728 [ # # ]:UBC 0 : elog(ERROR, "serialfunc not provided for serialization aggregation");
2938 rhaas@postgresql.org 3729 :CBC 168 : serialfn_oid = aggform->aggserialfn;
3730 : : }
3731 : :
3732 : : /* Likewise for deserialization functions */
2849 tgl@sss.pgh.pa.us 3733 [ + + ]: 10392 : if (DO_AGGSPLIT_DESERIALIZE(aggstate->aggsplit))
3734 : : {
3735 : : /* deserialization only valid when combining states */
3736 [ - + ]: 60 : Assert(DO_AGGSPLIT_COMBINE(aggstate->aggsplit));
3737 : :
3738 [ - + ]: 60 : if (!OidIsValid(aggform->aggdeserialfn))
2849 tgl@sss.pgh.pa.us 3739 [ # # ]:UBC 0 : elog(ERROR, "deserialfunc not provided for deserialization aggregation");
2938 rhaas@postgresql.org 3740 :CBC 60 : deserialfn_oid = aggform->aggdeserialfn;
3741 : : }
3742 : : }
3743 : :
3744 : : /* Check that aggregate owner has permission to call component fns */
3745 : : {
3746 : : HeapTuple procTuple;
3747 : :
5173 3748 : 24124 : procTuple = SearchSysCache1(PROCOID,
3749 : : ObjectIdGetDatum(aggref->aggfnoid));
7017 tgl@sss.pgh.pa.us 3750 [ - + ]: 24124 : if (!HeapTupleIsValid(procTuple))
7017 tgl@sss.pgh.pa.us 3751 [ # # ]:UBC 0 : elog(ERROR, "cache lookup failed for function %u",
3752 : : aggref->aggfnoid);
7017 tgl@sss.pgh.pa.us 3753 :CBC 24124 : aggOwner = ((Form_pg_proc) GETSTRUCT(procTuple))->proowner;
3754 : 24124 : ReleaseSysCache(procTuple);
3755 : :
3756 [ + + ]: 24124 : if (OidIsValid(finalfn_oid))
3757 : : {
518 peter@eisentraut.org 3758 : 11101 : aclresult = object_aclcheck(ProcedureRelationId, finalfn_oid, aggOwner,
3759 : : ACL_EXECUTE);
7017 tgl@sss.pgh.pa.us 3760 [ - + ]: 11101 : if (aclresult != ACLCHECK_OK)
2325 peter_e@gmx.net 3761 :UBC 0 : aclcheck_error(aclresult, OBJECT_FUNCTION,
7017 tgl@sss.pgh.pa.us 3762 : 0 : get_func_name(finalfn_oid));
4020 rhaas@postgresql.org 3763 [ - + ]:CBC 11101 : InvokeFunctionExecuteHook(finalfn_oid);
3764 : : }
2938 3765 [ + + ]: 24124 : if (OidIsValid(serialfn_oid))
3766 : : {
518 peter@eisentraut.org 3767 : 168 : aclresult = object_aclcheck(ProcedureRelationId, serialfn_oid, aggOwner,
3768 : : ACL_EXECUTE);
2938 rhaas@postgresql.org 3769 [ - + ]: 168 : if (aclresult != ACLCHECK_OK)
2325 peter_e@gmx.net 3770 :UBC 0 : aclcheck_error(aclresult, OBJECT_FUNCTION,
2938 rhaas@postgresql.org 3771 : 0 : get_func_name(serialfn_oid));
2938 rhaas@postgresql.org 3772 [ - + ]:CBC 168 : InvokeFunctionExecuteHook(serialfn_oid);
3773 : : }
3774 [ + + ]: 24124 : if (OidIsValid(deserialfn_oid))
3775 : : {
518 peter@eisentraut.org 3776 : 60 : aclresult = object_aclcheck(ProcedureRelationId, deserialfn_oid, aggOwner,
3777 : : ACL_EXECUTE);
2938 rhaas@postgresql.org 3778 [ - + ]: 60 : if (aclresult != ACLCHECK_OK)
2325 peter_e@gmx.net 3779 :UBC 0 : aclcheck_error(aclresult, OBJECT_FUNCTION,
2938 rhaas@postgresql.org 3780 : 0 : get_func_name(deserialfn_oid));
2938 rhaas@postgresql.org 3781 [ - + ]:CBC 60 : InvokeFunctionExecuteHook(deserialfn_oid);
3782 : : }
3783 : : }
3784 : :
3785 : : /*
3786 : : * Get actual datatypes of the (nominal) aggregate inputs. These
3787 : : * could be different from the agg's declared input types, when the
3788 : : * agg accepts ANY or a polymorphic type.
3789 : : */
1015 drowley@postgresql.o 3790 : 24124 : numAggTransFnArgs = get_aggregate_argtypes(aggref,
3791 : : aggTransFnInputTypes);
3792 : :
3793 : : /* Count the "direct" arguments, if any */
3765 tgl@sss.pgh.pa.us 3794 : 24124 : numDirectArgs = list_length(aggref->aggdirectargs);
3795 : :
3796 : : /* Detect how many arguments to pass to the finalfn */
3176 heikki.linnakangas@i 3797 [ + + ]: 24124 : if (aggform->aggfinalextra)
1015 drowley@postgresql.o 3798 : 7634 : peragg->numFinalArgs = numAggTransFnArgs + 1;
3799 : : else
3176 heikki.linnakangas@i 3800 : 16490 : peragg->numFinalArgs = numDirectArgs + 1;
3801 : :
3802 : : /* Initialize any direct-argument expressions */
2372 tgl@sss.pgh.pa.us 3803 : 24124 : peragg->aggdirectargs = ExecInitExprList(aggref->aggdirectargs,
3804 : : (PlanState *) aggstate);
3805 : :
3806 : : /*
3807 : : * build expression trees using actual argument & result types for the
3808 : : * finalfn, if it exists and is required.
3809 : : */
7593 3810 [ + + ]: 24124 : if (OidIsValid(finalfn_oid))
3811 : : {
1015 drowley@postgresql.o 3812 : 11101 : build_aggregate_finalfn_expr(aggTransFnInputTypes,
3813 : : peragg->numFinalArgs,
3814 : : aggtranstype,
3815 : : aggref->aggtype,
3816 : : aggref->inputcollid,
3817 : : finalfn_oid,
3818 : : &finalfnexpr);
3176 heikki.linnakangas@i 3819 : 11101 : fmgr_info(finalfn_oid, &peragg->finalfn);
3820 : 11101 : fmgr_info_set_expr((Node *) finalfnexpr, &peragg->finalfn);
3821 : : }
3822 : :
3823 : : /* get info about the output value's datatype */
2849 tgl@sss.pgh.pa.us 3824 : 24124 : get_typlenbyval(aggref->aggtype,
3825 : : &peragg->resulttypeLen,
3826 : : &peragg->resulttypeByVal);
3827 : :
3828 : : /*
3829 : : * Build working state for invoking the transition function, if we
3830 : : * haven't done it already.
3831 : : */
1237 heikki.linnakangas@i 3832 : 24124 : pertrans = &pertransstates[aggref->aggtransno];
3833 [ + + ]: 24124 : if (pertrans->aggref == NULL)
3834 : : {
3835 : : Datum textInitVal;
3836 : : Datum initValue;
3837 : : bool initValueIsNull;
3838 : : Oid transfn_oid;
3839 : :
3840 : : /*
3841 : : * If this aggregation is performing state combines, then instead
3842 : : * of using the transition function, we'll use the combine
3843 : : * function.
3844 : : */
3845 [ + + ]: 23995 : if (DO_AGGSPLIT_COMBINE(aggstate->aggsplit))
3846 : : {
3847 : 680 : transfn_oid = aggform->aggcombinefn;
3848 : :
3849 : : /* If not set then the planner messed up */
3850 [ - + ]: 680 : if (!OidIsValid(transfn_oid))
1237 heikki.linnakangas@i 3851 [ # # ]:UBC 0 : elog(ERROR, "combinefn not set for aggregate function");
3852 : : }
3853 : : else
1237 heikki.linnakangas@i 3854 :CBC 23315 : transfn_oid = aggform->aggtransfn;
3855 : :
518 peter@eisentraut.org 3856 : 23995 : aclresult = object_aclcheck(ProcedureRelationId, transfn_oid, aggOwner, ACL_EXECUTE);
1237 heikki.linnakangas@i 3857 [ - + ]: 23995 : if (aclresult != ACLCHECK_OK)
1237 heikki.linnakangas@i 3858 :UBC 0 : aclcheck_error(aclresult, OBJECT_FUNCTION,
3859 : 0 : get_func_name(transfn_oid));
1237 heikki.linnakangas@i 3860 [ - + ]:CBC 23995 : InvokeFunctionExecuteHook(transfn_oid);
3861 : :
3862 : : /*
3863 : : * initval is potentially null, so don't try to access it as a
3864 : : * struct field. Must do it the hard way with SysCacheGetAttr.
3865 : : */
3866 : 23995 : textInitVal = SysCacheGetAttr(AGGFNOID, aggTuple,
3867 : : Anum_pg_aggregate_agginitval,
3868 : : &initValueIsNull);
3869 [ + + ]: 23995 : if (initValueIsNull)
3870 : 14419 : initValue = (Datum) 0;
3871 : : else
3872 : 9576 : initValue = GetAggInitVal(textInitVal, aggtranstype);
3873 : :
1015 drowley@postgresql.o 3874 [ + + ]: 23995 : if (DO_AGGSPLIT_COMBINE(aggstate->aggsplit))
3875 : : {
3876 : 680 : Oid combineFnInputTypes[] = {aggtranstype,
3877 : : aggtranstype};
3878 : :
3879 : : /*
3880 : : * When combining there's only one input, the to-be-combined
3881 : : * transition value. The transition value is not counted
3882 : : * here.
3883 : : */
3884 : 680 : pertrans->numTransInputs = 1;
3885 : :
3886 : : /* aggcombinefn always has two arguments of aggtranstype */
3887 : 680 : build_pertrans_for_aggref(pertrans, aggstate, estate,
3888 : : aggref, transfn_oid, aggtranstype,
3889 : : serialfn_oid, deserialfn_oid,
3890 : : initValue, initValueIsNull,
3891 : : combineFnInputTypes, 2);
3892 : :
3893 : : /*
3894 : : * Ensure that a combine function to combine INTERNAL states
3895 : : * is not strict. This should have been checked during CREATE
3896 : : * AGGREGATE, but the strict property could have been changed
3897 : : * since then.
3898 : : */
3899 [ + + - + ]: 680 : if (pertrans->transfn.fn_strict && aggtranstype == INTERNALOID)
1015 drowley@postgresql.o 3900 [ # # ]:UBC 0 : ereport(ERROR,
3901 : : (errcode(ERRCODE_INVALID_FUNCTION_DEFINITION),
3902 : : errmsg("combine function with transition type %s must not be declared STRICT",
3903 : : format_type_be(aggtranstype))));
3904 : : }
3905 : : else
3906 : : {
3907 : : /* Detect how many arguments to pass to the transfn */
1015 drowley@postgresql.o 3908 [ + + ]:CBC 23315 : if (AGGKIND_IS_ORDERED_SET(aggref->aggkind))
3909 : 126 : pertrans->numTransInputs = list_length(aggref->args);
3910 : : else
3911 : 23189 : pertrans->numTransInputs = numAggTransFnArgs;
3912 : :
3913 : 23315 : build_pertrans_for_aggref(pertrans, aggstate, estate,
3914 : : aggref, transfn_oid, aggtranstype,
3915 : : serialfn_oid, deserialfn_oid,
3916 : : initValue, initValueIsNull,
3917 : : aggTransFnInputTypes,
3918 : : numAggTransFnArgs);
3919 : :
3920 : : /*
3921 : : * If the transfn is strict and the initval is NULL, make sure
3922 : : * input type and transtype are the same (or at least
3923 : : * binary-compatible), so that it's OK to use the first
3924 : : * aggregated input value as the initial transValue. This
3925 : : * should have been checked at agg definition time, but we
3926 : : * must check again in case the transfn's strictness property
3927 : : * has been changed.
3928 : : */
3929 [ + + + + ]: 23315 : if (pertrans->transfn.fn_strict && pertrans->initValueIsNull)
3930 : : {
3931 [ + - ]: 2419 : if (numAggTransFnArgs <= numDirectArgs ||
3932 [ - + ]: 2419 : !IsBinaryCoercible(aggTransFnInputTypes[numDirectArgs],
3933 : : aggtranstype))
1015 drowley@postgresql.o 3934 [ # # ]:UBC 0 : ereport(ERROR,
3935 : : (errcode(ERRCODE_INVALID_FUNCTION_DEFINITION),
3936 : : errmsg("aggregate %u needs to have compatible input type and transition type",
3937 : : aggref->aggfnoid)));
3938 : : }
3939 : : }
3940 : : }
3941 : : else
1237 heikki.linnakangas@i 3942 :CBC 129 : pertrans->aggshared = true;
3176 3943 : 24124 : ReleaseSysCache(aggTuple);
3944 : : }
3945 : :
3946 : : /*
3947 : : * Update aggstate->numaggs to be the number of unique aggregates found.
3948 : : * Also set numstates to the number of unique transition states found.
3949 : : */
1237 3950 : 21555 : aggstate->numaggs = numaggs;
3951 : 21555 : aggstate->numtrans = numtrans;
3952 : :
3953 : : /*
3954 : : * Last, check whether any more aggregates got added onto the node while
3955 : : * we processed the expressions for the aggregate arguments (including not
3956 : : * only the regular arguments and FILTER expressions handled immediately
3957 : : * above, but any direct arguments we might've handled earlier). If so,
3958 : : * we have nested aggregate functions, which is semantically nonsensical,
3959 : : * so complain. (This should have been caught by the parser, so we don't
3960 : : * need to work hard on a helpful error message; but we defend against it
3961 : : * here anyway, just to be sure.)
3962 : : */
3963 [ - + ]: 21555 : if (numaggrefs != list_length(aggstate->aggs))
2287 andres@anarazel.de 3964 [ # # ]:UBC 0 : ereport(ERROR,
3965 : : (errcode(ERRCODE_GROUPING_ERROR),
3966 : : errmsg("aggregate function calls cannot be nested")));
3967 : :
3968 : : /*
3969 : : * Build expressions doing all the transition work at once. We build a
3970 : : * different one for each phase, as the number of transition function
3971 : : * invocation can differ between phases. Note this'll work both for
3972 : : * transition and combination functions (although there'll only be one
3973 : : * phase in the latter case).
3974 : : */
2287 andres@anarazel.de 3975 [ + + ]:CBC 62307 : for (phaseidx = 0; phaseidx < aggstate->numphases; phaseidx++)
3976 : : {
3977 : 40752 : AggStatePerPhase phase = &aggstate->phases[phaseidx];
3978 : 40752 : bool dohash = false;
3979 : 40752 : bool dosort = false;
3980 : :
3981 : : /* phase 0 doesn't necessarily exist */
3982 [ + + ]: 40752 : if (!phase->aggnode)
3983 : 18985 : continue;
3984 : :
3985 [ + + + + ]: 21767 : if (aggstate->aggstrategy == AGG_MIXED && phaseidx == 1)
3986 : : {
3987 : : /*
3988 : : * Phase one, and only phase one, in a mixed agg performs both
3989 : : * sorting and aggregation.
3990 : : */
3991 : 98 : dohash = true;
3992 : 98 : dosort = true;
3993 : : }
3994 [ + + + + ]: 21669 : else if (aggstate->aggstrategy == AGG_MIXED && phaseidx == 0)
3995 : : {
3996 : : /*
3997 : : * No need to compute a transition function for an AGG_MIXED phase
3998 : : * 0 - the contents of the hashtables will have been computed
3999 : : * during phase 1.
4000 : : */
4001 : 98 : continue;
4002 : : }
4003 [ + + ]: 21571 : else if (phase->aggstrategy == AGG_PLAIN ||
4004 [ + + ]: 3550 : phase->aggstrategy == AGG_SORTED)
4005 : : {
4006 : 19099 : dohash = false;
4007 : 19099 : dosort = true;
4008 : : }
4009 [ + - ]: 2472 : else if (phase->aggstrategy == AGG_HASHED)
4010 : : {
4011 : 2472 : dohash = true;
4012 : 2472 : dosort = false;
4013 : : }
4014 : : else
2287 andres@anarazel.de 4015 :UBC 0 : Assert(false);
4016 : :
1502 jdavis@postgresql.or 4017 :CBC 21669 : phase->evaltrans = ExecBuildAggTrans(aggstate, phase, dosort, dohash,
4018 : : false);
4019 : :
4020 : : /* cache compiled expression for outer slot without NULL check */
1488 4021 : 21669 : phase->evaltrans_cache[0][0] = phase->evaltrans;
4022 : : }
4023 : :
3176 heikki.linnakangas@i 4024 : 21555 : return aggstate;
4025 : : }
4026 : :
4027 : : /*
4028 : : * Build the state needed to calculate a state value for an aggregate.
4029 : : *
4030 : : * This initializes all the fields in 'pertrans'. 'aggref' is the aggregate
4031 : : * to initialize the state for. 'transfn_oid', 'aggtranstype', and the rest
4032 : : * of the arguments could be calculated from 'aggref', but the caller has
4033 : : * calculated them already, so might as well pass them.
4034 : : *
4035 : : * 'transfn_oid' may be either the Oid of the aggtransfn or the aggcombinefn.
4036 : : */
4037 : : static void
4038 : 23995 : build_pertrans_for_aggref(AggStatePerTrans pertrans,
4039 : : AggState *aggstate, EState *estate,
4040 : : Aggref *aggref,
4041 : : Oid transfn_oid, Oid aggtranstype,
4042 : : Oid aggserialfn, Oid aggdeserialfn,
4043 : : Datum initValue, bool initValueIsNull,
4044 : : Oid *inputTypes, int numArguments)
4045 : : {
4046 : 23995 : int numGroupingSets = Max(aggstate->maxsets, 1);
4047 : : Expr *transfnexpr;
4048 : : int numTransArgs;
2938 rhaas@postgresql.org 4049 : 23995 : Expr *serialfnexpr = NULL;
4050 : 23995 : Expr *deserialfnexpr = NULL;
4051 : : ListCell *lc;
4052 : : int numInputs;
4053 : : int numDirectArgs;
4054 : : List *sortlist;
4055 : : int numSortCols;
4056 : : int numDistinctCols;
4057 : : int i;
4058 : :
4059 : : /* Begin filling in the pertrans data */
3176 heikki.linnakangas@i 4060 : 23995 : pertrans->aggref = aggref;
2372 tgl@sss.pgh.pa.us 4061 : 23995 : pertrans->aggshared = false;
3176 heikki.linnakangas@i 4062 : 23995 : pertrans->aggCollation = aggref->inputcollid;
1015 drowley@postgresql.o 4063 : 23995 : pertrans->transfn_oid = transfn_oid;
2938 rhaas@postgresql.org 4064 : 23995 : pertrans->serialfn_oid = aggserialfn;
4065 : 23995 : pertrans->deserialfn_oid = aggdeserialfn;
3176 heikki.linnakangas@i 4066 : 23995 : pertrans->initValue = initValue;
4067 : 23995 : pertrans->initValueIsNull = initValueIsNull;
4068 : :
4069 : : /* Count the "direct" arguments, if any */
4070 : 23995 : numDirectArgs = list_length(aggref->aggdirectargs);
4071 : :
4072 : : /* Count the number of aggregated input columns */
4073 : 23995 : pertrans->numInputs = numInputs = list_length(aggref->args);
4074 : :
4075 : 23995 : pertrans->aggtranstype = aggtranstype;
4076 : :
4077 : : /* account for the current transition state */
1015 drowley@postgresql.o 4078 : 23995 : numTransArgs = pertrans->numTransInputs + 1;
4079 : :
4080 : : /*
4081 : : * Set up infrastructure for calling the transfn. Note that invtransfn is
4082 : : * not needed here.
4083 : : */
4084 : 23995 : build_aggregate_transfn_expr(inputTypes,
4085 : : numArguments,
4086 : : numDirectArgs,
4087 : 23995 : aggref->aggvariadic,
4088 : : aggtranstype,
4089 : : aggref->inputcollid,
4090 : : transfn_oid,
4091 : : InvalidOid,
4092 : : &transfnexpr,
4093 : : NULL);
4094 : :
4095 : 23995 : fmgr_info(transfn_oid, &pertrans->transfn);
4096 : 23995 : fmgr_info_set_expr((Node *) transfnexpr, &pertrans->transfn);
4097 : :
4098 : 23995 : pertrans->transfn_fcinfo =
4099 : 23995 : (FunctionCallInfo) palloc(SizeForFunctionCallInfo(numTransArgs));
4100 : 23995 : InitFunctionCallInfoData(*pertrans->transfn_fcinfo,
4101 : : &pertrans->transfn,
4102 : : numTransArgs,
4103 : : pertrans->aggCollation,
4104 : : (void *) aggstate, NULL);
4105 : :
4106 : : /* get info about the state value's datatype */
3176 heikki.linnakangas@i 4107 : 23995 : get_typlenbyval(aggtranstype,
4108 : : &pertrans->transtypeLen,
4109 : : &pertrans->transtypeByVal);
4110 : :
2938 rhaas@postgresql.org 4111 [ + + ]: 23995 : if (OidIsValid(aggserialfn))
4112 : : {
2853 tgl@sss.pgh.pa.us 4113 : 168 : build_aggregate_serialfn_expr(aggserialfn,
4114 : : &serialfnexpr);
2938 rhaas@postgresql.org 4115 : 168 : fmgr_info(aggserialfn, &pertrans->serialfn);
4116 : 168 : fmgr_info_set_expr((Node *) serialfnexpr, &pertrans->serialfn);
4117 : :
1905 andres@anarazel.de 4118 : 168 : pertrans->serialfn_fcinfo =
4119 : 168 : (FunctionCallInfo) palloc(SizeForFunctionCallInfo(1));
4120 : 168 : InitFunctionCallInfoData(*pertrans->serialfn_fcinfo,
4121 : : &pertrans->serialfn,
4122 : : 1,
4123 : : InvalidOid,
4124 : : (void *) aggstate, NULL);
4125 : : }
4126 : :
2938 rhaas@postgresql.org 4127 [ + + ]: 23995 : if (OidIsValid(aggdeserialfn))
4128 : : {
2853 tgl@sss.pgh.pa.us 4129 : 60 : build_aggregate_deserialfn_expr(aggdeserialfn,
4130 : : &deserialfnexpr);
2938 rhaas@postgresql.org 4131 : 60 : fmgr_info(aggdeserialfn, &pertrans->deserialfn);
4132 : 60 : fmgr_info_set_expr((Node *) deserialfnexpr, &pertrans->deserialfn);
4133 : :
1905 andres@anarazel.de 4134 : 60 : pertrans->deserialfn_fcinfo =
4135 : 60 : (FunctionCallInfo) palloc(SizeForFunctionCallInfo(2));
4136 : 60 : InitFunctionCallInfoData(*pertrans->deserialfn_fcinfo,
4137 : : &pertrans->deserialfn,
4138 : : 2,
4139 : : InvalidOid,
4140 : : (void *) aggstate, NULL);
4141 : : }
4142 : :
4143 : : /*
4144 : : * If we're doing either DISTINCT or ORDER BY for a plain agg, then we
4145 : : * have a list of SortGroupClause nodes; fish out the data in them and
4146 : : * stick them into arrays. We ignore ORDER BY for an ordered-set agg,
4147 : : * however; the agg's transfn and finalfn are responsible for that.
4148 : : *
4149 : : * When the planner has set the aggpresorted flag, the input to the
4150 : : * aggregate is already correctly sorted. For ORDER BY aggregates we can
4151 : : * simply treat these as normal aggregates. For presorted DISTINCT
4152 : : * aggregates an extra step must be added to remove duplicate consecutive
4153 : : * inputs.
4154 : : *
4155 : : * Note that by construction, if there is a DISTINCT clause then the ORDER
4156 : : * BY clause is a prefix of it (see transformDistinctClause).
4157 : : */
3176 heikki.linnakangas@i 4158 [ + + ]: 23995 : if (AGGKIND_IS_ORDERED_SET(aggref->aggkind))
4159 : : {
4160 : 126 : sortlist = NIL;
4161 : 126 : numSortCols = numDistinctCols = 0;
621 drowley@postgresql.o 4162 : 126 : pertrans->aggsortrequired = false;
4163 : : }
4164 [ + + + + ]: 23869 : else if (aggref->aggpresorted && aggref->aggdistinct == NIL)
4165 : : {
4166 : 761 : sortlist = NIL;
4167 : 761 : numSortCols = numDistinctCols = 0;
4168 : 761 : pertrans->aggsortrequired = false;
4169 : : }
3176 heikki.linnakangas@i 4170 [ + + ]: 23108 : else if (aggref->aggdistinct)
4171 : : {
4172 : 279 : sortlist = aggref->aggdistinct;
4173 : 279 : numSortCols = numDistinctCols = list_length(sortlist);
4174 [ - + ]: 279 : Assert(numSortCols >= list_length(aggref->aggorder));
621 drowley@postgresql.o 4175 : 279 : pertrans->aggsortrequired = !aggref->aggpresorted;
4176 : : }
4177 : : else
4178 : : {
3176 heikki.linnakangas@i 4179 : 22829 : sortlist = aggref->aggorder;
4180 : 22829 : numSortCols = list_length(sortlist);
4181 : 22829 : numDistinctCols = 0;
621 drowley@postgresql.o 4182 : 22829 : pertrans->aggsortrequired = (numSortCols > 0);
4183 : : }
4184 : :
3176 heikki.linnakangas@i 4185 : 23995 : pertrans->numSortCols = numSortCols;
4186 : 23995 : pertrans->numDistinctCols = numDistinctCols;
4187 : :
4188 : : /*
4189 : : * If we have either sorting or filtering to do, create a tupledesc and
4190 : : * slot corresponding to the aggregated inputs (including sort
4191 : : * expressions) of the agg.
4192 : : */
2372 tgl@sss.pgh.pa.us 4193 [ + + + + ]: 23995 : if (numSortCols > 0 || aggref->aggfilter)
4194 : : {
1972 andres@anarazel.de 4195 : 696 : pertrans->sortdesc = ExecTypeFromTL(aggref->args);
2249 4196 : 696 : pertrans->sortslot =
1977 4197 : 696 : ExecInitExtraTupleSlot(estate, pertrans->sortdesc,
4198 : : &TTSOpsMinimalTuple);
4199 : : }
4200 : :
2372 tgl@sss.pgh.pa.us 4201 [ + + ]: 23995 : if (numSortCols > 0)
4202 : : {
4203 : : /*
4204 : : * We don't implement DISTINCT or ORDER BY aggs in the HASHED case
4205 : : * (yet)
4206 : : */
2575 rhodiumtoad@postgres 4207 [ + - - + ]: 342 : Assert(aggstate->aggstrategy != AGG_HASHED && aggstate->aggstrategy != AGG_MIXED);
4208 : :
4209 : : /* ORDER BY aggregates are not supported with partial aggregation */
1015 drowley@postgresql.o 4210 [ - + ]: 342 : Assert(!DO_AGGSPLIT_COMBINE(aggstate->aggsplit));
4211 : :
4212 : : /* If we have only one input, we need its len/byval info. */
3176 heikki.linnakangas@i 4213 [ + + ]: 342 : if (numInputs == 1)
4214 : : {
4215 : 279 : get_typlenbyval(inputTypes[numDirectArgs],
4216 : : &pertrans->inputtypeLen,
4217 : : &pertrans->inputtypeByVal);
4218 : : }
4219 [ + + ]: 63 : else if (numDistinctCols > 0)
4220 : : {
4221 : : /* we will need an extra slot to store prior values */
2249 andres@anarazel.de 4222 : 48 : pertrans->uniqslot =
1977 4223 : 48 : ExecInitExtraTupleSlot(estate, pertrans->sortdesc,
4224 : : &TTSOpsMinimalTuple);
4225 : : }
4226 : :
4227 : : /* Extract the sort information for use later */
3176 heikki.linnakangas@i 4228 : 342 : pertrans->sortColIdx =
4229 : 342 : (AttrNumber *) palloc(numSortCols * sizeof(AttrNumber));
4230 : 342 : pertrans->sortOperators =
4231 : 342 : (Oid *) palloc(numSortCols * sizeof(Oid));
4232 : 342 : pertrans->sortCollations =
4233 : 342 : (Oid *) palloc(numSortCols * sizeof(Oid));
4234 : 342 : pertrans->sortNullsFirst =
4235 : 342 : (bool *) palloc(numSortCols * sizeof(bool));
4236 : :
4237 : 342 : i = 0;
4238 [ + - + + : 777 : foreach(lc, sortlist)
+ + ]
4239 : : {
4240 : 435 : SortGroupClause *sortcl = (SortGroupClause *) lfirst(lc);
4241 : 435 : TargetEntry *tle = get_sortgroupclause_tle(sortcl, aggref->args);
4242 : :
4243 : : /* the parser should have made sure of this */
4244 [ - + ]: 435 : Assert(OidIsValid(sortcl->sortop));
4245 : :
4246 : 435 : pertrans->sortColIdx[i] = tle->resno;
4247 : 435 : pertrans->sortOperators[i] = sortcl->sortop;
4248 : 435 : pertrans->sortCollations[i] = exprCollation((Node *) tle->expr);
4249 : 435 : pertrans->sortNullsFirst[i] = sortcl->nulls_first;
4250 : 435 : i++;
4251 : : }
4252 [ - + ]: 342 : Assert(i == numSortCols);
4253 : : }
4254 : :
4255 [ + + ]: 23995 : if (aggref->aggdistinct)
4256 : : {
4257 : : Oid *ops;
4258 : :
4259 [ - + ]: 279 : Assert(numArguments > 0);
2250 andres@anarazel.de 4260 [ - + ]: 279 : Assert(list_length(aggref->aggdistinct) == numDistinctCols);
4261 : :
4262 : 279 : ops = palloc(numDistinctCols * sizeof(Oid));
4263 : :
3176 heikki.linnakangas@i 4264 : 279 : i = 0;
4265 [ + - + + : 642 : foreach(lc, aggref->aggdistinct)
+ + ]
2250 andres@anarazel.de 4266 : 363 : ops[i++] = ((SortGroupClause *) lfirst(lc))->eqop;
4267 : :
4268 : : /* lookup / build the necessary comparators */
4269 [ + + ]: 279 : if (numDistinctCols == 1)
4270 : 231 : fmgr_info(get_opcode(ops[0]), &pertrans->equalfnOne);
4271 : : else
4272 : 48 : pertrans->equalfnMulti =
4273 : 48 : execTuplesMatchPrepare(pertrans->sortdesc,
4274 : : numDistinctCols,
4275 : 48 : pertrans->sortColIdx,
4276 : : ops,
1850 peter@eisentraut.org 4277 : 48 : pertrans->sortCollations,
4278 : : &aggstate->ss.ps);
2250 andres@anarazel.de 4279 : 279 : pfree(ops);
4280 : : }
4281 : :
3176 heikki.linnakangas@i 4282 : 23995 : pertrans->sortstates = (Tuplesortstate **)
4283 : 23995 : palloc0(sizeof(Tuplesortstate *) * numGroupingSets);
10141 scrappy@hub.org 4284 : 23995 : }
4285 : :
4286 : :
4287 : : static Datum
8039 tgl@sss.pgh.pa.us 4288 : 9576 : GetAggInitVal(Datum textInitVal, Oid transtype)
4289 : : {
4290 : : Oid typinput,
4291 : : typioparam;
4292 : : char *strInitVal;
4293 : : Datum initVal;
4294 : :
7252 4295 : 9576 : getTypeInputInfo(transtype, &typinput, &typioparam);
5864 4296 : 9576 : strInitVal = TextDatumGetCString(textInitVal);
6585 4297 : 9576 : initVal = OidInputFunctionCall(typinput, strInitVal,
4298 : : typioparam, -1);
8039 4299 : 9576 : pfree(strInitVal);
4300 : 9576 : return initVal;
4301 : : }
4302 : :
4303 : : void
7801 4304 : 21502 : ExecEndAgg(AggState *node)
4305 : : {
4306 : : PlanState *outerPlan;
4307 : : int transno;
3256 andres@anarazel.de 4308 : 21502 : int numGroupingSets = Max(node->maxsets, 1);
4309 : : int setno;
4310 : :
4311 : : /*
4312 : : * When ending a parallel worker, copy the statistics gathered by the
4313 : : * worker back into shared memory so that it can be picked up by the main
4314 : : * process to report in EXPLAIN ANALYZE.
4315 : : */
1395 drowley@postgresql.o 4316 [ + + + + ]: 21502 : if (node->shared_info && IsParallelWorker())
4317 : : {
4318 : : AggregateInstrumentation *si;
4319 : :
4320 [ - + ]: 87 : Assert(ParallelWorkerNumber <= node->shared_info->num_workers);
4321 : 87 : si = &node->shared_info->sinstrument[ParallelWorkerNumber];
4322 : 87 : si->hash_batches_used = node->hash_batches_used;
4323 : 87 : si->hash_disk_used = node->hash_disk_used;
4324 : 87 : si->hash_mem_peak = node->hash_mem_peak;
4325 : : }
4326 : :
4327 : : /* Make sure we have closed any open tuplesorts */
4328 : :
3256 andres@anarazel.de 4329 [ + + ]: 21502 : if (node->sort_in)
4330 : 72 : tuplesort_end(node->sort_in);
4331 [ + + ]: 21502 : if (node->sort_out)
4332 : 21 : tuplesort_end(node->sort_out);
4333 : :
1488 jdavis@postgresql.or 4334 : 21502 : hashagg_reset_spill_state(node);
4335 : :
4336 [ + + ]: 21502 : if (node->hash_metacxt != NULL)
4337 : : {
4338 : 2566 : MemoryContextDelete(node->hash_metacxt);
4339 : 2566 : node->hash_metacxt = NULL;
4340 : : }
4341 : :
3176 heikki.linnakangas@i 4342 [ + + ]: 45442 : for (transno = 0; transno < node->numtrans; transno++)
4343 : : {
4344 : 23940 : AggStatePerTrans pertrans = &node->pertrans[transno];
4345 : :
3256 andres@anarazel.de 4346 [ + + ]: 48381 : for (setno = 0; setno < numGroupingSets; setno++)
4347 : : {
3176 heikki.linnakangas@i 4348 [ - + ]: 24441 : if (pertrans->sortstates[setno])
3176 heikki.linnakangas@i 4349 :UBC 0 : tuplesort_end(pertrans->sortstates[setno]);
4350 : : }
4351 : : }
4352 : :
4353 : : /* And ensure any agg shutdown callbacks have been called */
3256 andres@anarazel.de 4354 [ + + ]:CBC 43418 : for (setno = 0; setno < numGroupingSets; setno++)
4355 : 21916 : ReScanExprContext(node->aggcontexts[setno]);
2575 rhodiumtoad@postgres 4356 [ + + ]: 21502 : if (node->hashcontext)
4357 : 2566 : ReScanExprContext(node->hashcontext);
4358 : :
7801 tgl@sss.pgh.pa.us 4359 : 21502 : outerPlan = outerPlanState(node);
4360 : 21502 : ExecEndNode(outerPlan);
10141 scrappy@hub.org 4361 : 21502 : }
4362 : :
4363 : : void
5025 tgl@sss.pgh.pa.us 4364 : 18481 : ExecReScanAgg(AggState *node)
4365 : : {
7801 4366 : 18481 : ExprContext *econtext = node->ss.ps.ps_ExprContext;
3249 bruce@momjian.us 4367 : 18481 : PlanState *outerPlan = outerPlanState(node);
3256 andres@anarazel.de 4368 : 18481 : Agg *aggnode = (Agg *) node->ss.ps.plan;
4369 : : int transno;
3249 bruce@momjian.us 4370 : 18481 : int numGroupingSets = Max(node->maxsets, 1);
4371 : : int setno;
4372 : :
7625 tgl@sss.pgh.pa.us 4373 : 18481 : node->agg_done = false;
4374 : :
2575 rhodiumtoad@postgres 4375 [ + + ]: 18481 : if (node->aggstrategy == AGG_HASHED)
4376 : : {
4377 : : /*
4378 : : * In the hashed case, if we haven't yet built the hash table then we
4379 : : * can just return; nothing done yet, so nothing to undo. If subnode's
4380 : : * chgParam is not NULL then it will be re-scanned by ExecProcNode,
4381 : : * else no reason to re-scan it at all.
4382 : : */
7625 tgl@sss.pgh.pa.us 4383 [ + + ]: 547 : if (!node->table_filled)
4384 : 19 : return;
4385 : :
4386 : : /*
4387 : : * If we do have the hash table, and it never spilled, and the subplan
4388 : : * does not have any parameter changes, and none of our own parameter
4389 : : * changes affect input expressions of the aggregated functions, then
4390 : : * we can just rescan the existing hash table; no need to build it
4391 : : * again.
4392 : : */
1488 jdavis@postgresql.or 4393 [ + + + - ]: 528 : if (outerPlan->chgParam == NULL && !node->hash_ever_spilled &&
2790 tgl@sss.pgh.pa.us 4394 [ + + ]: 516 : !bms_overlap(node->ss.ps.chgParam, aggnode->aggParams))
4395 : : {
2575 rhodiumtoad@postgres 4396 : 504 : ResetTupleHashIterator(node->perhash[0].hashtable,
4397 : : &node->perhash[0].hashiter);
4398 : 504 : select_current_set(node, 0, true);
7625 tgl@sss.pgh.pa.us 4399 : 504 : return;
4400 : : }
4401 : : }
4402 : :
4403 : : /* Make sure we have closed any open tuplesorts */
3176 heikki.linnakangas@i 4404 [ + + ]: 49428 : for (transno = 0; transno < node->numtrans; transno++)
4405 : : {
3256 andres@anarazel.de 4406 [ + + ]: 62958 : for (setno = 0; setno < numGroupingSets; setno++)
4407 : : {
3176 heikki.linnakangas@i 4408 : 31488 : AggStatePerTrans pertrans = &node->pertrans[transno];
4409 : :
4410 [ - + ]: 31488 : if (pertrans->sortstates[setno])
4411 : : {
3176 heikki.linnakangas@i 4412 :UBC 0 : tuplesort_end(pertrans->sortstates[setno]);
4413 : 0 : pertrans->sortstates[setno] = NULL;
4414 : : }
4415 : : }
4416 : : }
4417 : :
4418 : : /*
4419 : : * We don't need to ReScanExprContext the output tuple context here;
4420 : : * ExecReScan already did it. But we do need to reset our per-grouping-set
4421 : : * contexts, which may have transvalues stored in them. (We use rescan
4422 : : * rather than just reset because transfns may have registered callbacks
4423 : : * that need to be run now.) For the AGG_HASHED case, see below.
4424 : : */
4425 : :
3256 andres@anarazel.de 4426 [ + + ]:CBC 35934 : for (setno = 0; setno < numGroupingSets; setno++)
4427 : : {
4428 : 17976 : ReScanExprContext(node->aggcontexts[setno]);
4429 : : }
4430 : :
4431 : : /* Release first tuple of group, if we have made a copy */
7801 tgl@sss.pgh.pa.us 4432 [ - + ]: 17958 : if (node->grp_firstTuple != NULL)
4433 : : {
7801 tgl@sss.pgh.pa.us 4434 :UBC 0 : heap_freetuple(node->grp_firstTuple);
4435 : 0 : node->grp_firstTuple = NULL;
4436 : : }
3256 andres@anarazel.de 4437 :CBC 17958 : ExecClearTuple(node->ss.ss_ScanTupleSlot);
4438 : :
4439 : : /* Forget current agg values */
7801 tgl@sss.pgh.pa.us 4440 [ + - + - : 49428 : MemSet(econtext->ecxt_aggvalues, 0, sizeof(Datum) * node->numaggs);
+ - + - +
+ ]
4441 [ + - + + : 17958 : MemSet(econtext->ecxt_aggnulls, 0, sizeof(bool) * node->numaggs);
+ - + - -
+ ]
4442 : :
4443 : : /*
4444 : : * With AGG_HASHED/MIXED, the hash table is allocated in a sub-context of
4445 : : * the hashcontext. This used to be an issue, but now, resetting a context
4446 : : * automatically deletes sub-contexts too.
4447 : : */
2575 rhodiumtoad@postgres 4448 [ + + + + ]: 17958 : if (node->aggstrategy == AGG_HASHED || node->aggstrategy == AGG_MIXED)
4449 : : {
1488 jdavis@postgresql.or 4450 : 39 : hashagg_reset_spill_state(node);
4451 : :
4452 : 39 : node->hash_ever_spilled = false;
4453 : 39 : node->hash_spill_mode = false;
4454 : 39 : node->hash_ngroups_current = 0;
4455 : :
2575 rhodiumtoad@postgres 4456 : 39 : ReScanExprContext(node->hashcontext);
4457 : : /* Rebuild an empty hash table */
1516 jdavis@postgresql.or 4458 : 39 : build_hash_tables(node);
7801 tgl@sss.pgh.pa.us 4459 : 39 : node->table_filled = false;
4460 : : /* iterator will be reset when the table is filled */
4461 : :
1488 jdavis@postgresql.or 4462 : 39 : hashagg_recompile_expressions(node, false, false);
4463 : : }
4464 : :
2575 rhodiumtoad@postgres 4465 [ + + ]: 17958 : if (node->aggstrategy != AGG_HASHED)
4466 : : {
4467 : : /*
4468 : : * Reset the per-group state (in particular, mark transvalues null)
4469 : : */
2294 andres@anarazel.de 4470 [ + + ]: 35886 : for (setno = 0; setno < numGroupingSets; setno++)
4471 : : {
4472 [ + - + - : 80880 : MemSet(node->pergroups[setno], 0,
+ - + - +
+ ]
4473 : : sizeof(AggStatePerGroupData) * node->numaggs);
4474 : : }
4475 : :
4476 : : /* reset to phase 1 */
2575 rhodiumtoad@postgres 4477 : 17934 : initialize_phase(node, 1);
4478 : :
3256 andres@anarazel.de 4479 : 17934 : node->input_done = false;
4480 : 17934 : node->projected_set = -1;
4481 : : }
4482 : :
3268 rhaas@postgresql.org 4483 [ + + ]: 17958 : if (outerPlan->chgParam == NULL)
4484 : 80 : ExecReScan(outerPlan);
4485 : : }
4486 : :
4487 : :
4488 : : /***********************************************************************
4489 : : * API exposed to aggregate functions
4490 : : ***********************************************************************/
4491 : :
4492 : :
4493 : : /*
4494 : : * AggCheckCallContext - test if a SQL function is being called as an aggregate
4495 : : *
4496 : : * The transition and/or final functions of an aggregate may want to verify
4497 : : * that they are being called as aggregates, rather than as plain SQL
4498 : : * functions. They should use this function to do so. The return value
4499 : : * is nonzero if being called as an aggregate, or zero if not. (Specific
4500 : : * nonzero values are AGG_CONTEXT_AGGREGATE or AGG_CONTEXT_WINDOW, but more
4501 : : * values could conceivably appear in future.)
4502 : : *
4503 : : * If aggcontext isn't NULL, the function also stores at *aggcontext the
4504 : : * identity of the memory context that aggregate transition values are being
4505 : : * stored in. Note that the same aggregate call site (flinfo) may be called
4506 : : * interleaved on different transition values in different contexts, so it's
4507 : : * not kosher to cache aggcontext under fn_extra. It is, however, kosher to
4508 : : * cache it in the transvalue itself (for internal-type transvalues).
4509 : : */
4510 : : int
5179 tgl@sss.pgh.pa.us 4511 : 2359658 : AggCheckCallContext(FunctionCallInfo fcinfo, MemoryContext *aggcontext)
4512 : : {
4513 [ + + + + ]: 2359658 : if (fcinfo->context && IsA(fcinfo->context, AggState))
4514 : : {
4515 [ + + ]: 2353894 : if (aggcontext)
4516 : : {
3249 bruce@momjian.us 4517 : 1011659 : AggState *aggstate = ((AggState *) fcinfo->context);
2575 rhodiumtoad@postgres 4518 : 1011659 : ExprContext *cxt = aggstate->curaggcontext;
4519 : :
3256 andres@anarazel.de 4520 : 1011659 : *aggcontext = cxt->ecxt_per_tuple_memory;
4521 : : }
5179 tgl@sss.pgh.pa.us 4522 : 2353894 : return AGG_CONTEXT_AGGREGATE;
4523 : : }
4524 [ + + + - ]: 5764 : if (fcinfo->context && IsA(fcinfo->context, WindowAggState))
4525 : : {
4526 [ + + ]: 4830 : if (aggcontext)
3655 4527 : 355 : *aggcontext = ((WindowAggState *) fcinfo->context)->curaggcontext;
5179 4528 : 4830 : return AGG_CONTEXT_WINDOW;
4529 : : }
4530 : :
4531 : : /* this is just to prevent "uninitialized variable" warnings */
4532 [ + + ]: 934 : if (aggcontext)
4533 : 910 : *aggcontext = NULL;
4534 : 934 : return 0;
4535 : : }
4536 : :
4537 : : /*
4538 : : * AggGetAggref - allow an aggregate support function to get its Aggref
4539 : : *
4540 : : * If the function is being called as an aggregate support function,
4541 : : * return the Aggref node for the aggregate call. Otherwise, return NULL.
4542 : : *
4543 : : * Aggregates sharing the same inputs and transition functions can get
4544 : : * merged into a single transition calculation. If the transition function
4545 : : * calls AggGetAggref, it will get some one of the Aggrefs for which it is
4546 : : * executing. It must therefore not pay attention to the Aggref fields that
4547 : : * relate to the final function, as those are indeterminate. But if a final
4548 : : * function calls AggGetAggref, it will get a precise result.
4549 : : *
4550 : : * Note that if an aggregate is being used as a window function, this will
4551 : : * return NULL. We could provide a similar function to return the relevant
4552 : : * WindowFunc node in such cases, but it's not needed yet.
4553 : : */
4554 : : Aggref *
3765 4555 : 123 : AggGetAggref(FunctionCallInfo fcinfo)
4556 : : {
4557 [ + - + - ]: 123 : if (fcinfo->context && IsA(fcinfo->context, AggState))
4558 : : {
2372 4559 : 123 : AggState *aggstate = (AggState *) fcinfo->context;
4560 : : AggStatePerAgg curperagg;
4561 : : AggStatePerTrans curpertrans;
4562 : :
4563 : : /* check curperagg (valid when in a final function) */
4564 : 123 : curperagg = aggstate->curperagg;
4565 : :
2376 4566 [ - + ]: 123 : if (curperagg)
2376 tgl@sss.pgh.pa.us 4567 :UBC 0 : return curperagg->aggref;
4568 : :
4569 : : /* check curpertrans (valid when in a transition function) */
2372 tgl@sss.pgh.pa.us 4570 :CBC 123 : curpertrans = aggstate->curpertrans;
4571 : :
3176 heikki.linnakangas@i 4572 [ + - ]: 123 : if (curpertrans)
4573 : 123 : return curpertrans->aggref;
4574 : : }
3765 tgl@sss.pgh.pa.us 4575 :UBC 0 : return NULL;
4576 : : }
4577 : :
4578 : : /*
4579 : : * AggGetTempMemoryContext - fetch short-term memory context for aggregates
4580 : : *
4581 : : * This is useful in agg final functions; the context returned is one that
4582 : : * the final function can safely reset as desired. This isn't useful for
4583 : : * transition functions, since the context returned MAY (we don't promise)
4584 : : * be the same as the context those are called in.
4585 : : *
4586 : : * As above, this is currently not useful for aggs called as window functions.
4587 : : */
4588 : : MemoryContext
3573 4589 : 0 : AggGetTempMemoryContext(FunctionCallInfo fcinfo)
4590 : : {
3765 4591 [ # # # # ]: 0 : if (fcinfo->context && IsA(fcinfo->context, AggState))
4592 : : {
4593 : 0 : AggState *aggstate = (AggState *) fcinfo->context;
4594 : :
3573 4595 : 0 : return aggstate->tmpcontext->ecxt_per_tuple_memory;
4596 : : }
3765 4597 : 0 : return NULL;
4598 : : }
4599 : :
4600 : : /*
4601 : : * AggStateIsShared - find out whether transition state is shared
4602 : : *
4603 : : * If the function is being called as an aggregate support function,
4604 : : * return true if the aggregate's transition state is shared across
4605 : : * multiple aggregates, false if it is not.
4606 : : *
4607 : : * Returns true if not called as an aggregate support function.
4608 : : * This is intended as a conservative answer, ie "no you'd better not
4609 : : * scribble on your input". In particular, will return true if the
4610 : : * aggregate is being used as a window function, which is a scenario
4611 : : * in which changing the transition state is a bad idea. We might
4612 : : * want to refine the behavior for the window case in future.
4613 : : */
4614 : : bool
2372 tgl@sss.pgh.pa.us 4615 :CBC 123 : AggStateIsShared(FunctionCallInfo fcinfo)
4616 : : {
4617 [ + - + - ]: 123 : if (fcinfo->context && IsA(fcinfo->context, AggState))
4618 : : {
4619 : 123 : AggState *aggstate = (AggState *) fcinfo->context;
4620 : : AggStatePerAgg curperagg;
4621 : : AggStatePerTrans curpertrans;
4622 : :
4623 : : /* check curperagg (valid when in a final function) */
4624 : 123 : curperagg = aggstate->curperagg;
4625 : :
4626 [ - + ]: 123 : if (curperagg)
2372 tgl@sss.pgh.pa.us 4627 :UBC 0 : return aggstate->pertrans[curperagg->transno].aggshared;
4628 : :
4629 : : /* check curpertrans (valid when in a transition function) */
2372 tgl@sss.pgh.pa.us 4630 :CBC 123 : curpertrans = aggstate->curpertrans;
4631 : :
4632 [ + - ]: 123 : if (curpertrans)
4633 : 123 : return curpertrans->aggshared;
4634 : : }
2372 tgl@sss.pgh.pa.us 4635 :UBC 0 : return true;
4636 : : }
4637 : :
4638 : : /*
4639 : : * AggRegisterCallback - register a cleanup callback for an aggregate
4640 : : *
4641 : : * This is useful for aggs to register shutdown callbacks, which will ensure
4642 : : * that non-memory resources are freed. The callback will occur just before
4643 : : * the associated aggcontext (as returned by AggCheckCallContext) is reset,
4644 : : * either between groups or as a result of rescanning the query. The callback
4645 : : * will NOT be called on error paths. The typical use-case is for freeing of
4646 : : * tuplestores or tuplesorts maintained in aggcontext, or pins held by slots
4647 : : * created by the agg functions. (The callback will not be called until after
4648 : : * the result of the finalfn is no longer needed, so it's safe for the finalfn
4649 : : * to return data that will be freed by the callback.)
4650 : : *
4651 : : * As above, this is currently not useful for aggs called as window functions.
4652 : : */
4653 : : void
3573 tgl@sss.pgh.pa.us 4654 :CBC 330 : AggRegisterCallback(FunctionCallInfo fcinfo,
4655 : : ExprContextCallbackFunction func,
4656 : : Datum arg)
4657 : : {
3765 4658 [ + - + - ]: 330 : if (fcinfo->context && IsA(fcinfo->context, AggState))
4659 : : {
4660 : 330 : AggState *aggstate = (AggState *) fcinfo->context;
2575 rhodiumtoad@postgres 4661 : 330 : ExprContext *cxt = aggstate->curaggcontext;
4662 : :
3256 andres@anarazel.de 4663 : 330 : RegisterExprContextCallback(cxt, func, arg);
4664 : :
3573 tgl@sss.pgh.pa.us 4665 : 330 : return;
4666 : : }
3573 tgl@sss.pgh.pa.us 4667 [ # # ]:UBC 0 : elog(ERROR, "aggregate function cannot register a callback in this context");
4668 : : }
4669 : :
4670 : :
4671 : : /* ----------------------------------------------------------------
4672 : : * Parallel Query Support
4673 : : * ----------------------------------------------------------------
4674 : : */
4675 : :
4676 : : /* ----------------------------------------------------------------
4677 : : * ExecAggEstimate
4678 : : *
4679 : : * Estimate space required to propagate aggregate statistics.
4680 : : * ----------------------------------------------------------------
4681 : : */
4682 : : void
1395 drowley@postgresql.o 4683 :CBC 283 : ExecAggEstimate(AggState *node, ParallelContext *pcxt)
4684 : : {
4685 : : Size size;
4686 : :
4687 : : /* don't need this if not instrumenting or no workers */
4688 [ + + - + ]: 283 : if (!node->ss.ps.instrument || pcxt->nworkers == 0)
4689 : 229 : return;
4690 : :
4691 : 54 : size = mul_size(pcxt->nworkers, sizeof(AggregateInstrumentation));
4692 : 54 : size = add_size(size, offsetof(SharedAggInfo, sinstrument));
4693 : 54 : shm_toc_estimate_chunk(&pcxt->estimator, size);
4694 : 54 : shm_toc_estimate_keys(&pcxt->estimator, 1);
4695 : : }
4696 : :
4697 : : /* ----------------------------------------------------------------
4698 : : * ExecAggInitializeDSM
4699 : : *
4700 : : * Initialize DSM space for aggregate statistics.
4701 : : * ----------------------------------------------------------------
4702 : : */
4703 : : void
4704 : 283 : ExecAggInitializeDSM(AggState *node, ParallelContext *pcxt)
4705 : : {
4706 : : Size size;
4707 : :
4708 : : /* don't need this if not instrumenting or no workers */
4709 [ + + - + ]: 283 : if (!node->ss.ps.instrument || pcxt->nworkers == 0)
4710 : 229 : return;
4711 : :
4712 : 54 : size = offsetof(SharedAggInfo, sinstrument)
4713 : 54 : + pcxt->nworkers * sizeof(AggregateInstrumentation);
4714 : 54 : node->shared_info = shm_toc_allocate(pcxt->toc, size);
4715 : : /* ensure any unfilled slots will contain zeroes */
4716 : 54 : memset(node->shared_info, 0, size);
4717 : 54 : node->shared_info->num_workers = pcxt->nworkers;
4718 : 54 : shm_toc_insert(pcxt->toc, node->ss.ps.plan->plan_node_id,
4719 : 54 : node->shared_info);
4720 : : }
4721 : :
4722 : : /* ----------------------------------------------------------------
4723 : : * ExecAggInitializeWorker
4724 : : *
4725 : : * Attach worker to DSM space for aggregate statistics.
4726 : : * ----------------------------------------------------------------
4727 : : */
4728 : : void
4729 : 780 : ExecAggInitializeWorker(AggState *node, ParallelWorkerContext *pwcxt)
4730 : : {
4731 : 780 : node->shared_info =
4732 : 780 : shm_toc_lookup(pwcxt->toc, node->ss.ps.plan->plan_node_id, true);
4733 : 780 : }
4734 : :
4735 : : /* ----------------------------------------------------------------
4736 : : * ExecAggRetrieveInstrumentation
4737 : : *
4738 : : * Transfer aggregate statistics from DSM to private memory.
4739 : : * ----------------------------------------------------------------
4740 : : */
4741 : : void
4742 : 54 : ExecAggRetrieveInstrumentation(AggState *node)
4743 : : {
4744 : : Size size;
4745 : : SharedAggInfo *si;
4746 : :
4747 [ - + ]: 54 : if (node->shared_info == NULL)
1395 drowley@postgresql.o 4748 :UBC 0 : return;
4749 : :
1395 drowley@postgresql.o 4750 :CBC 54 : size = offsetof(SharedAggInfo, sinstrument)
4751 : 54 : + node->shared_info->num_workers * sizeof(AggregateInstrumentation);
4752 : 54 : si = palloc(size);
4753 : 54 : memcpy(si, node->shared_info, size);
4754 : 54 : node->shared_info = si;
4755 : : }
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