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+/*-------------------------------------------------------------------------
+ *
+ * nodeAgg.c
+ * Routines to handle aggregate nodes.
+ *
+ * ExecAgg normally evaluates each aggregate in the following steps:
+ *
+ * transvalue = initcond
+ * foreach input_tuple do
+ * transvalue = transfunc(transvalue, input_value(s))
+ * result = finalfunc(transvalue, direct_argument(s))
+ *
+ * If a finalfunc is not supplied then the result is just the ending
+ * value of transvalue.
+ *
+ * Other behaviors can be selected by the "aggsplit" mode, which exists
+ * to support partial aggregation. It is possible to:
+ * * Skip running the finalfunc, so that the output is always the
+ * final transvalue state.
+ * * Substitute the combinefunc for the transfunc, so that transvalue
+ * states (propagated up from a child partial-aggregation step) are merged
+ * rather than processing raw input rows. (The statements below about
+ * the transfunc apply equally to the combinefunc, when it's selected.)
+ * * Apply the serializefunc to the output values (this only makes sense
+ * when skipping the finalfunc, since the serializefunc works on the
+ * transvalue data type).
+ * * Apply the deserializefunc to the input values (this only makes sense
+ * when using the combinefunc, for similar reasons).
+ * It is the planner's responsibility to connect up Agg nodes using these
+ * alternate behaviors in a way that makes sense, with partial aggregation
+ * results being fed to nodes that expect them.
+ *
+ * If a normal aggregate call specifies DISTINCT or ORDER BY, we sort the
+ * input tuples and eliminate duplicates (if required) before performing
+ * the above-depicted process. (However, we don't do that for ordered-set
+ * aggregates; their "ORDER BY" inputs are ordinary aggregate arguments
+ * so far as this module is concerned.) Note that partial aggregation
+ * is not supported in these cases, since we couldn't ensure global
+ * ordering or distinctness of the inputs.
+ *
+ * If transfunc is marked "strict" in pg_proc and initcond is NULL,
+ * then the first non-NULL input_value is assigned directly to transvalue,
+ * and transfunc isn't applied until the second non-NULL input_value.
+ * The agg's first input type and transtype must be the same in this case!
+ *
+ * If transfunc is marked "strict" then NULL input_values are skipped,
+ * keeping the previous transvalue. If transfunc is not strict then it
+ * is called for every input tuple and must deal with NULL initcond
+ * or NULL input_values for itself.
+ *
+ * If finalfunc is marked "strict" then it is not called when the
+ * ending transvalue is NULL, instead a NULL result is created
+ * automatically (this is just the usual handling of strict functions,
+ * of course). A non-strict finalfunc can make its own choice of
+ * what to return for a NULL ending transvalue.
+ *
+ * Ordered-set aggregates are treated specially in one other way: we
+ * evaluate any "direct" arguments and pass them to the finalfunc along
+ * with the transition value.
+ *
+ * A finalfunc can have additional arguments beyond the transvalue and
+ * any "direct" arguments, corresponding to the input arguments of the
+ * aggregate. These are always just passed as NULL. Such arguments may be
+ * needed to allow resolution of a polymorphic aggregate's result type.
+ *
+ * We compute aggregate input expressions and run the transition functions
+ * in a temporary econtext (aggstate->tmpcontext). This is reset at least
+ * once per input tuple, so when the transvalue datatype is
+ * pass-by-reference, we have to be careful to copy it into a longer-lived
+ * memory context, and free the prior value to avoid memory leakage. We
+ * store transvalues in another set of econtexts, aggstate->aggcontexts
+ * (one per grouping set, see below), which are also used for the hashtable
+ * structures in AGG_HASHED mode. These econtexts are rescanned, not just
+ * reset, at group boundaries so that aggregate transition functions can
+ * register shutdown callbacks via AggRegisterCallback.
+ *
+ * The node's regular econtext (aggstate->ss.ps.ps_ExprContext) is used to
+ * run finalize functions and compute the output tuple; this context can be
+ * reset once per output tuple.
+ *
+ * The executor's AggState node is passed as the fmgr "context" value in
+ * all transfunc and finalfunc calls. It is not recommended that the
+ * transition functions look at the AggState node directly, but they can
+ * use AggCheckCallContext() to verify that they are being called by
+ * nodeAgg.c (and not as ordinary SQL functions). The main reason a
+ * transition function might want to know this is so that it can avoid
+ * palloc'ing a fixed-size pass-by-ref transition value on every call:
+ * it can instead just scribble on and return its left input. Ordinarily
+ * it is completely forbidden for functions to modify pass-by-ref inputs,
+ * but in the aggregate case we know the left input is either the initial
+ * transition value or a previous function result, and in either case its
+ * value need not be preserved. See int8inc() for an example. Notice that
+ * the EEOP_AGG_PLAIN_TRANS step is coded to avoid a data copy step when
+ * the previous transition value pointer is returned. It is also possible
+ * to avoid repeated data copying when the transition value is an expanded
+ * object: to do that, the transition function must take care to return
+ * an expanded object that is in a child context of the memory context
+ * returned by AggCheckCallContext(). Also, some transition functions want
+ * to store working state in addition to the nominal transition value; they
+ * can use the memory context returned by AggCheckCallContext() to do that.
+ *
+ * Note: AggCheckCallContext() is available as of PostgreSQL 9.0. The
+ * AggState is available as context in earlier releases (back to 8.1),
+ * but direct examination of the node is needed to use it before 9.0.
+ *
+ * As of 9.4, aggregate transition functions can also use AggGetAggref()
+ * to get hold of the Aggref expression node for their aggregate call.
+ * This is mainly intended for ordered-set aggregates, which are not
+ * supported as window functions. (A regular aggregate function would
+ * need some fallback logic to use this, since there's no Aggref node
+ * for a window function.)
+ *
+ * Grouping sets:
+ *
+ * A list of grouping sets which is structurally equivalent to a ROLLUP
+ * clause (e.g. (a,b,c), (a,b), (a)) can be processed in a single pass over
+ * ordered data. We do this by keeping a separate set of transition values
+ * for each grouping set being concurrently processed; for each input tuple
+ * we update them all, and on group boundaries we reset those states
+ * (starting at the front of the list) whose grouping values have changed
+ * (the list of grouping sets is ordered from most specific to least
+ * specific).
+ *
+ * Where more complex grouping sets are used, we break them down into
+ * "phases", where each phase has a different sort order (except phase 0
+ * which is reserved for hashing). During each phase but the last, the
+ * input tuples are additionally stored in a tuplesort which is keyed to the
+ * next phase's sort order; during each phase but the first, the input
+ * tuples are drawn from the previously sorted data. (The sorting of the
+ * data for the first phase is handled by the planner, as it might be
+ * satisfied by underlying nodes.)
+ *
+ * Hashing can be mixed with sorted grouping. To do this, we have an
+ * AGG_MIXED strategy that populates the hashtables during the first sorted
+ * phase, and switches to reading them out after completing all sort phases.
+ * We can also support AGG_HASHED with multiple hash tables and no sorting
+ * at all.
+ *
+ * From the perspective of aggregate transition and final functions, the
+ * only issue regarding grouping sets is this: a single call site (flinfo)
+ * of an aggregate function may be used for updating several different
+ * transition values in turn. So the function must not cache in the flinfo
+ * anything which logically belongs as part of the transition value (most
+ * importantly, the memory context in which the transition value exists).
+ * The support API functions (AggCheckCallContext, AggRegisterCallback) are
+ * sensitive to the grouping set for which the aggregate function is
+ * currently being called.
+ *
+ * Plan structure:
+ *
+ * What we get from the planner is actually one "real" Agg node which is
+ * part of the plan tree proper, but which optionally has an additional list
+ * of Agg nodes hung off the side via the "chain" field. This is because an
+ * Agg node happens to be a convenient representation of all the data we
+ * need for grouping sets.
+ *
+ * For many purposes, we treat the "real" node as if it were just the first
+ * node in the chain. The chain must be ordered such that hashed entries
+ * come before sorted/plain entries; the real node is marked AGG_MIXED if
+ * there are both types present (in which case the real node describes one
+ * of the hashed groupings, other AGG_HASHED nodes may optionally follow in
+ * the chain, followed in turn by AGG_SORTED or (one) AGG_PLAIN node). If
+ * the real node is marked AGG_HASHED or AGG_SORTED, then all the chained
+ * nodes must be of the same type; if it is AGG_PLAIN, there can be no
+ * chained nodes.
+ *
+ * We collect all hashed nodes into a single "phase", numbered 0, and create
+ * a sorted phase (numbered 1..n) for each AGG_SORTED or AGG_PLAIN node.
+ * Phase 0 is allocated even if there are no hashes, but remains unused in
+ * that case.
+ *
+ * AGG_HASHED nodes actually refer to only a single grouping set each,
+ * because for each hashed grouping we need a separate grpColIdx and
+ * numGroups estimate. AGG_SORTED nodes represent a "rollup", a list of
+ * grouping sets that share a sort order. Each AGG_SORTED node other than
+ * the first one has an associated Sort node which describes the sort order
+ * to be used; the first sorted node takes its input from the outer subtree,
+ * which the planner has already arranged to provide ordered data.
+ *
+ * Memory and ExprContext usage:
+ *
+ * Because we're accumulating aggregate values across input rows, we need to
+ * use more memory contexts than just simple input/output tuple contexts.
+ * In fact, for a rollup, we need a separate context for each grouping set
+ * so that we can reset the inner (finer-grained) aggregates on their group
+ * boundaries while continuing to accumulate values for outer
+ * (coarser-grained) groupings. On top of this, we might be simultaneously
+ * populating hashtables; however, we only need one context for all the
+ * hashtables.
+ *
+ * So we create an array, aggcontexts, with an ExprContext for each grouping
+ * set in the largest rollup that we're going to process, and use the
+ * per-tuple memory context of those ExprContexts to store the aggregate
+ * transition values. hashcontext is the single context created to support
+ * all hash tables.
+ *
+ * Spilling To Disk
+ *
+ * When performing hash aggregation, if the hash table memory exceeds the
+ * limit (see hash_agg_check_limits()), we enter "spill mode". In spill
+ * mode, we advance the transition states only for groups already in the
+ * hash table. For tuples that would need to create a new hash table
+ * entries (and initialize new transition states), we instead spill them to
+ * disk to be processed later. The tuples are spilled in a partitioned
+ * manner, so that subsequent batches are smaller and less likely to exceed
+ * hash_mem (if a batch does exceed hash_mem, it must be spilled
+ * recursively).
+ *
+ * Spilled data is written to logical tapes. These provide better control
+ * over memory usage, disk space, and the number of files than if we were
+ * to use a BufFile for each spill.
+ *
+ * Note that it's possible for transition states to start small but then
+ * grow very large; for instance in the case of ARRAY_AGG. In such cases,
+ * it's still possible to significantly exceed hash_mem. We try to avoid
+ * this situation by estimating what will fit in the available memory, and
+ * imposing a limit on the number of groups separately from the amount of
+ * memory consumed.
+ *
+ * Transition / Combine function invocation:
+ *
+ * For performance reasons transition functions, including combine
+ * functions, aren't invoked one-by-one from nodeAgg.c after computing
+ * arguments using the expression evaluation engine. Instead
+ * ExecBuildAggTrans() builds one large expression that does both argument
+ * evaluation and transition function invocation. That avoids performance
+ * issues due to repeated uses of expression evaluation, complications due
+ * to filter expressions having to be evaluated early, and allows to JIT
+ * the entire expression into one native function.
+ *
+ * Portions Copyright (c) 1996-2021, PostgreSQL Global Development Group
+ * Portions Copyright (c) 1994, Regents of the University of California
+ *
+ * IDENTIFICATION
+ * src/backend/executor/nodeAgg.c
+ *
+ *-------------------------------------------------------------------------
+ */
+
+#include "postgres.h"
+
+#include "access/htup_details.h"
+#include "access/parallel.h"
+#include "catalog/objectaccess.h"
+#include "catalog/pg_aggregate.h"
+#include "catalog/pg_proc.h"
+#include "catalog/pg_type.h"
+#include "common/hashfn.h"
+#include "executor/execExpr.h"
+#include "executor/executor.h"
+#include "executor/nodeAgg.h"
+#include "lib/hyperloglog.h"
+#include "miscadmin.h"
+#include "nodes/makefuncs.h"
+#include "nodes/nodeFuncs.h"
+#include "optimizer/optimizer.h"
+#include "parser/parse_agg.h"
+#include "parser/parse_coerce.h"
+#include "utils/acl.h"
+#include "utils/builtins.h"
+#include "utils/datum.h"
+#include "utils/dynahash.h"
+#include "utils/expandeddatum.h"
+#include "utils/logtape.h"
+#include "utils/lsyscache.h"
+#include "utils/memutils.h"
+#include "utils/syscache.h"
+#include "utils/tuplesort.h"
+
+/*
+ * Control how many partitions are created when spilling HashAgg to
+ * disk.
+ *
+ * HASHAGG_PARTITION_FACTOR is multiplied by the estimated number of
+ * partitions needed such that each partition will fit in memory. The factor
+ * is set higher than one because there's not a high cost to having a few too
+ * many partitions, and it makes it less likely that a partition will need to
+ * be spilled recursively. Another benefit of having more, smaller partitions
+ * is that small hash tables may perform better than large ones due to memory
+ * caching effects.
+ *
+ * We also specify a min and max number of partitions per spill. Too few might
+ * mean a lot of wasted I/O from repeated spilling of the same tuples. Too
+ * many will result in lots of memory wasted buffering the spill files (which
+ * could instead be spent on a larger hash table).
+ */
+#define HASHAGG_PARTITION_FACTOR 1.50
+#define HASHAGG_MIN_PARTITIONS 4
+#define HASHAGG_MAX_PARTITIONS 1024
+
+/*
+ * For reading from tapes, the buffer size must be a multiple of
+ * BLCKSZ. Larger values help when reading from multiple tapes concurrently,
+ * but that doesn't happen in HashAgg, so we simply use BLCKSZ. Writing to a
+ * tape always uses a buffer of size BLCKSZ.
+ */
+#define HASHAGG_READ_BUFFER_SIZE BLCKSZ
+#define HASHAGG_WRITE_BUFFER_SIZE BLCKSZ
+
+/*
+ * HyperLogLog is used for estimating the cardinality of the spilled tuples in
+ * a given partition. 5 bits corresponds to a size of about 32 bytes and a
+ * worst-case error of around 18%. That's effective enough to choose a
+ * reasonable number of partitions when recursing.
+ */
+#define HASHAGG_HLL_BIT_WIDTH 5
+
+/*
+ * Estimate chunk overhead as a constant 16 bytes. XXX: should this be
+ * improved?
+ */
+#define CHUNKHDRSZ 16
+
+/*
+ * Track all tapes needed for a HashAgg that spills. We don't know the maximum
+ * number of tapes needed at the start of the algorithm (because it can
+ * recurse), so one tape set is allocated and extended as needed for new
+ * tapes. When a particular tape is already read, rewind it for write mode and
+ * put it in the free list.
+ *
+ * Tapes' buffers can take up substantial memory when many tapes are open at
+ * once. We only need one tape open at a time in read mode (using a buffer
+ * that's a multiple of BLCKSZ); but we need one tape open in write mode (each
+ * requiring a buffer of size BLCKSZ) for each partition.
+ */
+typedef struct HashTapeInfo
+{
+ LogicalTapeSet *tapeset;
+ int ntapes;
+ int *freetapes;
+ int nfreetapes;
+ int freetapes_alloc;
+} HashTapeInfo;
+
+/*
+ * Represents partitioned spill data for a single hashtable. Contains the
+ * necessary information to route tuples to the correct partition, and to
+ * transform the spilled data into new batches.
+ *
+ * The high bits are used for partition selection (when recursing, we ignore
+ * the bits that have already been used for partition selection at an earlier
+ * level).
+ */
+typedef struct HashAggSpill
+{
+ LogicalTapeSet *tapeset; /* borrowed reference to tape set */
+ int npartitions; /* number of partitions */
+ int *partitions; /* spill partition tape numbers */
+ int64 *ntuples; /* number of tuples in each partition */
+ uint32 mask; /* mask to find partition from hash value */
+ int shift; /* after masking, shift by this amount */
+ hyperLogLogState *hll_card; /* cardinality estimate for contents */
+} HashAggSpill;
+
+/*
+ * Represents work to be done for one pass of hash aggregation (with only one
+ * grouping set).
+ *
+ * Also tracks the bits of the hash already used for partition selection by
+ * earlier iterations, so that this batch can use new bits. If all bits have
+ * already been used, no partitioning will be done (any spilled data will go
+ * to a single output tape).
+ */
+typedef struct HashAggBatch
+{
+ int setno; /* grouping set */
+ int used_bits; /* number of bits of hash already used */
+ LogicalTapeSet *tapeset; /* borrowed reference to tape set */
+ int input_tapenum; /* input partition tape */
+ int64 input_tuples; /* number of tuples in this batch */
+ double input_card; /* estimated group cardinality */
+} HashAggBatch;
+
+/* used to find referenced colnos */
+typedef struct FindColsContext
+{
+ bool is_aggref; /* is under an aggref */
+ Bitmapset *aggregated; /* column references under an aggref */
+ Bitmapset *unaggregated; /* other column references */
+} FindColsContext;
+
+static void select_current_set(AggState *aggstate, int setno, bool is_hash);
+static void initialize_phase(AggState *aggstate, int newphase);
+static TupleTableSlot *fetch_input_tuple(AggState *aggstate);
+static void initialize_aggregates(AggState *aggstate,
+ AggStatePerGroup *pergroups,
+ int numReset);
+static void advance_transition_function(AggState *aggstate,
+ AggStatePerTrans pertrans,
+ AggStatePerGroup pergroupstate);
+static void advance_aggregates(AggState *aggstate);
+static void process_ordered_aggregate_single(AggState *aggstate,
+ AggStatePerTrans pertrans,
+ AggStatePerGroup pergroupstate);
+static void process_ordered_aggregate_multi(AggState *aggstate,
+ AggStatePerTrans pertrans,
+ AggStatePerGroup pergroupstate);
+static void finalize_aggregate(AggState *aggstate,
+ AggStatePerAgg peragg,
+ AggStatePerGroup pergroupstate,
+ Datum *resultVal, bool *resultIsNull);
+static void finalize_partialaggregate(AggState *aggstate,
+ AggStatePerAgg peragg,
+ AggStatePerGroup pergroupstate,
+ Datum *resultVal, bool *resultIsNull);
+static inline void prepare_hash_slot(AggStatePerHash perhash,
+ TupleTableSlot *inputslot,
+ TupleTableSlot *hashslot);
+static void prepare_projection_slot(AggState *aggstate,
+ TupleTableSlot *slot,
+ int currentSet);
+static void finalize_aggregates(AggState *aggstate,
+ AggStatePerAgg peragg,
+ AggStatePerGroup pergroup);
+static TupleTableSlot *project_aggregates(AggState *aggstate);
+static void find_cols(AggState *aggstate, Bitmapset **aggregated,
+ Bitmapset **unaggregated);
+static bool find_cols_walker(Node *node, FindColsContext *context);
+static void build_hash_tables(AggState *aggstate);
+static void build_hash_table(AggState *aggstate, int setno, long nbuckets);
+static void hashagg_recompile_expressions(AggState *aggstate, bool minslot,
+ bool nullcheck);
+static long hash_choose_num_buckets(double hashentrysize,
+ long estimated_nbuckets,
+ Size memory);
+static int hash_choose_num_partitions(double input_groups,
+ double hashentrysize,
+ int used_bits,
+ int *log2_npartittions);
+static void initialize_hash_entry(AggState *aggstate,
+ TupleHashTable hashtable,
+ TupleHashEntry entry);
+static void lookup_hash_entries(AggState *aggstate);
+static TupleTableSlot *agg_retrieve_direct(AggState *aggstate);
+static void agg_fill_hash_table(AggState *aggstate);
+static bool agg_refill_hash_table(AggState *aggstate);
+static TupleTableSlot *agg_retrieve_hash_table(AggState *aggstate);
+static TupleTableSlot *agg_retrieve_hash_table_in_memory(AggState *aggstate);
+static void hash_agg_check_limits(AggState *aggstate);
+static void hash_agg_enter_spill_mode(AggState *aggstate);
+static void hash_agg_update_metrics(AggState *aggstate, bool from_tape,
+ int npartitions);
+static void hashagg_finish_initial_spills(AggState *aggstate);
+static void hashagg_reset_spill_state(AggState *aggstate);
+static HashAggBatch *hashagg_batch_new(LogicalTapeSet *tapeset,
+ int input_tapenum, int setno,
+ int64 input_tuples, double input_card,
+ int used_bits);
+static MinimalTuple hashagg_batch_read(HashAggBatch *batch, uint32 *hashp);
+static void hashagg_spill_init(HashAggSpill *spill, HashTapeInfo *tapeinfo,
+ int used_bits, double input_groups,
+ double hashentrysize);
+static Size hashagg_spill_tuple(AggState *aggstate, HashAggSpill *spill,
+ TupleTableSlot *slot, uint32 hash);
+static void hashagg_spill_finish(AggState *aggstate, HashAggSpill *spill,
+ int setno);
+static void hashagg_tapeinfo_init(AggState *aggstate);
+static void hashagg_tapeinfo_assign(HashTapeInfo *tapeinfo, int *dest,
+ int ndest);
+static void hashagg_tapeinfo_release(HashTapeInfo *tapeinfo, int tapenum);
+static Datum GetAggInitVal(Datum textInitVal, Oid transtype);
+static void build_pertrans_for_aggref(AggStatePerTrans pertrans,
+ AggState *aggstate, EState *estate,
+ Aggref *aggref, Oid aggtransfn, Oid aggtranstype,
+ Oid aggserialfn, Oid aggdeserialfn,
+ Datum initValue, bool initValueIsNull,
+ Oid *inputTypes, int numArguments);
+
+
+/*
+ * Select the current grouping set; affects current_set and
+ * curaggcontext.
+ */
+static void
+select_current_set(AggState *aggstate, int setno, bool is_hash)
+{
+ /*
+ * When changing this, also adapt ExecAggPlainTransByVal() and
+ * ExecAggPlainTransByRef().
+ */
+ if (is_hash)
+ aggstate->curaggcontext = aggstate->hashcontext;
+ else
+ aggstate->curaggcontext = aggstate->aggcontexts[setno];
+
+ aggstate->current_set = setno;
+}
+
+/*
+ * Switch to phase "newphase", which must either be 0 or 1 (to reset) or
+ * current_phase + 1. Juggle the tuplesorts accordingly.
+ *
+ * Phase 0 is for hashing, which we currently handle last in the AGG_MIXED
+ * case, so when entering phase 0, all we need to do is drop open sorts.
+ */
+static void
+initialize_phase(AggState *aggstate, int newphase)
+{
+ Assert(newphase <= 1 || newphase == aggstate->current_phase + 1);
+
+ /*
+ * Whatever the previous state, we're now done with whatever input
+ * tuplesort was in use.
+ */
+ if (aggstate->sort_in)
+ {
+ tuplesort_end(aggstate->sort_in);
+ aggstate->sort_in = NULL;
+ }
+
+ if (newphase <= 1)
+ {
+ /*
+ * Discard any existing output tuplesort.
+ */
+ if (aggstate->sort_out)
+ {
+ tuplesort_end(aggstate->sort_out);
+ aggstate->sort_out = NULL;
+ }
+ }
+ else
+ {
+ /*
+ * The old output tuplesort becomes the new input one, and this is the
+ * right time to actually sort it.
+ */
+ aggstate->sort_in = aggstate->sort_out;
+ aggstate->sort_out = NULL;
+ Assert(aggstate->sort_in);
+ tuplesort_performsort(aggstate->sort_in);
+ }
+
+ /*
+ * If this isn't the last phase, we need to sort appropriately for the
+ * next phase in sequence.
+ */
+ if (newphase > 0 && newphase < aggstate->numphases - 1)
+ {
+ Sort *sortnode = aggstate->phases[newphase + 1].sortnode;
+ PlanState *outerNode = outerPlanState(aggstate);
+ TupleDesc tupDesc = ExecGetResultType(outerNode);
+
+ aggstate->sort_out = tuplesort_begin_heap(tupDesc,
+ sortnode->numCols,
+ sortnode->sortColIdx,
+ sortnode->sortOperators,
+ sortnode->collations,
+ sortnode->nullsFirst,
+ work_mem,
+ NULL, false);
+ }
+
+ aggstate->current_phase = newphase;
+ aggstate->phase = &aggstate->phases[newphase];
+}
+
+/*
+ * Fetch a tuple from either the outer plan (for phase 1) or from the sorter
+ * populated by the previous phase. Copy it to the sorter for the next phase
+ * if any.
+ *
+ * Callers cannot rely on memory for tuple in returned slot remaining valid
+ * past any subsequently fetched tuple.
+ */
+static TupleTableSlot *
+fetch_input_tuple(AggState *aggstate)
+{
+ TupleTableSlot *slot;
+
+ if (aggstate->sort_in)
+ {
+ /* make sure we check for interrupts in either path through here */
+ CHECK_FOR_INTERRUPTS();
+ if (!tuplesort_gettupleslot(aggstate->sort_in, true, false,
+ aggstate->sort_slot, NULL))
+ return NULL;
+ slot = aggstate->sort_slot;
+ }
+ else
+ slot = ExecProcNode(outerPlanState(aggstate));
+
+ if (!TupIsNull(slot) && aggstate->sort_out)
+ tuplesort_puttupleslot(aggstate->sort_out, slot);
+
+ return slot;
+}
+
+/*
+ * (Re)Initialize an individual aggregate.
+ *
+ * This function handles only one grouping set, already set in
+ * aggstate->current_set.
+ *
+ * When called, CurrentMemoryContext should be the per-query context.
+ */
+static void
+initialize_aggregate(AggState *aggstate, AggStatePerTrans pertrans,
+ AggStatePerGroup pergroupstate)
+{
+ /*
+ * Start a fresh sort operation for each DISTINCT/ORDER BY aggregate.
+ */
+ if (pertrans->numSortCols > 0)
+ {
+ /*
+ * In case of rescan, maybe there could be an uncompleted sort
+ * operation? Clean it up if so.
+ */
+ if (pertrans->sortstates[aggstate->current_set])
+ tuplesort_end(pertrans->sortstates[aggstate->current_set]);
+
+
+ /*
+ * We use a plain Datum sorter when there's a single input column;
+ * otherwise sort the full tuple. (See comments for
+ * process_ordered_aggregate_single.)
+ */
+ if (pertrans->numInputs == 1)
+ {
+ Form_pg_attribute attr = TupleDescAttr(pertrans->sortdesc, 0);
+
+ pertrans->sortstates[aggstate->current_set] =
+ tuplesort_begin_datum(attr->atttypid,
+ pertrans->sortOperators[0],
+ pertrans->sortCollations[0],
+ pertrans->sortNullsFirst[0],
+ work_mem, NULL, false);
+ }
+ else
+ pertrans->sortstates[aggstate->current_set] =
+ tuplesort_begin_heap(pertrans->sortdesc,
+ pertrans->numSortCols,
+ pertrans->sortColIdx,
+ pertrans->sortOperators,
+ pertrans->sortCollations,
+ pertrans->sortNullsFirst,
+ work_mem, NULL, false);
+ }
+
+ /*
+ * (Re)set transValue to the initial value.
+ *
+ * Note that when the initial value is pass-by-ref, we must copy it (into
+ * the aggcontext) since we will pfree the transValue later.
+ */
+ if (pertrans->initValueIsNull)
+ pergroupstate->transValue = pertrans->initValue;
+ else
+ {
+ MemoryContext oldContext;
+
+ oldContext = MemoryContextSwitchTo(aggstate->curaggcontext->ecxt_per_tuple_memory);
+ pergroupstate->transValue = datumCopy(pertrans->initValue,
+ pertrans->transtypeByVal,
+ pertrans->transtypeLen);
+ MemoryContextSwitchTo(oldContext);
+ }
+ pergroupstate->transValueIsNull = pertrans->initValueIsNull;
+
+ /*
+ * If the initial value for the transition state doesn't exist in the
+ * pg_aggregate table then we will let the first non-NULL value returned
+ * from the outer procNode become the initial value. (This is useful for
+ * aggregates like max() and min().) The noTransValue flag signals that we
+ * still need to do this.
+ */
+ pergroupstate->noTransValue = pertrans->initValueIsNull;
+}
+
+/*
+ * Initialize all aggregate transition states for a new group of input values.
+ *
+ * If there are multiple grouping sets, we initialize only the first numReset
+ * of them (the grouping sets are ordered so that the most specific one, which
+ * is reset most often, is first). As a convenience, if numReset is 0, we
+ * reinitialize all sets.
+ *
+ * NB: This cannot be used for hash aggregates, as for those the grouping set
+ * number has to be specified from further up.
+ *
+ * When called, CurrentMemoryContext should be the per-query context.
+ */
+static void
+initialize_aggregates(AggState *aggstate,
+ AggStatePerGroup *pergroups,
+ int numReset)
+{
+ int transno;
+ int numGroupingSets = Max(aggstate->phase->numsets, 1);
+ int setno = 0;
+ int numTrans = aggstate->numtrans;
+ AggStatePerTrans transstates = aggstate->pertrans;
+
+ if (numReset == 0)
+ numReset = numGroupingSets;
+
+ for (setno = 0; setno < numReset; setno++)
+ {
+ AggStatePerGroup pergroup = pergroups[setno];
+
+ select_current_set(aggstate, setno, false);
+
+ for (transno = 0; transno < numTrans; transno++)
+ {
+ AggStatePerTrans pertrans = &transstates[transno];
+ AggStatePerGroup pergroupstate = &pergroup[transno];
+
+ initialize_aggregate(aggstate, pertrans, pergroupstate);
+ }
+ }
+}
+
+/*
+ * Given new input value(s), advance the transition function of one aggregate
+ * state within one grouping set only (already set in aggstate->current_set)
+ *
+ * The new values (and null flags) have been preloaded into argument positions
+ * 1 and up in pertrans->transfn_fcinfo, so that we needn't copy them again to
+ * pass to the transition function. We also expect that the static fields of
+ * the fcinfo are already initialized; that was done by ExecInitAgg().
+ *
+ * It doesn't matter which memory context this is called in.
+ */
+static void
+advance_transition_function(AggState *aggstate,
+ AggStatePerTrans pertrans,
+ AggStatePerGroup pergroupstate)
+{
+ FunctionCallInfo fcinfo = pertrans->transfn_fcinfo;
+ MemoryContext oldContext;
+ Datum newVal;
+
+ if (pertrans->transfn.fn_strict)
+ {
+ /*
+ * For a strict transfn, nothing happens when there's a NULL input; we
+ * just keep the prior transValue.
+ */
+ int numTransInputs = pertrans->numTransInputs;
+ int i;
+
+ for (i = 1; i <= numTransInputs; i++)
+ {
+ if (fcinfo->args[i].isnull)
+ return;
+ }
+ if (pergroupstate->noTransValue)
+ {
+ /*
+ * transValue has not been initialized. This is the first non-NULL
+ * input value. We use it as the initial value for transValue. (We
+ * already checked that the agg's input type is binary-compatible
+ * with its transtype, so straight copy here is OK.)
+ *
+ * We must copy the datum into aggcontext if it is pass-by-ref. We
+ * do not need to pfree the old transValue, since it's NULL.
+ */
+ oldContext = MemoryContextSwitchTo(aggstate->curaggcontext->ecxt_per_tuple_memory);
+ pergroupstate->transValue = datumCopy(fcinfo->args[1].value,
+ pertrans->transtypeByVal,
+ pertrans->transtypeLen);
+ pergroupstate->transValueIsNull = false;
+ pergroupstate->noTransValue = false;
+ MemoryContextSwitchTo(oldContext);
+ return;
+ }
+ if (pergroupstate->transValueIsNull)
+ {
+ /*
+ * Don't call a strict function with NULL inputs. Note it is
+ * possible to get here despite the above tests, if the transfn is
+ * strict *and* returned a NULL on a prior cycle. If that happens
+ * we will propagate the NULL all the way to the end.
+ */
+ return;
+ }
+ }
+
+ /* We run the transition functions in per-input-tuple memory context */
+ oldContext = MemoryContextSwitchTo(aggstate->tmpcontext->ecxt_per_tuple_memory);
+
+ /* set up aggstate->curpertrans for AggGetAggref() */
+ aggstate->curpertrans = pertrans;
+
+ /*
+ * OK to call the transition function
+ */
+ fcinfo->args[0].value = pergroupstate->transValue;
+ fcinfo->args[0].isnull = pergroupstate->transValueIsNull;
+ fcinfo->isnull = false; /* just in case transfn doesn't set it */
+
+ newVal = FunctionCallInvoke(fcinfo);
+
+ aggstate->curpertrans = NULL;
+
+ /*
+ * If pass-by-ref datatype, must copy the new value into aggcontext and
+ * free the prior transValue. But if transfn returned a pointer to its
+ * first input, we don't need to do anything. Also, if transfn returned a
+ * pointer to a R/W expanded object that is already a child of the
+ * aggcontext, assume we can adopt that value without copying it.
+ *
+ * It's safe to compare newVal with pergroup->transValue without regard
+ * for either being NULL, because ExecAggTransReparent() takes care to set
+ * transValue to 0 when NULL. Otherwise we could end up accidentally not
+ * reparenting, when the transValue has the same numerical value as
+ * newValue, despite being NULL. This is a somewhat hot path, making it
+ * undesirable to instead solve this with another branch for the common
+ * case of the transition function returning its (modified) input
+ * argument.
+ */
+ if (!pertrans->transtypeByVal &&
+ DatumGetPointer(newVal) != DatumGetPointer(pergroupstate->transValue))
+ newVal = ExecAggTransReparent(aggstate, pertrans,
+ newVal, fcinfo->isnull,
+ pergroupstate->transValue,
+ pergroupstate->transValueIsNull);
+
+ pergroupstate->transValue = newVal;
+ pergroupstate->transValueIsNull = fcinfo->isnull;
+
+ MemoryContextSwitchTo(oldContext);
+}
+
+/*
+ * Advance each aggregate transition state for one input tuple. The input
+ * tuple has been stored in tmpcontext->ecxt_outertuple, so that it is
+ * accessible to ExecEvalExpr.
+ *
+ * We have two sets of transition states to handle: one for sorted aggregation
+ * and one for hashed; we do them both here, to avoid multiple evaluation of
+ * the inputs.
+ *
+ * When called, CurrentMemoryContext should be the per-query context.
+ */
+static void
+advance_aggregates(AggState *aggstate)
+{
+ bool dummynull;
+
+ ExecEvalExprSwitchContext(aggstate->phase->evaltrans,
+ aggstate->tmpcontext,
+ &dummynull);
+}
+
+/*
+ * Run the transition function for a DISTINCT or ORDER BY aggregate
+ * with only one input. This is called after we have completed
+ * entering all the input values into the sort object. We complete the
+ * sort, read out the values in sorted order, and run the transition
+ * function on each value (applying DISTINCT if appropriate).
+ *
+ * Note that the strictness of the transition function was checked when
+ * entering the values into the sort, so we don't check it again here;
+ * we just apply standard SQL DISTINCT logic.
+ *
+ * The one-input case is handled separately from the multi-input case
+ * for performance reasons: for single by-value inputs, such as the
+ * common case of count(distinct id), the tuplesort_getdatum code path
+ * is around 300% faster. (The speedup for by-reference types is less
+ * but still noticeable.)
+ *
+ * This function handles only one grouping set (already set in
+ * aggstate->current_set).
+ *
+ * When called, CurrentMemoryContext should be the per-query context.
+ */
+static void
+process_ordered_aggregate_single(AggState *aggstate,
+ AggStatePerTrans pertrans,
+ AggStatePerGroup pergroupstate)
+{
+ Datum oldVal = (Datum) 0;
+ bool oldIsNull = true;
+ bool haveOldVal = false;
+ MemoryContext workcontext = aggstate->tmpcontext->ecxt_per_tuple_memory;
+ MemoryContext oldContext;
+ bool isDistinct = (pertrans->numDistinctCols > 0);
+ Datum newAbbrevVal = (Datum) 0;
+ Datum oldAbbrevVal = (Datum) 0;
+ FunctionCallInfo fcinfo = pertrans->transfn_fcinfo;
+ Datum *newVal;
+ bool *isNull;
+
+ Assert(pertrans->numDistinctCols < 2);
+
+ tuplesort_performsort(pertrans->sortstates[aggstate->current_set]);
+
+ /* Load the column into argument 1 (arg 0 will be transition value) */
+ newVal = &fcinfo->args[1].value;
+ isNull = &fcinfo->args[1].isnull;
+
+ /*
+ * Note: if input type is pass-by-ref, the datums returned by the sort are
+ * freshly palloc'd in the per-query context, so we must be careful to
+ * pfree them when they are no longer needed.
+ */
+
+ while (tuplesort_getdatum(pertrans->sortstates[aggstate->current_set],
+ true, newVal, isNull, &newAbbrevVal))
+ {
+ /*
+ * Clear and select the working context for evaluation of the equality
+ * function and transition function.
+ */
+ MemoryContextReset(workcontext);
+ oldContext = MemoryContextSwitchTo(workcontext);
+
+ /*
+ * If DISTINCT mode, and not distinct from prior, skip it.
+ */
+ if (isDistinct &&
+ haveOldVal &&
+ ((oldIsNull && *isNull) ||
+ (!oldIsNull && !*isNull &&
+ oldAbbrevVal == newAbbrevVal &&
+ DatumGetBool(FunctionCall2Coll(&pertrans->equalfnOne,
+ pertrans->aggCollation,
+ oldVal, *newVal)))))
+ {
+ /* equal to prior, so forget this one */
+ if (!pertrans->inputtypeByVal && !*isNull)
+ pfree(DatumGetPointer(*newVal));
+ }
+ else
+ {
+ advance_transition_function(aggstate, pertrans, pergroupstate);
+ /* forget the old value, if any */
+ if (!oldIsNull && !pertrans->inputtypeByVal)
+ pfree(DatumGetPointer(oldVal));
+ /* and remember the new one for subsequent equality checks */
+ oldVal = *newVal;
+ oldAbbrevVal = newAbbrevVal;
+ oldIsNull = *isNull;
+ haveOldVal = true;
+ }
+
+ MemoryContextSwitchTo(oldContext);
+ }
+
+ if (!oldIsNull && !pertrans->inputtypeByVal)
+ pfree(DatumGetPointer(oldVal));
+
+ tuplesort_end(pertrans->sortstates[aggstate->current_set]);
+ pertrans->sortstates[aggstate->current_set] = NULL;
+}
+
+/*
+ * Run the transition function for a DISTINCT or ORDER BY aggregate
+ * with more than one input. This is called after we have completed
+ * entering all the input values into the sort object. We complete the
+ * sort, read out the values in sorted order, and run the transition
+ * function on each value (applying DISTINCT if appropriate).
+ *
+ * This function handles only one grouping set (already set in
+ * aggstate->current_set).
+ *
+ * When called, CurrentMemoryContext should be the per-query context.
+ */
+static void
+process_ordered_aggregate_multi(AggState *aggstate,
+ AggStatePerTrans pertrans,
+ AggStatePerGroup pergroupstate)
+{
+ ExprContext *tmpcontext = aggstate->tmpcontext;
+ FunctionCallInfo fcinfo = pertrans->transfn_fcinfo;
+ TupleTableSlot *slot1 = pertrans->sortslot;
+ TupleTableSlot *slot2 = pertrans->uniqslot;
+ int numTransInputs = pertrans->numTransInputs;
+ int numDistinctCols = pertrans->numDistinctCols;
+ Datum newAbbrevVal = (Datum) 0;
+ Datum oldAbbrevVal = (Datum) 0;
+ bool haveOldValue = false;
+ TupleTableSlot *save = aggstate->tmpcontext->ecxt_outertuple;
+ int i;
+
+ tuplesort_performsort(pertrans->sortstates[aggstate->current_set]);
+
+ ExecClearTuple(slot1);
+ if (slot2)
+ ExecClearTuple(slot2);
+
+ while (tuplesort_gettupleslot(pertrans->sortstates[aggstate->current_set],
+ true, true, slot1, &newAbbrevVal))
+ {
+ CHECK_FOR_INTERRUPTS();
+
+ tmpcontext->ecxt_outertuple = slot1;
+ tmpcontext->ecxt_innertuple = slot2;
+
+ if (numDistinctCols == 0 ||
+ !haveOldValue ||
+ newAbbrevVal != oldAbbrevVal ||
+ !ExecQual(pertrans->equalfnMulti, tmpcontext))
+ {
+ /*
+ * Extract the first numTransInputs columns as datums to pass to
+ * the transfn.
+ */
+ slot_getsomeattrs(slot1, numTransInputs);
+
+ /* Load values into fcinfo */
+ /* Start from 1, since the 0th arg will be the transition value */
+ for (i = 0; i < numTransInputs; i++)
+ {
+ fcinfo->args[i + 1].value = slot1->tts_values[i];
+ fcinfo->args[i + 1].isnull = slot1->tts_isnull[i];
+ }
+
+ advance_transition_function(aggstate, pertrans, pergroupstate);
+
+ if (numDistinctCols > 0)
+ {
+ /* swap the slot pointers to retain the current tuple */
+ TupleTableSlot *tmpslot = slot2;
+
+ slot2 = slot1;
+ slot1 = tmpslot;
+ /* avoid ExecQual() calls by reusing abbreviated keys */
+ oldAbbrevVal = newAbbrevVal;
+ haveOldValue = true;
+ }
+ }
+
+ /* Reset context each time */
+ ResetExprContext(tmpcontext);
+
+ ExecClearTuple(slot1);
+ }
+
+ if (slot2)
+ ExecClearTuple(slot2);
+
+ tuplesort_end(pertrans->sortstates[aggstate->current_set]);
+ pertrans->sortstates[aggstate->current_set] = NULL;
+
+ /* restore previous slot, potentially in use for grouping sets */
+ tmpcontext->ecxt_outertuple = save;
+}
+
+/*
+ * Compute the final value of one aggregate.
+ *
+ * This function handles only one grouping set (already set in
+ * aggstate->current_set).
+ *
+ * The finalfn will be run, and the result delivered, in the
+ * output-tuple context; caller's CurrentMemoryContext does not matter.
+ *
+ * The finalfn uses the state as set in the transno. This also might be
+ * being used by another aggregate function, so it's important that we do
+ * nothing destructive here.
+ */
+static void
+finalize_aggregate(AggState *aggstate,
+ AggStatePerAgg peragg,
+ AggStatePerGroup pergroupstate,
+ Datum *resultVal, bool *resultIsNull)
+{
+ LOCAL_FCINFO(fcinfo, FUNC_MAX_ARGS);
+ bool anynull = false;
+ MemoryContext oldContext;
+ int i;
+ ListCell *lc;
+ AggStatePerTrans pertrans = &aggstate->pertrans[peragg->transno];
+
+ oldContext = MemoryContextSwitchTo(aggstate->ss.ps.ps_ExprContext->ecxt_per_tuple_memory);
+
+ /*
+ * Evaluate any direct arguments. We do this even if there's no finalfn
+ * (which is unlikely anyway), so that side-effects happen as expected.
+ * The direct arguments go into arg positions 1 and up, leaving position 0
+ * for the transition state value.
+ */
+ i = 1;
+ foreach(lc, peragg->aggdirectargs)
+ {
+ ExprState *expr = (ExprState *) lfirst(lc);
+
+ fcinfo->args[i].value = ExecEvalExpr(expr,
+ aggstate->ss.ps.ps_ExprContext,
+ &fcinfo->args[i].isnull);
+ anynull |= fcinfo->args[i].isnull;
+ i++;
+ }
+
+ /*
+ * Apply the agg's finalfn if one is provided, else return transValue.
+ */
+ if (OidIsValid(peragg->finalfn_oid))
+ {
+ int numFinalArgs = peragg->numFinalArgs;
+
+ /* set up aggstate->curperagg for AggGetAggref() */
+ aggstate->curperagg = peragg;
+
+ InitFunctionCallInfoData(*fcinfo, &peragg->finalfn,
+ numFinalArgs,
+ pertrans->aggCollation,
+ (void *) aggstate, NULL);
+
+ /* Fill in the transition state value */
+ fcinfo->args[0].value =
+ MakeExpandedObjectReadOnly(pergroupstate->transValue,
+ pergroupstate->transValueIsNull,
+ pertrans->transtypeLen);
+ fcinfo->args[0].isnull = pergroupstate->transValueIsNull;
+ anynull |= pergroupstate->transValueIsNull;
+
+ /* Fill any remaining argument positions with nulls */
+ for (; i < numFinalArgs; i++)
+ {
+ fcinfo->args[i].value = (Datum) 0;
+ fcinfo->args[i].isnull = true;
+ anynull = true;
+ }
+
+ if (fcinfo->flinfo->fn_strict && anynull)
+ {
+ /* don't call a strict function with NULL inputs */
+ *resultVal = (Datum) 0;
+ *resultIsNull = true;
+ }
+ else
+ {
+ *resultVal = FunctionCallInvoke(fcinfo);
+ *resultIsNull = fcinfo->isnull;
+ }
+ aggstate->curperagg = NULL;
+ }
+ else
+ {
+ /* Don't need MakeExpandedObjectReadOnly; datumCopy will copy it */
+ *resultVal = pergroupstate->transValue;
+ *resultIsNull = pergroupstate->transValueIsNull;
+ }
+
+ /*
+ * If result is pass-by-ref, make sure it is in the right context.
+ */
+ if (!peragg->resulttypeByVal && !*resultIsNull &&
+ !MemoryContextContains(CurrentMemoryContext,
+ DatumGetPointer(*resultVal)))
+ *resultVal = datumCopy(*resultVal,
+ peragg->resulttypeByVal,
+ peragg->resulttypeLen);
+
+ MemoryContextSwitchTo(oldContext);
+}
+
+/*
+ * Compute the output value of one partial aggregate.
+ *
+ * The serialization function will be run, and the result delivered, in the
+ * output-tuple context; caller's CurrentMemoryContext does not matter.
+ */
+static void
+finalize_partialaggregate(AggState *aggstate,
+ AggStatePerAgg peragg,
+ AggStatePerGroup pergroupstate,
+ Datum *resultVal, bool *resultIsNull)
+{
+ AggStatePerTrans pertrans = &aggstate->pertrans[peragg->transno];
+ MemoryContext oldContext;
+
+ oldContext = MemoryContextSwitchTo(aggstate->ss.ps.ps_ExprContext->ecxt_per_tuple_memory);
+
+ /*
+ * serialfn_oid will be set if we must serialize the transvalue before
+ * returning it
+ */
+ if (OidIsValid(pertrans->serialfn_oid))
+ {
+ /* Don't call a strict serialization function with NULL input. */
+ if (pertrans->serialfn.fn_strict && pergroupstate->transValueIsNull)
+ {
+ *resultVal = (Datum) 0;
+ *resultIsNull = true;
+ }
+ else
+ {
+ FunctionCallInfo fcinfo = pertrans->serialfn_fcinfo;
+
+ fcinfo->args[0].value =
+ MakeExpandedObjectReadOnly(pergroupstate->transValue,
+ pergroupstate->transValueIsNull,
+ pertrans->transtypeLen);
+ fcinfo->args[0].isnull = pergroupstate->transValueIsNull;
+ fcinfo->isnull = false;
+
+ *resultVal = FunctionCallInvoke(fcinfo);
+ *resultIsNull = fcinfo->isnull;
+ }
+ }
+ else
+ {
+ /* Don't need MakeExpandedObjectReadOnly; datumCopy will copy it */
+ *resultVal = pergroupstate->transValue;
+ *resultIsNull = pergroupstate->transValueIsNull;
+ }
+
+ /* If result is pass-by-ref, make sure it is in the right context. */
+ if (!peragg->resulttypeByVal && !*resultIsNull &&
+ !MemoryContextContains(CurrentMemoryContext,
+ DatumGetPointer(*resultVal)))
+ *resultVal = datumCopy(*resultVal,
+ peragg->resulttypeByVal,
+ peragg->resulttypeLen);
+
+ MemoryContextSwitchTo(oldContext);
+}
+
+/*
+ * Extract the attributes that make up the grouping key into the
+ * hashslot. This is necessary to compute the hash or perform a lookup.
+ */
+static inline void
+prepare_hash_slot(AggStatePerHash perhash,
+ TupleTableSlot *inputslot,
+ TupleTableSlot *hashslot)
+{
+ int i;
+
+ /* transfer just the needed columns into hashslot */
+ slot_getsomeattrs(inputslot, perhash->largestGrpColIdx);
+ ExecClearTuple(hashslot);
+
+ for (i = 0; i < perhash->numhashGrpCols; i++)
+ {
+ int varNumber = perhash->hashGrpColIdxInput[i] - 1;
+
+ hashslot->tts_values[i] = inputslot->tts_values[varNumber];
+ hashslot->tts_isnull[i] = inputslot->tts_isnull[varNumber];
+ }
+ ExecStoreVirtualTuple(hashslot);
+}
+
+/*
+ * Prepare to finalize and project based on the specified representative tuple
+ * slot and grouping set.
+ *
+ * In the specified tuple slot, force to null all attributes that should be
+ * read as null in the context of the current grouping set. Also stash the
+ * current group bitmap where GroupingExpr can get at it.
+ *
+ * This relies on three conditions:
+ *
+ * 1) Nothing is ever going to try and extract the whole tuple from this slot,
+ * only reference it in evaluations, which will only access individual
+ * attributes.
+ *
+ * 2) No system columns are going to need to be nulled. (If a system column is
+ * referenced in a group clause, it is actually projected in the outer plan
+ * tlist.)
+ *
+ * 3) Within a given phase, we never need to recover the value of an attribute
+ * once it has been set to null.
+ *
+ * Poking into the slot this way is a bit ugly, but the consensus is that the
+ * alternative was worse.
+ */
+static void
+prepare_projection_slot(AggState *aggstate, TupleTableSlot *slot, int currentSet)
+{
+ if (aggstate->phase->grouped_cols)
+ {
+ Bitmapset *grouped_cols = aggstate->phase->grouped_cols[currentSet];
+
+ aggstate->grouped_cols = grouped_cols;
+
+ if (TTS_EMPTY(slot))
+ {
+ /*
+ * Force all values to be NULL if working on an empty input tuple
+ * (i.e. an empty grouping set for which no input rows were
+ * supplied).
+ */
+ ExecStoreAllNullTuple(slot);
+ }
+ else if (aggstate->all_grouped_cols)
+ {
+ ListCell *lc;
+
+ /* all_grouped_cols is arranged in desc order */
+ slot_getsomeattrs(slot, linitial_int(aggstate->all_grouped_cols));
+
+ foreach(lc, aggstate->all_grouped_cols)
+ {
+ int attnum = lfirst_int(lc);
+
+ if (!bms_is_member(attnum, grouped_cols))
+ slot->tts_isnull[attnum - 1] = true;
+ }
+ }
+ }
+}
+
+/*
+ * Compute the final value of all aggregates for one group.
+ *
+ * This function handles only one grouping set at a time, which the caller must
+ * have selected. It's also the caller's responsibility to adjust the supplied
+ * pergroup parameter to point to the current set's transvalues.
+ *
+ * Results are stored in the output econtext aggvalues/aggnulls.
+ */
+static void
+finalize_aggregates(AggState *aggstate,
+ AggStatePerAgg peraggs,
+ AggStatePerGroup pergroup)
+{
+ ExprContext *econtext = aggstate->ss.ps.ps_ExprContext;
+ Datum *aggvalues = econtext->ecxt_aggvalues;
+ bool *aggnulls = econtext->ecxt_aggnulls;
+ int aggno;
+ int transno;
+
+ /*
+ * If there were any DISTINCT and/or ORDER BY aggregates, sort their
+ * inputs and run the transition functions.
+ */
+ for (transno = 0; transno < aggstate->numtrans; transno++)
+ {
+ AggStatePerTrans pertrans = &aggstate->pertrans[transno];
+ AggStatePerGroup pergroupstate;
+
+ pergroupstate = &pergroup[transno];
+
+ if (pertrans->numSortCols > 0)
+ {
+ Assert(aggstate->aggstrategy != AGG_HASHED &&
+ aggstate->aggstrategy != AGG_MIXED);
+
+ if (pertrans->numInputs == 1)
+ process_ordered_aggregate_single(aggstate,
+ pertrans,
+ pergroupstate);
+ else
+ process_ordered_aggregate_multi(aggstate,
+ pertrans,
+ pergroupstate);
+ }
+ }
+
+ /*
+ * Run the final functions.
+ */
+ for (aggno = 0; aggno < aggstate->numaggs; aggno++)
+ {
+ AggStatePerAgg peragg = &peraggs[aggno];
+ int transno = peragg->transno;
+ AggStatePerGroup pergroupstate;
+
+ pergroupstate = &pergroup[transno];
+
+ if (DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit))
+ finalize_partialaggregate(aggstate, peragg, pergroupstate,
+ &aggvalues[aggno], &aggnulls[aggno]);
+ else
+ finalize_aggregate(aggstate, peragg, pergroupstate,
+ &aggvalues[aggno], &aggnulls[aggno]);
+ }
+}
+
+/*
+ * Project the result of a group (whose aggs have already been calculated by
+ * finalize_aggregates). Returns the result slot, or NULL if no row is
+ * projected (suppressed by qual).
+ */
+static TupleTableSlot *
+project_aggregates(AggState *aggstate)
+{
+ ExprContext *econtext = aggstate->ss.ps.ps_ExprContext;
+
+ /*
+ * Check the qual (HAVING clause); if the group does not match, ignore it.
+ */
+ if (ExecQual(aggstate->ss.ps.qual, econtext))
+ {
+ /*
+ * Form and return projection tuple using the aggregate results and
+ * the representative input tuple.
+ */
+ return ExecProject(aggstate->ss.ps.ps_ProjInfo);
+ }
+ else
+ InstrCountFiltered1(aggstate, 1);
+
+ return NULL;
+}
+
+/*
+ * Find input-tuple columns that are needed, dividing them into
+ * aggregated and unaggregated sets.
+ */
+static void
+find_cols(AggState *aggstate, Bitmapset **aggregated, Bitmapset **unaggregated)
+{
+ Agg *agg = (Agg *) aggstate->ss.ps.plan;
+ FindColsContext context;
+
+ context.is_aggref = false;
+ context.aggregated = NULL;
+ context.unaggregated = NULL;
+
+ /* Examine tlist and quals */
+ (void) find_cols_walker((Node *) agg->plan.targetlist, &context);
+ (void) find_cols_walker((Node *) agg->plan.qual, &context);
+
+ /* In some cases, grouping columns will not appear in the tlist */
+ for (int i = 0; i < agg->numCols; i++)
+ context.unaggregated = bms_add_member(context.unaggregated,
+ agg->grpColIdx[i]);
+
+ *aggregated = context.aggregated;
+ *unaggregated = context.unaggregated;
+}
+
+static bool
+find_cols_walker(Node *node, FindColsContext *context)
+{
+ if (node == NULL)
+ return false;
+ if (IsA(node, Var))
+ {
+ Var *var = (Var *) node;
+
+ /* setrefs.c should have set the varno to OUTER_VAR */
+ Assert(var->varno == OUTER_VAR);
+ Assert(var->varlevelsup == 0);
+ if (context->is_aggref)
+ context->aggregated = bms_add_member(context->aggregated,
+ var->varattno);
+ else
+ context->unaggregated = bms_add_member(context->unaggregated,
+ var->varattno);
+ return false;
+ }
+ if (IsA(node, Aggref))
+ {
+ Assert(!context->is_aggref);
+ context->is_aggref = true;
+ expression_tree_walker(node, find_cols_walker, (void *) context);
+ context->is_aggref = false;
+ return false;
+ }
+ return expression_tree_walker(node, find_cols_walker,
+ (void *) context);
+}
+
+/*
+ * (Re-)initialize the hash table(s) to empty.
+ *
+ * To implement hashed aggregation, we need a hashtable that stores a
+ * representative tuple and an array of AggStatePerGroup structs for each
+ * distinct set of GROUP BY column values. We compute the hash key from the
+ * GROUP BY columns. The per-group data is allocated in lookup_hash_entry(),
+ * for each entry.
+ *
+ * We have a separate hashtable and associated perhash data structure for each
+ * grouping set for which we're doing hashing.
+ *
+ * The contents of the hash tables always live in the hashcontext's per-tuple
+ * memory context (there is only one of these for all tables together, since
+ * they are all reset at the same time).
+ */
+static void
+build_hash_tables(AggState *aggstate)
+{
+ int setno;
+
+ for (setno = 0; setno < aggstate->num_hashes; ++setno)
+ {
+ AggStatePerHash perhash = &aggstate->perhash[setno];
+ long nbuckets;
+ Size memory;
+
+ if (perhash->hashtable != NULL)
+ {
+ ResetTupleHashTable(perhash->hashtable);
+ continue;
+ }
+
+ Assert(perhash->aggnode->numGroups > 0);
+
+ memory = aggstate->hash_mem_limit / aggstate->num_hashes;
+
+ /* choose reasonable number of buckets per hashtable */
+ nbuckets = hash_choose_num_buckets(aggstate->hashentrysize,
+ perhash->aggnode->numGroups,
+ memory);
+
+ build_hash_table(aggstate, setno, nbuckets);
+ }
+
+ aggstate->hash_ngroups_current = 0;
+}
+
+/*
+ * Build a single hashtable for this grouping set.
+ */
+static void
+build_hash_table(AggState *aggstate, int setno, long nbuckets)
+{
+ AggStatePerHash perhash = &aggstate->perhash[setno];
+ MemoryContext metacxt = aggstate->hash_metacxt;
+ MemoryContext hashcxt = aggstate->hashcontext->ecxt_per_tuple_memory;
+ MemoryContext tmpcxt = aggstate->tmpcontext->ecxt_per_tuple_memory;
+ Size additionalsize;
+
+ Assert(aggstate->aggstrategy == AGG_HASHED ||
+ aggstate->aggstrategy == AGG_MIXED);
+
+ /*
+ * Used to make sure initial hash table allocation does not exceed
+ * hash_mem. Note that the estimate does not include space for
+ * pass-by-reference transition data values, nor for the representative
+ * tuple of each group.
+ */
+ additionalsize = aggstate->numtrans * sizeof(AggStatePerGroupData);
+
+ perhash->hashtable = BuildTupleHashTableExt(&aggstate->ss.ps,
+ perhash->hashslot->tts_tupleDescriptor,
+ perhash->numCols,
+ perhash->hashGrpColIdxHash,
+ perhash->eqfuncoids,
+ perhash->hashfunctions,
+ perhash->aggnode->grpCollations,
+ nbuckets,
+ additionalsize,
+ metacxt,
+ hashcxt,
+ tmpcxt,
+ DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit));
+}
+
+/*
+ * Compute columns that actually need to be stored in hashtable entries. The
+ * incoming tuples from the child plan node will contain grouping columns,
+ * other columns referenced in our targetlist and qual, columns used to
+ * compute the aggregate functions, and perhaps just junk columns we don't use
+ * at all. Only columns of the first two types need to be stored in the
+ * hashtable, and getting rid of the others can make the table entries
+ * significantly smaller. The hashtable only contains the relevant columns,
+ * and is packed/unpacked in lookup_hash_entry() / agg_retrieve_hash_table()
+ * into the format of the normal input descriptor.
+ *
+ * Additional columns, in addition to the columns grouped by, come from two
+ * sources: Firstly functionally dependent columns that we don't need to group
+ * by themselves, and secondly ctids for row-marks.
+ *
+ * To eliminate duplicates, we build a bitmapset of the needed columns, and
+ * then build an array of the columns included in the hashtable. We might
+ * still have duplicates if the passed-in grpColIdx has them, which can happen
+ * in edge cases from semijoins/distinct; these can't always be removed,
+ * because it's not certain that the duplicate cols will be using the same
+ * hash function.
+ *
+ * Note that the array is preserved over ExecReScanAgg, so we allocate it in
+ * the per-query context (unlike the hash table itself).
+ */
+static void
+find_hash_columns(AggState *aggstate)
+{
+ Bitmapset *base_colnos;
+ Bitmapset *aggregated_colnos;
+ TupleDesc scanDesc = aggstate->ss.ss_ScanTupleSlot->tts_tupleDescriptor;
+ List *outerTlist = outerPlanState(aggstate)->plan->targetlist;
+ int numHashes = aggstate->num_hashes;
+ EState *estate = aggstate->ss.ps.state;
+ int j;
+
+ /* Find Vars that will be needed in tlist and qual */
+ find_cols(aggstate, &aggregated_colnos, &base_colnos);
+ aggstate->colnos_needed = bms_union(base_colnos, aggregated_colnos);
+ aggstate->max_colno_needed = 0;
+ aggstate->all_cols_needed = true;
+
+ for (int i = 0; i < scanDesc->natts; i++)
+ {
+ int colno = i + 1;
+
+ if (bms_is_member(colno, aggstate->colnos_needed))
+ aggstate->max_colno_needed = colno;
+ else
+ aggstate->all_cols_needed = false;
+ }
+
+ for (j = 0; j < numHashes; ++j)
+ {
+ AggStatePerHash perhash = &aggstate->perhash[j];
+ Bitmapset *colnos = bms_copy(base_colnos);
+ AttrNumber *grpColIdx = perhash->aggnode->grpColIdx;
+ List *hashTlist = NIL;
+ TupleDesc hashDesc;
+ int maxCols;
+ int i;
+
+ perhash->largestGrpColIdx = 0;
+
+ /*
+ * If we're doing grouping sets, then some Vars might be referenced in
+ * tlist/qual for the benefit of other grouping sets, but not needed
+ * when hashing; i.e. prepare_projection_slot will null them out, so
+ * there'd be no point storing them. Use prepare_projection_slot's
+ * logic to determine which.
+ */
+ if (aggstate->phases[0].grouped_cols)
+ {
+ Bitmapset *grouped_cols = aggstate->phases[0].grouped_cols[j];
+ ListCell *lc;
+
+ foreach(lc, aggstate->all_grouped_cols)
+ {
+ int attnum = lfirst_int(lc);
+
+ if (!bms_is_member(attnum, grouped_cols))
+ colnos = bms_del_member(colnos, attnum);
+ }
+ }
+
+ /*
+ * Compute maximum number of input columns accounting for possible
+ * duplications in the grpColIdx array, which can happen in some edge
+ * cases where HashAggregate was generated as part of a semijoin or a
+ * DISTINCT.
+ */
+ maxCols = bms_num_members(colnos) + perhash->numCols;
+
+ perhash->hashGrpColIdxInput =
+ palloc(maxCols * sizeof(AttrNumber));
+ perhash->hashGrpColIdxHash =
+ palloc(perhash->numCols * sizeof(AttrNumber));
+
+ /* Add all the grouping columns to colnos */
+ for (i = 0; i < perhash->numCols; i++)
+ colnos = bms_add_member(colnos, grpColIdx[i]);
+
+ /*
+ * First build mapping for columns directly hashed. These are the
+ * first, because they'll be accessed when computing hash values and
+ * comparing tuples for exact matches. We also build simple mapping
+ * for execGrouping, so it knows where to find the to-be-hashed /
+ * compared columns in the input.
+ */
+ for (i = 0; i < perhash->numCols; i++)
+ {
+ perhash->hashGrpColIdxInput[i] = grpColIdx[i];
+ perhash->hashGrpColIdxHash[i] = i + 1;
+ perhash->numhashGrpCols++;
+ /* delete already mapped columns */
+ bms_del_member(colnos, grpColIdx[i]);
+ }
+
+ /* and add the remaining columns */
+ while ((i = bms_first_member(colnos)) >= 0)
+ {
+ perhash->hashGrpColIdxInput[perhash->numhashGrpCols] = i;
+ perhash->numhashGrpCols++;
+ }
+
+ /* and build a tuple descriptor for the hashtable */
+ for (i = 0; i < perhash->numhashGrpCols; i++)
+ {
+ int varNumber = perhash->hashGrpColIdxInput[i] - 1;
+
+ hashTlist = lappend(hashTlist, list_nth(outerTlist, varNumber));
+ perhash->largestGrpColIdx =
+ Max(varNumber + 1, perhash->largestGrpColIdx);
+ }
+
+ hashDesc = ExecTypeFromTL(hashTlist);
+
+ execTuplesHashPrepare(perhash->numCols,
+ perhash->aggnode->grpOperators,
+ &perhash->eqfuncoids,
+ &perhash->hashfunctions);
+ perhash->hashslot =
+ ExecAllocTableSlot(&estate->es_tupleTable, hashDesc,
+ &TTSOpsMinimalTuple);
+
+ list_free(hashTlist);
+ bms_free(colnos);
+ }
+
+ bms_free(base_colnos);
+}
+
+/*
+ * Estimate per-hash-table-entry overhead.
+ */
+Size
+hash_agg_entry_size(int numTrans, Size tupleWidth, Size transitionSpace)
+{
+ Size tupleChunkSize;
+ Size pergroupChunkSize;
+ Size transitionChunkSize;
+ Size tupleSize = (MAXALIGN(SizeofMinimalTupleHeader) +
+ tupleWidth);
+ Size pergroupSize = numTrans * sizeof(AggStatePerGroupData);
+
+ tupleChunkSize = CHUNKHDRSZ + tupleSize;
+
+ if (pergroupSize > 0)
+ pergroupChunkSize = CHUNKHDRSZ + pergroupSize;
+ else
+ pergroupChunkSize = 0;
+
+ if (transitionSpace > 0)
+ transitionChunkSize = CHUNKHDRSZ + transitionSpace;
+ else
+ transitionChunkSize = 0;
+
+ return
+ sizeof(TupleHashEntryData) +
+ tupleChunkSize +
+ pergroupChunkSize +
+ transitionChunkSize;
+}
+
+/*
+ * hashagg_recompile_expressions()
+ *
+ * Identifies the right phase, compiles the right expression given the
+ * arguments, and then sets phase->evalfunc to that expression.
+ *
+ * Different versions of the compiled expression are needed depending on
+ * whether hash aggregation has spilled or not, and whether it's reading from
+ * the outer plan or a tape. Before spilling to disk, the expression reads
+ * from the outer plan and does not need to perform a NULL check. After
+ * HashAgg begins to spill, new groups will not be created in the hash table,
+ * and the AggStatePerGroup array may be NULL; therefore we need to add a null
+ * pointer check to the expression. Then, when reading spilled data from a
+ * tape, we change the outer slot type to be a fixed minimal tuple slot.
+ *
+ * It would be wasteful to recompile every time, so cache the compiled
+ * expressions in the AggStatePerPhase, and reuse when appropriate.
+ */
+static void
+hashagg_recompile_expressions(AggState *aggstate, bool minslot, bool nullcheck)
+{
+ AggStatePerPhase phase;
+ int i = minslot ? 1 : 0;
+ int j = nullcheck ? 1 : 0;
+
+ Assert(aggstate->aggstrategy == AGG_HASHED ||
+ aggstate->aggstrategy == AGG_MIXED);
+
+ if (aggstate->aggstrategy == AGG_HASHED)
+ phase = &aggstate->phases[0];
+ else /* AGG_MIXED */
+ phase = &aggstate->phases[1];
+
+ if (phase->evaltrans_cache[i][j] == NULL)
+ {
+ const TupleTableSlotOps *outerops = aggstate->ss.ps.outerops;
+ bool outerfixed = aggstate->ss.ps.outeropsfixed;
+ bool dohash = true;
+ bool dosort = false;
+
+ /*
+ * If minslot is true, that means we are processing a spilled batch
+ * (inside agg_refill_hash_table()), and we must not advance the
+ * sorted grouping sets.
+ */
+ if (aggstate->aggstrategy == AGG_MIXED && !minslot)
+ dosort = true;
+
+ /* temporarily change the outerops while compiling the expression */
+ if (minslot)
+ {
+ aggstate->ss.ps.outerops = &TTSOpsMinimalTuple;
+ aggstate->ss.ps.outeropsfixed = true;
+ }
+
+ phase->evaltrans_cache[i][j] = ExecBuildAggTrans(aggstate, phase,
+ dosort, dohash,
+ nullcheck);
+
+ /* change back */
+ aggstate->ss.ps.outerops = outerops;
+ aggstate->ss.ps.outeropsfixed = outerfixed;
+ }
+
+ phase->evaltrans = phase->evaltrans_cache[i][j];
+}
+
+/*
+ * Set limits that trigger spilling to avoid exceeding hash_mem. Consider the
+ * number of partitions we expect to create (if we do spill).
+ *
+ * There are two limits: a memory limit, and also an ngroups limit. The
+ * ngroups limit becomes important when we expect transition values to grow
+ * substantially larger than the initial value.
+ */
+void
+hash_agg_set_limits(double hashentrysize, double input_groups, int used_bits,
+ Size *mem_limit, uint64 *ngroups_limit,
+ int *num_partitions)
+{
+ int npartitions;
+ Size partition_mem;
+ Size hash_mem_limit = get_hash_memory_limit();
+
+ /* if not expected to spill, use all of hash_mem */
+ if (input_groups * hashentrysize <= hash_mem_limit)
+ {
+ if (num_partitions != NULL)
+ *num_partitions = 0;
+ *mem_limit = hash_mem_limit;
+ *ngroups_limit = hash_mem_limit / hashentrysize;
+ return;
+ }
+
+ /*
+ * Calculate expected memory requirements for spilling, which is the size
+ * of the buffers needed for all the tapes that need to be open at once.
+ * Then, subtract that from the memory available for holding hash tables.
+ */
+ npartitions = hash_choose_num_partitions(input_groups,
+ hashentrysize,
+ used_bits,
+ NULL);
+ if (num_partitions != NULL)
+ *num_partitions = npartitions;
+
+ partition_mem =
+ HASHAGG_READ_BUFFER_SIZE +
+ HASHAGG_WRITE_BUFFER_SIZE * npartitions;
+
+ /*
+ * Don't set the limit below 3/4 of hash_mem. In that case, we are at the
+ * minimum number of partitions, so we aren't going to dramatically exceed
+ * work mem anyway.
+ */
+ if (hash_mem_limit > 4 * partition_mem)
+ *mem_limit = hash_mem_limit - partition_mem;
+ else
+ *mem_limit = hash_mem_limit * 0.75;
+
+ if (*mem_limit > hashentrysize)
+ *ngroups_limit = *mem_limit / hashentrysize;
+ else
+ *ngroups_limit = 1;
+}
+
+/*
+ * hash_agg_check_limits
+ *
+ * After adding a new group to the hash table, check whether we need to enter
+ * spill mode. Allocations may happen without adding new groups (for instance,
+ * if the transition state size grows), so this check is imperfect.
+ */
+static void
+hash_agg_check_limits(AggState *aggstate)
+{
+ uint64 ngroups = aggstate->hash_ngroups_current;
+ Size meta_mem = MemoryContextMemAllocated(aggstate->hash_metacxt,
+ true);
+ Size hashkey_mem = MemoryContextMemAllocated(aggstate->hashcontext->ecxt_per_tuple_memory,
+ true);
+
+ /*
+ * Don't spill unless there's at least one group in the hash table so we
+ * can be sure to make progress even in edge cases.
+ */
+ if (aggstate->hash_ngroups_current > 0 &&
+ (meta_mem + hashkey_mem > aggstate->hash_mem_limit ||
+ ngroups > aggstate->hash_ngroups_limit))
+ {
+ hash_agg_enter_spill_mode(aggstate);
+ }
+}
+
+/*
+ * Enter "spill mode", meaning that no new groups are added to any of the hash
+ * tables. Tuples that would create a new group are instead spilled, and
+ * processed later.
+ */
+static void
+hash_agg_enter_spill_mode(AggState *aggstate)
+{
+ aggstate->hash_spill_mode = true;
+ hashagg_recompile_expressions(aggstate, aggstate->table_filled, true);
+
+ if (!aggstate->hash_ever_spilled)
+ {
+ Assert(aggstate->hash_tapeinfo == NULL);
+ Assert(aggstate->hash_spills == NULL);
+
+ aggstate->hash_ever_spilled = true;
+
+ hashagg_tapeinfo_init(aggstate);
+
+ aggstate->hash_spills = palloc(sizeof(HashAggSpill) * aggstate->num_hashes);
+
+ for (int setno = 0; setno < aggstate->num_hashes; setno++)
+ {
+ AggStatePerHash perhash = &aggstate->perhash[setno];
+ HashAggSpill *spill = &aggstate->hash_spills[setno];
+
+ hashagg_spill_init(spill, aggstate->hash_tapeinfo, 0,
+ perhash->aggnode->numGroups,
+ aggstate->hashentrysize);
+ }
+ }
+}
+
+/*
+ * Update metrics after filling the hash table.
+ *
+ * If reading from the outer plan, from_tape should be false; if reading from
+ * another tape, from_tape should be true.
+ */
+static void
+hash_agg_update_metrics(AggState *aggstate, bool from_tape, int npartitions)
+{
+ Size meta_mem;
+ Size hashkey_mem;
+ Size buffer_mem;
+ Size total_mem;
+
+ if (aggstate->aggstrategy != AGG_MIXED &&
+ aggstate->aggstrategy != AGG_HASHED)
+ return;
+
+ /* memory for the hash table itself */
+ meta_mem = MemoryContextMemAllocated(aggstate->hash_metacxt, true);
+
+ /* memory for the group keys and transition states */
+ hashkey_mem = MemoryContextMemAllocated(aggstate->hashcontext->ecxt_per_tuple_memory, true);
+
+ /* memory for read/write tape buffers, if spilled */
+ buffer_mem = npartitions * HASHAGG_WRITE_BUFFER_SIZE;
+ if (from_tape)
+ buffer_mem += HASHAGG_READ_BUFFER_SIZE;
+
+ /* update peak mem */
+ total_mem = meta_mem + hashkey_mem + buffer_mem;
+ if (total_mem > aggstate->hash_mem_peak)
+ aggstate->hash_mem_peak = total_mem;
+
+ /* update disk usage */
+ if (aggstate->hash_tapeinfo != NULL)
+ {
+ uint64 disk_used = LogicalTapeSetBlocks(aggstate->hash_tapeinfo->tapeset) * (BLCKSZ / 1024);
+
+ if (aggstate->hash_disk_used < disk_used)
+ aggstate->hash_disk_used = disk_used;
+ }
+
+ /* update hashentrysize estimate based on contents */
+ if (aggstate->hash_ngroups_current > 0)
+ {
+ aggstate->hashentrysize =
+ sizeof(TupleHashEntryData) +
+ (hashkey_mem / (double) aggstate->hash_ngroups_current);
+ }
+}
+
+/*
+ * Choose a reasonable number of buckets for the initial hash table size.
+ */
+static long
+hash_choose_num_buckets(double hashentrysize, long ngroups, Size memory)
+{
+ long max_nbuckets;
+ long nbuckets = ngroups;
+
+ max_nbuckets = memory / hashentrysize;
+
+ /*
+ * Underestimating is better than overestimating. Too many buckets crowd
+ * out space for group keys and transition state values.
+ */
+ max_nbuckets >>= 1;
+
+ if (nbuckets > max_nbuckets)
+ nbuckets = max_nbuckets;
+
+ return Max(nbuckets, 1);
+}
+
+/*
+ * Determine the number of partitions to create when spilling, which will
+ * always be a power of two. If log2_npartitions is non-NULL, set
+ * *log2_npartitions to the log2() of the number of partitions.
+ */
+static int
+hash_choose_num_partitions(double input_groups, double hashentrysize,
+ int used_bits, int *log2_npartitions)
+{
+ Size hash_mem_limit = get_hash_memory_limit();
+ double partition_limit;
+ double mem_wanted;
+ double dpartitions;
+ int npartitions;
+ int partition_bits;
+
+ /*
+ * Avoid creating so many partitions that the memory requirements of the
+ * open partition files are greater than 1/4 of hash_mem.
+ */
+ partition_limit =
+ (hash_mem_limit * 0.25 - HASHAGG_READ_BUFFER_SIZE) /
+ HASHAGG_WRITE_BUFFER_SIZE;
+
+ mem_wanted = HASHAGG_PARTITION_FACTOR * input_groups * hashentrysize;
+
+ /* make enough partitions so that each one is likely to fit in memory */
+ dpartitions = 1 + (mem_wanted / hash_mem_limit);
+
+ if (dpartitions > partition_limit)
+ dpartitions = partition_limit;
+
+ if (dpartitions < HASHAGG_MIN_PARTITIONS)
+ dpartitions = HASHAGG_MIN_PARTITIONS;
+ if (dpartitions > HASHAGG_MAX_PARTITIONS)
+ dpartitions = HASHAGG_MAX_PARTITIONS;
+
+ /* HASHAGG_MAX_PARTITIONS limit makes this safe */
+ npartitions = (int) dpartitions;
+
+ /* ceil(log2(npartitions)) */
+ partition_bits = my_log2(npartitions);
+
+ /* make sure that we don't exhaust the hash bits */
+ if (partition_bits + used_bits >= 32)
+ partition_bits = 32 - used_bits;
+
+ if (log2_npartitions != NULL)
+ *log2_npartitions = partition_bits;
+
+ /* number of partitions will be a power of two */
+ npartitions = 1 << partition_bits;
+
+ return npartitions;
+}
+
+/*
+ * Initialize a freshly-created TupleHashEntry.
+ */
+static void
+initialize_hash_entry(AggState *aggstate, TupleHashTable hashtable,
+ TupleHashEntry entry)
+{
+ AggStatePerGroup pergroup;
+ int transno;
+
+ aggstate->hash_ngroups_current++;
+ hash_agg_check_limits(aggstate);
+
+ /* no need to allocate or initialize per-group state */
+ if (aggstate->numtrans == 0)
+ return;
+
+ pergroup = (AggStatePerGroup)
+ MemoryContextAlloc(hashtable->tablecxt,
+ sizeof(AggStatePerGroupData) * aggstate->numtrans);
+
+ entry->additional = pergroup;
+
+ /*
+ * Initialize aggregates for new tuple group, lookup_hash_entries()
+ * already has selected the relevant grouping set.
+ */
+ for (transno = 0; transno < aggstate->numtrans; transno++)
+ {
+ AggStatePerTrans pertrans = &aggstate->pertrans[transno];
+ AggStatePerGroup pergroupstate = &pergroup[transno];
+
+ initialize_aggregate(aggstate, pertrans, pergroupstate);
+ }
+}
+
+/*
+ * Look up hash entries for the current tuple in all hashed grouping sets.
+ *
+ * Be aware that lookup_hash_entry can reset the tmpcontext.
+ *
+ * Some entries may be left NULL if we are in "spill mode". The same tuple
+ * will belong to different groups for each grouping set, so may match a group
+ * already in memory for one set and match a group not in memory for another
+ * set. When in "spill mode", the tuple will be spilled for each grouping set
+ * where it doesn't match a group in memory.
+ *
+ * NB: It's possible to spill the same tuple for several different grouping
+ * sets. This may seem wasteful, but it's actually a trade-off: if we spill
+ * the tuple multiple times for multiple grouping sets, it can be partitioned
+ * for each grouping set, making the refilling of the hash table very
+ * efficient.
+ */
+static void
+lookup_hash_entries(AggState *aggstate)
+{
+ AggStatePerGroup *pergroup = aggstate->hash_pergroup;
+ TupleTableSlot *outerslot = aggstate->tmpcontext->ecxt_outertuple;
+ int setno;
+
+ for (setno = 0; setno < aggstate->num_hashes; setno++)
+ {
+ AggStatePerHash perhash = &aggstate->perhash[setno];
+ TupleHashTable hashtable = perhash->hashtable;
+ TupleTableSlot *hashslot = perhash->hashslot;
+ TupleHashEntry entry;
+ uint32 hash;
+ bool isnew = false;
+ bool *p_isnew;
+
+ /* if hash table already spilled, don't create new entries */
+ p_isnew = aggstate->hash_spill_mode ? NULL : &isnew;
+
+ select_current_set(aggstate, setno, true);
+ prepare_hash_slot(perhash,
+ outerslot,
+ hashslot);
+
+ entry = LookupTupleHashEntry(hashtable, hashslot,
+ p_isnew, &hash);
+
+ if (entry != NULL)
+ {
+ if (isnew)
+ initialize_hash_entry(aggstate, hashtable, entry);
+ pergroup[setno] = entry->additional;
+ }
+ else
+ {
+ HashAggSpill *spill = &aggstate->hash_spills[setno];
+ TupleTableSlot *slot = aggstate->tmpcontext->ecxt_outertuple;
+
+ if (spill->partitions == NULL)
+ hashagg_spill_init(spill, aggstate->hash_tapeinfo, 0,
+ perhash->aggnode->numGroups,
+ aggstate->hashentrysize);
+
+ hashagg_spill_tuple(aggstate, spill, slot, hash);
+ pergroup[setno] = NULL;
+ }
+ }
+}
+
+/*
+ * ExecAgg -
+ *
+ * ExecAgg receives tuples from its outer subplan and aggregates over
+ * the appropriate attribute for each aggregate function use (Aggref
+ * node) appearing in the targetlist or qual of the node. The number
+ * of tuples to aggregate over depends on whether grouped or plain
+ * aggregation is selected. In grouped aggregation, we produce a result
+ * row for each group; in plain aggregation there's a single result row
+ * for the whole query. In either case, the value of each aggregate is
+ * stored in the expression context to be used when ExecProject evaluates
+ * the result tuple.
+ */
+static TupleTableSlot *
+ExecAgg(PlanState *pstate)
+{
+ AggState *node = castNode(AggState, pstate);
+ TupleTableSlot *result = NULL;
+
+ CHECK_FOR_INTERRUPTS();
+
+ if (!node->agg_done)
+ {
+ /* Dispatch based on strategy */
+ switch (node->phase->aggstrategy)
+ {
+ case AGG_HASHED:
+ if (!node->table_filled)
+ agg_fill_hash_table(node);
+ /* FALLTHROUGH */
+ case AGG_MIXED:
+ result = agg_retrieve_hash_table(node);
+ break;
+ case AGG_PLAIN:
+ case AGG_SORTED:
+ result = agg_retrieve_direct(node);
+ break;
+ }
+
+ if (!TupIsNull(result))
+ return result;
+ }
+
+ return NULL;
+}
+
+/*
+ * ExecAgg for non-hashed case
+ */
+static TupleTableSlot *
+agg_retrieve_direct(AggState *aggstate)
+{
+ Agg *node = aggstate->phase->aggnode;
+ ExprContext *econtext;
+ ExprContext *tmpcontext;
+ AggStatePerAgg peragg;
+ AggStatePerGroup *pergroups;
+ TupleTableSlot *outerslot;
+ TupleTableSlot *firstSlot;
+ TupleTableSlot *result;
+ bool hasGroupingSets = aggstate->phase->numsets > 0;
+ int numGroupingSets = Max(aggstate->phase->numsets, 1);
+ int currentSet;
+ int nextSetSize;
+ int numReset;
+ int i;
+
+ /*
+ * get state info from node
+ *
+ * econtext is the per-output-tuple expression context
+ *
+ * tmpcontext is the per-input-tuple expression context
+ */
+ econtext = aggstate->ss.ps.ps_ExprContext;
+ tmpcontext = aggstate->tmpcontext;
+
+ peragg = aggstate->peragg;
+ pergroups = aggstate->pergroups;
+ firstSlot = aggstate->ss.ss_ScanTupleSlot;
+
+ /*
+ * We loop retrieving groups until we find one matching
+ * aggstate->ss.ps.qual
+ *
+ * For grouping sets, we have the invariant that aggstate->projected_set
+ * is either -1 (initial call) or the index (starting from 0) in
+ * gset_lengths for the group we just completed (either by projecting a
+ * row or by discarding it in the qual).
+ */
+ while (!aggstate->agg_done)
+ {
+ /*
+ * Clear the per-output-tuple context for each group, as well as
+ * aggcontext (which contains any pass-by-ref transvalues of the old
+ * group). Some aggregate functions store working state in child
+ * contexts; those now get reset automatically without us needing to
+ * do anything special.
+ *
+ * We use ReScanExprContext not just ResetExprContext because we want
+ * any registered shutdown callbacks to be called. That allows
+ * aggregate functions to ensure they've cleaned up any non-memory
+ * resources.
+ */
+ ReScanExprContext(econtext);
+
+ /*
+ * Determine how many grouping sets need to be reset at this boundary.
+ */
+ if (aggstate->projected_set >= 0 &&
+ aggstate->projected_set < numGroupingSets)
+ numReset = aggstate->projected_set + 1;
+ else
+ numReset = numGroupingSets;
+
+ /*
+ * numReset can change on a phase boundary, but that's OK; we want to
+ * reset the contexts used in _this_ phase, and later, after possibly
+ * changing phase, initialize the right number of aggregates for the
+ * _new_ phase.
+ */
+
+ for (i = 0; i < numReset; i++)
+ {
+ ReScanExprContext(aggstate->aggcontexts[i]);
+ }
+
+ /*
+ * Check if input is complete and there are no more groups to project
+ * in this phase; move to next phase or mark as done.
+ */
+ if (aggstate->input_done == true &&
+ aggstate->projected_set >= (numGroupingSets - 1))
+ {
+ if (aggstate->current_phase < aggstate->numphases - 1)
+ {
+ initialize_phase(aggstate, aggstate->current_phase + 1);
+ aggstate->input_done = false;
+ aggstate->projected_set = -1;
+ numGroupingSets = Max(aggstate->phase->numsets, 1);
+ node = aggstate->phase->aggnode;
+ numReset = numGroupingSets;
+ }
+ else if (aggstate->aggstrategy == AGG_MIXED)
+ {
+ /*
+ * Mixed mode; we've output all the grouped stuff and have
+ * full hashtables, so switch to outputting those.
+ */
+ initialize_phase(aggstate, 0);
+ aggstate->table_filled = true;
+ ResetTupleHashIterator(aggstate->perhash[0].hashtable,
+ &aggstate->perhash[0].hashiter);
+ select_current_set(aggstate, 0, true);
+ return agg_retrieve_hash_table(aggstate);
+ }
+ else
+ {
+ aggstate->agg_done = true;
+ break;
+ }
+ }
+
+ /*
+ * Get the number of columns in the next grouping set after the last
+ * projected one (if any). This is the number of columns to compare to
+ * see if we reached the boundary of that set too.
+ */
+ if (aggstate->projected_set >= 0 &&
+ aggstate->projected_set < (numGroupingSets - 1))
+ nextSetSize = aggstate->phase->gset_lengths[aggstate->projected_set + 1];
+ else
+ nextSetSize = 0;
+
+ /*----------
+ * If a subgroup for the current grouping set is present, project it.
+ *
+ * We have a new group if:
+ * - we're out of input but haven't projected all grouping sets
+ * (checked above)
+ * OR
+ * - we already projected a row that wasn't from the last grouping
+ * set
+ * AND
+ * - the next grouping set has at least one grouping column (since
+ * empty grouping sets project only once input is exhausted)
+ * AND
+ * - the previous and pending rows differ on the grouping columns
+ * of the next grouping set
+ *----------
+ */
+ tmpcontext->ecxt_innertuple = econtext->ecxt_outertuple;
+ if (aggstate->input_done ||
+ (node->aggstrategy != AGG_PLAIN &&
+ aggstate->projected_set != -1 &&
+ aggstate->projected_set < (numGroupingSets - 1) &&
+ nextSetSize > 0 &&
+ !ExecQualAndReset(aggstate->phase->eqfunctions[nextSetSize - 1],
+ tmpcontext)))
+ {
+ aggstate->projected_set += 1;
+
+ Assert(aggstate->projected_set < numGroupingSets);
+ Assert(nextSetSize > 0 || aggstate->input_done);
+ }
+ else
+ {
+ /*
+ * We no longer care what group we just projected, the next
+ * projection will always be the first (or only) grouping set
+ * (unless the input proves to be empty).
+ */
+ aggstate->projected_set = 0;
+
+ /*
+ * If we don't already have the first tuple of the new group,
+ * fetch it from the outer plan.
+ */
+ if (aggstate->grp_firstTuple == NULL)
+ {
+ outerslot = fetch_input_tuple(aggstate);
+ if (!TupIsNull(outerslot))
+ {
+ /*
+ * Make a copy of the first input tuple; we will use this
+ * for comparisons (in group mode) and for projection.
+ */
+ aggstate->grp_firstTuple = ExecCopySlotHeapTuple(outerslot);
+ }
+ else
+ {
+ /* outer plan produced no tuples at all */
+ if (hasGroupingSets)
+ {
+ /*
+ * If there was no input at all, we need to project
+ * rows only if there are grouping sets of size 0.
+ * Note that this implies that there can't be any
+ * references to ungrouped Vars, which would otherwise
+ * cause issues with the empty output slot.
+ *
+ * XXX: This is no longer true, we currently deal with
+ * this in finalize_aggregates().
+ */
+ aggstate->input_done = true;
+
+ while (aggstate->phase->gset_lengths[aggstate->projected_set] > 0)
+ {
+ aggstate->projected_set += 1;
+ if (aggstate->projected_set >= numGroupingSets)
+ {
+ /*
+ * We can't set agg_done here because we might
+ * have more phases to do, even though the
+ * input is empty. So we need to restart the
+ * whole outer loop.
+ */
+ break;
+ }
+ }
+
+ if (aggstate->projected_set >= numGroupingSets)
+ continue;
+ }
+ else
+ {
+ aggstate->agg_done = true;
+ /* If we are grouping, we should produce no tuples too */
+ if (node->aggstrategy != AGG_PLAIN)
+ return NULL;
+ }
+ }
+ }
+
+ /*
+ * Initialize working state for a new input tuple group.
+ */
+ initialize_aggregates(aggstate, pergroups, numReset);
+
+ if (aggstate->grp_firstTuple != NULL)
+ {
+ /*
+ * Store the copied first input tuple in the tuple table slot
+ * reserved for it. The tuple will be deleted when it is
+ * cleared from the slot.
+ */
+ ExecForceStoreHeapTuple(aggstate->grp_firstTuple,
+ firstSlot, true);
+ aggstate->grp_firstTuple = NULL; /* don't keep two pointers */
+
+ /* set up for first advance_aggregates call */
+ tmpcontext->ecxt_outertuple = firstSlot;
+
+ /*
+ * Process each outer-plan tuple, and then fetch the next one,
+ * until we exhaust the outer plan or cross a group boundary.
+ */
+ for (;;)
+ {
+ /*
+ * During phase 1 only of a mixed agg, we need to update
+ * hashtables as well in advance_aggregates.
+ */
+ if (aggstate->aggstrategy == AGG_MIXED &&
+ aggstate->current_phase == 1)
+ {
+ lookup_hash_entries(aggstate);
+ }
+
+ /* Advance the aggregates (or combine functions) */
+ advance_aggregates(aggstate);
+
+ /* Reset per-input-tuple context after each tuple */
+ ResetExprContext(tmpcontext);
+
+ outerslot = fetch_input_tuple(aggstate);
+ if (TupIsNull(outerslot))
+ {
+ /* no more outer-plan tuples available */
+
+ /* if we built hash tables, finalize any spills */
+ if (aggstate->aggstrategy == AGG_MIXED &&
+ aggstate->current_phase == 1)
+ hashagg_finish_initial_spills(aggstate);
+
+ if (hasGroupingSets)
+ {
+ aggstate->input_done = true;
+ break;
+ }
+ else
+ {
+ aggstate->agg_done = true;
+ break;
+ }
+ }
+ /* set up for next advance_aggregates call */
+ tmpcontext->ecxt_outertuple = outerslot;
+
+ /*
+ * If we are grouping, check whether we've crossed a group
+ * boundary.
+ */
+ if (node->aggstrategy != AGG_PLAIN)
+ {
+ tmpcontext->ecxt_innertuple = firstSlot;
+ if (!ExecQual(aggstate->phase->eqfunctions[node->numCols - 1],
+ tmpcontext))
+ {
+ aggstate->grp_firstTuple = ExecCopySlotHeapTuple(outerslot);
+ break;
+ }
+ }
+ }
+ }
+
+ /*
+ * Use the representative input tuple for any references to
+ * non-aggregated input columns in aggregate direct args, the node
+ * qual, and the tlist. (If we are not grouping, and there are no
+ * input rows at all, we will come here with an empty firstSlot
+ * ... but if not grouping, there can't be any references to
+ * non-aggregated input columns, so no problem.)
+ */
+ econtext->ecxt_outertuple = firstSlot;
+ }
+
+ Assert(aggstate->projected_set >= 0);
+
+ currentSet = aggstate->projected_set;
+
+ prepare_projection_slot(aggstate, econtext->ecxt_outertuple, currentSet);
+
+ select_current_set(aggstate, currentSet, false);
+
+ finalize_aggregates(aggstate,
+ peragg,
+ pergroups[currentSet]);
+
+ /*
+ * If there's no row to project right now, we must continue rather
+ * than returning a null since there might be more groups.
+ */
+ result = project_aggregates(aggstate);
+ if (result)
+ return result;
+ }
+
+ /* No more groups */
+ return NULL;
+}
+
+/*
+ * ExecAgg for hashed case: read input and build hash table
+ */
+static void
+agg_fill_hash_table(AggState *aggstate)
+{
+ TupleTableSlot *outerslot;
+ ExprContext *tmpcontext = aggstate->tmpcontext;
+
+ /*
+ * Process each outer-plan tuple, and then fetch the next one, until we
+ * exhaust the outer plan.
+ */
+ for (;;)
+ {
+ outerslot = fetch_input_tuple(aggstate);
+ if (TupIsNull(outerslot))
+ break;
+
+ /* set up for lookup_hash_entries and advance_aggregates */
+ tmpcontext->ecxt_outertuple = outerslot;
+
+ /* Find or build hashtable entries */
+ lookup_hash_entries(aggstate);
+
+ /* Advance the aggregates (or combine functions) */
+ advance_aggregates(aggstate);
+
+ /*
+ * Reset per-input-tuple context after each tuple, but note that the
+ * hash lookups do this too
+ */
+ ResetExprContext(aggstate->tmpcontext);
+ }
+
+ /* finalize spills, if any */
+ hashagg_finish_initial_spills(aggstate);
+
+ aggstate->table_filled = true;
+ /* Initialize to walk the first hash table */
+ select_current_set(aggstate, 0, true);
+ ResetTupleHashIterator(aggstate->perhash[0].hashtable,
+ &aggstate->perhash[0].hashiter);
+}
+
+/*
+ * If any data was spilled during hash aggregation, reset the hash table and
+ * reprocess one batch of spilled data. After reprocessing a batch, the hash
+ * table will again contain data, ready to be consumed by
+ * agg_retrieve_hash_table_in_memory().
+ *
+ * Should only be called after all in memory hash table entries have been
+ * finalized and emitted.
+ *
+ * Return false when input is exhausted and there's no more work to be done;
+ * otherwise return true.
+ */
+static bool
+agg_refill_hash_table(AggState *aggstate)
+{
+ HashAggBatch *batch;
+ AggStatePerHash perhash;
+ HashAggSpill spill;
+ HashTapeInfo *tapeinfo = aggstate->hash_tapeinfo;
+ bool spill_initialized = false;
+
+ if (aggstate->hash_batches == NIL)
+ return false;
+
+ /* hash_batches is a stack, with the top item at the end of the list */
+ batch = llast(aggstate->hash_batches);
+ aggstate->hash_batches = list_delete_last(aggstate->hash_batches);
+
+ hash_agg_set_limits(aggstate->hashentrysize, batch->input_card,
+ batch->used_bits, &aggstate->hash_mem_limit,
+ &aggstate->hash_ngroups_limit, NULL);
+
+ /*
+ * Each batch only processes one grouping set; set the rest to NULL so
+ * that advance_aggregates() knows to ignore them. We don't touch
+ * pergroups for sorted grouping sets here, because they will be needed if
+ * we rescan later. The expressions for sorted grouping sets will not be
+ * evaluated after we recompile anyway.
+ */
+ MemSet(aggstate->hash_pergroup, 0,
+ sizeof(AggStatePerGroup) * aggstate->num_hashes);
+
+ /* free memory and reset hash tables */
+ ReScanExprContext(aggstate->hashcontext);
+ for (int setno = 0; setno < aggstate->num_hashes; setno++)
+ ResetTupleHashTable(aggstate->perhash[setno].hashtable);
+
+ aggstate->hash_ngroups_current = 0;
+
+ /*
+ * In AGG_MIXED mode, hash aggregation happens in phase 1 and the output
+ * happens in phase 0. So, we switch to phase 1 when processing a batch,
+ * and back to phase 0 after the batch is done.
+ */
+ Assert(aggstate->current_phase == 0);
+ if (aggstate->phase->aggstrategy == AGG_MIXED)
+ {
+ aggstate->current_phase = 1;
+ aggstate->phase = &aggstate->phases[aggstate->current_phase];
+ }
+
+ select_current_set(aggstate, batch->setno, true);
+
+ perhash = &aggstate->perhash[aggstate->current_set];
+
+ /*
+ * Spilled tuples are always read back as MinimalTuples, which may be
+ * different from the outer plan, so recompile the aggregate expressions.
+ *
+ * We still need the NULL check, because we are only processing one
+ * grouping set at a time and the rest will be NULL.
+ */
+ hashagg_recompile_expressions(aggstate, true, true);
+
+ for (;;)
+ {
+ TupleTableSlot *spillslot = aggstate->hash_spill_rslot;
+ TupleTableSlot *hashslot = perhash->hashslot;
+ TupleHashEntry entry;
+ MinimalTuple tuple;
+ uint32 hash;
+ bool isnew = false;
+ bool *p_isnew = aggstate->hash_spill_mode ? NULL : &isnew;
+
+ CHECK_FOR_INTERRUPTS();
+
+ tuple = hashagg_batch_read(batch, &hash);
+ if (tuple == NULL)
+ break;
+
+ ExecStoreMinimalTuple(tuple, spillslot, true);
+ aggstate->tmpcontext->ecxt_outertuple = spillslot;
+
+ prepare_hash_slot(perhash,
+ aggstate->tmpcontext->ecxt_outertuple,
+ hashslot);
+ entry = LookupTupleHashEntryHash(
+ perhash->hashtable, hashslot, p_isnew, hash);
+
+ if (entry != NULL)
+ {
+ if (isnew)
+ initialize_hash_entry(aggstate, perhash->hashtable, entry);
+ aggstate->hash_pergroup[batch->setno] = entry->additional;
+ advance_aggregates(aggstate);
+ }
+ else
+ {
+ if (!spill_initialized)
+ {
+ /*
+ * Avoid initializing the spill until we actually need it so
+ * that we don't assign tapes that will never be used.
+ */
+ spill_initialized = true;
+ hashagg_spill_init(&spill, tapeinfo, batch->used_bits,
+ batch->input_card, aggstate->hashentrysize);
+ }
+ /* no memory for a new group, spill */
+ hashagg_spill_tuple(aggstate, &spill, spillslot, hash);
+
+ aggstate->hash_pergroup[batch->setno] = NULL;
+ }
+
+ /*
+ * Reset per-input-tuple context after each tuple, but note that the
+ * hash lookups do this too
+ */
+ ResetExprContext(aggstate->tmpcontext);
+ }
+
+ hashagg_tapeinfo_release(tapeinfo, batch->input_tapenum);
+
+ /* change back to phase 0 */
+ aggstate->current_phase = 0;
+ aggstate->phase = &aggstate->phases[aggstate->current_phase];
+
+ if (spill_initialized)
+ {
+ hashagg_spill_finish(aggstate, &spill, batch->setno);
+ hash_agg_update_metrics(aggstate, true, spill.npartitions);
+ }
+ else
+ hash_agg_update_metrics(aggstate, true, 0);
+
+ aggstate->hash_spill_mode = false;
+
+ /* prepare to walk the first hash table */
+ select_current_set(aggstate, batch->setno, true);
+ ResetTupleHashIterator(aggstate->perhash[batch->setno].hashtable,
+ &aggstate->perhash[batch->setno].hashiter);
+
+ pfree(batch);
+
+ return true;
+}
+
+/*
+ * ExecAgg for hashed case: retrieving groups from hash table
+ *
+ * After exhausting in-memory tuples, also try refilling the hash table using
+ * previously-spilled tuples. Only returns NULL after all in-memory and
+ * spilled tuples are exhausted.
+ */
+static TupleTableSlot *
+agg_retrieve_hash_table(AggState *aggstate)
+{
+ TupleTableSlot *result = NULL;
+
+ while (result == NULL)
+ {
+ result = agg_retrieve_hash_table_in_memory(aggstate);
+ if (result == NULL)
+ {
+ if (!agg_refill_hash_table(aggstate))
+ {
+ aggstate->agg_done = true;
+ break;
+ }
+ }
+ }
+
+ return result;
+}
+
+/*
+ * Retrieve the groups from the in-memory hash tables without considering any
+ * spilled tuples.
+ */
+static TupleTableSlot *
+agg_retrieve_hash_table_in_memory(AggState *aggstate)
+{
+ ExprContext *econtext;
+ AggStatePerAgg peragg;
+ AggStatePerGroup pergroup;
+ TupleHashEntryData *entry;
+ TupleTableSlot *firstSlot;
+ TupleTableSlot *result;
+ AggStatePerHash perhash;
+
+ /*
+ * get state info from node.
+ *
+ * econtext is the per-output-tuple expression context.
+ */
+ econtext = aggstate->ss.ps.ps_ExprContext;
+ peragg = aggstate->peragg;
+ firstSlot = aggstate->ss.ss_ScanTupleSlot;
+
+ /*
+ * Note that perhash (and therefore anything accessed through it) can
+ * change inside the loop, as we change between grouping sets.
+ */
+ perhash = &aggstate->perhash[aggstate->current_set];
+
+ /*
+ * We loop retrieving groups until we find one satisfying
+ * aggstate->ss.ps.qual
+ */
+ for (;;)
+ {
+ TupleTableSlot *hashslot = perhash->hashslot;
+ int i;
+
+ CHECK_FOR_INTERRUPTS();
+
+ /*
+ * Find the next entry in the hash table
+ */
+ entry = ScanTupleHashTable(perhash->hashtable, &perhash->hashiter);
+ if (entry == NULL)
+ {
+ int nextset = aggstate->current_set + 1;
+
+ if (nextset < aggstate->num_hashes)
+ {
+ /*
+ * Switch to next grouping set, reinitialize, and restart the
+ * loop.
+ */
+ select_current_set(aggstate, nextset, true);
+
+ perhash = &aggstate->perhash[aggstate->current_set];
+
+ ResetTupleHashIterator(perhash->hashtable, &perhash->hashiter);
+
+ continue;
+ }
+ else
+ {
+ return NULL;
+ }
+ }
+
+ /*
+ * Clear the per-output-tuple context for each group
+ *
+ * We intentionally don't use ReScanExprContext here; if any aggs have
+ * registered shutdown callbacks, they mustn't be called yet, since we
+ * might not be done with that agg.
+ */
+ ResetExprContext(econtext);
+
+ /*
+ * Transform representative tuple back into one with the right
+ * columns.
+ */
+ ExecStoreMinimalTuple(entry->firstTuple, hashslot, false);
+ slot_getallattrs(hashslot);
+
+ ExecClearTuple(firstSlot);
+ memset(firstSlot->tts_isnull, true,
+ firstSlot->tts_tupleDescriptor->natts * sizeof(bool));
+
+ for (i = 0; i < perhash->numhashGrpCols; i++)
+ {
+ int varNumber = perhash->hashGrpColIdxInput[i] - 1;
+
+ firstSlot->tts_values[varNumber] = hashslot->tts_values[i];
+ firstSlot->tts_isnull[varNumber] = hashslot->tts_isnull[i];
+ }
+ ExecStoreVirtualTuple(firstSlot);
+
+ pergroup = (AggStatePerGroup) entry->additional;
+
+ /*
+ * Use the representative input tuple for any references to
+ * non-aggregated input columns in the qual and tlist.
+ */
+ econtext->ecxt_outertuple = firstSlot;
+
+ prepare_projection_slot(aggstate,
+ econtext->ecxt_outertuple,
+ aggstate->current_set);
+
+ finalize_aggregates(aggstate, peragg, pergroup);
+
+ result = project_aggregates(aggstate);
+ if (result)
+ return result;
+ }
+
+ /* No more groups */
+ return NULL;
+}
+
+/*
+ * Initialize HashTapeInfo
+ */
+static void
+hashagg_tapeinfo_init(AggState *aggstate)
+{
+ HashTapeInfo *tapeinfo = palloc(sizeof(HashTapeInfo));
+ int init_tapes = 16; /* expanded dynamically */
+
+ tapeinfo->tapeset = LogicalTapeSetCreate(init_tapes, true, NULL, NULL, -1);
+ tapeinfo->ntapes = init_tapes;
+ tapeinfo->nfreetapes = init_tapes;
+ tapeinfo->freetapes_alloc = init_tapes;
+ tapeinfo->freetapes = palloc(init_tapes * sizeof(int));
+ for (int i = 0; i < init_tapes; i++)
+ tapeinfo->freetapes[i] = i;
+
+ aggstate->hash_tapeinfo = tapeinfo;
+}
+
+/*
+ * Assign unused tapes to spill partitions, extending the tape set if
+ * necessary.
+ */
+static void
+hashagg_tapeinfo_assign(HashTapeInfo *tapeinfo, int *partitions,
+ int npartitions)
+{
+ int partidx = 0;
+
+ /* use free tapes if available */
+ while (partidx < npartitions && tapeinfo->nfreetapes > 0)
+ partitions[partidx++] = tapeinfo->freetapes[--tapeinfo->nfreetapes];
+
+ if (partidx < npartitions)
+ {
+ LogicalTapeSetExtend(tapeinfo->tapeset, npartitions - partidx);
+
+ while (partidx < npartitions)
+ partitions[partidx++] = tapeinfo->ntapes++;
+ }
+}
+
+/*
+ * After a tape has already been written to and then read, this function
+ * rewinds it for writing and adds it to the free list.
+ */
+static void
+hashagg_tapeinfo_release(HashTapeInfo *tapeinfo, int tapenum)
+{
+ /* rewinding frees the buffer while not in use */
+ LogicalTapeRewindForWrite(tapeinfo->tapeset, tapenum);
+ if (tapeinfo->freetapes_alloc == tapeinfo->nfreetapes)
+ {
+ tapeinfo->freetapes_alloc <<= 1;
+ tapeinfo->freetapes = repalloc(tapeinfo->freetapes,
+ tapeinfo->freetapes_alloc * sizeof(int));
+ }
+ tapeinfo->freetapes[tapeinfo->nfreetapes++] = tapenum;
+}
+
+/*
+ * hashagg_spill_init
+ *
+ * Called after we determined that spilling is necessary. Chooses the number
+ * of partitions to create, and initializes them.
+ */
+static void
+hashagg_spill_init(HashAggSpill *spill, HashTapeInfo *tapeinfo, int used_bits,
+ double input_groups, double hashentrysize)
+{
+ int npartitions;
+ int partition_bits;
+
+ npartitions = hash_choose_num_partitions(input_groups, hashentrysize,
+ used_bits, &partition_bits);
+
+ spill->partitions = palloc0(sizeof(int) * npartitions);
+ spill->ntuples = palloc0(sizeof(int64) * npartitions);
+ spill->hll_card = palloc0(sizeof(hyperLogLogState) * npartitions);
+
+ hashagg_tapeinfo_assign(tapeinfo, spill->partitions, npartitions);
+
+ spill->tapeset = tapeinfo->tapeset;
+ spill->shift = 32 - used_bits - partition_bits;
+ spill->mask = (npartitions - 1) << spill->shift;
+ spill->npartitions = npartitions;
+
+ for (int i = 0; i < npartitions; i++)
+ initHyperLogLog(&spill->hll_card[i], HASHAGG_HLL_BIT_WIDTH);
+}
+
+/*
+ * hashagg_spill_tuple
+ *
+ * No room for new groups in the hash table. Save for later in the appropriate
+ * partition.
+ */
+static Size
+hashagg_spill_tuple(AggState *aggstate, HashAggSpill *spill,
+ TupleTableSlot *inputslot, uint32 hash)
+{
+ LogicalTapeSet *tapeset = spill->tapeset;
+ TupleTableSlot *spillslot;
+ int partition;
+ MinimalTuple tuple;
+ int tapenum;
+ int total_written = 0;
+ bool shouldFree;
+
+ Assert(spill->partitions != NULL);
+
+ /* spill only attributes that we actually need */
+ if (!aggstate->all_cols_needed)
+ {
+ spillslot = aggstate->hash_spill_wslot;
+ slot_getsomeattrs(inputslot, aggstate->max_colno_needed);
+ ExecClearTuple(spillslot);
+ for (int i = 0; i < spillslot->tts_tupleDescriptor->natts; i++)
+ {
+ if (bms_is_member(i + 1, aggstate->colnos_needed))
+ {
+ spillslot->tts_values[i] = inputslot->tts_values[i];
+ spillslot->tts_isnull[i] = inputslot->tts_isnull[i];
+ }
+ else
+ spillslot->tts_isnull[i] = true;
+ }
+ ExecStoreVirtualTuple(spillslot);
+ }
+ else
+ spillslot = inputslot;
+
+ tuple = ExecFetchSlotMinimalTuple(spillslot, &shouldFree);
+
+ partition = (hash & spill->mask) >> spill->shift;
+ spill->ntuples[partition]++;
+
+ /*
+ * All hash values destined for a given partition have some bits in
+ * common, which causes bad HLL cardinality estimates. Hash the hash to
+ * get a more uniform distribution.
+ */
+ addHyperLogLog(&spill->hll_card[partition], hash_bytes_uint32(hash));
+
+ tapenum = spill->partitions[partition];
+
+ LogicalTapeWrite(tapeset, tapenum, (void *) &hash, sizeof(uint32));
+ total_written += sizeof(uint32);
+
+ LogicalTapeWrite(tapeset, tapenum, (void *) tuple, tuple->t_len);
+ total_written += tuple->t_len;
+
+ if (shouldFree)
+ pfree(tuple);
+
+ return total_written;
+}
+
+/*
+ * hashagg_batch_new
+ *
+ * Construct a HashAggBatch item, which represents one iteration of HashAgg to
+ * be done.
+ */
+static HashAggBatch *
+hashagg_batch_new(LogicalTapeSet *tapeset, int tapenum, int setno,
+ int64 input_tuples, double input_card, int used_bits)
+{
+ HashAggBatch *batch = palloc0(sizeof(HashAggBatch));
+
+ batch->setno = setno;
+ batch->used_bits = used_bits;
+ batch->tapeset = tapeset;
+ batch->input_tapenum = tapenum;
+ batch->input_tuples = input_tuples;
+ batch->input_card = input_card;
+
+ return batch;
+}
+
+/*
+ * read_spilled_tuple
+ * read the next tuple from a batch's tape. Return NULL if no more.
+ */
+static MinimalTuple
+hashagg_batch_read(HashAggBatch *batch, uint32 *hashp)
+{
+ LogicalTapeSet *tapeset = batch->tapeset;
+ int tapenum = batch->input_tapenum;
+ MinimalTuple tuple;
+ uint32 t_len;
+ size_t nread;
+ uint32 hash;
+
+ nread = LogicalTapeRead(tapeset, tapenum, &hash, sizeof(uint32));
+ if (nread == 0)
+ return NULL;
+ if (nread != sizeof(uint32))
+ ereport(ERROR,
+ (errcode_for_file_access(),
+ errmsg("unexpected EOF for tape %d: requested %zu bytes, read %zu bytes",
+ tapenum, sizeof(uint32), nread)));
+ if (hashp != NULL)
+ *hashp = hash;
+
+ nread = LogicalTapeRead(tapeset, tapenum, &t_len, sizeof(t_len));
+ if (nread != sizeof(uint32))
+ ereport(ERROR,
+ (errcode_for_file_access(),
+ errmsg("unexpected EOF for tape %d: requested %zu bytes, read %zu bytes",
+ tapenum, sizeof(uint32), nread)));
+
+ tuple = (MinimalTuple) palloc(t_len);
+ tuple->t_len = t_len;
+
+ nread = LogicalTapeRead(tapeset, tapenum,
+ (void *) ((char *) tuple + sizeof(uint32)),
+ t_len - sizeof(uint32));
+ if (nread != t_len - sizeof(uint32))
+ ereport(ERROR,
+ (errcode_for_file_access(),
+ errmsg("unexpected EOF for tape %d: requested %zu bytes, read %zu bytes",
+ tapenum, t_len - sizeof(uint32), nread)));
+
+ return tuple;
+}
+
+/*
+ * hashagg_finish_initial_spills
+ *
+ * After a HashAggBatch has been processed, it may have spilled tuples to
+ * disk. If so, turn the spilled partitions into new batches that must later
+ * be executed.
+ */
+static void
+hashagg_finish_initial_spills(AggState *aggstate)
+{
+ int setno;
+ int total_npartitions = 0;
+
+ if (aggstate->hash_spills != NULL)
+ {
+ for (setno = 0; setno < aggstate->num_hashes; setno++)
+ {
+ HashAggSpill *spill = &aggstate->hash_spills[setno];
+
+ total_npartitions += spill->npartitions;
+ hashagg_spill_finish(aggstate, spill, setno);
+ }
+
+ /*
+ * We're not processing tuples from outer plan any more; only
+ * processing batches of spilled tuples. The initial spill structures
+ * are no longer needed.
+ */
+ pfree(aggstate->hash_spills);
+ aggstate->hash_spills = NULL;
+ }
+
+ hash_agg_update_metrics(aggstate, false, total_npartitions);
+ aggstate->hash_spill_mode = false;
+}
+
+/*
+ * hashagg_spill_finish
+ *
+ * Transform spill partitions into new batches.
+ */
+static void
+hashagg_spill_finish(AggState *aggstate, HashAggSpill *spill, int setno)
+{
+ int i;
+ int used_bits = 32 - spill->shift;
+
+ if (spill->npartitions == 0)
+ return; /* didn't spill */
+
+ for (i = 0; i < spill->npartitions; i++)
+ {
+ LogicalTapeSet *tapeset = aggstate->hash_tapeinfo->tapeset;
+ int tapenum = spill->partitions[i];
+ HashAggBatch *new_batch;
+ double cardinality;
+
+ /* if the partition is empty, don't create a new batch of work */
+ if (spill->ntuples[i] == 0)
+ continue;
+
+ cardinality = estimateHyperLogLog(&spill->hll_card[i]);
+ freeHyperLogLog(&spill->hll_card[i]);
+
+ /* rewinding frees the buffer while not in use */
+ LogicalTapeRewindForRead(tapeset, tapenum,
+ HASHAGG_READ_BUFFER_SIZE);
+
+ new_batch = hashagg_batch_new(tapeset, tapenum, setno,
+ spill->ntuples[i], cardinality,
+ used_bits);
+ aggstate->hash_batches = lappend(aggstate->hash_batches, new_batch);
+ aggstate->hash_batches_used++;
+ }
+
+ pfree(spill->ntuples);
+ pfree(spill->hll_card);
+ pfree(spill->partitions);
+}
+
+/*
+ * Free resources related to a spilled HashAgg.
+ */
+static void
+hashagg_reset_spill_state(AggState *aggstate)
+{
+ /* free spills from initial pass */
+ if (aggstate->hash_spills != NULL)
+ {
+ int setno;
+
+ for (setno = 0; setno < aggstate->num_hashes; setno++)
+ {
+ HashAggSpill *spill = &aggstate->hash_spills[setno];
+
+ pfree(spill->ntuples);
+ pfree(spill->partitions);
+ }
+ pfree(aggstate->hash_spills);
+ aggstate->hash_spills = NULL;
+ }
+
+ /* free batches */
+ list_free_deep(aggstate->hash_batches);
+ aggstate->hash_batches = NIL;
+
+ /* close tape set */
+ if (aggstate->hash_tapeinfo != NULL)
+ {
+ HashTapeInfo *tapeinfo = aggstate->hash_tapeinfo;
+
+ LogicalTapeSetClose(tapeinfo->tapeset);
+ pfree(tapeinfo->freetapes);
+ pfree(tapeinfo);
+ aggstate->hash_tapeinfo = NULL;
+ }
+}
+
+
+/* -----------------
+ * ExecInitAgg
+ *
+ * Creates the run-time information for the agg node produced by the
+ * planner and initializes its outer subtree.
+ *
+ * -----------------
+ */
+AggState *
+ExecInitAgg(Agg *node, EState *estate, int eflags)
+{
+ AggState *aggstate;
+ AggStatePerAgg peraggs;
+ AggStatePerTrans pertransstates;
+ AggStatePerGroup *pergroups;
+ Plan *outerPlan;
+ ExprContext *econtext;
+ TupleDesc scanDesc;
+ int max_aggno;
+ int max_transno;
+ int numaggrefs;
+ int numaggs;
+ int numtrans;
+ int phase;
+ int phaseidx;
+ ListCell *l;
+ Bitmapset *all_grouped_cols = NULL;
+ int numGroupingSets = 1;
+ int numPhases;
+ int numHashes;
+ int i = 0;
+ int j = 0;
+ bool use_hashing = (node->aggstrategy == AGG_HASHED ||
+ node->aggstrategy == AGG_MIXED);
+
+ /* check for unsupported flags */
+ Assert(!(eflags & (EXEC_FLAG_BACKWARD | EXEC_FLAG_MARK)));
+
+ /*
+ * create state structure
+ */
+ aggstate = makeNode(AggState);
+ aggstate->ss.ps.plan = (Plan *) node;
+ aggstate->ss.ps.state = estate;
+ aggstate->ss.ps.ExecProcNode = ExecAgg;
+
+ aggstate->aggs = NIL;
+ aggstate->numaggs = 0;
+ aggstate->numtrans = 0;
+ aggstate->aggstrategy = node->aggstrategy;
+ aggstate->aggsplit = node->aggsplit;
+ aggstate->maxsets = 0;
+ aggstate->projected_set = -1;
+ aggstate->current_set = 0;
+ aggstate->peragg = NULL;
+ aggstate->pertrans = NULL;
+ aggstate->curperagg = NULL;
+ aggstate->curpertrans = NULL;
+ aggstate->input_done = false;
+ aggstate->agg_done = false;
+ aggstate->pergroups = NULL;
+ aggstate->grp_firstTuple = NULL;
+ aggstate->sort_in = NULL;
+ aggstate->sort_out = NULL;
+
+ /*
+ * phases[0] always exists, but is dummy in sorted/plain mode
+ */
+ numPhases = (use_hashing ? 1 : 2);
+ numHashes = (use_hashing ? 1 : 0);
+
+ /*
+ * Calculate the maximum number of grouping sets in any phase; this
+ * determines the size of some allocations. Also calculate the number of
+ * phases, since all hashed/mixed nodes contribute to only a single phase.
+ */
+ if (node->groupingSets)
+ {
+ numGroupingSets = list_length(node->groupingSets);
+
+ foreach(l, node->chain)
+ {
+ Agg *agg = lfirst(l);
+
+ numGroupingSets = Max(numGroupingSets,
+ list_length(agg->groupingSets));
+
+ /*
+ * additional AGG_HASHED aggs become part of phase 0, but all
+ * others add an extra phase.
+ */
+ if (agg->aggstrategy != AGG_HASHED)
+ ++numPhases;
+ else
+ ++numHashes;
+ }
+ }
+
+ aggstate->maxsets = numGroupingSets;
+ aggstate->numphases = numPhases;
+
+ aggstate->aggcontexts = (ExprContext **)
+ palloc0(sizeof(ExprContext *) * numGroupingSets);
+
+ /*
+ * Create expression contexts. We need three or more, one for
+ * per-input-tuple processing, one for per-output-tuple processing, one
+ * for all the hashtables, and one for each grouping set. The per-tuple
+ * memory context of the per-grouping-set ExprContexts (aggcontexts)
+ * replaces the standalone memory context formerly used to hold transition
+ * values. We cheat a little by using ExecAssignExprContext() to build
+ * all of them.
+ *
+ * NOTE: the details of what is stored in aggcontexts and what is stored
+ * in the regular per-query memory context are driven by a simple
+ * decision: we want to reset the aggcontext at group boundaries (if not
+ * hashing) and in ExecReScanAgg to recover no-longer-wanted space.
+ */
+ ExecAssignExprContext(estate, &aggstate->ss.ps);
+ aggstate->tmpcontext = aggstate->ss.ps.ps_ExprContext;
+
+ for (i = 0; i < numGroupingSets; ++i)
+ {
+ ExecAssignExprContext(estate, &aggstate->ss.ps);
+ aggstate->aggcontexts[i] = aggstate->ss.ps.ps_ExprContext;
+ }
+
+ if (use_hashing)
+ aggstate->hashcontext = CreateWorkExprContext(estate);
+
+ ExecAssignExprContext(estate, &aggstate->ss.ps);
+
+ /*
+ * Initialize child nodes.
+ *
+ * If we are doing a hashed aggregation then the child plan does not need
+ * to handle REWIND efficiently; see ExecReScanAgg.
+ */
+ if (node->aggstrategy == AGG_HASHED)
+ eflags &= ~EXEC_FLAG_REWIND;
+ outerPlan = outerPlan(node);
+ outerPlanState(aggstate) = ExecInitNode(outerPlan, estate, eflags);
+
+ /*
+ * initialize source tuple type.
+ */
+ aggstate->ss.ps.outerops =
+ ExecGetResultSlotOps(outerPlanState(&aggstate->ss),
+ &aggstate->ss.ps.outeropsfixed);
+ aggstate->ss.ps.outeropsset = true;
+
+ ExecCreateScanSlotFromOuterPlan(estate, &aggstate->ss,
+ aggstate->ss.ps.outerops);
+ scanDesc = aggstate->ss.ss_ScanTupleSlot->tts_tupleDescriptor;
+
+ /*
+ * If there are more than two phases (including a potential dummy phase
+ * 0), input will be resorted using tuplesort. Need a slot for that.
+ */
+ if (numPhases > 2)
+ {
+ aggstate->sort_slot = ExecInitExtraTupleSlot(estate, scanDesc,
+ &TTSOpsMinimalTuple);
+
+ /*
+ * The output of the tuplesort, and the output from the outer child
+ * might not use the same type of slot. In most cases the child will
+ * be a Sort, and thus return a TTSOpsMinimalTuple type slot - but the
+ * input can also be presorted due an index, in which case it could be
+ * a different type of slot.
+ *
+ * XXX: For efficiency it would be good to instead/additionally
+ * generate expressions with corresponding settings of outerops* for
+ * the individual phases - deforming is often a bottleneck for
+ * aggregations with lots of rows per group. If there's multiple
+ * sorts, we know that all but the first use TTSOpsMinimalTuple (via
+ * the nodeAgg.c internal tuplesort).
+ */
+ if (aggstate->ss.ps.outeropsfixed &&
+ aggstate->ss.ps.outerops != &TTSOpsMinimalTuple)
+ aggstate->ss.ps.outeropsfixed = false;
+ }
+
+ /*
+ * Initialize result type, slot and projection.
+ */
+ ExecInitResultTupleSlotTL(&aggstate->ss.ps, &TTSOpsVirtual);
+ ExecAssignProjectionInfo(&aggstate->ss.ps, NULL);
+
+ /*
+ * initialize child expressions
+ *
+ * We expect the parser to have checked that no aggs contain other agg
+ * calls in their arguments (and just to be sure, we verify it again while
+ * initializing the plan node). This would make no sense under SQL
+ * semantics, and it's forbidden by the spec. Because it is true, we
+ * don't need to worry about evaluating the aggs in any particular order.
+ *
+ * Note: execExpr.c finds Aggrefs for us, and adds them to aggstate->aggs.
+ * Aggrefs in the qual are found here; Aggrefs in the targetlist are found
+ * during ExecAssignProjectionInfo, above.
+ */
+ aggstate->ss.ps.qual =
+ ExecInitQual(node->plan.qual, (PlanState *) aggstate);
+
+ /*
+ * We should now have found all Aggrefs in the targetlist and quals.
+ */
+ numaggrefs = list_length(aggstate->aggs);
+ max_aggno = -1;
+ max_transno = -1;
+ foreach(l, aggstate->aggs)
+ {
+ Aggref *aggref = (Aggref *) lfirst(l);
+
+ max_aggno = Max(max_aggno, aggref->aggno);
+ max_transno = Max(max_transno, aggref->aggtransno);
+ }
+ numaggs = max_aggno + 1;
+ numtrans = max_transno + 1;
+
+ /*
+ * For each phase, prepare grouping set data and fmgr lookup data for
+ * compare functions. Accumulate all_grouped_cols in passing.
+ */
+ aggstate->phases = palloc0(numPhases * sizeof(AggStatePerPhaseData));
+
+ aggstate->num_hashes = numHashes;
+ if (numHashes)
+ {
+ aggstate->perhash = palloc0(sizeof(AggStatePerHashData) * numHashes);
+ aggstate->phases[0].numsets = 0;
+ aggstate->phases[0].gset_lengths = palloc(numHashes * sizeof(int));
+ aggstate->phases[0].grouped_cols = palloc(numHashes * sizeof(Bitmapset *));
+ }
+
+ phase = 0;
+ for (phaseidx = 0; phaseidx <= list_length(node->chain); ++phaseidx)
+ {
+ Agg *aggnode;
+ Sort *sortnode;
+
+ if (phaseidx > 0)
+ {
+ aggnode = list_nth_node(Agg, node->chain, phaseidx - 1);
+ sortnode = castNode(Sort, aggnode->plan.lefttree);
+ }
+ else
+ {
+ aggnode = node;
+ sortnode = NULL;
+ }
+
+ Assert(phase <= 1 || sortnode);
+
+ if (aggnode->aggstrategy == AGG_HASHED
+ || aggnode->aggstrategy == AGG_MIXED)
+ {
+ AggStatePerPhase phasedata = &aggstate->phases[0];
+ AggStatePerHash perhash;
+ Bitmapset *cols = NULL;
+
+ Assert(phase == 0);
+ i = phasedata->numsets++;
+ perhash = &aggstate->perhash[i];
+
+ /* phase 0 always points to the "real" Agg in the hash case */
+ phasedata->aggnode = node;
+ phasedata->aggstrategy = node->aggstrategy;
+
+ /* but the actual Agg node representing this hash is saved here */
+ perhash->aggnode = aggnode;
+
+ phasedata->gset_lengths[i] = perhash->numCols = aggnode->numCols;
+
+ for (j = 0; j < aggnode->numCols; ++j)
+ cols = bms_add_member(cols, aggnode->grpColIdx[j]);
+
+ phasedata->grouped_cols[i] = cols;
+
+ all_grouped_cols = bms_add_members(all_grouped_cols, cols);
+ continue;
+ }
+ else
+ {
+ AggStatePerPhase phasedata = &aggstate->phases[++phase];
+ int num_sets;
+
+ phasedata->numsets = num_sets = list_length(aggnode->groupingSets);
+
+ if (num_sets)
+ {
+ phasedata->gset_lengths = palloc(num_sets * sizeof(int));
+ phasedata->grouped_cols = palloc(num_sets * sizeof(Bitmapset *));
+
+ i = 0;
+ foreach(l, aggnode->groupingSets)
+ {
+ int current_length = list_length(lfirst(l));
+ Bitmapset *cols = NULL;
+
+ /* planner forces this to be correct */
+ for (j = 0; j < current_length; ++j)
+ cols = bms_add_member(cols, aggnode->grpColIdx[j]);
+
+ phasedata->grouped_cols[i] = cols;
+ phasedata->gset_lengths[i] = current_length;
+
+ ++i;
+ }
+
+ all_grouped_cols = bms_add_members(all_grouped_cols,
+ phasedata->grouped_cols[0]);
+ }
+ else
+ {
+ Assert(phaseidx == 0);
+
+ phasedata->gset_lengths = NULL;
+ phasedata->grouped_cols = NULL;
+ }
+
+ /*
+ * If we are grouping, precompute fmgr lookup data for inner loop.
+ */
+ if (aggnode->aggstrategy == AGG_SORTED)
+ {
+ int i = 0;
+
+ Assert(aggnode->numCols > 0);
+
+ /*
+ * Build a separate function for each subset of columns that
+ * need to be compared.
+ */
+ phasedata->eqfunctions =
+ (ExprState **) palloc0(aggnode->numCols * sizeof(ExprState *));
+
+ /* for each grouping set */
+ for (i = 0; i < phasedata->numsets; i++)
+ {
+ int length = phasedata->gset_lengths[i];
+
+ if (phasedata->eqfunctions[length - 1] != NULL)
+ continue;
+
+ phasedata->eqfunctions[length - 1] =
+ execTuplesMatchPrepare(scanDesc,
+ length,
+ aggnode->grpColIdx,
+ aggnode->grpOperators,
+ aggnode->grpCollations,
+ (PlanState *) aggstate);
+ }
+
+ /* and for all grouped columns, unless already computed */
+ if (phasedata->eqfunctions[aggnode->numCols - 1] == NULL)
+ {
+ phasedata->eqfunctions[aggnode->numCols - 1] =
+ execTuplesMatchPrepare(scanDesc,
+ aggnode->numCols,
+ aggnode->grpColIdx,
+ aggnode->grpOperators,
+ aggnode->grpCollations,
+ (PlanState *) aggstate);
+ }
+ }
+
+ phasedata->aggnode = aggnode;
+ phasedata->aggstrategy = aggnode->aggstrategy;
+ phasedata->sortnode = sortnode;
+ }
+ }
+
+ /*
+ * Convert all_grouped_cols to a descending-order list.
+ */
+ i = -1;
+ while ((i = bms_next_member(all_grouped_cols, i)) >= 0)
+ aggstate->all_grouped_cols = lcons_int(i, aggstate->all_grouped_cols);
+
+ /*
+ * Set up aggregate-result storage in the output expr context, and also
+ * allocate my private per-agg working storage
+ */
+ econtext = aggstate->ss.ps.ps_ExprContext;
+ econtext->ecxt_aggvalues = (Datum *) palloc0(sizeof(Datum) * numaggs);
+ econtext->ecxt_aggnulls = (bool *) palloc0(sizeof(bool) * numaggs);
+
+ peraggs = (AggStatePerAgg) palloc0(sizeof(AggStatePerAggData) * numaggs);
+ pertransstates = (AggStatePerTrans) palloc0(sizeof(AggStatePerTransData) * numtrans);
+
+ aggstate->peragg = peraggs;
+ aggstate->pertrans = pertransstates;
+
+
+ aggstate->all_pergroups =
+ (AggStatePerGroup *) palloc0(sizeof(AggStatePerGroup)
+ * (numGroupingSets + numHashes));
+ pergroups = aggstate->all_pergroups;
+
+ if (node->aggstrategy != AGG_HASHED)
+ {
+ for (i = 0; i < numGroupingSets; i++)
+ {
+ pergroups[i] = (AggStatePerGroup) palloc0(sizeof(AggStatePerGroupData)
+ * numaggs);
+ }
+
+ aggstate->pergroups = pergroups;
+ pergroups += numGroupingSets;
+ }
+
+ /*
+ * Hashing can only appear in the initial phase.
+ */
+ if (use_hashing)
+ {
+ Plan *outerplan = outerPlan(node);
+ uint64 totalGroups = 0;
+ int i;
+
+ aggstate->hash_metacxt = AllocSetContextCreate(aggstate->ss.ps.state->es_query_cxt,
+ "HashAgg meta context",
+ ALLOCSET_DEFAULT_SIZES);
+ aggstate->hash_spill_rslot = ExecInitExtraTupleSlot(estate, scanDesc,
+ &TTSOpsMinimalTuple);
+ aggstate->hash_spill_wslot = ExecInitExtraTupleSlot(estate, scanDesc,
+ &TTSOpsVirtual);
+
+ /* this is an array of pointers, not structures */
+ aggstate->hash_pergroup = pergroups;
+
+ aggstate->hashentrysize = hash_agg_entry_size(aggstate->numtrans,
+ outerplan->plan_width,
+ node->transitionSpace);
+
+ /*
+ * Consider all of the grouping sets together when setting the limits
+ * and estimating the number of partitions. This can be inaccurate
+ * when there is more than one grouping set, but should still be
+ * reasonable.
+ */
+ for (i = 0; i < aggstate->num_hashes; i++)
+ totalGroups += aggstate->perhash[i].aggnode->numGroups;
+
+ hash_agg_set_limits(aggstate->hashentrysize, totalGroups, 0,
+ &aggstate->hash_mem_limit,
+ &aggstate->hash_ngroups_limit,
+ &aggstate->hash_planned_partitions);
+ find_hash_columns(aggstate);
+
+ /* Skip massive memory allocation if we are just doing EXPLAIN */
+ if (!(eflags & EXEC_FLAG_EXPLAIN_ONLY))
+ build_hash_tables(aggstate);
+
+ aggstate->table_filled = false;
+
+ /* Initialize this to 1, meaning nothing spilled, yet */
+ aggstate->hash_batches_used = 1;
+ }
+
+ /*
+ * Initialize current phase-dependent values to initial phase. The initial
+ * phase is 1 (first sort pass) for all strategies that use sorting (if
+ * hashing is being done too, then phase 0 is processed last); but if only
+ * hashing is being done, then phase 0 is all there is.
+ */
+ if (node->aggstrategy == AGG_HASHED)
+ {
+ aggstate->current_phase = 0;
+ initialize_phase(aggstate, 0);
+ select_current_set(aggstate, 0, true);
+ }
+ else
+ {
+ aggstate->current_phase = 1;
+ initialize_phase(aggstate, 1);
+ select_current_set(aggstate, 0, false);
+ }
+
+ /*
+ * Perform lookups of aggregate function info, and initialize the
+ * unchanging fields of the per-agg and per-trans data.
+ */
+ foreach(l, aggstate->aggs)
+ {
+ Aggref *aggref = lfirst(l);
+ AggStatePerAgg peragg;
+ AggStatePerTrans pertrans;
+ Oid inputTypes[FUNC_MAX_ARGS];
+ int numArguments;
+ int numDirectArgs;
+ HeapTuple aggTuple;
+ Form_pg_aggregate aggform;
+ AclResult aclresult;
+ Oid finalfn_oid;
+ Oid serialfn_oid,
+ deserialfn_oid;
+ Oid aggOwner;
+ Expr *finalfnexpr;
+ Oid aggtranstype;
+
+ /* Planner should have assigned aggregate to correct level */
+ Assert(aggref->agglevelsup == 0);
+ /* ... and the split mode should match */
+ Assert(aggref->aggsplit == aggstate->aggsplit);
+
+ peragg = &peraggs[aggref->aggno];
+
+ /* Check if we initialized the state for this aggregate already. */
+ if (peragg->aggref != NULL)
+ continue;
+
+ peragg->aggref = aggref;
+ peragg->transno = aggref->aggtransno;
+
+ /* Fetch the pg_aggregate row */
+ aggTuple = SearchSysCache1(AGGFNOID,
+ ObjectIdGetDatum(aggref->aggfnoid));
+ if (!HeapTupleIsValid(aggTuple))
+ elog(ERROR, "cache lookup failed for aggregate %u",
+ aggref->aggfnoid);
+ aggform = (Form_pg_aggregate) GETSTRUCT(aggTuple);
+
+ /* Check permission to call aggregate function */
+ aclresult = pg_proc_aclcheck(aggref->aggfnoid, GetUserId(),
+ ACL_EXECUTE);
+ if (aclresult != ACLCHECK_OK)
+ aclcheck_error(aclresult, OBJECT_AGGREGATE,
+ get_func_name(aggref->aggfnoid));
+ InvokeFunctionExecuteHook(aggref->aggfnoid);
+
+ /* planner recorded transition state type in the Aggref itself */
+ aggtranstype = aggref->aggtranstype;
+ Assert(OidIsValid(aggtranstype));
+
+ /* Final function only required if we're finalizing the aggregates */
+ if (DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit))
+ peragg->finalfn_oid = finalfn_oid = InvalidOid;
+ else
+ peragg->finalfn_oid = finalfn_oid = aggform->aggfinalfn;
+
+ serialfn_oid = InvalidOid;
+ deserialfn_oid = InvalidOid;
+
+ /*
+ * Check if serialization/deserialization is required. We only do it
+ * for aggregates that have transtype INTERNAL.
+ */
+ if (aggtranstype == INTERNALOID)
+ {
+ /*
+ * The planner should only have generated a serialize agg node if
+ * every aggregate with an INTERNAL state has a serialization
+ * function. Verify that.
+ */
+ if (DO_AGGSPLIT_SERIALIZE(aggstate->aggsplit))
+ {
+ /* serialization only valid when not running finalfn */
+ Assert(DO_AGGSPLIT_SKIPFINAL(aggstate->aggsplit));
+
+ if (!OidIsValid(aggform->aggserialfn))
+ elog(ERROR, "serialfunc not provided for serialization aggregation");
+ serialfn_oid = aggform->aggserialfn;
+ }
+
+ /* Likewise for deserialization functions */
+ if (DO_AGGSPLIT_DESERIALIZE(aggstate->aggsplit))
+ {
+ /* deserialization only valid when combining states */
+ Assert(DO_AGGSPLIT_COMBINE(aggstate->aggsplit));
+
+ if (!OidIsValid(aggform->aggdeserialfn))
+ elog(ERROR, "deserialfunc not provided for deserialization aggregation");
+ deserialfn_oid = aggform->aggdeserialfn;
+ }
+ }
+
+ /* Check that aggregate owner has permission to call component fns */
+ {
+ HeapTuple procTuple;
+
+ procTuple = SearchSysCache1(PROCOID,
+ ObjectIdGetDatum(aggref->aggfnoid));
+ if (!HeapTupleIsValid(procTuple))
+ elog(ERROR, "cache lookup failed for function %u",
+ aggref->aggfnoid);
+ aggOwner = ((Form_pg_proc) GETSTRUCT(procTuple))->proowner;
+ ReleaseSysCache(procTuple);
+
+ if (OidIsValid(finalfn_oid))
+ {
+ aclresult = pg_proc_aclcheck(finalfn_oid, aggOwner,
+ ACL_EXECUTE);
+ if (aclresult != ACLCHECK_OK)
+ aclcheck_error(aclresult, OBJECT_FUNCTION,
+ get_func_name(finalfn_oid));
+ InvokeFunctionExecuteHook(finalfn_oid);
+ }
+ if (OidIsValid(serialfn_oid))
+ {
+ aclresult = pg_proc_aclcheck(serialfn_oid, aggOwner,
+ ACL_EXECUTE);
+ if (aclresult != ACLCHECK_OK)
+ aclcheck_error(aclresult, OBJECT_FUNCTION,
+ get_func_name(serialfn_oid));
+ InvokeFunctionExecuteHook(serialfn_oid);
+ }
+ if (OidIsValid(deserialfn_oid))
+ {
+ aclresult = pg_proc_aclcheck(deserialfn_oid, aggOwner,
+ ACL_EXECUTE);
+ if (aclresult != ACLCHECK_OK)
+ aclcheck_error(aclresult, OBJECT_FUNCTION,
+ get_func_name(deserialfn_oid));
+ InvokeFunctionExecuteHook(deserialfn_oid);
+ }
+ }
+
+ /*
+ * Get actual datatypes of the (nominal) aggregate inputs. These
+ * could be different from the agg's declared input types, when the
+ * agg accepts ANY or a polymorphic type.
+ */
+ numArguments = get_aggregate_argtypes(aggref, inputTypes);
+
+ /* Count the "direct" arguments, if any */
+ numDirectArgs = list_length(aggref->aggdirectargs);
+
+ /* Detect how many arguments to pass to the finalfn */
+ if (aggform->aggfinalextra)
+ peragg->numFinalArgs = numArguments + 1;
+ else
+ peragg->numFinalArgs = numDirectArgs + 1;
+
+ /* Initialize any direct-argument expressions */
+ peragg->aggdirectargs = ExecInitExprList(aggref->aggdirectargs,
+ (PlanState *) aggstate);
+
+ /*
+ * build expression trees using actual argument & result types for the
+ * finalfn, if it exists and is required.
+ */
+ if (OidIsValid(finalfn_oid))
+ {
+ build_aggregate_finalfn_expr(inputTypes,
+ peragg->numFinalArgs,
+ aggtranstype,
+ aggref->aggtype,
+ aggref->inputcollid,
+ finalfn_oid,
+ &finalfnexpr);
+ fmgr_info(finalfn_oid, &peragg->finalfn);
+ fmgr_info_set_expr((Node *) finalfnexpr, &peragg->finalfn);
+ }
+
+ /* get info about the output value's datatype */
+ get_typlenbyval(aggref->aggtype,
+ &peragg->resulttypeLen,
+ &peragg->resulttypeByVal);
+
+ /*
+ * Build working state for invoking the transition function, if we
+ * haven't done it already.
+ */
+ pertrans = &pertransstates[aggref->aggtransno];
+ if (pertrans->aggref == NULL)
+ {
+ Datum textInitVal;
+ Datum initValue;
+ bool initValueIsNull;
+ Oid transfn_oid;
+
+ /*
+ * If this aggregation is performing state combines, then instead
+ * of using the transition function, we'll use the combine
+ * function
+ */
+ if (DO_AGGSPLIT_COMBINE(aggstate->aggsplit))
+ {
+ transfn_oid = aggform->aggcombinefn;
+
+ /* If not set then the planner messed up */
+ if (!OidIsValid(transfn_oid))
+ elog(ERROR, "combinefn not set for aggregate function");
+ }
+ else
+ transfn_oid = aggform->aggtransfn;
+
+ aclresult = pg_proc_aclcheck(transfn_oid, aggOwner,
+ ACL_EXECUTE);
+ if (aclresult != ACLCHECK_OK)
+ aclcheck_error(aclresult, OBJECT_FUNCTION,
+ get_func_name(transfn_oid));
+ InvokeFunctionExecuteHook(transfn_oid);
+
+ /*
+ * initval is potentially null, so don't try to access it as a
+ * struct field. Must do it the hard way with SysCacheGetAttr.
+ */
+ textInitVal = SysCacheGetAttr(AGGFNOID, aggTuple,
+ Anum_pg_aggregate_agginitval,
+ &initValueIsNull);
+ if (initValueIsNull)
+ initValue = (Datum) 0;
+ else
+ initValue = GetAggInitVal(textInitVal, aggtranstype);
+
+ build_pertrans_for_aggref(pertrans, aggstate, estate,
+ aggref, transfn_oid, aggtranstype,
+ serialfn_oid, deserialfn_oid,
+ initValue, initValueIsNull,
+ inputTypes, numArguments);
+ }
+ else
+ pertrans->aggshared = true;
+ ReleaseSysCache(aggTuple);
+ }
+
+ /*
+ * Update aggstate->numaggs to be the number of unique aggregates found.
+ * Also set numstates to the number of unique transition states found.
+ */
+ aggstate->numaggs = numaggs;
+ aggstate->numtrans = numtrans;
+
+ /*
+ * Last, check whether any more aggregates got added onto the node while
+ * we processed the expressions for the aggregate arguments (including not
+ * only the regular arguments and FILTER expressions handled immediately
+ * above, but any direct arguments we might've handled earlier). If so,
+ * we have nested aggregate functions, which is semantically nonsensical,
+ * so complain. (This should have been caught by the parser, so we don't
+ * need to work hard on a helpful error message; but we defend against it
+ * here anyway, just to be sure.)
+ */
+ if (numaggrefs != list_length(aggstate->aggs))
+ ereport(ERROR,
+ (errcode(ERRCODE_GROUPING_ERROR),
+ errmsg("aggregate function calls cannot be nested")));
+
+ /*
+ * Build expressions doing all the transition work at once. We build a
+ * different one for each phase, as the number of transition function
+ * invocation can differ between phases. Note this'll work both for
+ * transition and combination functions (although there'll only be one
+ * phase in the latter case).
+ */
+ for (phaseidx = 0; phaseidx < aggstate->numphases; phaseidx++)
+ {
+ AggStatePerPhase phase = &aggstate->phases[phaseidx];
+ bool dohash = false;
+ bool dosort = false;
+
+ /* phase 0 doesn't necessarily exist */
+ if (!phase->aggnode)
+ continue;
+
+ if (aggstate->aggstrategy == AGG_MIXED && phaseidx == 1)
+ {
+ /*
+ * Phase one, and only phase one, in a mixed agg performs both
+ * sorting and aggregation.
+ */
+ dohash = true;
+ dosort = true;
+ }
+ else if (aggstate->aggstrategy == AGG_MIXED && phaseidx == 0)
+ {
+ /*
+ * No need to compute a transition function for an AGG_MIXED phase
+ * 0 - the contents of the hashtables will have been computed
+ * during phase 1.
+ */
+ continue;
+ }
+ else if (phase->aggstrategy == AGG_PLAIN ||
+ phase->aggstrategy == AGG_SORTED)
+ {
+ dohash = false;
+ dosort = true;
+ }
+ else if (phase->aggstrategy == AGG_HASHED)
+ {
+ dohash = true;
+ dosort = false;
+ }
+ else
+ Assert(false);
+
+ phase->evaltrans = ExecBuildAggTrans(aggstate, phase, dosort, dohash,
+ false);
+
+ /* cache compiled expression for outer slot without NULL check */
+ phase->evaltrans_cache[0][0] = phase->evaltrans;
+ }
+
+ return aggstate;
+}
+
+/*
+ * Build the state needed to calculate a state value for an aggregate.
+ *
+ * This initializes all the fields in 'pertrans'. 'aggref' is the aggregate
+ * to initialize the state for. 'aggtransfn', 'aggtranstype', and the rest
+ * of the arguments could be calculated from 'aggref', but the caller has
+ * calculated them already, so might as well pass them.
+ */
+static void
+build_pertrans_for_aggref(AggStatePerTrans pertrans,
+ AggState *aggstate, EState *estate,
+ Aggref *aggref,
+ Oid aggtransfn, Oid aggtranstype,
+ Oid aggserialfn, Oid aggdeserialfn,
+ Datum initValue, bool initValueIsNull,
+ Oid *inputTypes, int numArguments)
+{
+ int numGroupingSets = Max(aggstate->maxsets, 1);
+ Expr *serialfnexpr = NULL;
+ Expr *deserialfnexpr = NULL;
+ ListCell *lc;
+ int numInputs;
+ int numDirectArgs;
+ List *sortlist;
+ int numSortCols;
+ int numDistinctCols;
+ int i;
+
+ /* Begin filling in the pertrans data */
+ pertrans->aggref = aggref;
+ pertrans->aggshared = false;
+ pertrans->aggCollation = aggref->inputcollid;
+ pertrans->transfn_oid = aggtransfn;
+ pertrans->serialfn_oid = aggserialfn;
+ pertrans->deserialfn_oid = aggdeserialfn;
+ pertrans->initValue = initValue;
+ pertrans->initValueIsNull = initValueIsNull;
+
+ /* Count the "direct" arguments, if any */
+ numDirectArgs = list_length(aggref->aggdirectargs);
+
+ /* Count the number of aggregated input columns */
+ pertrans->numInputs = numInputs = list_length(aggref->args);
+
+ pertrans->aggtranstype = aggtranstype;
+
+ /*
+ * When combining states, we have no use at all for the aggregate
+ * function's transfn. Instead we use the combinefn. In this case, the
+ * transfn and transfn_oid fields of pertrans refer to the combine
+ * function rather than the transition function.
+ */
+ if (DO_AGGSPLIT_COMBINE(aggstate->aggsplit))
+ {
+ Expr *combinefnexpr;
+ size_t numTransArgs;
+
+ /*
+ * When combining there's only one input, the to-be-combined added
+ * transition value from below (this node's transition value is
+ * counted separately).
+ */
+ pertrans->numTransInputs = 1;
+
+ /* account for the current transition state */
+ numTransArgs = pertrans->numTransInputs + 1;
+
+ build_aggregate_combinefn_expr(aggtranstype,
+ aggref->inputcollid,
+ aggtransfn,
+ &combinefnexpr);
+ fmgr_info(aggtransfn, &pertrans->transfn);
+ fmgr_info_set_expr((Node *) combinefnexpr, &pertrans->transfn);
+
+ pertrans->transfn_fcinfo =
+ (FunctionCallInfo) palloc(SizeForFunctionCallInfo(2));
+ InitFunctionCallInfoData(*pertrans->transfn_fcinfo,
+ &pertrans->transfn,
+ numTransArgs,
+ pertrans->aggCollation,
+ (void *) aggstate, NULL);
+
+ /*
+ * Ensure that a combine function to combine INTERNAL states is not
+ * strict. This should have been checked during CREATE AGGREGATE, but
+ * the strict property could have been changed since then.
+ */
+ if (pertrans->transfn.fn_strict && aggtranstype == INTERNALOID)
+ ereport(ERROR,
+ (errcode(ERRCODE_INVALID_FUNCTION_DEFINITION),
+ errmsg("combine function with transition type %s must not be declared STRICT",
+ format_type_be(aggtranstype))));
+ }
+ else
+ {
+ Expr *transfnexpr;
+ size_t numTransArgs;
+
+ /* Detect how many arguments to pass to the transfn */
+ if (AGGKIND_IS_ORDERED_SET(aggref->aggkind))
+ pertrans->numTransInputs = numInputs;
+ else
+ pertrans->numTransInputs = numArguments;
+
+ /* account for the current transition state */
+ numTransArgs = pertrans->numTransInputs + 1;
+
+ /*
+ * Set up infrastructure for calling the transfn. Note that
+ * invtransfn is not needed here.
+ */
+ build_aggregate_transfn_expr(inputTypes,
+ numArguments,
+ numDirectArgs,
+ aggref->aggvariadic,
+ aggtranstype,
+ aggref->inputcollid,
+ aggtransfn,
+ InvalidOid,
+ &transfnexpr,
+ NULL);
+ fmgr_info(aggtransfn, &pertrans->transfn);
+ fmgr_info_set_expr((Node *) transfnexpr, &pertrans->transfn);
+
+ pertrans->transfn_fcinfo =
+ (FunctionCallInfo) palloc(SizeForFunctionCallInfo(numTransArgs));
+ InitFunctionCallInfoData(*pertrans->transfn_fcinfo,
+ &pertrans->transfn,
+ numTransArgs,
+ pertrans->aggCollation,
+ (void *) aggstate, NULL);
+
+ /*
+ * If the transfn is strict and the initval is NULL, make sure input
+ * type and transtype are the same (or at least binary-compatible), so
+ * that it's OK to use the first aggregated input value as the initial
+ * transValue. This should have been checked at agg definition time,
+ * but we must check again in case the transfn's strictness property
+ * has been changed.
+ */
+ if (pertrans->transfn.fn_strict && pertrans->initValueIsNull)
+ {
+ if (numArguments <= numDirectArgs ||
+ !IsBinaryCoercible(inputTypes[numDirectArgs],
+ aggtranstype))
+ ereport(ERROR,
+ (errcode(ERRCODE_INVALID_FUNCTION_DEFINITION),
+ errmsg("aggregate %u needs to have compatible input type and transition type",
+ aggref->aggfnoid)));
+ }
+ }
+
+ /* get info about the state value's datatype */
+ get_typlenbyval(aggtranstype,
+ &pertrans->transtypeLen,
+ &pertrans->transtypeByVal);
+
+ if (OidIsValid(aggserialfn))
+ {
+ build_aggregate_serialfn_expr(aggserialfn,
+ &serialfnexpr);
+ fmgr_info(aggserialfn, &pertrans->serialfn);
+ fmgr_info_set_expr((Node *) serialfnexpr, &pertrans->serialfn);
+
+ pertrans->serialfn_fcinfo =
+ (FunctionCallInfo) palloc(SizeForFunctionCallInfo(1));
+ InitFunctionCallInfoData(*pertrans->serialfn_fcinfo,
+ &pertrans->serialfn,
+ 1,
+ InvalidOid,
+ (void *) aggstate, NULL);
+ }
+
+ if (OidIsValid(aggdeserialfn))
+ {
+ build_aggregate_deserialfn_expr(aggdeserialfn,
+ &deserialfnexpr);
+ fmgr_info(aggdeserialfn, &pertrans->deserialfn);
+ fmgr_info_set_expr((Node *) deserialfnexpr, &pertrans->deserialfn);
+
+ pertrans->deserialfn_fcinfo =
+ (FunctionCallInfo) palloc(SizeForFunctionCallInfo(2));
+ InitFunctionCallInfoData(*pertrans->deserialfn_fcinfo,
+ &pertrans->deserialfn,
+ 2,
+ InvalidOid,
+ (void *) aggstate, NULL);
+
+ }
+
+ /*
+ * If we're doing either DISTINCT or ORDER BY for a plain agg, then we
+ * have a list of SortGroupClause nodes; fish out the data in them and
+ * stick them into arrays. We ignore ORDER BY for an ordered-set agg,
+ * however; the agg's transfn and finalfn are responsible for that.
+ *
+ * Note that by construction, if there is a DISTINCT clause then the ORDER
+ * BY clause is a prefix of it (see transformDistinctClause).
+ */
+ if (AGGKIND_IS_ORDERED_SET(aggref->aggkind))
+ {
+ sortlist = NIL;
+ numSortCols = numDistinctCols = 0;
+ }
+ else if (aggref->aggdistinct)
+ {
+ sortlist = aggref->aggdistinct;
+ numSortCols = numDistinctCols = list_length(sortlist);
+ Assert(numSortCols >= list_length(aggref->aggorder));
+ }
+ else
+ {
+ sortlist = aggref->aggorder;
+ numSortCols = list_length(sortlist);
+ numDistinctCols = 0;
+ }
+
+ pertrans->numSortCols = numSortCols;
+ pertrans->numDistinctCols = numDistinctCols;
+
+ /*
+ * If we have either sorting or filtering to do, create a tupledesc and
+ * slot corresponding to the aggregated inputs (including sort
+ * expressions) of the agg.
+ */
+ if (numSortCols > 0 || aggref->aggfilter)
+ {
+ pertrans->sortdesc = ExecTypeFromTL(aggref->args);
+ pertrans->sortslot =
+ ExecInitExtraTupleSlot(estate, pertrans->sortdesc,
+ &TTSOpsMinimalTuple);
+ }
+
+ if (numSortCols > 0)
+ {
+ /*
+ * We don't implement DISTINCT or ORDER BY aggs in the HASHED case
+ * (yet)
+ */
+ Assert(aggstate->aggstrategy != AGG_HASHED && aggstate->aggstrategy != AGG_MIXED);
+
+ /* If we have only one input, we need its len/byval info. */
+ if (numInputs == 1)
+ {
+ get_typlenbyval(inputTypes[numDirectArgs],
+ &pertrans->inputtypeLen,
+ &pertrans->inputtypeByVal);
+ }
+ else if (numDistinctCols > 0)
+ {
+ /* we will need an extra slot to store prior values */
+ pertrans->uniqslot =
+ ExecInitExtraTupleSlot(estate, pertrans->sortdesc,
+ &TTSOpsMinimalTuple);
+ }
+
+ /* Extract the sort information for use later */
+ pertrans->sortColIdx =
+ (AttrNumber *) palloc(numSortCols * sizeof(AttrNumber));
+ pertrans->sortOperators =
+ (Oid *) palloc(numSortCols * sizeof(Oid));
+ pertrans->sortCollations =
+ (Oid *) palloc(numSortCols * sizeof(Oid));
+ pertrans->sortNullsFirst =
+ (bool *) palloc(numSortCols * sizeof(bool));
+
+ i = 0;
+ foreach(lc, sortlist)
+ {
+ SortGroupClause *sortcl = (SortGroupClause *) lfirst(lc);
+ TargetEntry *tle = get_sortgroupclause_tle(sortcl, aggref->args);
+
+ /* the parser should have made sure of this */
+ Assert(OidIsValid(sortcl->sortop));
+
+ pertrans->sortColIdx[i] = tle->resno;
+ pertrans->sortOperators[i] = sortcl->sortop;
+ pertrans->sortCollations[i] = exprCollation((Node *) tle->expr);
+ pertrans->sortNullsFirst[i] = sortcl->nulls_first;
+ i++;
+ }
+ Assert(i == numSortCols);
+ }
+
+ if (aggref->aggdistinct)
+ {
+ Oid *ops;
+
+ Assert(numArguments > 0);
+ Assert(list_length(aggref->aggdistinct) == numDistinctCols);
+
+ ops = palloc(numDistinctCols * sizeof(Oid));
+
+ i = 0;
+ foreach(lc, aggref->aggdistinct)
+ ops[i++] = ((SortGroupClause *) lfirst(lc))->eqop;
+
+ /* lookup / build the necessary comparators */
+ if (numDistinctCols == 1)
+ fmgr_info(get_opcode(ops[0]), &pertrans->equalfnOne);
+ else
+ pertrans->equalfnMulti =
+ execTuplesMatchPrepare(pertrans->sortdesc,
+ numDistinctCols,
+ pertrans->sortColIdx,
+ ops,
+ pertrans->sortCollations,
+ &aggstate->ss.ps);
+ pfree(ops);
+ }
+
+ pertrans->sortstates = (Tuplesortstate **)
+ palloc0(sizeof(Tuplesortstate *) * numGroupingSets);
+}
+
+
+static Datum
+GetAggInitVal(Datum textInitVal, Oid transtype)
+{
+ Oid typinput,
+ typioparam;
+ char *strInitVal;
+ Datum initVal;
+
+ getTypeInputInfo(transtype, &typinput, &typioparam);
+ strInitVal = TextDatumGetCString(textInitVal);
+ initVal = OidInputFunctionCall(typinput, strInitVal,
+ typioparam, -1);
+ pfree(strInitVal);
+ return initVal;
+}
+
+void
+ExecEndAgg(AggState *node)
+{
+ PlanState *outerPlan;
+ int transno;
+ int numGroupingSets = Max(node->maxsets, 1);
+ int setno;
+
+ /*
+ * When ending a parallel worker, copy the statistics gathered by the
+ * worker back into shared memory so that it can be picked up by the main
+ * process to report in EXPLAIN ANALYZE.
+ */
+ if (node->shared_info && IsParallelWorker())
+ {
+ AggregateInstrumentation *si;
+
+ Assert(ParallelWorkerNumber <= node->shared_info->num_workers);
+ si = &node->shared_info->sinstrument[ParallelWorkerNumber];
+ si->hash_batches_used = node->hash_batches_used;
+ si->hash_disk_used = node->hash_disk_used;
+ si->hash_mem_peak = node->hash_mem_peak;
+ }
+
+ /* Make sure we have closed any open tuplesorts */
+
+ if (node->sort_in)
+ tuplesort_end(node->sort_in);
+ if (node->sort_out)
+ tuplesort_end(node->sort_out);
+
+ hashagg_reset_spill_state(node);
+
+ if (node->hash_metacxt != NULL)
+ {
+ MemoryContextDelete(node->hash_metacxt);
+ node->hash_metacxt = NULL;
+ }
+
+ for (transno = 0; transno < node->numtrans; transno++)
+ {
+ AggStatePerTrans pertrans = &node->pertrans[transno];
+
+ for (setno = 0; setno < numGroupingSets; setno++)
+ {
+ if (pertrans->sortstates[setno])
+ tuplesort_end(pertrans->sortstates[setno]);
+ }
+ }
+
+ /* And ensure any agg shutdown callbacks have been called */
+ for (setno = 0; setno < numGroupingSets; setno++)
+ ReScanExprContext(node->aggcontexts[setno]);
+ if (node->hashcontext)
+ ReScanExprContext(node->hashcontext);
+
+ /*
+ * We don't actually free any ExprContexts here (see comment in
+ * ExecFreeExprContext), just unlinking the output one from the plan node
+ * suffices.
+ */
+ ExecFreeExprContext(&node->ss.ps);
+
+ /* clean up tuple table */
+ ExecClearTuple(node->ss.ss_ScanTupleSlot);
+
+ outerPlan = outerPlanState(node);
+ ExecEndNode(outerPlan);
+}
+
+void
+ExecReScanAgg(AggState *node)
+{
+ ExprContext *econtext = node->ss.ps.ps_ExprContext;
+ PlanState *outerPlan = outerPlanState(node);
+ Agg *aggnode = (Agg *) node->ss.ps.plan;
+ int transno;
+ int numGroupingSets = Max(node->maxsets, 1);
+ int setno;
+
+ node->agg_done = false;
+
+ if (node->aggstrategy == AGG_HASHED)
+ {
+ /*
+ * In the hashed case, if we haven't yet built the hash table then we
+ * can just return; nothing done yet, so nothing to undo. If subnode's
+ * chgParam is not NULL then it will be re-scanned by ExecProcNode,
+ * else no reason to re-scan it at all.
+ */
+ if (!node->table_filled)
+ return;
+
+ /*
+ * If we do have the hash table, and it never spilled, and the subplan
+ * does not have any parameter changes, and none of our own parameter
+ * changes affect input expressions of the aggregated functions, then
+ * we can just rescan the existing hash table; no need to build it
+ * again.
+ */
+ if (outerPlan->chgParam == NULL && !node->hash_ever_spilled &&
+ !bms_overlap(node->ss.ps.chgParam, aggnode->aggParams))
+ {
+ ResetTupleHashIterator(node->perhash[0].hashtable,
+ &node->perhash[0].hashiter);
+ select_current_set(node, 0, true);
+ return;
+ }
+ }
+
+ /* Make sure we have closed any open tuplesorts */
+ for (transno = 0; transno < node->numtrans; transno++)
+ {
+ for (setno = 0; setno < numGroupingSets; setno++)
+ {
+ AggStatePerTrans pertrans = &node->pertrans[transno];
+
+ if (pertrans->sortstates[setno])
+ {
+ tuplesort_end(pertrans->sortstates[setno]);
+ pertrans->sortstates[setno] = NULL;
+ }
+ }
+ }
+
+ /*
+ * We don't need to ReScanExprContext the output tuple context here;
+ * ExecReScan already did it. But we do need to reset our per-grouping-set
+ * contexts, which may have transvalues stored in them. (We use rescan
+ * rather than just reset because transfns may have registered callbacks
+ * that need to be run now.) For the AGG_HASHED case, see below.
+ */
+
+ for (setno = 0; setno < numGroupingSets; setno++)
+ {
+ ReScanExprContext(node->aggcontexts[setno]);
+ }
+
+ /* Release first tuple of group, if we have made a copy */
+ if (node->grp_firstTuple != NULL)
+ {
+ heap_freetuple(node->grp_firstTuple);
+ node->grp_firstTuple = NULL;
+ }
+ ExecClearTuple(node->ss.ss_ScanTupleSlot);
+
+ /* Forget current agg values */
+ MemSet(econtext->ecxt_aggvalues, 0, sizeof(Datum) * node->numaggs);
+ MemSet(econtext->ecxt_aggnulls, 0, sizeof(bool) * node->numaggs);
+
+ /*
+ * With AGG_HASHED/MIXED, the hash table is allocated in a sub-context of
+ * the hashcontext. This used to be an issue, but now, resetting a context
+ * automatically deletes sub-contexts too.
+ */
+ if (node->aggstrategy == AGG_HASHED || node->aggstrategy == AGG_MIXED)
+ {
+ hashagg_reset_spill_state(node);
+
+ node->hash_ever_spilled = false;
+ node->hash_spill_mode = false;
+ node->hash_ngroups_current = 0;
+
+ ReScanExprContext(node->hashcontext);
+ /* Rebuild an empty hash table */
+ build_hash_tables(node);
+ node->table_filled = false;
+ /* iterator will be reset when the table is filled */
+
+ hashagg_recompile_expressions(node, false, false);
+ }
+
+ if (node->aggstrategy != AGG_HASHED)
+ {
+ /*
+ * Reset the per-group state (in particular, mark transvalues null)
+ */
+ for (setno = 0; setno < numGroupingSets; setno++)
+ {
+ MemSet(node->pergroups[setno], 0,
+ sizeof(AggStatePerGroupData) * node->numaggs);
+ }
+
+ /* reset to phase 1 */
+ initialize_phase(node, 1);
+
+ node->input_done = false;
+ node->projected_set = -1;
+ }
+
+ if (outerPlan->chgParam == NULL)
+ ExecReScan(outerPlan);
+}
+
+
+/***********************************************************************
+ * API exposed to aggregate functions
+ ***********************************************************************/
+
+
+/*
+ * AggCheckCallContext - test if a SQL function is being called as an aggregate
+ *
+ * The transition and/or final functions of an aggregate may want to verify
+ * that they are being called as aggregates, rather than as plain SQL
+ * functions. They should use this function to do so. The return value
+ * is nonzero if being called as an aggregate, or zero if not. (Specific
+ * nonzero values are AGG_CONTEXT_AGGREGATE or AGG_CONTEXT_WINDOW, but more
+ * values could conceivably appear in future.)
+ *
+ * If aggcontext isn't NULL, the function also stores at *aggcontext the
+ * identity of the memory context that aggregate transition values are being
+ * stored in. Note that the same aggregate call site (flinfo) may be called
+ * interleaved on different transition values in different contexts, so it's
+ * not kosher to cache aggcontext under fn_extra. It is, however, kosher to
+ * cache it in the transvalue itself (for internal-type transvalues).
+ */
+int
+AggCheckCallContext(FunctionCallInfo fcinfo, MemoryContext *aggcontext)
+{
+ if (fcinfo->context && IsA(fcinfo->context, AggState))
+ {
+ if (aggcontext)
+ {
+ AggState *aggstate = ((AggState *) fcinfo->context);
+ ExprContext *cxt = aggstate->curaggcontext;
+
+ *aggcontext = cxt->ecxt_per_tuple_memory;
+ }
+ return AGG_CONTEXT_AGGREGATE;
+ }
+ if (fcinfo->context && IsA(fcinfo->context, WindowAggState))
+ {
+ if (aggcontext)
+ *aggcontext = ((WindowAggState *) fcinfo->context)->curaggcontext;
+ return AGG_CONTEXT_WINDOW;
+ }
+
+ /* this is just to prevent "uninitialized variable" warnings */
+ if (aggcontext)
+ *aggcontext = NULL;
+ return 0;
+}
+
+/*
+ * AggGetAggref - allow an aggregate support function to get its Aggref
+ *
+ * If the function is being called as an aggregate support function,
+ * return the Aggref node for the aggregate call. Otherwise, return NULL.
+ *
+ * Aggregates sharing the same inputs and transition functions can get
+ * merged into a single transition calculation. If the transition function
+ * calls AggGetAggref, it will get some one of the Aggrefs for which it is
+ * executing. It must therefore not pay attention to the Aggref fields that
+ * relate to the final function, as those are indeterminate. But if a final
+ * function calls AggGetAggref, it will get a precise result.
+ *
+ * Note that if an aggregate is being used as a window function, this will
+ * return NULL. We could provide a similar function to return the relevant
+ * WindowFunc node in such cases, but it's not needed yet.
+ */
+Aggref *
+AggGetAggref(FunctionCallInfo fcinfo)
+{
+ if (fcinfo->context && IsA(fcinfo->context, AggState))
+ {
+ AggState *aggstate = (AggState *) fcinfo->context;
+ AggStatePerAgg curperagg;
+ AggStatePerTrans curpertrans;
+
+ /* check curperagg (valid when in a final function) */
+ curperagg = aggstate->curperagg;
+
+ if (curperagg)
+ return curperagg->aggref;
+
+ /* check curpertrans (valid when in a transition function) */
+ curpertrans = aggstate->curpertrans;
+
+ if (curpertrans)
+ return curpertrans->aggref;
+ }
+ return NULL;
+}
+
+/*
+ * AggGetTempMemoryContext - fetch short-term memory context for aggregates
+ *
+ * This is useful in agg final functions; the context returned is one that
+ * the final function can safely reset as desired. This isn't useful for
+ * transition functions, since the context returned MAY (we don't promise)
+ * be the same as the context those are called in.
+ *
+ * As above, this is currently not useful for aggs called as window functions.
+ */
+MemoryContext
+AggGetTempMemoryContext(FunctionCallInfo fcinfo)
+{
+ if (fcinfo->context && IsA(fcinfo->context, AggState))
+ {
+ AggState *aggstate = (AggState *) fcinfo->context;
+
+ return aggstate->tmpcontext->ecxt_per_tuple_memory;
+ }
+ return NULL;
+}
+
+/*
+ * AggStateIsShared - find out whether transition state is shared
+ *
+ * If the function is being called as an aggregate support function,
+ * return true if the aggregate's transition state is shared across
+ * multiple aggregates, false if it is not.
+ *
+ * Returns true if not called as an aggregate support function.
+ * This is intended as a conservative answer, ie "no you'd better not
+ * scribble on your input". In particular, will return true if the
+ * aggregate is being used as a window function, which is a scenario
+ * in which changing the transition state is a bad idea. We might
+ * want to refine the behavior for the window case in future.
+ */
+bool
+AggStateIsShared(FunctionCallInfo fcinfo)
+{
+ if (fcinfo->context && IsA(fcinfo->context, AggState))
+ {
+ AggState *aggstate = (AggState *) fcinfo->context;
+ AggStatePerAgg curperagg;
+ AggStatePerTrans curpertrans;
+
+ /* check curperagg (valid when in a final function) */
+ curperagg = aggstate->curperagg;
+
+ if (curperagg)
+ return aggstate->pertrans[curperagg->transno].aggshared;
+
+ /* check curpertrans (valid when in a transition function) */
+ curpertrans = aggstate->curpertrans;
+
+ if (curpertrans)
+ return curpertrans->aggshared;
+ }
+ return true;
+}
+
+/*
+ * AggRegisterCallback - register a cleanup callback for an aggregate
+ *
+ * This is useful for aggs to register shutdown callbacks, which will ensure
+ * that non-memory resources are freed. The callback will occur just before
+ * the associated aggcontext (as returned by AggCheckCallContext) is reset,
+ * either between groups or as a result of rescanning the query. The callback
+ * will NOT be called on error paths. The typical use-case is for freeing of
+ * tuplestores or tuplesorts maintained in aggcontext, or pins held by slots
+ * created by the agg functions. (The callback will not be called until after
+ * the result of the finalfn is no longer needed, so it's safe for the finalfn
+ * to return data that will be freed by the callback.)
+ *
+ * As above, this is currently not useful for aggs called as window functions.
+ */
+void
+AggRegisterCallback(FunctionCallInfo fcinfo,
+ ExprContextCallbackFunction func,
+ Datum arg)
+{
+ if (fcinfo->context && IsA(fcinfo->context, AggState))
+ {
+ AggState *aggstate = (AggState *) fcinfo->context;
+ ExprContext *cxt = aggstate->curaggcontext;
+
+ RegisterExprContextCallback(cxt, func, arg);
+
+ return;
+ }
+ elog(ERROR, "aggregate function cannot register a callback in this context");
+}
+
+
+/* ----------------------------------------------------------------
+ * Parallel Query Support
+ * ----------------------------------------------------------------
+ */
+
+ /* ----------------------------------------------------------------
+ * ExecAggEstimate
+ *
+ * Estimate space required to propagate aggregate statistics.
+ * ----------------------------------------------------------------
+ */
+void
+ExecAggEstimate(AggState *node, ParallelContext *pcxt)
+{
+ Size size;
+
+ /* don't need this if not instrumenting or no workers */
+ if (!node->ss.ps.instrument || pcxt->nworkers == 0)
+ return;
+
+ size = mul_size(pcxt->nworkers, sizeof(AggregateInstrumentation));
+ size = add_size(size, offsetof(SharedAggInfo, sinstrument));
+ shm_toc_estimate_chunk(&pcxt->estimator, size);
+ shm_toc_estimate_keys(&pcxt->estimator, 1);
+}
+
+/* ----------------------------------------------------------------
+ * ExecAggInitializeDSM
+ *
+ * Initialize DSM space for aggregate statistics.
+ * ----------------------------------------------------------------
+ */
+void
+ExecAggInitializeDSM(AggState *node, ParallelContext *pcxt)
+{
+ Size size;
+
+ /* don't need this if not instrumenting or no workers */
+ if (!node->ss.ps.instrument || pcxt->nworkers == 0)
+ return;
+
+ size = offsetof(SharedAggInfo, sinstrument)
+ + pcxt->nworkers * sizeof(AggregateInstrumentation);
+ node->shared_info = shm_toc_allocate(pcxt->toc, size);
+ /* ensure any unfilled slots will contain zeroes */
+ memset(node->shared_info, 0, size);
+ node->shared_info->num_workers = pcxt->nworkers;
+ shm_toc_insert(pcxt->toc, node->ss.ps.plan->plan_node_id,
+ node->shared_info);
+}
+
+/* ----------------------------------------------------------------
+ * ExecAggInitializeWorker
+ *
+ * Attach worker to DSM space for aggregate statistics.
+ * ----------------------------------------------------------------
+ */
+void
+ExecAggInitializeWorker(AggState *node, ParallelWorkerContext *pwcxt)
+{
+ node->shared_info =
+ shm_toc_lookup(pwcxt->toc, node->ss.ps.plan->plan_node_id, true);
+}
+
+/* ----------------------------------------------------------------
+ * ExecAggRetrieveInstrumentation
+ *
+ * Transfer aggregate statistics from DSM to private memory.
+ * ----------------------------------------------------------------
+ */
+void
+ExecAggRetrieveInstrumentation(AggState *node)
+{
+ Size size;
+ SharedAggInfo *si;
+
+ if (node->shared_info == NULL)
+ return;
+
+ size = offsetof(SharedAggInfo, sinstrument)
+ + node->shared_info->num_workers * sizeof(AggregateInstrumentation);
+ si = palloc(size);
+ memcpy(si, node->shared_info, size);
+ node->shared_info = si;
+}