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postgres/src/backend/executor/nodeHash.c
Andres Freund 4e2970f880 Fix assert with side effects in the new PHJ code. 
Instead of asserting the assert just set the value to what it was
supposed to test...

Per coverity.
2017-12-24 02:57:55 -08:00

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/*-------------------------------------------------------------------------
*
* nodeHash.c
* Routines to hash relations for hashjoin
*
* Portions Copyright (c) 1996-2017, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
*
* IDENTIFICATION
* src/backend/executor/nodeHash.c
*
* See note on parallelism in nodeHashjoin.c.
*
*-------------------------------------------------------------------------
*/
/*
* INTERFACE ROUTINES
* MultiExecHash - generate an in-memory hash table of the relation
* ExecInitHash - initialize node and subnodes
* ExecEndHash - shutdown node and subnodes
*/
#include "postgres.h"
#include <math.h>
#include <limits.h>
#include "access/htup_details.h"
#include "access/parallel.h"
#include "catalog/pg_statistic.h"
#include "commands/tablespace.h"
#include "executor/execdebug.h"
#include "executor/hashjoin.h"
#include "executor/nodeHash.h"
#include "executor/nodeHashjoin.h"
#include "miscadmin.h"
#include "pgstat.h"
#include "port/atomics.h"
#include "utils/dynahash.h"
#include "utils/memutils.h"
#include "utils/lsyscache.h"
#include "utils/syscache.h"
static void ExecHashIncreaseNumBatches(HashJoinTable hashtable);
static void ExecHashIncreaseNumBuckets(HashJoinTable hashtable);
static void ExecParallelHashIncreaseNumBatches(HashJoinTable hashtable);
static void ExecParallelHashIncreaseNumBuckets(HashJoinTable hashtable);
static void ExecHashBuildSkewHash(HashJoinTable hashtable, Hash *node,
int mcvsToUse);
static void ExecHashSkewTableInsert(HashJoinTable hashtable,
TupleTableSlot *slot,
uint32 hashvalue,
int bucketNumber);
static void ExecHashRemoveNextSkewBucket(HashJoinTable hashtable);
static void *dense_alloc(HashJoinTable hashtable, Size size);
static HashJoinTuple ExecParallelHashTupleAlloc(HashJoinTable hashtable,
size_t size,
dsa_pointer *shared);
static void MultiExecPrivateHash(HashState *node);
static void MultiExecParallelHash(HashState *node);
static inline HashJoinTuple ExecParallelHashFirstTuple(HashJoinTable table,
int bucketno);
static inline HashJoinTuple ExecParallelHashNextTuple(HashJoinTable table,
HashJoinTuple tuple);
static inline void ExecParallelHashPushTuple(dsa_pointer_atomic *head,
HashJoinTuple tuple,
dsa_pointer tuple_shared);
static void ExecParallelHashJoinSetUpBatches(HashJoinTable hashtable, int nbatch);
static void ExecParallelHashEnsureBatchAccessors(HashJoinTable hashtable);
static void ExecParallelHashRepartitionFirst(HashJoinTable hashtable);
static void ExecParallelHashRepartitionRest(HashJoinTable hashtable);
static HashMemoryChunk ExecParallelHashPopChunkQueue(HashJoinTable table,
dsa_pointer *shared);
static bool ExecParallelHashTuplePrealloc(HashJoinTable hashtable,
int batchno,
size_t size);
static void ExecParallelHashMergeCounters(HashJoinTable hashtable);
static void ExecParallelHashCloseBatchAccessors(HashJoinTable hashtable);
/* ----------------------------------------------------------------
* ExecHash
*
* stub for pro forma compliance
* ----------------------------------------------------------------
*/
static TupleTableSlot *
ExecHash(PlanState *pstate)
{
elog(ERROR, "Hash node does not support ExecProcNode call convention");
return NULL;
}
/* ----------------------------------------------------------------
* MultiExecHash
*
* build hash table for hashjoin, doing partitioning if more
* than one batch is required.
* ----------------------------------------------------------------
*/
Node *
MultiExecHash(HashState *node)
{
/* must provide our own instrumentation support */
if (node->ps.instrument)
InstrStartNode(node->ps.instrument);
if (node->parallel_state != NULL)
MultiExecParallelHash(node);
else
MultiExecPrivateHash(node);
/* must provide our own instrumentation support */
if (node->ps.instrument)
InstrStopNode(node->ps.instrument, node->hashtable->partialTuples);
/*
* We do not return the hash table directly because it's not a subtype of
* Node, and so would violate the MultiExecProcNode API. Instead, our
* parent Hashjoin node is expected to know how to fish it out of our node
* state. Ugly but not really worth cleaning up, since Hashjoin knows
* quite a bit more about Hash besides that.
*/
return NULL;
}
/* ----------------------------------------------------------------
* MultiExecPrivateHash
*
* parallel-oblivious version, building a backend-private
* hash table and (if necessary) batch files.
* ----------------------------------------------------------------
*/
static void
MultiExecPrivateHash(HashState *node)
{
PlanState *outerNode;
List *hashkeys;
HashJoinTable hashtable;
TupleTableSlot *slot;
ExprContext *econtext;
uint32 hashvalue;
/*
* get state info from node
*/
outerNode = outerPlanState(node);
hashtable = node->hashtable;
/*
* set expression context
*/
hashkeys = node->hashkeys;
econtext = node->ps.ps_ExprContext;
/*
* get all inner tuples and insert into the hash table (or temp files)
*/
for (;;)
{
slot = ExecProcNode(outerNode);
if (TupIsNull(slot))
break;
/* We have to compute the hash value */
econtext->ecxt_innertuple = slot;
if (ExecHashGetHashValue(hashtable, econtext, hashkeys,
false, hashtable->keepNulls,
&hashvalue))
{
int bucketNumber;
bucketNumber = ExecHashGetSkewBucket(hashtable, hashvalue);
if (bucketNumber != INVALID_SKEW_BUCKET_NO)
{
/* It's a skew tuple, so put it into that hash table */
ExecHashSkewTableInsert(hashtable, slot, hashvalue,
bucketNumber);
hashtable->skewTuples += 1;
}
else
{
/* Not subject to skew optimization, so insert normally */
ExecHashTableInsert(hashtable, slot, hashvalue);
}
hashtable->totalTuples += 1;
}
}
/* resize the hash table if needed (NTUP_PER_BUCKET exceeded) */
if (hashtable->nbuckets != hashtable->nbuckets_optimal)
ExecHashIncreaseNumBuckets(hashtable);
/* Account for the buckets in spaceUsed (reported in EXPLAIN ANALYZE) */
hashtable->spaceUsed += hashtable->nbuckets * sizeof(HashJoinTuple);
if (hashtable->spaceUsed > hashtable->spacePeak)
hashtable->spacePeak = hashtable->spaceUsed;
hashtable->partialTuples = hashtable->totalTuples;
}
/* ----------------------------------------------------------------
* MultiExecParallelHash
*
* parallel-aware version, building a shared hash table and
* (if necessary) batch files using the combined effort of
* a set of co-operating backends.
* ----------------------------------------------------------------
*/
static void
MultiExecParallelHash(HashState *node)
{
ParallelHashJoinState *pstate;
PlanState *outerNode;
List *hashkeys;
HashJoinTable hashtable;
TupleTableSlot *slot;
ExprContext *econtext;
uint32 hashvalue;
Barrier *build_barrier;
int i;
/*
* get state info from node
*/
outerNode = outerPlanState(node);
hashtable = node->hashtable;
/*
* set expression context
*/
hashkeys = node->hashkeys;
econtext = node->ps.ps_ExprContext;
/*
* Synchronize the parallel hash table build. At this stage we know that
* the shared hash table has been or is being set up by
* ExecHashTableCreate(), but we don't know if our peers have returned
* from there or are here in MultiExecParallelHash(), and if so how far
* through they are. To find out, we check the build_barrier phase then
* and jump to the right step in the build algorithm.
*/
pstate = hashtable->parallel_state;
build_barrier = &pstate->build_barrier;
Assert(BarrierPhase(build_barrier) >= PHJ_BUILD_ALLOCATING);
switch (BarrierPhase(build_barrier))
{
case PHJ_BUILD_ALLOCATING:
/*
* Either I just allocated the initial hash table in
* ExecHashTableCreate(), or someone else is doing that. Either
* way, wait for everyone to arrive here so we can proceed.
*/
BarrierArriveAndWait(build_barrier, WAIT_EVENT_HASH_BUILD_ALLOCATING);
/* Fall through. */
case PHJ_BUILD_HASHING_INNER:
/*
* It's time to begin hashing, or if we just arrived here then
* hashing is already underway, so join in that effort. While
* hashing we have to be prepared to help increase the number of
* batches or buckets at any time, and if we arrived here when
* that was already underway we'll have to help complete that work
* immediately so that it's safe to access batches and buckets
* below.
*/
if (PHJ_GROW_BATCHES_PHASE(BarrierAttach(&pstate->grow_batches_barrier)) !=
PHJ_GROW_BATCHES_ELECTING)
ExecParallelHashIncreaseNumBatches(hashtable);
if (PHJ_GROW_BUCKETS_PHASE(BarrierAttach(&pstate->grow_buckets_barrier)) !=
PHJ_GROW_BUCKETS_ELECTING)
ExecParallelHashIncreaseNumBuckets(hashtable);
ExecParallelHashEnsureBatchAccessors(hashtable);
ExecParallelHashTableSetCurrentBatch(hashtable, 0);
for (;;)
{
slot = ExecProcNode(outerNode);
if (TupIsNull(slot))
break;
econtext->ecxt_innertuple = slot;
if (ExecHashGetHashValue(hashtable, econtext, hashkeys,
false, hashtable->keepNulls,
&hashvalue))
ExecParallelHashTableInsert(hashtable, slot, hashvalue);
hashtable->partialTuples++;
}
BarrierDetach(&pstate->grow_buckets_barrier);
BarrierDetach(&pstate->grow_batches_barrier);
/*
* Make sure that any tuples we wrote to disk are visible to
* others before anyone tries to load them.
*/
for (i = 0; i < hashtable->nbatch; ++i)
sts_end_write(hashtable->batches[i].inner_tuples);
/*
* Update shared counters. We need an accurate total tuple count
* to control the empty table optimization.
*/
ExecParallelHashMergeCounters(hashtable);
/*
* Wait for everyone to finish building and flushing files and
* counters.
*/
if (BarrierArriveAndWait(build_barrier,
WAIT_EVENT_HASH_BUILD_HASHING_INNER))
{
/*
* Elect one backend to disable any further growth. Batches
* are now fixed. While building them we made sure they'd fit
* in our memory budget when we load them back in later (or we
* tried to do that and gave up because we detected extreme
* skew).
*/
pstate->growth = PHJ_GROWTH_DISABLED;
}
}
/*
* We're not yet attached to a batch. We all agree on the dimensions and
* number of inner tuples (for the empty table optimization).
*/
hashtable->curbatch = -1;
hashtable->nbuckets = pstate->nbuckets;
hashtable->log2_nbuckets = my_log2(hashtable->nbuckets);
hashtable->totalTuples = pstate->total_tuples;
ExecParallelHashEnsureBatchAccessors(hashtable);
/*
* The next synchronization point is in ExecHashJoin's HJ_BUILD_HASHTABLE
* case, which will bring the build phase to PHJ_BUILD_DONE (if it isn't
* there already).
*/
Assert(BarrierPhase(build_barrier) == PHJ_BUILD_HASHING_OUTER ||
BarrierPhase(build_barrier) == PHJ_BUILD_DONE);
}
/* ----------------------------------------------------------------
* ExecInitHash
*
* Init routine for Hash node
* ----------------------------------------------------------------
*/
HashState *
ExecInitHash(Hash *node, EState *estate, int eflags)
{
HashState *hashstate;
/* check for unsupported flags */
Assert(!(eflags & (EXEC_FLAG_BACKWARD | EXEC_FLAG_MARK)));
/*
* create state structure
*/
hashstate = makeNode(HashState);
hashstate->ps.plan = (Plan *) node;
hashstate->ps.state = estate;
hashstate->ps.ExecProcNode = ExecHash;
hashstate->hashtable = NULL;
hashstate->hashkeys = NIL; /* will be set by parent HashJoin */
/*
* Miscellaneous initialization
*
* create expression context for node
*/
ExecAssignExprContext(estate, &hashstate->ps);
/*
* initialize our result slot
*/
ExecInitResultTupleSlot(estate, &hashstate->ps);
/*
* initialize child expressions
*/
hashstate->ps.qual =
ExecInitQual(node->plan.qual, (PlanState *) hashstate);
/*
* initialize child nodes
*/
outerPlanState(hashstate) = ExecInitNode(outerPlan(node), estate, eflags);
/*
* initialize tuple type. no need to initialize projection info because
* this node doesn't do projections
*/
ExecAssignResultTypeFromTL(&hashstate->ps);
hashstate->ps.ps_ProjInfo = NULL;
return hashstate;
}
/* ---------------------------------------------------------------
* ExecEndHash
*
* clean up routine for Hash node
* ----------------------------------------------------------------
*/
void
ExecEndHash(HashState *node)
{
PlanState *outerPlan;
/*
* free exprcontext
*/
ExecFreeExprContext(&node->ps);
/*
* shut down the subplan
*/
outerPlan = outerPlanState(node);
ExecEndNode(outerPlan);
}
/* ----------------------------------------------------------------
* ExecHashTableCreate
*
* create an empty hashtable data structure for hashjoin.
* ----------------------------------------------------------------
*/
HashJoinTable
ExecHashTableCreate(HashState *state, List *hashOperators, bool keepNulls)
{
Hash *node;
HashJoinTable hashtable;
Plan *outerNode;
size_t space_allowed;
int nbuckets;
int nbatch;
double rows;
int num_skew_mcvs;
int log2_nbuckets;
int nkeys;
int i;
ListCell *ho;
MemoryContext oldcxt;
/*
* Get information about the size of the relation to be hashed (it's the
* "outer" subtree of this node, but the inner relation of the hashjoin).
* Compute the appropriate size of the hash table.
*/
node = (Hash *) state->ps.plan;
outerNode = outerPlan(node);
/*
* If this is shared hash table with a partial plan, then we can't use
* outerNode->plan_rows to estimate its size. We need an estimate of the
* total number of rows across all copies of the partial plan.
*/
rows = node->plan.parallel_aware ? node->rows_total : outerNode->plan_rows;
ExecChooseHashTableSize(rows, outerNode->plan_width,
OidIsValid(node->skewTable),
state->parallel_state != NULL,
state->parallel_state != NULL ?
state->parallel_state->nparticipants - 1 : 0,
&space_allowed,
&nbuckets, &nbatch, &num_skew_mcvs);
/* nbuckets must be a power of 2 */
log2_nbuckets = my_log2(nbuckets);
Assert(nbuckets == (1 << log2_nbuckets));
/*
* Initialize the hash table control block.
*
* The hashtable control block is just palloc'd from the executor's
* per-query memory context.
*/
hashtable = (HashJoinTable) palloc(sizeof(HashJoinTableData));
hashtable->nbuckets = nbuckets;
hashtable->nbuckets_original = nbuckets;
hashtable->nbuckets_optimal = nbuckets;
hashtable->log2_nbuckets = log2_nbuckets;
hashtable->log2_nbuckets_optimal = log2_nbuckets;
hashtable->buckets.unshared = NULL;
hashtable->keepNulls = keepNulls;
hashtable->skewEnabled = false;
hashtable->skewBucket = NULL;
hashtable->skewBucketLen = 0;
hashtable->nSkewBuckets = 0;
hashtable->skewBucketNums = NULL;
hashtable->nbatch = nbatch;
hashtable->curbatch = 0;
hashtable->nbatch_original = nbatch;
hashtable->nbatch_outstart = nbatch;
hashtable->growEnabled = true;
hashtable->totalTuples = 0;
hashtable->partialTuples = 0;
hashtable->skewTuples = 0;
hashtable->innerBatchFile = NULL;
hashtable->outerBatchFile = NULL;
hashtable->spaceUsed = 0;
hashtable->spacePeak = 0;
hashtable->spaceAllowed = space_allowed;
hashtable->spaceUsedSkew = 0;
hashtable->spaceAllowedSkew =
hashtable->spaceAllowed * SKEW_WORK_MEM_PERCENT / 100;
hashtable->chunks = NULL;
hashtable->current_chunk = NULL;
hashtable->parallel_state = state->parallel_state;
hashtable->area = state->ps.state->es_query_dsa;
hashtable->batches = NULL;
#ifdef HJDEBUG
printf("Hashjoin %p: initial nbatch = %d, nbuckets = %d\n",
hashtable, nbatch, nbuckets);
#endif
/*
* Get info about the hash functions to be used for each hash key. Also
* remember whether the join operators are strict.
*/
nkeys = list_length(hashOperators);
hashtable->outer_hashfunctions =
(FmgrInfo *) palloc(nkeys * sizeof(FmgrInfo));
hashtable->inner_hashfunctions =
(FmgrInfo *) palloc(nkeys * sizeof(FmgrInfo));
hashtable->hashStrict = (bool *) palloc(nkeys * sizeof(bool));
i = 0;
foreach(ho, hashOperators)
{
Oid hashop = lfirst_oid(ho);
Oid left_hashfn;
Oid right_hashfn;
if (!get_op_hash_functions(hashop, &left_hashfn, &right_hashfn))
elog(ERROR, "could not find hash function for hash operator %u",
hashop);
fmgr_info(left_hashfn, &hashtable->outer_hashfunctions[i]);
fmgr_info(right_hashfn, &hashtable->inner_hashfunctions[i]);
hashtable->hashStrict[i] = op_strict(hashop);
i++;
}
/*
* Create temporary memory contexts in which to keep the hashtable working
* storage. See notes in executor/hashjoin.h.
*/
hashtable->hashCxt = AllocSetContextCreate(CurrentMemoryContext,
"HashTableContext",
ALLOCSET_DEFAULT_SIZES);
hashtable->batchCxt = AllocSetContextCreate(hashtable->hashCxt,
"HashBatchContext",
ALLOCSET_DEFAULT_SIZES);
/* Allocate data that will live for the life of the hashjoin */
oldcxt = MemoryContextSwitchTo(hashtable->hashCxt);
if (nbatch > 1 && hashtable->parallel_state == NULL)
{
/*
* allocate and initialize the file arrays in hashCxt (not needed for
* parallel case which uses shared tuplestores instead of raw files)
*/
hashtable->innerBatchFile = (BufFile **)
palloc0(nbatch * sizeof(BufFile *));
hashtable->outerBatchFile = (BufFile **)
palloc0(nbatch * sizeof(BufFile *));
/* The files will not be opened until needed... */
/* ... but make sure we have temp tablespaces established for them */
PrepareTempTablespaces();
}
MemoryContextSwitchTo(oldcxt);
if (hashtable->parallel_state)
{
ParallelHashJoinState *pstate = hashtable->parallel_state;
Barrier *build_barrier;
/*
* Attach to the build barrier. The corresponding detach operation is
* in ExecHashTableDetach. Note that we won't attach to the
* batch_barrier for batch 0 yet. We'll attach later and start it out
* in PHJ_BATCH_PROBING phase, because batch 0 is allocated up front
* and then loaded while hashing (the standard hybrid hash join
* algorithm), and we'll coordinate that using build_barrier.
*/
build_barrier = &pstate->build_barrier;
BarrierAttach(build_barrier);
/*
* So far we have no idea whether there are any other participants,
* and if so, what phase they are working on. The only thing we care
* about at this point is whether someone has already created the
* SharedHashJoinBatch objects and the hash table for batch 0. One
* backend will be elected to do that now if necessary.
*/
if (BarrierPhase(build_barrier) == PHJ_BUILD_ELECTING &&
BarrierArriveAndWait(build_barrier, WAIT_EVENT_HASH_BUILD_ELECTING))
{
pstate->nbatch = nbatch;
pstate->space_allowed = space_allowed;
pstate->growth = PHJ_GROWTH_OK;
/* Set up the shared state for coordinating batches. */
ExecParallelHashJoinSetUpBatches(hashtable, nbatch);
/*
* Allocate batch 0's hash table up front so we can load it
* directly while hashing.
*/
pstate->nbuckets = nbuckets;
ExecParallelHashTableAlloc(hashtable, 0);
}
/*
* The next Parallel Hash synchronization point is in
* MultiExecParallelHash(), which will progress it all the way to
* PHJ_BUILD_DONE. The caller must not return control from this
* executor node between now and then.
*/
}
else
{
/*
* Prepare context for the first-scan space allocations; allocate the
* hashbucket array therein, and set each bucket "empty".
*/
MemoryContextSwitchTo(hashtable->batchCxt);
hashtable->buckets.unshared = (HashJoinTuple *)
palloc0(nbuckets * sizeof(HashJoinTuple));
/*
* Set up for skew optimization, if possible and there's a need for
* more than one batch. (In a one-batch join, there's no point in
* it.)
*/
if (nbatch > 1)
ExecHashBuildSkewHash(hashtable, node, num_skew_mcvs);
MemoryContextSwitchTo(oldcxt);
}
return hashtable;
}
/*
* Compute appropriate size for hashtable given the estimated size of the
* relation to be hashed (number of rows and average row width).
*
* This is exported so that the planner's costsize.c can use it.
*/
/* Target bucket loading (tuples per bucket) */
#define NTUP_PER_BUCKET 1
void
ExecChooseHashTableSize(double ntuples, int tupwidth, bool useskew,
bool try_combined_work_mem,
int parallel_workers,
size_t *space_allowed,
int *numbuckets,
int *numbatches,
int *num_skew_mcvs)
{
int tupsize;
double inner_rel_bytes;
long bucket_bytes;
long hash_table_bytes;
long skew_table_bytes;
long max_pointers;
long mppow2;
int nbatch = 1;
int nbuckets;
double dbuckets;
/* Force a plausible relation size if no info */
if (ntuples <= 0.0)
ntuples = 1000.0;
/*
* Estimate tupsize based on footprint of tuple in hashtable... note this
* does not allow for any palloc overhead. The manipulations of spaceUsed
* don't count palloc overhead either.
*/
tupsize = HJTUPLE_OVERHEAD +
MAXALIGN(SizeofMinimalTupleHeader) +
MAXALIGN(tupwidth);
inner_rel_bytes = ntuples * tupsize;
/*
* Target in-memory hashtable size is work_mem kilobytes.
*/
hash_table_bytes = work_mem * 1024L;
/*
* Parallel Hash tries to use the combined work_mem of all workers to
* avoid the need to batch. If that won't work, it falls back to work_mem
* per worker and tries to process batches in parallel.
*/
if (try_combined_work_mem)
hash_table_bytes += hash_table_bytes * parallel_workers;
*space_allowed = hash_table_bytes;
/*
* If skew optimization is possible, estimate the number of skew buckets
* that will fit in the memory allowed, and decrement the assumed space
* available for the main hash table accordingly.
*
* We make the optimistic assumption that each skew bucket will contain
* one inner-relation tuple. If that turns out to be low, we will recover
* at runtime by reducing the number of skew buckets.
*
* hashtable->skewBucket will have up to 8 times as many HashSkewBucket
* pointers as the number of MCVs we allow, since ExecHashBuildSkewHash
* will round up to the next power of 2 and then multiply by 4 to reduce
* collisions.
*/
if (useskew)
{
skew_table_bytes = hash_table_bytes * SKEW_WORK_MEM_PERCENT / 100;
/*----------
* Divisor is:
* size of a hash tuple +
* worst-case size of skewBucket[] per MCV +
* size of skewBucketNums[] entry +
* size of skew bucket struct itself
*----------
*/
*num_skew_mcvs = skew_table_bytes / (tupsize +
(8 * sizeof(HashSkewBucket *)) +
sizeof(int) +
SKEW_BUCKET_OVERHEAD);
if (*num_skew_mcvs > 0)
hash_table_bytes -= skew_table_bytes;
}
else
*num_skew_mcvs = 0;
/*
* Set nbuckets to achieve an average bucket load of NTUP_PER_BUCKET when
* memory is filled, assuming a single batch; but limit the value so that
* the pointer arrays we'll try to allocate do not exceed work_mem nor
* MaxAllocSize.
*
* Note that both nbuckets and nbatch must be powers of 2 to make
* ExecHashGetBucketAndBatch fast.
*/
max_pointers = *space_allowed / sizeof(HashJoinTuple);
max_pointers = Min(max_pointers, MaxAllocSize / sizeof(HashJoinTuple));
/* If max_pointers isn't a power of 2, must round it down to one */
mppow2 = 1L << my_log2(max_pointers);
if (max_pointers != mppow2)
max_pointers = mppow2 / 2;
/* Also ensure we avoid integer overflow in nbatch and nbuckets */
/* (this step is redundant given the current value of MaxAllocSize) */
max_pointers = Min(max_pointers, INT_MAX / 2);
dbuckets = ceil(ntuples / NTUP_PER_BUCKET);
dbuckets = Min(dbuckets, max_pointers);
nbuckets = (int) dbuckets;
/* don't let nbuckets be really small, though ... */
nbuckets = Max(nbuckets, 1024);
/* ... and force it to be a power of 2. */
nbuckets = 1 << my_log2(nbuckets);
/*
* If there's not enough space to store the projected number of tuples and
* the required bucket headers, we will need multiple batches.
*/
bucket_bytes = sizeof(HashJoinTuple) * nbuckets;
if (inner_rel_bytes + bucket_bytes > hash_table_bytes)
{
/* We'll need multiple batches */
long lbuckets;
double dbatch;
int minbatch;
long bucket_size;
/*
* If Parallel Hash with combined work_mem would still need multiple
* batches, we'll have to fall back to regular work_mem budget.
*/
if (try_combined_work_mem)
{
ExecChooseHashTableSize(ntuples, tupwidth, useskew,
false, parallel_workers,
space_allowed,
numbuckets,
numbatches,
num_skew_mcvs);
return;
}
/*
* Estimate the number of buckets we'll want to have when work_mem is
* entirely full. Each bucket will contain a bucket pointer plus
* NTUP_PER_BUCKET tuples, whose projected size already includes
* overhead for the hash code, pointer to the next tuple, etc.
*/
bucket_size = (tupsize * NTUP_PER_BUCKET + sizeof(HashJoinTuple));
lbuckets = 1L << my_log2(hash_table_bytes / bucket_size);
lbuckets = Min(lbuckets, max_pointers);
nbuckets = (int) lbuckets;
nbuckets = 1 << my_log2(nbuckets);
bucket_bytes = nbuckets * sizeof(HashJoinTuple);
/*
* Buckets are simple pointers to hashjoin tuples, while tupsize
* includes the pointer, hash code, and MinimalTupleData. So buckets
* should never really exceed 25% of work_mem (even for
* NTUP_PER_BUCKET=1); except maybe for work_mem values that are not
* 2^N bytes, where we might get more because of doubling. So let's
* look for 50% here.
*/
Assert(bucket_bytes <= hash_table_bytes / 2);
/* Calculate required number of batches. */
dbatch = ceil(inner_rel_bytes / (hash_table_bytes - bucket_bytes));
dbatch = Min(dbatch, max_pointers);
minbatch = (int) dbatch;
nbatch = 2;
while (nbatch < minbatch)
nbatch <<= 1;
}
Assert(nbuckets > 0);
Assert(nbatch > 0);
*numbuckets = nbuckets;
*numbatches = nbatch;
}
/* ----------------------------------------------------------------
* ExecHashTableDestroy
*
* destroy a hash table
* ----------------------------------------------------------------
*/
void
ExecHashTableDestroy(HashJoinTable hashtable)
{
int i;
/*
* Make sure all the temp files are closed. We skip batch 0, since it
* can't have any temp files (and the arrays might not even exist if
* nbatch is only 1). Parallel hash joins don't use these files.
*/
if (hashtable->innerBatchFile != NULL)
{
for (i = 1; i < hashtable->nbatch; i++)
{
if (hashtable->innerBatchFile[i])
BufFileClose(hashtable->innerBatchFile[i]);
if (hashtable->outerBatchFile[i])
BufFileClose(hashtable->outerBatchFile[i]);
}
}
/* Release working memory (batchCxt is a child, so it goes away too) */
MemoryContextDelete(hashtable->hashCxt);
/* And drop the control block */
pfree(hashtable);
}
/*
* ExecHashIncreaseNumBatches
* increase the original number of batches in order to reduce
* current memory consumption
*/
static void
ExecHashIncreaseNumBatches(HashJoinTable hashtable)
{
int oldnbatch = hashtable->nbatch;
int curbatch = hashtable->curbatch;
int nbatch;
MemoryContext oldcxt;
long ninmemory;
long nfreed;
HashMemoryChunk oldchunks;
/* do nothing if we've decided to shut off growth */
if (!hashtable->growEnabled)
return;
/* safety check to avoid overflow */
if (oldnbatch > Min(INT_MAX / 2, MaxAllocSize / (sizeof(void *) * 2)))
return;
nbatch = oldnbatch * 2;
Assert(nbatch > 1);
#ifdef HJDEBUG
printf("Hashjoin %p: increasing nbatch to %d because space = %zu\n",
hashtable, nbatch, hashtable->spaceUsed);
#endif
oldcxt = MemoryContextSwitchTo(hashtable->hashCxt);
if (hashtable->innerBatchFile == NULL)
{
/* we had no file arrays before */
hashtable->innerBatchFile = (BufFile **)
palloc0(nbatch * sizeof(BufFile *));
hashtable->outerBatchFile = (BufFile **)
palloc0(nbatch * sizeof(BufFile *));
/* time to establish the temp tablespaces, too */
PrepareTempTablespaces();
}
else
{
/* enlarge arrays and zero out added entries */
hashtable->innerBatchFile = (BufFile **)
repalloc(hashtable->innerBatchFile, nbatch * sizeof(BufFile *));
hashtable->outerBatchFile = (BufFile **)
repalloc(hashtable->outerBatchFile, nbatch * sizeof(BufFile *));
MemSet(hashtable->innerBatchFile + oldnbatch, 0,
(nbatch - oldnbatch) * sizeof(BufFile *));
MemSet(hashtable->outerBatchFile + oldnbatch, 0,
(nbatch - oldnbatch) * sizeof(BufFile *));
}
MemoryContextSwitchTo(oldcxt);
hashtable->nbatch = nbatch;
/*
* Scan through the existing hash table entries and dump out any that are
* no longer of the current batch.
*/
ninmemory = nfreed = 0;
/* If know we need to resize nbuckets, we can do it while rebatching. */
if (hashtable->nbuckets_optimal != hashtable->nbuckets)
{
/* we never decrease the number of buckets */
Assert(hashtable->nbuckets_optimal > hashtable->nbuckets);
hashtable->nbuckets = hashtable->nbuckets_optimal;
hashtable->log2_nbuckets = hashtable->log2_nbuckets_optimal;
hashtable->buckets.unshared =
repalloc(hashtable->buckets.unshared,
sizeof(HashJoinTuple) * hashtable->nbuckets);
}
/*
* We will scan through the chunks directly, so that we can reset the
* buckets now and not have to keep track which tuples in the buckets have
* already been processed. We will free the old chunks as we go.
*/
memset(hashtable->buckets.unshared, 0,
sizeof(HashJoinTuple) * hashtable->nbuckets);
oldchunks = hashtable->chunks;
hashtable->chunks = NULL;
/* so, let's scan through the old chunks, and all tuples in each chunk */
while (oldchunks != NULL)
{
HashMemoryChunk nextchunk = oldchunks->next.unshared;
/* position within the buffer (up to oldchunks->used) */
size_t idx = 0;
/* process all tuples stored in this chunk (and then free it) */
while (idx < oldchunks->used)
{
HashJoinTuple hashTuple = (HashJoinTuple) (oldchunks->data + idx);
MinimalTuple tuple = HJTUPLE_MINTUPLE(hashTuple);
int hashTupleSize = (HJTUPLE_OVERHEAD + tuple->t_len);
int bucketno;
int batchno;
ninmemory++;
ExecHashGetBucketAndBatch(hashtable, hashTuple->hashvalue,
&bucketno, &batchno);
if (batchno == curbatch)
{
/* keep tuple in memory - copy it into the new chunk */
HashJoinTuple copyTuple;
copyTuple = (HashJoinTuple) dense_alloc(hashtable, hashTupleSize);
memcpy(copyTuple, hashTuple, hashTupleSize);
/* and add it back to the appropriate bucket */
copyTuple->next.unshared = hashtable->buckets.unshared[bucketno];
hashtable->buckets.unshared[bucketno] = copyTuple;
}
else
{
/* dump it out */
Assert(batchno > curbatch);
ExecHashJoinSaveTuple(HJTUPLE_MINTUPLE(hashTuple),
hashTuple->hashvalue,
&hashtable->innerBatchFile[batchno]);
hashtable->spaceUsed -= hashTupleSize;
nfreed++;
}
/* next tuple in this chunk */
idx += MAXALIGN(hashTupleSize);
/* allow this loop to be cancellable */
CHECK_FOR_INTERRUPTS();
}
/* we're done with this chunk - free it and proceed to the next one */
pfree(oldchunks);
oldchunks = nextchunk;
}
#ifdef HJDEBUG
printf("Hashjoin %p: freed %ld of %ld tuples, space now %zu\n",
hashtable, nfreed, ninmemory, hashtable->spaceUsed);
#endif
/*
* If we dumped out either all or none of the tuples in the table, disable
* further expansion of nbatch. This situation implies that we have
* enough tuples of identical hashvalues to overflow spaceAllowed.
* Increasing nbatch will not fix it since there's no way to subdivide the
* group any more finely. We have to just gut it out and hope the server
* has enough RAM.
*/
if (nfreed == 0 || nfreed == ninmemory)
{
hashtable->growEnabled = false;
#ifdef HJDEBUG
printf("Hashjoin %p: disabling further increase of nbatch\n",
hashtable);
#endif
}
}
/*
* ExecParallelHashIncreaseNumBatches
* Every participant attached to grow_barrier must run this function
* when it observes growth == PHJ_GROWTH_NEED_MORE_BATCHES.
*/
static void
ExecParallelHashIncreaseNumBatches(HashJoinTable hashtable)
{
ParallelHashJoinState *pstate = hashtable->parallel_state;
int i;
Assert(BarrierPhase(&pstate->build_barrier) == PHJ_BUILD_HASHING_INNER);
/*
* It's unlikely, but we need to be prepared for new participants to show
* up while we're in the middle of this operation so we need to switch on
* barrier phase here.
*/
switch (PHJ_GROW_BATCHES_PHASE(BarrierPhase(&pstate->grow_batches_barrier)))
{
case PHJ_GROW_BATCHES_ELECTING:
/*
* Elect one participant to prepare to grow the number of batches.
* This involves reallocating or resetting the buckets of batch 0
* in preparation for all participants to begin repartitioning the
* tuples.
*/
if (BarrierArriveAndWait(&pstate->grow_batches_barrier,
WAIT_EVENT_HASH_GROW_BATCHES_ELECTING))
{
dsa_pointer_atomic *buckets;
ParallelHashJoinBatch *old_batch0;
int new_nbatch;
int i;
/* Move the old batch out of the way. */
old_batch0 = hashtable->batches[0].shared;
pstate->old_batches = pstate->batches;
pstate->old_nbatch = hashtable->nbatch;
pstate->batches = InvalidDsaPointer;
/* Free this backend's old accessors. */
ExecParallelHashCloseBatchAccessors(hashtable);
/* Figure out how many batches to use. */
if (hashtable->nbatch == 1)
{
/*
* We are going from single-batch to multi-batch. We need
* to switch from one large combined memory budget to the
* regular work_mem budget.
*/
pstate->space_allowed = work_mem * 1024L;
/*
* The combined work_mem of all participants wasn't
* enough. Therefore one batch per participant would be
* approximately equivalent and would probably also be
* insufficient. So try two batches per particiant,
* rounded up to a power of two.
*/
new_nbatch = 1 << my_log2(pstate->nparticipants * 2);
}
else
{
/*
* We were already multi-batched. Try doubling the number
* of batches.
*/
new_nbatch = hashtable->nbatch * 2;
}
/* Allocate new larger generation of batches. */
Assert(hashtable->nbatch == pstate->nbatch);
ExecParallelHashJoinSetUpBatches(hashtable, new_nbatch);
Assert(hashtable->nbatch == pstate->nbatch);
/* Replace or recycle batch 0's bucket array. */
if (pstate->old_nbatch == 1)
{
double dtuples;
double dbuckets;
int new_nbuckets;
/*
* We probably also need a smaller bucket array. How many
* tuples do we expect per batch, assuming we have only
* half of them so far? Normally we don't need to change
* the bucket array's size, because the size of each batch
* stays the same as we add more batches, but in this
* special case we move from a large batch to many smaller
* batches and it would be wasteful to keep the large
* array.
*/
dtuples = (old_batch0->ntuples * 2.0) / new_nbatch;
dbuckets = ceil(dtuples / NTUP_PER_BUCKET);
dbuckets = Min(dbuckets,
MaxAllocSize / sizeof(dsa_pointer_atomic));
new_nbuckets = (int) dbuckets;
new_nbuckets = Max(new_nbuckets, 1024);
new_nbuckets = 1 << my_log2(new_nbuckets);
dsa_free(hashtable->area, old_batch0->buckets);
hashtable->batches[0].shared->buckets =
dsa_allocate(hashtable->area,
sizeof(dsa_pointer_atomic) * new_nbuckets);
buckets = (dsa_pointer_atomic *)
dsa_get_address(hashtable->area,
hashtable->batches[0].shared->buckets);
for (i = 0; i < new_nbuckets; ++i)
dsa_pointer_atomic_init(&buckets[i], InvalidDsaPointer);
pstate->nbuckets = new_nbuckets;
}
else
{
/* Recycle the existing bucket array. */
hashtable->batches[0].shared->buckets = old_batch0->buckets;
buckets = (dsa_pointer_atomic *)
dsa_get_address(hashtable->area, old_batch0->buckets);
for (i = 0; i < hashtable->nbuckets; ++i)
dsa_pointer_atomic_write(&buckets[i], InvalidDsaPointer);
}
/* Move all chunks to the work queue for parallel processing. */
pstate->chunk_work_queue = old_batch0->chunks;
/* Disable further growth temporarily while we're growing. */
pstate->growth = PHJ_GROWTH_DISABLED;
}
else
{
/* All other participants just flush their tuples to disk. */
ExecParallelHashCloseBatchAccessors(hashtable);
}
/* Fall through. */
case PHJ_GROW_BATCHES_ALLOCATING:
/* Wait for the above to be finished. */
BarrierArriveAndWait(&pstate->grow_batches_barrier,
WAIT_EVENT_HASH_GROW_BATCHES_ALLOCATING);
/* Fall through. */
case PHJ_GROW_BATCHES_REPARTITIONING:
/* Make sure that we have the current dimensions and buckets. */
ExecParallelHashEnsureBatchAccessors(hashtable);
ExecParallelHashTableSetCurrentBatch(hashtable, 0);
/* Then partition, flush counters. */
ExecParallelHashRepartitionFirst(hashtable);
ExecParallelHashRepartitionRest(hashtable);
ExecParallelHashMergeCounters(hashtable);
/* Wait for the above to be finished. */
BarrierArriveAndWait(&pstate->grow_batches_barrier,
WAIT_EVENT_HASH_GROW_BATCHES_REPARTITIONING);
/* Fall through. */
case PHJ_GROW_BATCHES_DECIDING:
/*
* Elect one participant to clean up and decide whether further
* repartitioning is needed, or should be disabled because it's
* not helping.
*/
if (BarrierArriveAndWait(&pstate->grow_batches_barrier,
WAIT_EVENT_HASH_GROW_BATCHES_DECIDING))
{
bool space_exhausted = false;
bool extreme_skew_detected = false;
/* Make sure that we have the current dimensions and buckets. */
ExecParallelHashEnsureBatchAccessors(hashtable);
ExecParallelHashTableSetCurrentBatch(hashtable, 0);
/* Are any of the new generation of batches exhausted? */
for (i = 0; i < hashtable->nbatch; ++i)
{
ParallelHashJoinBatch *batch = hashtable->batches[i].shared;
if (batch->space_exhausted ||
batch->estimated_size > pstate->space_allowed)
{
int parent;
space_exhausted = true;
/*
* Did this batch receive ALL of the tuples from its
* parent batch? That would indicate that further
* repartitioning isn't going to help (the hash values
* are probably all the same).
*/
parent = i % pstate->old_nbatch;
if (batch->ntuples == hashtable->batches[parent].shared->old_ntuples)
extreme_skew_detected = true;
}
}
/* Don't keep growing if it's not helping or we'd overflow. */
if (extreme_skew_detected || hashtable->nbatch >= INT_MAX / 2)
pstate->growth = PHJ_GROWTH_DISABLED;
else if (space_exhausted)
pstate->growth = PHJ_GROWTH_NEED_MORE_BATCHES;
else
pstate->growth = PHJ_GROWTH_OK;
/* Free the old batches in shared memory. */
dsa_free(hashtable->area, pstate->old_batches);
pstate->old_batches = InvalidDsaPointer;
}
/* Fall through. */
case PHJ_GROW_BATCHES_FINISHING:
/* Wait for the above to complete. */
BarrierArriveAndWait(&pstate->grow_batches_barrier,
WAIT_EVENT_HASH_GROW_BATCHES_FINISHING);
}
}
/*
* Repartition the tuples currently loaded into memory for inner batch 0
* because the number of batches has been increased. Some tuples are retained
* in memory and some are written out to a later batch.
*/
static void
ExecParallelHashRepartitionFirst(HashJoinTable hashtable)
{
dsa_pointer chunk_shared;
HashMemoryChunk chunk;
Assert(hashtable->nbatch == hashtable->parallel_state->nbatch);
while ((chunk = ExecParallelHashPopChunkQueue(hashtable, &chunk_shared)))
{
size_t idx = 0;
/* Repartition all tuples in this chunk. */
while (idx < chunk->used)
{
HashJoinTuple hashTuple = (HashJoinTuple) (chunk->data + idx);
MinimalTuple tuple = HJTUPLE_MINTUPLE(hashTuple);
HashJoinTuple copyTuple;
dsa_pointer shared;
int bucketno;
int batchno;
ExecHashGetBucketAndBatch(hashtable, hashTuple->hashvalue,
&bucketno, &batchno);
Assert(batchno < hashtable->nbatch);
if (batchno == 0)
{
/* It still belongs in batch 0. Copy to a new chunk. */
copyTuple =
ExecParallelHashTupleAlloc(hashtable,
HJTUPLE_OVERHEAD + tuple->t_len,
&shared);
copyTuple->hashvalue = hashTuple->hashvalue;
memcpy(HJTUPLE_MINTUPLE(copyTuple), tuple, tuple->t_len);
ExecParallelHashPushTuple(&hashtable->buckets.shared[bucketno],
copyTuple, shared);
}
else
{
size_t tuple_size =
MAXALIGN(HJTUPLE_OVERHEAD + tuple->t_len);
/* It belongs in a later batch. */
hashtable->batches[batchno].estimated_size += tuple_size;
sts_puttuple(hashtable->batches[batchno].inner_tuples,
&hashTuple->hashvalue, tuple);
}
/* Count this tuple. */
++hashtable->batches[0].old_ntuples;
++hashtable->batches[batchno].ntuples;
idx += MAXALIGN(HJTUPLE_OVERHEAD +
HJTUPLE_MINTUPLE(hashTuple)->t_len);
}
/* Free this chunk. */
dsa_free(hashtable->area, chunk_shared);
CHECK_FOR_INTERRUPTS();
}
}
/*
* Help repartition inner batches 1..n.
*/
static void
ExecParallelHashRepartitionRest(HashJoinTable hashtable)
{
ParallelHashJoinState *pstate = hashtable->parallel_state;
int old_nbatch = pstate->old_nbatch;
SharedTuplestoreAccessor **old_inner_tuples;
ParallelHashJoinBatch *old_batches;
int i;
/* Get our hands on the previous generation of batches. */
old_batches = (ParallelHashJoinBatch *)
dsa_get_address(hashtable->area, pstate->old_batches);
old_inner_tuples = palloc0(sizeof(SharedTuplestoreAccessor *) * old_nbatch);
for (i = 1; i < old_nbatch; ++i)
{
ParallelHashJoinBatch *shared =
NthParallelHashJoinBatch(old_batches, i);
old_inner_tuples[i] = sts_attach(ParallelHashJoinBatchInner(shared),
ParallelWorkerNumber + 1,
&pstate->fileset);
}
/* Join in the effort to repartition them. */
for (i = 1; i < old_nbatch; ++i)
{
MinimalTuple tuple;
uint32 hashvalue;
/* Scan one partition from the previous generation. */
sts_begin_parallel_scan(old_inner_tuples[i]);
while ((tuple = sts_parallel_scan_next(old_inner_tuples[i], &hashvalue)))
{
size_t tuple_size = MAXALIGN(HJTUPLE_OVERHEAD + tuple->t_len);
int bucketno;
int batchno;
/* Decide which partition it goes to in the new generation. */
ExecHashGetBucketAndBatch(hashtable, hashvalue, &bucketno,
&batchno);
hashtable->batches[batchno].estimated_size += tuple_size;
++hashtable->batches[batchno].ntuples;
++hashtable->batches[i].old_ntuples;
/* Store the tuple its new batch. */
sts_puttuple(hashtable->batches[batchno].inner_tuples,
&hashvalue, tuple);
CHECK_FOR_INTERRUPTS();
}
sts_end_parallel_scan(old_inner_tuples[i]);
}
pfree(old_inner_tuples);
}
/*
* Transfer the backend-local per-batch counters to the shared totals.
*/
static void
ExecParallelHashMergeCounters(HashJoinTable hashtable)
{
ParallelHashJoinState *pstate = hashtable->parallel_state;
int i;
LWLockAcquire(&pstate->lock, LW_EXCLUSIVE);
pstate->total_tuples = 0;
for (i = 0; i < hashtable->nbatch; ++i)
{
ParallelHashJoinBatchAccessor *batch = &hashtable->batches[i];
batch->shared->size += batch->size;
batch->shared->estimated_size += batch->estimated_size;
batch->shared->ntuples += batch->ntuples;
batch->shared->old_ntuples += batch->old_ntuples;
batch->size = 0;
batch->estimated_size = 0;
batch->ntuples = 0;
batch->old_ntuples = 0;
pstate->total_tuples += batch->shared->ntuples;
}
LWLockRelease(&pstate->lock);
}
/*
* ExecHashIncreaseNumBuckets
* increase the original number of buckets in order to reduce
* number of tuples per bucket
*/
static void
ExecHashIncreaseNumBuckets(HashJoinTable hashtable)
{
HashMemoryChunk chunk;
/* do nothing if not an increase (it's called increase for a reason) */
if (hashtable->nbuckets >= hashtable->nbuckets_optimal)
return;
#ifdef HJDEBUG
printf("Hashjoin %p: increasing nbuckets %d => %d\n",
hashtable, hashtable->nbuckets, hashtable->nbuckets_optimal);
#endif
hashtable->nbuckets = hashtable->nbuckets_optimal;
hashtable->log2_nbuckets = hashtable->log2_nbuckets_optimal;
Assert(hashtable->nbuckets > 1);
Assert(hashtable->nbuckets <= (INT_MAX / 2));
Assert(hashtable->nbuckets == (1 << hashtable->log2_nbuckets));
/*
* Just reallocate the proper number of buckets - we don't need to walk
* through them - we can walk the dense-allocated chunks (just like in
* ExecHashIncreaseNumBatches, but without all the copying into new
* chunks)
*/
hashtable->buckets.unshared =
(HashJoinTuple *) repalloc(hashtable->buckets.unshared,
hashtable->nbuckets * sizeof(HashJoinTuple));
memset(hashtable->buckets.unshared, 0,
hashtable->nbuckets * sizeof(HashJoinTuple));
/* scan through all tuples in all chunks to rebuild the hash table */
for (chunk = hashtable->chunks; chunk != NULL; chunk = chunk->next.unshared)
{
/* process all tuples stored in this chunk */
size_t idx = 0;
while (idx < chunk->used)
{
HashJoinTuple hashTuple = (HashJoinTuple) (chunk->data + idx);
int bucketno;
int batchno;
ExecHashGetBucketAndBatch(hashtable, hashTuple->hashvalue,
&bucketno, &batchno);
/* add the tuple to the proper bucket */
hashTuple->next.unshared = hashtable->buckets.unshared[bucketno];
hashtable->buckets.unshared[bucketno] = hashTuple;
/* advance index past the tuple */
idx += MAXALIGN(HJTUPLE_OVERHEAD +
HJTUPLE_MINTUPLE(hashTuple)->t_len);
}
/* allow this loop to be cancellable */
CHECK_FOR_INTERRUPTS();
}
}
static void
ExecParallelHashIncreaseNumBuckets(HashJoinTable hashtable)
{
ParallelHashJoinState *pstate = hashtable->parallel_state;
int i;
HashMemoryChunk chunk;
dsa_pointer chunk_s;
Assert(BarrierPhase(&pstate->build_barrier) == PHJ_BUILD_HASHING_INNER);
/*
* It's unlikely, but we need to be prepared for new participants to show
* up while we're in the middle of this operation so we need to switch on
* barrier phase here.
*/
switch (PHJ_GROW_BUCKETS_PHASE(BarrierPhase(&pstate->grow_buckets_barrier)))
{
case PHJ_GROW_BUCKETS_ELECTING:
/* Elect one participant to prepare to increase nbuckets. */
if (BarrierArriveAndWait(&pstate->grow_buckets_barrier,
WAIT_EVENT_HASH_GROW_BUCKETS_ELECTING))
{
size_t size;
dsa_pointer_atomic *buckets;
/* Double the size of the bucket array. */
pstate->nbuckets *= 2;
size = pstate->nbuckets * sizeof(dsa_pointer_atomic);
hashtable->batches[0].shared->size += size / 2;
dsa_free(hashtable->area, hashtable->batches[0].shared->buckets);
hashtable->batches[0].shared->buckets =
dsa_allocate(hashtable->area, size);
buckets = (dsa_pointer_atomic *)
dsa_get_address(hashtable->area,
hashtable->batches[0].shared->buckets);
for (i = 0; i < pstate->nbuckets; ++i)
dsa_pointer_atomic_init(&buckets[i], InvalidDsaPointer);
/* Put the chunk list onto the work queue. */
pstate->chunk_work_queue = hashtable->batches[0].shared->chunks;
/* Clear the flag. */
pstate->growth = PHJ_GROWTH_OK;
}
/* Fall through. */
case PHJ_GROW_BUCKETS_ALLOCATING:
/* Wait for the above to complete. */
BarrierArriveAndWait(&pstate->grow_buckets_barrier,
WAIT_EVENT_HASH_GROW_BUCKETS_ALLOCATING);
/* Fall through. */
case PHJ_GROW_BUCKETS_REINSERTING:
/* Reinsert all tuples into the hash table. */
ExecParallelHashEnsureBatchAccessors(hashtable);
ExecParallelHashTableSetCurrentBatch(hashtable, 0);
while ((chunk = ExecParallelHashPopChunkQueue(hashtable, &chunk_s)))
{
size_t idx = 0;
while (idx < chunk->used)
{
HashJoinTuple hashTuple = (HashJoinTuple) (chunk->data + idx);
dsa_pointer shared = chunk_s + HASH_CHUNK_HEADER_SIZE + idx;
int bucketno;
int batchno;
ExecHashGetBucketAndBatch(hashtable, hashTuple->hashvalue,
&bucketno, &batchno);
Assert(batchno == 0);
/* add the tuple to the proper bucket */
ExecParallelHashPushTuple(&hashtable->buckets.shared[bucketno],
hashTuple, shared);
/* advance index past the tuple */
idx += MAXALIGN(HJTUPLE_OVERHEAD +
HJTUPLE_MINTUPLE(hashTuple)->t_len);
}
/* allow this loop to be cancellable */
CHECK_FOR_INTERRUPTS();
}
BarrierArriveAndWait(&pstate->grow_buckets_barrier,
WAIT_EVENT_HASH_GROW_BUCKETS_REINSERTING);
}
}
/*
* ExecHashTableInsert
* insert a tuple into the hash table depending on the hash value
* it may just go to a temp file for later batches
*
* Note: the passed TupleTableSlot may contain a regular, minimal, or virtual
* tuple; the minimal case in particular is certain to happen while reloading
* tuples from batch files. We could save some cycles in the regular-tuple
* case by not forcing the slot contents into minimal form; not clear if it's
* worth the messiness required.
*/
void
ExecHashTableInsert(HashJoinTable hashtable,
TupleTableSlot *slot,
uint32 hashvalue)
{
MinimalTuple tuple = ExecFetchSlotMinimalTuple(slot);
int bucketno;
int batchno;
ExecHashGetBucketAndBatch(hashtable, hashvalue,
&bucketno, &batchno);
/*
* decide whether to put the tuple in the hash table or a temp file
*/
if (batchno == hashtable->curbatch)
{
/*
* put the tuple in hash table
*/
HashJoinTuple hashTuple;
int hashTupleSize;
double ntuples = (hashtable->totalTuples - hashtable->skewTuples);
/* Create the HashJoinTuple */
hashTupleSize = HJTUPLE_OVERHEAD + tuple->t_len;
hashTuple = (HashJoinTuple) dense_alloc(hashtable, hashTupleSize);
hashTuple->hashvalue = hashvalue;
memcpy(HJTUPLE_MINTUPLE(hashTuple), tuple, tuple->t_len);
/*
* We always reset the tuple-matched flag on insertion. This is okay
* even when reloading a tuple from a batch file, since the tuple
* could not possibly have been matched to an outer tuple before it
* went into the batch file.
*/
HeapTupleHeaderClearMatch(HJTUPLE_MINTUPLE(hashTuple));
/* Push it onto the front of the bucket's list */
hashTuple->next.unshared = hashtable->buckets.unshared[bucketno];
hashtable->buckets.unshared[bucketno] = hashTuple;
/*
* Increase the (optimal) number of buckets if we just exceeded the
* NTUP_PER_BUCKET threshold, but only when there's still a single
* batch.
*/
if (hashtable->nbatch == 1 &&
ntuples > (hashtable->nbuckets_optimal * NTUP_PER_BUCKET))
{
/* Guard against integer overflow and alloc size overflow */
if (hashtable->nbuckets_optimal <= INT_MAX / 2 &&
hashtable->nbuckets_optimal * 2 <= MaxAllocSize / sizeof(HashJoinTuple))
{
hashtable->nbuckets_optimal *= 2;
hashtable->log2_nbuckets_optimal += 1;
}
}
/* Account for space used, and back off if we've used too much */
hashtable->spaceUsed += hashTupleSize;
if (hashtable->spaceUsed > hashtable->spacePeak)
hashtable->spacePeak = hashtable->spaceUsed;
if (hashtable->spaceUsed +
hashtable->nbuckets_optimal * sizeof(HashJoinTuple)
> hashtable->spaceAllowed)
ExecHashIncreaseNumBatches(hashtable);
}
else
{
/*
* put the tuple into a temp file for later batches
*/
Assert(batchno > hashtable->curbatch);
ExecHashJoinSaveTuple(tuple,
hashvalue,
&hashtable->innerBatchFile[batchno]);
}
}
/*
* ExecHashTableParallelInsert
* insert a tuple into a shared hash table or shared batch tuplestore
*/
void
ExecParallelHashTableInsert(HashJoinTable hashtable,
TupleTableSlot *slot,
uint32 hashvalue)
{
MinimalTuple tuple = ExecFetchSlotMinimalTuple(slot);
dsa_pointer shared;
int bucketno;
int batchno;
retry:
ExecHashGetBucketAndBatch(hashtable, hashvalue, &bucketno, &batchno);
if (batchno == 0)
{
HashJoinTuple hashTuple;
/* Try to load it into memory. */
Assert(BarrierPhase(&hashtable->parallel_state->build_barrier) ==
PHJ_BUILD_HASHING_INNER);
hashTuple = ExecParallelHashTupleAlloc(hashtable,
HJTUPLE_OVERHEAD + tuple->t_len,
&shared);
if (hashTuple == NULL)
goto retry;
/* Store the hash value in the HashJoinTuple header. */
hashTuple->hashvalue = hashvalue;
memcpy(HJTUPLE_MINTUPLE(hashTuple), tuple, tuple->t_len);
/* Push it onto the front of the bucket's list */
ExecParallelHashPushTuple(&hashtable->buckets.shared[bucketno],
hashTuple, shared);
}
else
{
size_t tuple_size = MAXALIGN(HJTUPLE_OVERHEAD + tuple->t_len);
Assert(batchno > 0);
/* Try to preallocate space in the batch if necessary. */
if (hashtable->batches[batchno].preallocated < tuple_size)
{
if (!ExecParallelHashTuplePrealloc(hashtable, batchno, tuple_size))
goto retry;
}
Assert(hashtable->batches[batchno].preallocated >= tuple_size);
hashtable->batches[batchno].preallocated -= tuple_size;
sts_puttuple(hashtable->batches[batchno].inner_tuples, &hashvalue,
tuple);
}
++hashtable->batches[batchno].ntuples;
}
/*
* Insert a tuple into the current hash table. Unlike
* ExecParallelHashTableInsert, this version is not prepared to send the tuple
* to other batches or to run out of memory, and should only be called with
* tuples that belong in the current batch once growth has been disabled.
*/
void
ExecParallelHashTableInsertCurrentBatch(HashJoinTable hashtable,
TupleTableSlot *slot,
uint32 hashvalue)
{
MinimalTuple tuple = ExecFetchSlotMinimalTuple(slot);
HashJoinTuple hashTuple;
dsa_pointer shared;
int batchno;
int bucketno;
ExecHashGetBucketAndBatch(hashtable, hashvalue, &bucketno, &batchno);
Assert(batchno == hashtable->curbatch);
hashTuple = ExecParallelHashTupleAlloc(hashtable,
HJTUPLE_OVERHEAD + tuple->t_len,
&shared);
hashTuple->hashvalue = hashvalue;
memcpy(HJTUPLE_MINTUPLE(hashTuple), tuple, tuple->t_len);
HeapTupleHeaderClearMatch(HJTUPLE_MINTUPLE(hashTuple));
ExecParallelHashPushTuple(&hashtable->buckets.shared[bucketno],
hashTuple, shared);
}
/*
* ExecHashGetHashValue
* Compute the hash value for a tuple
*
* The tuple to be tested must be in either econtext->ecxt_outertuple or
* econtext->ecxt_innertuple. Vars in the hashkeys expressions should have
* varno either OUTER_VAR or INNER_VAR.
*
* A true result means the tuple's hash value has been successfully computed
* and stored at *hashvalue. A false result means the tuple cannot match
* because it contains a null attribute, and hence it should be discarded
* immediately. (If keep_nulls is true then false is never returned.)
*/
bool
ExecHashGetHashValue(HashJoinTable hashtable,
ExprContext *econtext,
List *hashkeys,
bool outer_tuple,
bool keep_nulls,
uint32 *hashvalue)
{
uint32 hashkey = 0;
FmgrInfo *hashfunctions;
ListCell *hk;
int i = 0;
MemoryContext oldContext;
/*
* We reset the eval context each time to reclaim any memory leaked in the
* hashkey expressions.
*/
ResetExprContext(econtext);
oldContext = MemoryContextSwitchTo(econtext->ecxt_per_tuple_memory);
if (outer_tuple)
hashfunctions = hashtable->outer_hashfunctions;
else
hashfunctions = hashtable->inner_hashfunctions;
foreach(hk, hashkeys)
{
ExprState *keyexpr = (ExprState *) lfirst(hk);
Datum keyval;
bool isNull;
/* rotate hashkey left 1 bit at each step */
hashkey = (hashkey << 1) | ((hashkey & 0x80000000) ? 1 : 0);
/*
* Get the join attribute value of the tuple
*/
keyval = ExecEvalExpr(keyexpr, econtext, &isNull);
/*
* If the attribute is NULL, and the join operator is strict, then
* this tuple cannot pass the join qual so we can reject it
* immediately (unless we're scanning the outside of an outer join, in
* which case we must not reject it). Otherwise we act like the
* hashcode of NULL is zero (this will support operators that act like
* IS NOT DISTINCT, though not any more-random behavior). We treat
* the hash support function as strict even if the operator is not.
*
* Note: currently, all hashjoinable operators must be strict since
* the hash index AM assumes that. However, it takes so little extra
* code here to allow non-strict that we may as well do it.
*/
if (isNull)
{
if (hashtable->hashStrict[i] && !keep_nulls)
{
MemoryContextSwitchTo(oldContext);
return false; /* cannot match */
}
/* else, leave hashkey unmodified, equivalent to hashcode 0 */
}
else
{
/* Compute the hash function */
uint32 hkey;
hkey = DatumGetUInt32(FunctionCall1(&hashfunctions[i], keyval));
hashkey ^= hkey;
}
i++;
}
MemoryContextSwitchTo(oldContext);
*hashvalue = hashkey;
return true;
}
/*
* ExecHashGetBucketAndBatch
* Determine the bucket number and batch number for a hash value
*
* Note: on-the-fly increases of nbatch must not change the bucket number
* for a given hash code (since we don't move tuples to different hash
* chains), and must only cause the batch number to remain the same or
* increase. Our algorithm is
* bucketno = hashvalue MOD nbuckets
* batchno = (hashvalue DIV nbuckets) MOD nbatch
* where nbuckets and nbatch are both expected to be powers of 2, so we can
* do the computations by shifting and masking. (This assumes that all hash
* functions are good about randomizing all their output bits, else we are
* likely to have very skewed bucket or batch occupancy.)
*
* nbuckets and log2_nbuckets may change while nbatch == 1 because of dynamic
* bucket count growth. Once we start batching, the value is fixed and does
* not change over the course of the join (making it possible to compute batch
* number the way we do here).
*
* nbatch is always a power of 2; we increase it only by doubling it. This
* effectively adds one more bit to the top of the batchno.
*/
void
ExecHashGetBucketAndBatch(HashJoinTable hashtable,
uint32 hashvalue,
int *bucketno,
int *batchno)
{
uint32 nbuckets = (uint32) hashtable->nbuckets;
uint32 nbatch = (uint32) hashtable->nbatch;
if (nbatch > 1)
{
/* we can do MOD by masking, DIV by shifting */
*bucketno = hashvalue & (nbuckets - 1);
*batchno = (hashvalue >> hashtable->log2_nbuckets) & (nbatch - 1);
}
else
{
*bucketno = hashvalue & (nbuckets - 1);
*batchno = 0;
}
}
/*
* ExecScanHashBucket
* scan a hash bucket for matches to the current outer tuple
*
* The current outer tuple must be stored in econtext->ecxt_outertuple.
*
* On success, the inner tuple is stored into hjstate->hj_CurTuple and
* econtext->ecxt_innertuple, using hjstate->hj_HashTupleSlot as the slot
* for the latter.
*/
bool
ExecScanHashBucket(HashJoinState *hjstate,
ExprContext *econtext)
{
ExprState *hjclauses = hjstate->hashclauses;
HashJoinTable hashtable = hjstate->hj_HashTable;
HashJoinTuple hashTuple = hjstate->hj_CurTuple;
uint32 hashvalue = hjstate->hj_CurHashValue;
/*
* hj_CurTuple is the address of the tuple last returned from the current
* bucket, or NULL if it's time to start scanning a new bucket.
*
* If the tuple hashed to a skew bucket then scan the skew bucket
* otherwise scan the standard hashtable bucket.
*/
if (hashTuple != NULL)
hashTuple = hashTuple->next.unshared;
else if (hjstate->hj_CurSkewBucketNo != INVALID_SKEW_BUCKET_NO)
hashTuple = hashtable->skewBucket[hjstate->hj_CurSkewBucketNo]->tuples;
else
hashTuple = hashtable->buckets.unshared[hjstate->hj_CurBucketNo];
while (hashTuple != NULL)
{
if (hashTuple->hashvalue == hashvalue)
{
TupleTableSlot *inntuple;
/* insert hashtable's tuple into exec slot so ExecQual sees it */
inntuple = ExecStoreMinimalTuple(HJTUPLE_MINTUPLE(hashTuple),
hjstate->hj_HashTupleSlot,
false); /* do not pfree */
econtext->ecxt_innertuple = inntuple;
/* reset temp memory each time to avoid leaks from qual expr */
ResetExprContext(econtext);
if (ExecQual(hjclauses, econtext))
{
hjstate->hj_CurTuple = hashTuple;
return true;
}
}
hashTuple = hashTuple->next.unshared;
}
/*
* no match
*/
return false;
}
/*
* ExecParallelScanHashBucket
* scan a hash bucket for matches to the current outer tuple
*
* The current outer tuple must be stored in econtext->ecxt_outertuple.
*
* On success, the inner tuple is stored into hjstate->hj_CurTuple and
* econtext->ecxt_innertuple, using hjstate->hj_HashTupleSlot as the slot
* for the latter.
*/
bool
ExecParallelScanHashBucket(HashJoinState *hjstate,
ExprContext *econtext)
{
ExprState *hjclauses = hjstate->hashclauses;
HashJoinTable hashtable = hjstate->hj_HashTable;
HashJoinTuple hashTuple = hjstate->hj_CurTuple;
uint32 hashvalue = hjstate->hj_CurHashValue;
/*
* hj_CurTuple is the address of the tuple last returned from the current
* bucket, or NULL if it's time to start scanning a new bucket.
*/
if (hashTuple != NULL)
hashTuple = ExecParallelHashNextTuple(hashtable, hashTuple);
else
hashTuple = ExecParallelHashFirstTuple(hashtable,
hjstate->hj_CurBucketNo);
while (hashTuple != NULL)
{
if (hashTuple->hashvalue == hashvalue)
{
TupleTableSlot *inntuple;
/* insert hashtable's tuple into exec slot so ExecQual sees it */
inntuple = ExecStoreMinimalTuple(HJTUPLE_MINTUPLE(hashTuple),
hjstate->hj_HashTupleSlot,
false); /* do not pfree */
econtext->ecxt_innertuple = inntuple;
/* reset temp memory each time to avoid leaks from qual expr */
ResetExprContext(econtext);
if (ExecQual(hjclauses, econtext))
{
hjstate->hj_CurTuple = hashTuple;
return true;
}
}
hashTuple = ExecParallelHashNextTuple(hashtable, hashTuple);
}
/*
* no match
*/
return false;
}
/*
* ExecPrepHashTableForUnmatched
* set up for a series of ExecScanHashTableForUnmatched calls
*/
void
ExecPrepHashTableForUnmatched(HashJoinState *hjstate)
{
/*----------
* During this scan we use the HashJoinState fields as follows:
*
* hj_CurBucketNo: next regular bucket to scan
* hj_CurSkewBucketNo: next skew bucket (an index into skewBucketNums)
* hj_CurTuple: last tuple returned, or NULL to start next bucket
*----------
*/
hjstate->hj_CurBucketNo = 0;
hjstate->hj_CurSkewBucketNo = 0;
hjstate->hj_CurTuple = NULL;
}
/*
* ExecScanHashTableForUnmatched
* scan the hash table for unmatched inner tuples
*
* On success, the inner tuple is stored into hjstate->hj_CurTuple and
* econtext->ecxt_innertuple, using hjstate->hj_HashTupleSlot as the slot
* for the latter.
*/
bool
ExecScanHashTableForUnmatched(HashJoinState *hjstate, ExprContext *econtext)
{
HashJoinTable hashtable = hjstate->hj_HashTable;
HashJoinTuple hashTuple = hjstate->hj_CurTuple;
for (;;)
{
/*
* hj_CurTuple is the address of the tuple last returned from the
* current bucket, or NULL if it's time to start scanning a new
* bucket.
*/
if (hashTuple != NULL)
hashTuple = hashTuple->next.unshared;
else if (hjstate->hj_CurBucketNo < hashtable->nbuckets)
{
hashTuple = hashtable->buckets.unshared[hjstate->hj_CurBucketNo];
hjstate->hj_CurBucketNo++;
}
else if (hjstate->hj_CurSkewBucketNo < hashtable->nSkewBuckets)
{
int j = hashtable->skewBucketNums[hjstate->hj_CurSkewBucketNo];
hashTuple = hashtable->skewBucket[j]->tuples;
hjstate->hj_CurSkewBucketNo++;
}
else
break; /* finished all buckets */
while (hashTuple != NULL)
{
if (!HeapTupleHeaderHasMatch(HJTUPLE_MINTUPLE(hashTuple)))
{
TupleTableSlot *inntuple;
/* insert hashtable's tuple into exec slot */
inntuple = ExecStoreMinimalTuple(HJTUPLE_MINTUPLE(hashTuple),
hjstate->hj_HashTupleSlot,
false); /* do not pfree */
econtext->ecxt_innertuple = inntuple;
/*
* Reset temp memory each time; although this function doesn't
* do any qual eval, the caller will, so let's keep it
* parallel to ExecScanHashBucket.
*/
ResetExprContext(econtext);
hjstate->hj_CurTuple = hashTuple;
return true;
}
hashTuple = hashTuple->next.unshared;
}
/* allow this loop to be cancellable */
CHECK_FOR_INTERRUPTS();
}
/*
* no more unmatched tuples
*/
return false;
}
/*
* ExecHashTableReset
*
* reset hash table header for new batch
*/
void
ExecHashTableReset(HashJoinTable hashtable)
{
MemoryContext oldcxt;
int nbuckets = hashtable->nbuckets;
/*
* Release all the hash buckets and tuples acquired in the prior pass, and
* reinitialize the context for a new pass.
*/
MemoryContextReset(hashtable->batchCxt);
oldcxt = MemoryContextSwitchTo(hashtable->batchCxt);
/* Reallocate and reinitialize the hash bucket headers. */
hashtable->buckets.unshared = (HashJoinTuple *)
palloc0(nbuckets * sizeof(HashJoinTuple));
hashtable->spaceUsed = 0;
MemoryContextSwitchTo(oldcxt);
/* Forget the chunks (the memory was freed by the context reset above). */
hashtable->chunks = NULL;
}
/*
* ExecHashTableResetMatchFlags
* Clear all the HeapTupleHeaderHasMatch flags in the table
*/
void
ExecHashTableResetMatchFlags(HashJoinTable hashtable)
{
HashJoinTuple tuple;
int i;
/* Reset all flags in the main table ... */
for (i = 0; i < hashtable->nbuckets; i++)
{
for (tuple = hashtable->buckets.unshared[i]; tuple != NULL;
tuple = tuple->next.unshared)
HeapTupleHeaderClearMatch(HJTUPLE_MINTUPLE(tuple));
}
/* ... and the same for the skew buckets, if any */
for (i = 0; i < hashtable->nSkewBuckets; i++)
{
int j = hashtable->skewBucketNums[i];
HashSkewBucket *skewBucket = hashtable->skewBucket[j];
for (tuple = skewBucket->tuples; tuple != NULL; tuple = tuple->next.unshared)
HeapTupleHeaderClearMatch(HJTUPLE_MINTUPLE(tuple));
}
}
void
ExecReScanHash(HashState *node)
{
/*
* if chgParam of subnode is not null then plan will be re-scanned by
* first ExecProcNode.
*/
if (node->ps.lefttree->chgParam == NULL)
ExecReScan(node->ps.lefttree);
}
/*
* ExecHashBuildSkewHash
*
* Set up for skew optimization if we can identify the most common values
* (MCVs) of the outer relation's join key. We make a skew hash bucket
* for the hash value of each MCV, up to the number of slots allowed
* based on available memory.
*/
static void
ExecHashBuildSkewHash(HashJoinTable hashtable, Hash *node, int mcvsToUse)
{
HeapTupleData *statsTuple;
AttStatsSlot sslot;
/* Do nothing if planner didn't identify the outer relation's join key */
if (!OidIsValid(node->skewTable))
return;
/* Also, do nothing if we don't have room for at least one skew bucket */
if (mcvsToUse <= 0)
return;
/*
* Try to find the MCV statistics for the outer relation's join key.
*/
statsTuple = SearchSysCache3(STATRELATTINH,
ObjectIdGetDatum(node->skewTable),
Int16GetDatum(node->skewColumn),
BoolGetDatum(node->skewInherit));
if (!HeapTupleIsValid(statsTuple))
return;
if (get_attstatsslot(&sslot, statsTuple,
STATISTIC_KIND_MCV, InvalidOid,
ATTSTATSSLOT_VALUES | ATTSTATSSLOT_NUMBERS))
{
double frac;
int nbuckets;
FmgrInfo *hashfunctions;
int i;
if (mcvsToUse > sslot.nvalues)
mcvsToUse = sslot.nvalues;
/*
* Calculate the expected fraction of outer relation that will
* participate in the skew optimization. If this isn't at least
* SKEW_MIN_OUTER_FRACTION, don't use skew optimization.
*/
frac = 0;
for (i = 0; i < mcvsToUse; i++)
frac += sslot.numbers[i];
if (frac < SKEW_MIN_OUTER_FRACTION)
{
free_attstatsslot(&sslot);
ReleaseSysCache(statsTuple);
return;
}
/*
* Okay, set up the skew hashtable.
*
* skewBucket[] is an open addressing hashtable with a power of 2 size
* that is greater than the number of MCV values. (This ensures there
* will be at least one null entry, so searches will always
* terminate.)
*
* Note: this code could fail if mcvsToUse exceeds INT_MAX/8 or
* MaxAllocSize/sizeof(void *)/8, but that is not currently possible
* since we limit pg_statistic entries to much less than that.
*/
nbuckets = 2;
while (nbuckets <= mcvsToUse)
nbuckets <<= 1;
/* use two more bits just to help avoid collisions */
nbuckets <<= 2;
hashtable->skewEnabled = true;
hashtable->skewBucketLen = nbuckets;
/*
* We allocate the bucket memory in the hashtable's batch context. It
* is only needed during the first batch, and this ensures it will be
* automatically removed once the first batch is done.
*/
hashtable->skewBucket = (HashSkewBucket **)
MemoryContextAllocZero(hashtable->batchCxt,
nbuckets * sizeof(HashSkewBucket *));
hashtable->skewBucketNums = (int *)
MemoryContextAllocZero(hashtable->batchCxt,
mcvsToUse * sizeof(int));
hashtable->spaceUsed += nbuckets * sizeof(HashSkewBucket *)
+ mcvsToUse * sizeof(int);
hashtable->spaceUsedSkew += nbuckets * sizeof(HashSkewBucket *)
+ mcvsToUse * sizeof(int);
if (hashtable->spaceUsed > hashtable->spacePeak)
hashtable->spacePeak = hashtable->spaceUsed;
/*
* Create a skew bucket for each MCV hash value.
*
* Note: it is very important that we create the buckets in order of
* decreasing MCV frequency. If we have to remove some buckets, they
* must be removed in reverse order of creation (see notes in
* ExecHashRemoveNextSkewBucket) and we want the least common MCVs to
* be removed first.
*/
hashfunctions = hashtable->outer_hashfunctions;
for (i = 0; i < mcvsToUse; i++)
{
uint32 hashvalue;
int bucket;
hashvalue = DatumGetUInt32(FunctionCall1(&hashfunctions[0],
sslot.values[i]));
/*
* While we have not hit a hole in the hashtable and have not hit
* the desired bucket, we have collided with some previous hash
* value, so try the next bucket location. NB: this code must
* match ExecHashGetSkewBucket.
*/
bucket = hashvalue & (nbuckets - 1);
while (hashtable->skewBucket[bucket] != NULL &&
hashtable->skewBucket[bucket]->hashvalue != hashvalue)
bucket = (bucket + 1) & (nbuckets - 1);
/*
* If we found an existing bucket with the same hashvalue, leave
* it alone. It's okay for two MCVs to share a hashvalue.
*/
if (hashtable->skewBucket[bucket] != NULL)
continue;
/* Okay, create a new skew bucket for this hashvalue. */
hashtable->skewBucket[bucket] = (HashSkewBucket *)
MemoryContextAlloc(hashtable->batchCxt,
sizeof(HashSkewBucket));
hashtable->skewBucket[bucket]->hashvalue = hashvalue;
hashtable->skewBucket[bucket]->tuples = NULL;
hashtable->skewBucketNums[hashtable->nSkewBuckets] = bucket;
hashtable->nSkewBuckets++;
hashtable->spaceUsed += SKEW_BUCKET_OVERHEAD;
hashtable->spaceUsedSkew += SKEW_BUCKET_OVERHEAD;
if (hashtable->spaceUsed > hashtable->spacePeak)
hashtable->spacePeak = hashtable->spaceUsed;
}
free_attstatsslot(&sslot);
}
ReleaseSysCache(statsTuple);
}
/*
* ExecHashGetSkewBucket
*
* Returns the index of the skew bucket for this hashvalue,
* or INVALID_SKEW_BUCKET_NO if the hashvalue is not
* associated with any active skew bucket.
*/
int
ExecHashGetSkewBucket(HashJoinTable hashtable, uint32 hashvalue)
{
int bucket;
/*
* Always return INVALID_SKEW_BUCKET_NO if not doing skew optimization (in
* particular, this happens after the initial batch is done).
*/
if (!hashtable->skewEnabled)
return INVALID_SKEW_BUCKET_NO;
/*
* Since skewBucketLen is a power of 2, we can do a modulo by ANDing.
*/
bucket = hashvalue & (hashtable->skewBucketLen - 1);
/*
* While we have not hit a hole in the hashtable and have not hit the
* desired bucket, we have collided with some other hash value, so try the
* next bucket location.
*/
while (hashtable->skewBucket[bucket] != NULL &&
hashtable->skewBucket[bucket]->hashvalue != hashvalue)
bucket = (bucket + 1) & (hashtable->skewBucketLen - 1);
/*
* Found the desired bucket?
*/
if (hashtable->skewBucket[bucket] != NULL)
return bucket;
/*
* There must not be any hashtable entry for this hash value.
*/
return INVALID_SKEW_BUCKET_NO;
}
/*
* ExecHashSkewTableInsert
*
* Insert a tuple into the skew hashtable.
*
* This should generally match up with the current-batch case in
* ExecHashTableInsert.
*/
static void
ExecHashSkewTableInsert(HashJoinTable hashtable,
TupleTableSlot *slot,
uint32 hashvalue,
int bucketNumber)
{
MinimalTuple tuple = ExecFetchSlotMinimalTuple(slot);
HashJoinTuple hashTuple;
int hashTupleSize;
/* Create the HashJoinTuple */
hashTupleSize = HJTUPLE_OVERHEAD + tuple->t_len;
hashTuple = (HashJoinTuple) MemoryContextAlloc(hashtable->batchCxt,
hashTupleSize);
hashTuple->hashvalue = hashvalue;
memcpy(HJTUPLE_MINTUPLE(hashTuple), tuple, tuple->t_len);
HeapTupleHeaderClearMatch(HJTUPLE_MINTUPLE(hashTuple));
/* Push it onto the front of the skew bucket's list */
hashTuple->next.unshared = hashtable->skewBucket[bucketNumber]->tuples;
hashtable->skewBucket[bucketNumber]->tuples = hashTuple;
Assert(hashTuple != hashTuple->next.unshared);
/* Account for space used, and back off if we've used too much */
hashtable->spaceUsed += hashTupleSize;
hashtable->spaceUsedSkew += hashTupleSize;
if (hashtable->spaceUsed > hashtable->spacePeak)
hashtable->spacePeak = hashtable->spaceUsed;
while (hashtable->spaceUsedSkew > hashtable->spaceAllowedSkew)
ExecHashRemoveNextSkewBucket(hashtable);
/* Check we are not over the total spaceAllowed, either */
if (hashtable->spaceUsed > hashtable->spaceAllowed)
ExecHashIncreaseNumBatches(hashtable);
}
/*
* ExecHashRemoveNextSkewBucket
*
* Remove the least valuable skew bucket by pushing its tuples into
* the main hash table.
*/
static void
ExecHashRemoveNextSkewBucket(HashJoinTable hashtable)
{
int bucketToRemove;
HashSkewBucket *bucket;
uint32 hashvalue;
int bucketno;
int batchno;
HashJoinTuple hashTuple;
/* Locate the bucket to remove */
bucketToRemove = hashtable->skewBucketNums[hashtable->nSkewBuckets - 1];
bucket = hashtable->skewBucket[bucketToRemove];
/*
* Calculate which bucket and batch the tuples belong to in the main
* hashtable. They all have the same hash value, so it's the same for all
* of them. Also note that it's not possible for nbatch to increase while
* we are processing the tuples.
*/
hashvalue = bucket->hashvalue;
ExecHashGetBucketAndBatch(hashtable, hashvalue, &bucketno, &batchno);
/* Process all tuples in the bucket */
hashTuple = bucket->tuples;
while (hashTuple != NULL)
{
HashJoinTuple nextHashTuple = hashTuple->next.unshared;
MinimalTuple tuple;
Size tupleSize;
/*
* This code must agree with ExecHashTableInsert. We do not use
* ExecHashTableInsert directly as ExecHashTableInsert expects a
* TupleTableSlot while we already have HashJoinTuples.
*/
tuple = HJTUPLE_MINTUPLE(hashTuple);
tupleSize = HJTUPLE_OVERHEAD + tuple->t_len;
/* Decide whether to put the tuple in the hash table or a temp file */
if (batchno == hashtable->curbatch)
{
/* Move the tuple to the main hash table */
HashJoinTuple copyTuple;
/*
* We must copy the tuple into the dense storage, else it will not
* be found by, eg, ExecHashIncreaseNumBatches.
*/
copyTuple = (HashJoinTuple) dense_alloc(hashtable, tupleSize);
memcpy(copyTuple, hashTuple, tupleSize);
pfree(hashTuple);
copyTuple->next.unshared = hashtable->buckets.unshared[bucketno];
hashtable->buckets.unshared[bucketno] = copyTuple;
/* We have reduced skew space, but overall space doesn't change */
hashtable->spaceUsedSkew -= tupleSize;
}
else
{
/* Put the tuple into a temp file for later batches */
Assert(batchno > hashtable->curbatch);
ExecHashJoinSaveTuple(tuple, hashvalue,
&hashtable->innerBatchFile[batchno]);
pfree(hashTuple);
hashtable->spaceUsed -= tupleSize;
hashtable->spaceUsedSkew -= tupleSize;
}
hashTuple = nextHashTuple;
/* allow this loop to be cancellable */
CHECK_FOR_INTERRUPTS();
}
/*
* Free the bucket struct itself and reset the hashtable entry to NULL.
*
* NOTE: this is not nearly as simple as it looks on the surface, because
* of the possibility of collisions in the hashtable. Suppose that hash
* values A and B collide at a particular hashtable entry, and that A was
* entered first so B gets shifted to a different table entry. If we were
* to remove A first then ExecHashGetSkewBucket would mistakenly start
* reporting that B is not in the hashtable, because it would hit the NULL
* before finding B. However, we always remove entries in the reverse
* order of creation, so this failure cannot happen.
*/
hashtable->skewBucket[bucketToRemove] = NULL;
hashtable->nSkewBuckets--;
pfree(bucket);
hashtable->spaceUsed -= SKEW_BUCKET_OVERHEAD;
hashtable->spaceUsedSkew -= SKEW_BUCKET_OVERHEAD;
/*
* If we have removed all skew buckets then give up on skew optimization.
* Release the arrays since they aren't useful any more.
*/
if (hashtable->nSkewBuckets == 0)
{
hashtable->skewEnabled = false;
pfree(hashtable->skewBucket);
pfree(hashtable->skewBucketNums);
hashtable->skewBucket = NULL;
hashtable->skewBucketNums = NULL;
hashtable->spaceUsed -= hashtable->spaceUsedSkew;
hashtable->spaceUsedSkew = 0;
}
}
/*
* Reserve space in the DSM segment for instrumentation data.
*/
void
ExecHashEstimate(HashState *node, ParallelContext *pcxt)
{
size_t size;
size = mul_size(pcxt->nworkers, sizeof(HashInstrumentation));
size = add_size(size, offsetof(SharedHashInfo, hinstrument));
shm_toc_estimate_chunk(&pcxt->estimator, size);
shm_toc_estimate_keys(&pcxt->estimator, 1);
}
/*
* Set up a space in the DSM for all workers to record instrumentation data
* about their hash table.
*/
void
ExecHashInitializeDSM(HashState *node, ParallelContext *pcxt)
{
size_t size;
size = offsetof(SharedHashInfo, hinstrument) +
pcxt->nworkers * sizeof(HashInstrumentation);
node->shared_info = (SharedHashInfo *) shm_toc_allocate(pcxt->toc, size);
memset(node->shared_info, 0, size);
node->shared_info->num_workers = pcxt->nworkers;
shm_toc_insert(pcxt->toc, node->ps.plan->plan_node_id,
node->shared_info);
}
/*
* Locate the DSM space for hash table instrumentation data that we'll write
* to at shutdown time.
*/
void
ExecHashInitializeWorker(HashState *node, ParallelWorkerContext *pwcxt)
{
SharedHashInfo *shared_info;
shared_info = (SharedHashInfo *)
shm_toc_lookup(pwcxt->toc, node->ps.plan->plan_node_id, true);
node->hinstrument = &shared_info->hinstrument[ParallelWorkerNumber];
}
/*
* Copy instrumentation data from this worker's hash table (if it built one)
* to DSM memory so the leader can retrieve it. This must be done in an
* ExecShutdownHash() rather than ExecEndHash() because the latter runs after
* we've detached from the DSM segment.
*/
void
ExecShutdownHash(HashState *node)
{
if (node->hinstrument && node->hashtable)
ExecHashGetInstrumentation(node->hinstrument, node->hashtable);
}
/*
* Retrieve instrumentation data from workers before the DSM segment is
* detached, so that EXPLAIN can access it.
*/
void
ExecHashRetrieveInstrumentation(HashState *node)
{
SharedHashInfo *shared_info = node->shared_info;
size_t size;
/* Replace node->shared_info with a copy in backend-local memory. */
size = offsetof(SharedHashInfo, hinstrument) +
shared_info->num_workers * sizeof(HashInstrumentation);
node->shared_info = palloc(size);
memcpy(node->shared_info, shared_info, size);
}
/*
* Copy the instrumentation data from 'hashtable' into a HashInstrumentation
* struct.
*/
void
ExecHashGetInstrumentation(HashInstrumentation *instrument,
HashJoinTable hashtable)
{
instrument->nbuckets = hashtable->nbuckets;
instrument->nbuckets_original = hashtable->nbuckets_original;
instrument->nbatch = hashtable->nbatch;
instrument->nbatch_original = hashtable->nbatch_original;
instrument->space_peak = hashtable->spacePeak;
}
/*
* Allocate 'size' bytes from the currently active HashMemoryChunk
*/
static void *
dense_alloc(HashJoinTable hashtable, Size size)
{
HashMemoryChunk newChunk;
char *ptr;
/* just in case the size is not already aligned properly */
size = MAXALIGN(size);
/*
* If tuple size is larger than of 1/4 of chunk size, allocate a separate
* chunk.
*/
if (size > HASH_CHUNK_THRESHOLD)
{
/* allocate new chunk and put it at the beginning of the list */
newChunk = (HashMemoryChunk) MemoryContextAlloc(hashtable->batchCxt,
offsetof(HashMemoryChunkData, data) + size);
newChunk->maxlen = size;
newChunk->used = 0;
newChunk->ntuples = 0;
/*
* Add this chunk to the list after the first existing chunk, so that
* we don't lose the remaining space in the "current" chunk.
*/
if (hashtable->chunks != NULL)
{
newChunk->next = hashtable->chunks->next;
hashtable->chunks->next.unshared = newChunk;
}
else
{
newChunk->next.unshared = hashtable->chunks;
hashtable->chunks = newChunk;
}
newChunk->used += size;
newChunk->ntuples += 1;
return newChunk->data;
}
/*
* See if we have enough space for it in the current chunk (if any). If
* not, allocate a fresh chunk.
*/
if ((hashtable->chunks == NULL) ||
(hashtable->chunks->maxlen - hashtable->chunks->used) < size)
{
/* allocate new chunk and put it at the beginning of the list */
newChunk = (HashMemoryChunk) MemoryContextAlloc(hashtable->batchCxt,
offsetof(HashMemoryChunkData, data) + HASH_CHUNK_SIZE);
newChunk->maxlen = HASH_CHUNK_SIZE;
newChunk->used = size;
newChunk->ntuples = 1;
newChunk->next.unshared = hashtable->chunks;
hashtable->chunks = newChunk;
return newChunk->data;
}
/* There is enough space in the current chunk, let's add the tuple */
ptr = hashtable->chunks->data + hashtable->chunks->used;
hashtable->chunks->used += size;
hashtable->chunks->ntuples += 1;
/* return pointer to the start of the tuple memory */
return ptr;
}
/*
* Allocate space for a tuple in shared dense storage. This is equivalent to
* dense_alloc but for Parallel Hash using shared memory.
*
* While loading a tuple into shared memory, we might run out of memory and
* decide to repartition, or determine that the load factor is too high and
* decide to expand the bucket array, or discover that another participant has
* commanded us to help do that. Return NULL if number of buckets or batches
* has changed, indicating that the caller must retry (considering the
* possibility that the tuple no longer belongs in the same batch).
*/
static HashJoinTuple
ExecParallelHashTupleAlloc(HashJoinTable hashtable, size_t size,
dsa_pointer *shared)
{
ParallelHashJoinState *pstate = hashtable->parallel_state;
dsa_pointer chunk_shared;
HashMemoryChunk chunk;
Size chunk_size;
HashJoinTuple result;
int curbatch = hashtable->curbatch;
size = MAXALIGN(size);
/*
* Fast path: if there is enough space in this backend's current chunk,
* then we can allocate without any locking.
*/
chunk = hashtable->current_chunk;
if (chunk != NULL &&
size < HASH_CHUNK_THRESHOLD &&
chunk->maxlen - chunk->used >= size)
{
chunk_shared = hashtable->current_chunk_shared;
Assert(chunk == dsa_get_address(hashtable->area, chunk_shared));
*shared = chunk_shared + HASH_CHUNK_HEADER_SIZE + chunk->used;
result = (HashJoinTuple) (chunk->data + chunk->used);
chunk->used += size;
Assert(chunk->used <= chunk->maxlen);
Assert(result == dsa_get_address(hashtable->area, *shared));
return result;
}
/* Slow path: try to allocate a new chunk. */
LWLockAcquire(&pstate->lock, LW_EXCLUSIVE);
/*
* Check if we need to help increase the number of buckets or batches.
*/
if (pstate->growth == PHJ_GROWTH_NEED_MORE_BATCHES ||
pstate->growth == PHJ_GROWTH_NEED_MORE_BUCKETS)
{
ParallelHashGrowth growth = pstate->growth;
hashtable->current_chunk = NULL;
LWLockRelease(&pstate->lock);
/* Another participant has commanded us to help grow. */
if (growth == PHJ_GROWTH_NEED_MORE_BATCHES)
ExecParallelHashIncreaseNumBatches(hashtable);
else if (growth == PHJ_GROWTH_NEED_MORE_BUCKETS)
ExecParallelHashIncreaseNumBuckets(hashtable);
/* The caller must retry. */
return NULL;
}
/* Oversized tuples get their own chunk. */
if (size > HASH_CHUNK_THRESHOLD)
chunk_size = size + HASH_CHUNK_HEADER_SIZE;
else
chunk_size = HASH_CHUNK_SIZE;
/* Check if it's time to grow batches or buckets. */
if (pstate->growth != PHJ_GROWTH_DISABLED)
{
Assert(curbatch == 0);
Assert(BarrierPhase(&pstate->build_barrier) == PHJ_BUILD_HASHING_INNER);
/*
* Check if our space limit would be exceeded. To avoid choking on
* very large tuples or very low work_mem setting, we'll always allow
* each backend to allocate at least one chunk.
*/
if (hashtable->batches[0].at_least_one_chunk &&
hashtable->batches[0].shared->size +
chunk_size > pstate->space_allowed)
{
pstate->growth = PHJ_GROWTH_NEED_MORE_BATCHES;
hashtable->batches[0].shared->space_exhausted = true;
LWLockRelease(&pstate->lock);
return NULL;
}
/* Check if our load factor limit would be exceeded. */
if (hashtable->nbatch == 1)
{
hashtable->batches[0].shared->ntuples += hashtable->batches[0].ntuples;
hashtable->batches[0].ntuples = 0;
if (hashtable->batches[0].shared->ntuples + 1 >
hashtable->nbuckets * NTUP_PER_BUCKET &&
hashtable->nbuckets < (INT_MAX / 2))
{
pstate->growth = PHJ_GROWTH_NEED_MORE_BUCKETS;
LWLockRelease(&pstate->lock);
return NULL;
}
}
}
/* We are cleared to allocate a new chunk. */
chunk_shared = dsa_allocate(hashtable->area, chunk_size);
hashtable->batches[curbatch].shared->size += chunk_size;
hashtable->batches[curbatch].at_least_one_chunk = true;
/* Set up the chunk. */
chunk = (HashMemoryChunk) dsa_get_address(hashtable->area, chunk_shared);
*shared = chunk_shared + HASH_CHUNK_HEADER_SIZE;
chunk->maxlen = chunk_size - HASH_CHUNK_HEADER_SIZE;
chunk->used = size;
/*
* Push it onto the list of chunks, so that it can be found if we need to
* increase the number of buckets or batches (batch 0 only) and later for
* freeing the memory (all batches).
*/
chunk->next.shared = hashtable->batches[curbatch].shared->chunks;
hashtable->batches[curbatch].shared->chunks = chunk_shared;
if (size <= HASH_CHUNK_THRESHOLD)
{
/*
* Make this the current chunk so that we can use the fast path to
* fill the rest of it up in future calls.
*/
hashtable->current_chunk = chunk;
hashtable->current_chunk_shared = chunk_shared;
}
LWLockRelease(&pstate->lock);
Assert(chunk->data == dsa_get_address(hashtable->area, *shared));
result = (HashJoinTuple) chunk->data;
return result;
}
/*
* One backend needs to set up the shared batch state including tuplestores.
* Other backends will ensure they have correctly configured accessors by
* called ExecParallelHashEnsureBatchAccessors().
*/
static void
ExecParallelHashJoinSetUpBatches(HashJoinTable hashtable, int nbatch)
{
ParallelHashJoinState *pstate = hashtable->parallel_state;
ParallelHashJoinBatch *batches;
MemoryContext oldcxt;
int i;
Assert(hashtable->batches == NULL);
/* Allocate space. */
pstate->batches =
dsa_allocate0(hashtable->area,
EstimateParallelHashJoinBatch(hashtable) * nbatch);
pstate->nbatch = nbatch;
batches = dsa_get_address(hashtable->area, pstate->batches);
/* Use hash join memory context. */
oldcxt = MemoryContextSwitchTo(hashtable->hashCxt);
/* Allocate this backend's accessor array. */
hashtable->nbatch = nbatch;
hashtable->batches = (ParallelHashJoinBatchAccessor *)
palloc0(sizeof(ParallelHashJoinBatchAccessor) * hashtable->nbatch);
/* Set up the shared state, tuplestores and backend-local accessors. */
for (i = 0; i < hashtable->nbatch; ++i)
{
ParallelHashJoinBatchAccessor *accessor = &hashtable->batches[i];
ParallelHashJoinBatch *shared = NthParallelHashJoinBatch(batches, i);
char name[MAXPGPATH];
/*
* All members of shared were zero-initialized. We just need to set
* up the Barrier.
*/
BarrierInit(&shared->batch_barrier, 0);
if (i == 0)
{
/* Batch 0 doesn't need to be loaded. */
BarrierAttach(&shared->batch_barrier);
while (BarrierPhase(&shared->batch_barrier) < PHJ_BATCH_PROBING)
BarrierArriveAndWait(&shared->batch_barrier, 0);
BarrierDetach(&shared->batch_barrier);
}
/* Initialize accessor state. All members were zero-initialized. */
accessor->shared = shared;
/* Initialize the shared tuplestores. */
snprintf(name, sizeof(name), "i%dof%d", i, hashtable->nbatch);
accessor->inner_tuples =
sts_initialize(ParallelHashJoinBatchInner(shared),
pstate->nparticipants,
ParallelWorkerNumber + 1,
sizeof(uint32),
SHARED_TUPLESTORE_SINGLE_PASS,
&pstate->fileset,
name);
snprintf(name, sizeof(name), "o%dof%d", i, hashtable->nbatch);
accessor->outer_tuples =
sts_initialize(ParallelHashJoinBatchOuter(shared,
pstate->nparticipants),
pstate->nparticipants,
ParallelWorkerNumber + 1,
sizeof(uint32),
SHARED_TUPLESTORE_SINGLE_PASS,
&pstate->fileset,
name);
}
MemoryContextSwitchTo(oldcxt);
}
/*
* Free the current set of ParallelHashJoinBatchAccessor objects.
*/
static void
ExecParallelHashCloseBatchAccessors(HashJoinTable hashtable)
{
int i;
for (i = 0; i < hashtable->nbatch; ++i)
{
/* Make sure no files are left open. */
sts_end_write(hashtable->batches[i].inner_tuples);
sts_end_write(hashtable->batches[i].outer_tuples);
sts_end_parallel_scan(hashtable->batches[i].inner_tuples);
sts_end_parallel_scan(hashtable->batches[i].outer_tuples);
}
pfree(hashtable->batches);
hashtable->batches = NULL;
}
/*
* Make sure this backend has up-to-date accessors for the current set of
* batches.
*/
static void
ExecParallelHashEnsureBatchAccessors(HashJoinTable hashtable)
{
ParallelHashJoinState *pstate = hashtable->parallel_state;
ParallelHashJoinBatch *batches;
MemoryContext oldcxt;
int i;
if (hashtable->batches != NULL)
{
if (hashtable->nbatch == pstate->nbatch)
return;
ExecParallelHashCloseBatchAccessors(hashtable);
}
/*
* It's possible for a backend to start up very late so that the whole
* join is finished and the shm state for tracking batches has already
* been freed by ExecHashTableDetach(). In that case we'll just leave
* hashtable->batches as NULL so that ExecParallelHashJoinNewBatch() gives
* up early.
*/
if (!DsaPointerIsValid(pstate->batches))
return;
/* Use hash join memory context. */
oldcxt = MemoryContextSwitchTo(hashtable->hashCxt);
/* Allocate this backend's accessor array. */
hashtable->nbatch = pstate->nbatch;
hashtable->batches = (ParallelHashJoinBatchAccessor *)
palloc0(sizeof(ParallelHashJoinBatchAccessor) * hashtable->nbatch);
/* Find the base of the pseudo-array of ParallelHashJoinBatch objects. */
batches = (ParallelHashJoinBatch *)
dsa_get_address(hashtable->area, pstate->batches);
/* Set up the accessor array and attach to the tuplestores. */
for (i = 0; i < hashtable->nbatch; ++i)
{
ParallelHashJoinBatchAccessor *accessor = &hashtable->batches[i];
ParallelHashJoinBatch *shared = NthParallelHashJoinBatch(batches, i);
accessor->shared = shared;
accessor->preallocated = 0;
accessor->done = false;
accessor->inner_tuples =
sts_attach(ParallelHashJoinBatchInner(shared),
ParallelWorkerNumber + 1,
&pstate->fileset);
accessor->outer_tuples =
sts_attach(ParallelHashJoinBatchOuter(shared,
pstate->nparticipants),
ParallelWorkerNumber + 1,
&pstate->fileset);
}
MemoryContextSwitchTo(oldcxt);
}
/*
* Allocate an empty shared memory hash table for a given batch.
*/
void
ExecParallelHashTableAlloc(HashJoinTable hashtable, int batchno)
{
ParallelHashJoinBatch *batch = hashtable->batches[batchno].shared;
dsa_pointer_atomic *buckets;
int nbuckets = hashtable->parallel_state->nbuckets;
int i;
batch->buckets =
dsa_allocate(hashtable->area, sizeof(dsa_pointer_atomic) * nbuckets);
buckets = (dsa_pointer_atomic *)
dsa_get_address(hashtable->area, batch->buckets);
for (i = 0; i < nbuckets; ++i)
dsa_pointer_atomic_init(&buckets[i], InvalidDsaPointer);
}
/*
* If we are currently attached to a shared hash join batch, detach. If we
* are last to detach, clean up.
*/
void
ExecHashTableDetachBatch(HashJoinTable hashtable)
{
if (hashtable->parallel_state != NULL &&
hashtable->curbatch >= 0)
{
int curbatch = hashtable->curbatch;
ParallelHashJoinBatch *batch = hashtable->batches[curbatch].shared;
/* Make sure any temporary files are closed. */
sts_end_parallel_scan(hashtable->batches[curbatch].inner_tuples);
sts_end_parallel_scan(hashtable->batches[curbatch].outer_tuples);
/* Detach from the batch we were last working on. */
if (BarrierArriveAndDetach(&batch->batch_barrier))
{
/*
* Technically we shouldn't access the barrier because we're no
* longer attached, but since there is no way it's moving after
* this point it seems safe to make the following assertion.
*/
Assert(BarrierPhase(&batch->batch_barrier) == PHJ_BATCH_DONE);
/* Free shared chunks and buckets. */
while (DsaPointerIsValid(batch->chunks))
{
HashMemoryChunk chunk =
dsa_get_address(hashtable->area, batch->chunks);
dsa_pointer next = chunk->next.shared;
dsa_free(hashtable->area, batch->chunks);
batch->chunks = next;
}
if (DsaPointerIsValid(batch->buckets))
{
dsa_free(hashtable->area, batch->buckets);
batch->buckets = InvalidDsaPointer;
}
}
ExecParallelHashUpdateSpacePeak(hashtable, curbatch);
/* Remember that we are not attached to a batch. */
hashtable->curbatch = -1;
}
}
/*
* Detach from all shared resources. If we are last to detach, clean up.
*/
void
ExecHashTableDetach(HashJoinTable hashtable)
{
if (hashtable->parallel_state)
{
ParallelHashJoinState *pstate = hashtable->parallel_state;
int i;
/* Make sure any temporary files are closed. */
if (hashtable->batches)
{
for (i = 0; i < hashtable->nbatch; ++i)
{
sts_end_write(hashtable->batches[i].inner_tuples);
sts_end_write(hashtable->batches[i].outer_tuples);
sts_end_parallel_scan(hashtable->batches[i].inner_tuples);
sts_end_parallel_scan(hashtable->batches[i].outer_tuples);
}
}
/* If we're last to detach, clean up shared memory. */
if (BarrierDetach(&pstate->build_barrier))
{
if (DsaPointerIsValid(pstate->batches))
{
dsa_free(hashtable->area, pstate->batches);
pstate->batches = InvalidDsaPointer;
}
}
hashtable->parallel_state = NULL;
}
}
/*
* Get the first tuple in a given bucket identified by number.
*/
static inline HashJoinTuple
ExecParallelHashFirstTuple(HashJoinTable hashtable, int bucketno)
{
HashJoinTuple tuple;
dsa_pointer p;
Assert(hashtable->parallel_state);
p = dsa_pointer_atomic_read(&hashtable->buckets.shared[bucketno]);
tuple = (HashJoinTuple) dsa_get_address(hashtable->area, p);
return tuple;
}
/*
* Get the next tuple in the same bucket as 'tuple'.
*/
static inline HashJoinTuple
ExecParallelHashNextTuple(HashJoinTable hashtable, HashJoinTuple tuple)
{
HashJoinTuple next;
Assert(hashtable->parallel_state);
next = (HashJoinTuple) dsa_get_address(hashtable->area, tuple->next.shared);
return next;
}
/*
* Insert a tuple at the front of a chain of tuples in DSA memory atomically.
*/
static inline void
ExecParallelHashPushTuple(dsa_pointer_atomic *head,
HashJoinTuple tuple,
dsa_pointer tuple_shared)
{
for (;;)
{
tuple->next.shared = dsa_pointer_atomic_read(head);
if (dsa_pointer_atomic_compare_exchange(head,
&tuple->next.shared,
tuple_shared))
break;
}
}
/*
* Prepare to work on a given batch.
*/
void
ExecParallelHashTableSetCurrentBatch(HashJoinTable hashtable, int batchno)
{
Assert(hashtable->batches[batchno].shared->buckets != InvalidDsaPointer);
hashtable->curbatch = batchno;
hashtable->buckets.shared = (dsa_pointer_atomic *)
dsa_get_address(hashtable->area,
hashtable->batches[batchno].shared->buckets);
hashtable->nbuckets = hashtable->parallel_state->nbuckets;
hashtable->log2_nbuckets = my_log2(hashtable->nbuckets);
hashtable->current_chunk = NULL;
hashtable->current_chunk_shared = InvalidDsaPointer;
hashtable->batches[batchno].at_least_one_chunk = false;
}
/*
* Take the next available chunk from the queue of chunks being worked on in
* parallel. Return NULL if there are none left. Otherwise return a pointer
* to the chunk, and set *shared to the DSA pointer to the chunk.
*/
static HashMemoryChunk
ExecParallelHashPopChunkQueue(HashJoinTable hashtable, dsa_pointer *shared)
{
ParallelHashJoinState *pstate = hashtable->parallel_state;
HashMemoryChunk chunk;
LWLockAcquire(&pstate->lock, LW_EXCLUSIVE);
if (DsaPointerIsValid(pstate->chunk_work_queue))
{
*shared = pstate->chunk_work_queue;
chunk = (HashMemoryChunk)
dsa_get_address(hashtable->area, *shared);
pstate->chunk_work_queue = chunk->next.shared;
}
else
chunk = NULL;
LWLockRelease(&pstate->lock);
return chunk;
}
/*
* Increase the space preallocated in this backend for a given inner batch by
* at least a given amount. This allows us to track whether a given batch
* would fit in memory when loaded back in. Also increase the number of
* batches or buckets if required.
*
* This maintains a running estimation of how much space will be taken when we
* load the batch back into memory by simulating the way chunks will be handed
* out to workers. It's not perfectly accurate because the tuples will be
* packed into memory chunks differently by ExecParallelHashTupleAlloc(), but
* it should be pretty close. It tends to overestimate by a fraction of a
* chunk per worker since all workers gang up to preallocate during hashing,
* but workers tend to reload batches alone if there are enough to go around,
* leaving fewer partially filled chunks. This effect is bounded by
* nparticipants.
*
* Return false if the number of batches or buckets has changed, and the
* caller should reconsider which batch a given tuple now belongs in and call
* again.
*/
static bool
ExecParallelHashTuplePrealloc(HashJoinTable hashtable, int batchno, size_t size)
{
ParallelHashJoinState *pstate = hashtable->parallel_state;
ParallelHashJoinBatchAccessor *batch = &hashtable->batches[batchno];
size_t want = Max(size, HASH_CHUNK_SIZE - HASH_CHUNK_HEADER_SIZE);
Assert(batchno > 0);
Assert(batchno < hashtable->nbatch);
LWLockAcquire(&pstate->lock, LW_EXCLUSIVE);
/* Has another participant commanded us to help grow? */
if (pstate->growth == PHJ_GROWTH_NEED_MORE_BATCHES ||
pstate->growth == PHJ_GROWTH_NEED_MORE_BUCKETS)
{
ParallelHashGrowth growth = pstate->growth;
LWLockRelease(&pstate->lock);
if (growth == PHJ_GROWTH_NEED_MORE_BATCHES)
ExecParallelHashIncreaseNumBatches(hashtable);
else if (growth == PHJ_GROWTH_NEED_MORE_BUCKETS)
ExecParallelHashIncreaseNumBuckets(hashtable);
return false;
}
if (pstate->growth != PHJ_GROWTH_DISABLED &&
batch->at_least_one_chunk &&
(batch->shared->estimated_size + size > pstate->space_allowed))
{
/*
* We have determined that this batch would exceed the space budget if
* loaded into memory. Command all participants to help repartition.
*/
batch->shared->space_exhausted = true;
pstate->growth = PHJ_GROWTH_NEED_MORE_BATCHES;
LWLockRelease(&pstate->lock);
return false;
}
batch->at_least_one_chunk = true;
batch->shared->estimated_size += want + HASH_CHUNK_HEADER_SIZE;
batch->preallocated = want;
LWLockRelease(&pstate->lock);
return true;
}
/*
* Update this backend's copy of hashtable->spacePeak to account for a given
* batch. This is called at the end of hashing for batch 0, and then for each
* batch when it is done or discovered to be already done. The result is used
* for EXPLAIN output.
*/
void
ExecParallelHashUpdateSpacePeak(HashJoinTable hashtable, int batchno)
{
size_t size;
size = hashtable->batches[batchno].shared->size;
size += sizeof(dsa_pointer_atomic) * hashtable->nbuckets;
hashtable->spacePeak = Max(hashtable->spacePeak, size);
}
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