postgresql/src/backend/executor/nodeGatherMerge.c

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/*-------------------------------------------------------------------------
*
* nodeGatherMerge.c
* Scan a plan in multiple workers, and do order-preserving merge.
*
* Portions Copyright (c) 1996-2017, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
* IDENTIFICATION
* src/backend/executor/nodeGatherMerge.c
*
*-------------------------------------------------------------------------
*/
#include "postgres.h"
#include "access/relscan.h"
#include "access/xact.h"
#include "executor/execdebug.h"
#include "executor/execParallel.h"
#include "executor/nodeGatherMerge.h"
#include "executor/nodeSubplan.h"
#include "executor/tqueue.h"
#include "lib/binaryheap.h"
#include "miscadmin.h"
#include "utils/memutils.h"
#include "utils/rel.h"
/*
* Tuple array for each worker
*/
typedef struct GMReaderTupleBuffer
{
HeapTuple *tuple;
int readCounter;
int nTuples;
bool done;
} GMReaderTupleBuffer;
/*
* When we read tuples from workers, it's a good idea to read several at once
* for efficiency when possible: this minimizes context-switching overhead.
* But reading too many at a time wastes memory without improving performance.
*/
#define MAX_TUPLE_STORE 10
static TupleTableSlot *ExecGatherMerge(PlanState *pstate);
static int32 heap_compare_slots(Datum a, Datum b, void *arg);
static TupleTableSlot *gather_merge_getnext(GatherMergeState *gm_state);
static HeapTuple gm_readnext_tuple(GatherMergeState *gm_state, int nreader,
bool nowait, bool *done);
static void gather_merge_init(GatherMergeState *gm_state);
static void ExecShutdownGatherMergeWorkers(GatherMergeState *node);
static bool gather_merge_readnext(GatherMergeState *gm_state, int reader,
bool nowait);
static void form_tuple_array(GatherMergeState *gm_state, int reader);
/* ----------------------------------------------------------------
* ExecInitGather
* ----------------------------------------------------------------
*/
GatherMergeState *
ExecInitGatherMerge(GatherMerge *node, EState *estate, int eflags)
{
GatherMergeState *gm_state;
Plan *outerNode;
bool hasoid;
TupleDesc tupDesc;
/* Gather merge node doesn't have innerPlan node. */
Assert(innerPlan(node) == NULL);
/*
* create state structure
*/
gm_state = makeNode(GatherMergeState);
gm_state->ps.plan = (Plan *) node;
gm_state->ps.state = estate;
gm_state->ps.ExecProcNode = ExecGatherMerge;
/*
* Miscellaneous initialization
*
* create expression context for node
*/
ExecAssignExprContext(estate, &gm_state->ps);
/*
* initialize child expressions
*/
Faster expression evaluation and targetlist projection. This replaces the old, recursive tree-walk based evaluation, with non-recursive, opcode dispatch based, expression evaluation. Projection is now implemented as part of expression evaluation. This both leads to significant performance improvements, and makes future just-in-time compilation of expressions easier. The speed gains primarily come from: - non-recursive implementation reduces stack usage / overhead - simple sub-expressions are implemented with a single jump, without function calls - sharing some state between different sub-expressions - reduced amount of indirect/hard to predict memory accesses by laying out operation metadata sequentially; including the avoidance of nearly all of the previously used linked lists - more code has been moved to expression initialization, avoiding constant re-checks at evaluation time Future just-in-time compilation (JIT) has become easier, as demonstrated by released patches intended to be merged in a later release, for primarily two reasons: Firstly, due to a stricter split between expression initialization and evaluation, less code has to be handled by the JIT. Secondly, due to the non-recursive nature of the generated "instructions", less performance-critical code-paths can easily be shared between interpreted and compiled evaluation. The new framework allows for significant future optimizations. E.g.: - basic infrastructure for to later reduce the per executor-startup overhead of expression evaluation, by caching state in prepared statements. That'd be helpful in OLTPish scenarios where initialization overhead is measurable. - optimizing the generated "code". A number of proposals for potential work has already been made. - optimizing the interpreter. Similarly a number of proposals have been made here too. The move of logic into the expression initialization step leads to some backward-incompatible changes: - Function permission checks are now done during expression initialization, whereas previously they were done during execution. In edge cases this can lead to errors being raised that previously wouldn't have been, e.g. a NULL array being coerced to a different array type previously didn't perform checks. - The set of domain constraints to be checked, is now evaluated once during expression initialization, previously it was re-built every time a domain check was evaluated. For normal queries this doesn't change much, but e.g. for plpgsql functions, which caches ExprStates, the old set could stick around longer. The behavior around might still change. Author: Andres Freund, with significant changes by Tom Lane, changes by Heikki Linnakangas Reviewed-By: Tom Lane, Heikki Linnakangas Discussion: https://postgr.es/m/20161206034955.bh33paeralxbtluv@alap3.anarazel.de
2017-03-14 18:45:36 -04:00
gm_state->ps.qual =
ExecInitQual(node->plan.qual, &gm_state->ps);
/*
* tuple table initialization
*/
ExecInitResultTupleSlot(estate, &gm_state->ps);
/*
* now initialize outer plan
*/
outerNode = outerPlan(node);
outerPlanState(gm_state) = ExecInitNode(outerNode, estate, eflags);
/*
* Initialize result tuple type and projection info.
*/
ExecAssignResultTypeFromTL(&gm_state->ps);
ExecAssignProjectionInfo(&gm_state->ps, NULL);
gm_state->gm_initialized = false;
/*
* initialize sort-key information
*/
if (node->numCols)
{
int i;
gm_state->gm_nkeys = node->numCols;
gm_state->gm_sortkeys =
palloc0(sizeof(SortSupportData) * node->numCols);
for (i = 0; i < node->numCols; i++)
{
SortSupport sortKey = gm_state->gm_sortkeys + i;
sortKey->ssup_cxt = CurrentMemoryContext;
sortKey->ssup_collation = node->collations[i];
sortKey->ssup_nulls_first = node->nullsFirst[i];
sortKey->ssup_attno = node->sortColIdx[i];
/*
* We don't perform abbreviated key conversion here, for the same
* reasons that it isn't used in MergeAppend
*/
sortKey->abbreviate = false;
PrepareSortSupportFromOrderingOp(node->sortOperators[i], sortKey);
}
}
/*
* store the tuple descriptor into gather merge state, so we can use it
* later while initializing the gather merge slots.
*/
if (!ExecContextForcesOids(&gm_state->ps, &hasoid))
hasoid = false;
tupDesc = ExecTypeFromTL(outerNode->targetlist, hasoid);
gm_state->tupDesc = tupDesc;
return gm_state;
}
/* ----------------------------------------------------------------
* ExecGatherMerge(node)
*
* Scans the relation via multiple workers and returns
* the next qualifying tuple.
* ----------------------------------------------------------------
*/
static TupleTableSlot *
ExecGatherMerge(PlanState *pstate)
{
GatherMergeState *node = castNode(GatherMergeState, pstate);
TupleTableSlot *slot;
ExprContext *econtext;
int i;
CHECK_FOR_INTERRUPTS();
/*
* As with Gather, we don't launch workers until this node is actually
* executed.
*/
if (!node->initialized)
{
EState *estate = node->ps.state;
GatherMerge *gm = (GatherMerge *) node->ps.plan;
/*
* Sometimes we might have to run without parallelism; but if parallel
* mode is active then we can try to fire up some workers.
*/
if (gm->num_workers > 0 && IsInParallelMode())
{
ParallelContext *pcxt;
/* Initialize, or re-initialize, shared state needed by workers. */
if (!node->pei)
node->pei = ExecInitParallelPlan(node->ps.lefttree,
estate,
gm->num_workers);
else
ExecParallelReinitialize(node->ps.lefttree,
node->pei);
/* Try to launch workers. */
pcxt = node->pei->pcxt;
LaunchParallelWorkers(pcxt);
node->nworkers_launched = pcxt->nworkers_launched;
/* Set up tuple queue readers to read the results. */
if (pcxt->nworkers_launched > 0)
{
node->nreaders = 0;
node->reader = palloc(pcxt->nworkers_launched *
sizeof(TupleQueueReader *));
Assert(gm->numCols);
for (i = 0; i < pcxt->nworkers_launched; ++i)
{
shm_mq_set_handle(node->pei->tqueue[i],
pcxt->worker[i].bgwhandle);
node->reader[node->nreaders++] =
CreateTupleQueueReader(node->pei->tqueue[i],
node->tupDesc);
}
}
else
{
/* No workers? Then never mind. */
ExecShutdownGatherMergeWorkers(node);
}
}
/* always allow leader to participate */
node->need_to_scan_locally = true;
node->initialized = true;
}
/*
* Reset per-tuple memory context to free any expression evaluation
* storage allocated in the previous tuple cycle.
*/
econtext = node->ps.ps_ExprContext;
ResetExprContext(econtext);
/*
* Get next tuple, either from one of our workers, or by running the plan
* ourselves.
*/
slot = gather_merge_getnext(node);
if (TupIsNull(slot))
return NULL;
/*
* form the result tuple using ExecProject(), and return it --- unless the
* projection produces an empty set, in which case we must loop back
* around for another tuple
*/
econtext->ecxt_outertuple = slot;
return ExecProject(node->ps.ps_ProjInfo);
}
/* ----------------------------------------------------------------
* ExecEndGatherMerge
*
* frees any storage allocated through C routines.
* ----------------------------------------------------------------
*/
void
ExecEndGatherMerge(GatherMergeState *node)
{
ExecEndNode(outerPlanState(node)); /* let children clean up first */
ExecShutdownGatherMerge(node);
ExecFreeExprContext(&node->ps);
ExecClearTuple(node->ps.ps_ResultTupleSlot);
}
/* ----------------------------------------------------------------
* ExecShutdownGatherMerge
*
* Destroy the setup for parallel workers including parallel context.
* Collect all the stats after workers are stopped, else some work
* done by workers won't be accounted.
* ----------------------------------------------------------------
*/
void
ExecShutdownGatherMerge(GatherMergeState *node)
{
ExecShutdownGatherMergeWorkers(node);
/* Now destroy the parallel context. */
if (node->pei != NULL)
{
ExecParallelCleanup(node->pei);
node->pei = NULL;
}
}
/* ----------------------------------------------------------------
* ExecShutdownGatherMergeWorkers
*
* Destroy the parallel workers. Collect all the stats after
* workers are stopped, else some work done by workers won't be
* accounted.
* ----------------------------------------------------------------
*/
static void
ExecShutdownGatherMergeWorkers(GatherMergeState *node)
{
/* Shut down tuple queue readers before shutting down workers. */
if (node->reader != NULL)
{
int i;
for (i = 0; i < node->nreaders; ++i)
if (node->reader[i])
DestroyTupleQueueReader(node->reader[i]);
pfree(node->reader);
node->reader = NULL;
}
/* Now shut down the workers. */
if (node->pei != NULL)
ExecParallelFinish(node->pei);
}
/* ----------------------------------------------------------------
* ExecReScanGatherMerge
*
* Prepare to re-scan the result of a GatherMerge.
* ----------------------------------------------------------------
*/
void
ExecReScanGatherMerge(GatherMergeState *node)
{
Force rescanning of parallel-aware scan nodes below a Gather[Merge]. The ExecReScan machinery contains various optimizations for postponing or skipping rescans of plan subtrees; for example a HashAgg node may conclude that it can re-use the table it built before, instead of re-reading its input subtree. But that is wrong if the input contains a parallel-aware table scan node, since the portion of the table scanned by the leader process is likely to vary from one rescan to the next. This explains the timing-dependent buildfarm failures we saw after commit a2b70c89c. The established mechanism for showing that a plan node's output is potentially variable is to mark it as depending on some runtime Param. Hence, to fix this, invent a dummy Param (one that has a PARAM_EXEC parameter number, but carries no actual value) associated with each Gather or GatherMerge node, mark parallel-aware nodes below that node as dependent on that Param, and arrange for ExecReScanGather[Merge] to flag that Param as changed whenever the Gather[Merge] node is rescanned. This solution breaks an undocumented assumption made by the parallel executor logic, namely that all rescans of nodes below a Gather[Merge] will happen synchronously during the ReScan of the top node itself. But that's fundamentally contrary to the design of the ExecReScan code, and so was doomed to fail someday anyway (even if you want to argue that the bug being fixed here wasn't a failure of that assumption). A follow-on patch will address that issue. In the meantime, the worst that's expected to happen is that given very bad timing luck, the leader might have to do all the work during a rescan, because workers think they have nothing to do, if they are able to start up before the eventual ReScan of the leader's parallel-aware table scan node has reset the shared scan state. Although this problem exists in 9.6, there does not seem to be any way for it to manifest there. Without GatherMerge, it seems that a plan tree that has a rescan-short-circuiting node below Gather will always also have one above it that will short-circuit in the same cases, preventing the Gather from being rescanned. Hence we won't take the risk of back-patching this change into 9.6. But v10 needs it. Discussion: https://postgr.es/m/CAA4eK1JkByysFJNh9M349u_nNjqETuEnY_y1VUc_kJiU0bxtaQ@mail.gmail.com
2017-08-30 09:29:56 -04:00
GatherMerge *gm = (GatherMerge *) node->ps.plan;
PlanState *outerPlan = outerPlanState(node);
/* Make sure any existing workers are gracefully shut down */
ExecShutdownGatherMergeWorkers(node);
/* Mark node so that shared state will be rebuilt at next call */
node->initialized = false;
node->gm_initialized = false;
Force rescanning of parallel-aware scan nodes below a Gather[Merge]. The ExecReScan machinery contains various optimizations for postponing or skipping rescans of plan subtrees; for example a HashAgg node may conclude that it can re-use the table it built before, instead of re-reading its input subtree. But that is wrong if the input contains a parallel-aware table scan node, since the portion of the table scanned by the leader process is likely to vary from one rescan to the next. This explains the timing-dependent buildfarm failures we saw after commit a2b70c89c. The established mechanism for showing that a plan node's output is potentially variable is to mark it as depending on some runtime Param. Hence, to fix this, invent a dummy Param (one that has a PARAM_EXEC parameter number, but carries no actual value) associated with each Gather or GatherMerge node, mark parallel-aware nodes below that node as dependent on that Param, and arrange for ExecReScanGather[Merge] to flag that Param as changed whenever the Gather[Merge] node is rescanned. This solution breaks an undocumented assumption made by the parallel executor logic, namely that all rescans of nodes below a Gather[Merge] will happen synchronously during the ReScan of the top node itself. But that's fundamentally contrary to the design of the ExecReScan code, and so was doomed to fail someday anyway (even if you want to argue that the bug being fixed here wasn't a failure of that assumption). A follow-on patch will address that issue. In the meantime, the worst that's expected to happen is that given very bad timing luck, the leader might have to do all the work during a rescan, because workers think they have nothing to do, if they are able to start up before the eventual ReScan of the leader's parallel-aware table scan node has reset the shared scan state. Although this problem exists in 9.6, there does not seem to be any way for it to manifest there. Without GatherMerge, it seems that a plan tree that has a rescan-short-circuiting node below Gather will always also have one above it that will short-circuit in the same cases, preventing the Gather from being rescanned. Hence we won't take the risk of back-patching this change into 9.6. But v10 needs it. Discussion: https://postgr.es/m/CAA4eK1JkByysFJNh9M349u_nNjqETuEnY_y1VUc_kJiU0bxtaQ@mail.gmail.com
2017-08-30 09:29:56 -04:00
/*
* Set child node's chgParam to tell it that the next scan might deliver a
* different set of rows within the leader process. (The overall rowset
* shouldn't change, but the leader process's subset might; hence nodes
* between here and the parallel table scan node mustn't optimize on the
* assumption of an unchanging rowset.)
*/
if (gm->rescan_param >= 0)
outerPlan->chgParam = bms_add_member(outerPlan->chgParam,
gm->rescan_param);
/*
* If chgParam of subnode is not null then plan will be re-scanned by
* first ExecProcNode. Note: because this does nothing if we have a
* rescan_param, it's currently guaranteed that parallel-aware child nodes
* will not see a ReScan call until after they get a ReInitializeDSM call.
* That ordering might not be something to rely on, though. A good rule
* of thumb is that ReInitializeDSM should reset only shared state, ReScan
* should reset only local state, and anything that depends on both of
* those steps being finished must wait until the first ExecProcNode call.
Force rescanning of parallel-aware scan nodes below a Gather[Merge]. The ExecReScan machinery contains various optimizations for postponing or skipping rescans of plan subtrees; for example a HashAgg node may conclude that it can re-use the table it built before, instead of re-reading its input subtree. But that is wrong if the input contains a parallel-aware table scan node, since the portion of the table scanned by the leader process is likely to vary from one rescan to the next. This explains the timing-dependent buildfarm failures we saw after commit a2b70c89c. The established mechanism for showing that a plan node's output is potentially variable is to mark it as depending on some runtime Param. Hence, to fix this, invent a dummy Param (one that has a PARAM_EXEC parameter number, but carries no actual value) associated with each Gather or GatherMerge node, mark parallel-aware nodes below that node as dependent on that Param, and arrange for ExecReScanGather[Merge] to flag that Param as changed whenever the Gather[Merge] node is rescanned. This solution breaks an undocumented assumption made by the parallel executor logic, namely that all rescans of nodes below a Gather[Merge] will happen synchronously during the ReScan of the top node itself. But that's fundamentally contrary to the design of the ExecReScan code, and so was doomed to fail someday anyway (even if you want to argue that the bug being fixed here wasn't a failure of that assumption). A follow-on patch will address that issue. In the meantime, the worst that's expected to happen is that given very bad timing luck, the leader might have to do all the work during a rescan, because workers think they have nothing to do, if they are able to start up before the eventual ReScan of the leader's parallel-aware table scan node has reset the shared scan state. Although this problem exists in 9.6, there does not seem to be any way for it to manifest there. Without GatherMerge, it seems that a plan tree that has a rescan-short-circuiting node below Gather will always also have one above it that will short-circuit in the same cases, preventing the Gather from being rescanned. Hence we won't take the risk of back-patching this change into 9.6. But v10 needs it. Discussion: https://postgr.es/m/CAA4eK1JkByysFJNh9M349u_nNjqETuEnY_y1VUc_kJiU0bxtaQ@mail.gmail.com
2017-08-30 09:29:56 -04:00
*/
if (outerPlan->chgParam == NULL)
ExecReScan(outerPlan);
}
/*
* Initialize the Gather merge tuple read.
*
* Pull at least a single tuple from each worker + leader and set up the heap.
*/
static void
gather_merge_init(GatherMergeState *gm_state)
{
int nreaders = gm_state->nreaders;
bool initialize = true;
int i;
/*
* Allocate gm_slots for the number of worker + one more slot for leader.
* Last slot is always for leader. Leader always calls ExecProcNode() to
* read the tuple which will return the TupleTableSlot. Later it will
* directly get assigned to gm_slot. So just initialize leader gm_slot
* with NULL. For other slots below code will call
* ExecInitExtraTupleSlot() which will do the initialization of worker
* slots.
*/
gm_state->gm_slots =
palloc((gm_state->nreaders + 1) * sizeof(TupleTableSlot *));
gm_state->gm_slots[gm_state->nreaders] = NULL;
/* Initialize the tuple slot and tuple array for each worker */
gm_state->gm_tuple_buffers =
(GMReaderTupleBuffer *) palloc0(sizeof(GMReaderTupleBuffer) *
(gm_state->nreaders + 1));
for (i = 0; i < gm_state->nreaders; i++)
{
/* Allocate the tuple array with MAX_TUPLE_STORE size */
gm_state->gm_tuple_buffers[i].tuple =
(HeapTuple *) palloc0(sizeof(HeapTuple) * MAX_TUPLE_STORE);
/* Initialize slot for worker */
gm_state->gm_slots[i] = ExecInitExtraTupleSlot(gm_state->ps.state);
ExecSetSlotDescriptor(gm_state->gm_slots[i],
gm_state->tupDesc);
}
/* Allocate the resources for the merge */
gm_state->gm_heap = binaryheap_allocate(gm_state->nreaders + 1,
heap_compare_slots,
gm_state);
/*
* First, try to read a tuple from each worker (including leader) in
* nowait mode, so that we initialize read from each worker as well as
* leader. After this, if all active workers are unable to produce a
* tuple, then re-read and this time use wait mode. For workers that were
* able to produce a tuple in the earlier loop and are still active, just
* try to fill the tuple array if more tuples are avaiable.
*/
reread:
for (i = 0; i < nreaders + 1; i++)
{
CHECK_FOR_INTERRUPTS();
if (!gm_state->gm_tuple_buffers[i].done &&
(TupIsNull(gm_state->gm_slots[i]) ||
gm_state->gm_slots[i]->tts_isempty))
{
if (gather_merge_readnext(gm_state, i, initialize))
{
binaryheap_add_unordered(gm_state->gm_heap,
Int32GetDatum(i));
}
}
else
form_tuple_array(gm_state, i);
}
initialize = false;
for (i = 0; i < nreaders; i++)
if (!gm_state->gm_tuple_buffers[i].done &&
(TupIsNull(gm_state->gm_slots[i]) ||
gm_state->gm_slots[i]->tts_isempty))
goto reread;
binaryheap_build(gm_state->gm_heap);
gm_state->gm_initialized = true;
}
/*
* Clear out the tuple table slots for each gather merge input.
*/
static void
gather_merge_clear_slots(GatherMergeState *gm_state)
{
int i;
for (i = 0; i < gm_state->nreaders; i++)
{
pfree(gm_state->gm_tuple_buffers[i].tuple);
gm_state->gm_slots[i] = ExecClearTuple(gm_state->gm_slots[i]);
}
/* Free tuple array as we don't need it any more */
pfree(gm_state->gm_tuple_buffers);
/* Free the binaryheap, which was created for sort */
binaryheap_free(gm_state->gm_heap);
}
/*
* Read the next tuple for gather merge.
*
* Fetch the sorted tuple out of the heap.
*/
static TupleTableSlot *
gather_merge_getnext(GatherMergeState *gm_state)
{
int i;
if (!gm_state->gm_initialized)
{
/*
* First time through: pull the first tuple from each participant, and
* set up the heap.
*/
gather_merge_init(gm_state);
}
else
{
/*
* Otherwise, pull the next tuple from whichever participant we
* returned from last time, and reinsert that participant's index into
* the heap, because it might now compare differently against the
* other elements of the heap.
*/
i = DatumGetInt32(binaryheap_first(gm_state->gm_heap));
if (gather_merge_readnext(gm_state, i, false))
binaryheap_replace_first(gm_state->gm_heap, Int32GetDatum(i));
else
(void) binaryheap_remove_first(gm_state->gm_heap);
}
if (binaryheap_empty(gm_state->gm_heap))
{
/* All the queues are exhausted, and so is the heap */
gather_merge_clear_slots(gm_state);
return NULL;
}
else
{
/* Return next tuple from whichever participant has the leading one */
i = DatumGetInt32(binaryheap_first(gm_state->gm_heap));
return gm_state->gm_slots[i];
}
}
/*
* Read the tuple for given reader in nowait mode, and form the tuple array.
*/
static void
form_tuple_array(GatherMergeState *gm_state, int reader)
{
GMReaderTupleBuffer *tuple_buffer = &gm_state->gm_tuple_buffers[reader];
int i;
/* Last slot is for leader and we don't build tuple array for leader */
if (reader == gm_state->nreaders)
return;
/*
* We here because we already read all the tuples from the tuple array, so
* initialize the counter to zero.
*/
if (tuple_buffer->nTuples == tuple_buffer->readCounter)
tuple_buffer->nTuples = tuple_buffer->readCounter = 0;
/* Tuple array is already full? */
if (tuple_buffer->nTuples == MAX_TUPLE_STORE)
return;
for (i = tuple_buffer->nTuples; i < MAX_TUPLE_STORE; i++)
{
tuple_buffer->tuple[i] = heap_copytuple(gm_readnext_tuple(gm_state,
reader,
false,
&tuple_buffer->done));
if (!HeapTupleIsValid(tuple_buffer->tuple[i]))
break;
tuple_buffer->nTuples++;
}
}
/*
* Store the next tuple for a given reader into the appropriate slot.
*
* Returns false if the reader is exhausted, and true otherwise.
*/
static bool
gather_merge_readnext(GatherMergeState *gm_state, int reader, bool nowait)
{
GMReaderTupleBuffer *tuple_buffer;
HeapTuple tup = NULL;
/*
* If we're being asked to generate a tuple from the leader, then we just
* call ExecProcNode as normal to produce one.
*/
if (gm_state->nreaders == reader)
{
if (gm_state->need_to_scan_locally)
{
PlanState *outerPlan = outerPlanState(gm_state);
TupleTableSlot *outerTupleSlot;
outerTupleSlot = ExecProcNode(outerPlan);
if (!TupIsNull(outerTupleSlot))
{
gm_state->gm_slots[reader] = outerTupleSlot;
return true;
}
gm_state->gm_tuple_buffers[reader].done = true;
gm_state->need_to_scan_locally = false;
}
return false;
}
/* Otherwise, check the state of the relevant tuple buffer. */
tuple_buffer = &gm_state->gm_tuple_buffers[reader];
if (tuple_buffer->nTuples > tuple_buffer->readCounter)
{
/* Return any tuple previously read that is still buffered. */
tuple_buffer = &gm_state->gm_tuple_buffers[reader];
tup = tuple_buffer->tuple[tuple_buffer->readCounter++];
}
else if (tuple_buffer->done)
{
/* Reader is known to be exhausted. */
DestroyTupleQueueReader(gm_state->reader[reader]);
gm_state->reader[reader] = NULL;
return false;
}
else
{
/* Read and buffer next tuple. */
tup = heap_copytuple(gm_readnext_tuple(gm_state,
reader,
nowait,
&tuple_buffer->done));
/*
* Attempt to read more tuples in nowait mode and store them in the
* tuple array.
*/
if (HeapTupleIsValid(tup))
form_tuple_array(gm_state, reader);
else
return false;
}
Assert(HeapTupleIsValid(tup));
/* Build the TupleTableSlot for the given tuple */
ExecStoreTuple(tup, /* tuple to store */
gm_state->gm_slots[reader], /* slot in which to store the
* tuple */
Phase 2 of pgindent updates. Change pg_bsd_indent to follow upstream rules for placement of comments to the right of code, and remove pgindent hack that caused comments following #endif to not obey the general rule. Commit e3860ffa4dd0dad0dd9eea4be9cc1412373a8c89 wasn't actually using the published version of pg_bsd_indent, but a hacked-up version that tried to minimize the amount of movement of comments to the right of code. The situation of interest is where such a comment has to be moved to the right of its default placement at column 33 because there's code there. BSD indent has always moved right in units of tab stops in such cases --- but in the previous incarnation, indent was working in 8-space tab stops, while now it knows we use 4-space tabs. So the net result is that in about half the cases, such comments are placed one tab stop left of before. This is better all around: it leaves more room on the line for comment text, and it means that in such cases the comment uniformly starts at the next 4-space tab stop after the code, rather than sometimes one and sometimes two tabs after. Also, ensure that comments following #endif are indented the same as comments following other preprocessor commands such as #else. That inconsistency turns out to have been self-inflicted damage from a poorly-thought-through post-indent "fixup" in pgindent. This patch is much less interesting than the first round of indent changes, but also bulkier, so I thought it best to separate the effects. Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
2017-06-21 15:18:54 -04:00
InvalidBuffer, /* buffer associated with this tuple */
true); /* pfree this pointer if not from heap */
return true;
}
/*
* Attempt to read a tuple from given reader.
*/
static HeapTuple
gm_readnext_tuple(GatherMergeState *gm_state, int nreader, bool nowait,
bool *done)
{
TupleQueueReader *reader;
HeapTuple tup = NULL;
MemoryContext oldContext;
MemoryContext tupleContext;
tupleContext = gm_state->ps.ps_ExprContext->ecxt_per_tuple_memory;
if (done != NULL)
*done = false;
/* Check for async events, particularly messages from workers. */
CHECK_FOR_INTERRUPTS();
/* Attempt to read a tuple. */
reader = gm_state->reader[nreader];
/* Run TupleQueueReaders in per-tuple context */
oldContext = MemoryContextSwitchTo(tupleContext);
tup = TupleQueueReaderNext(reader, nowait, done);
MemoryContextSwitchTo(oldContext);
return tup;
}
/*
* We have one slot for each item in the heap array. We use SlotNumber
* to store slot indexes. This doesn't actually provide any formal
* type-safety, but it makes the code more self-documenting.
*/
typedef int32 SlotNumber;
/*
* Compare the tuples in the two given slots.
*/
static int32
heap_compare_slots(Datum a, Datum b, void *arg)
{
GatherMergeState *node = (GatherMergeState *) arg;
SlotNumber slot1 = DatumGetInt32(a);
SlotNumber slot2 = DatumGetInt32(b);
TupleTableSlot *s1 = node->gm_slots[slot1];
TupleTableSlot *s2 = node->gm_slots[slot2];
int nkey;
Assert(!TupIsNull(s1));
Assert(!TupIsNull(s2));
for (nkey = 0; nkey < node->gm_nkeys; nkey++)
{
SortSupport sortKey = node->gm_sortkeys + nkey;
AttrNumber attno = sortKey->ssup_attno;
Datum datum1,
datum2;
bool isNull1,
isNull2;
int compare;
datum1 = slot_getattr(s1, attno, &isNull1);
datum2 = slot_getattr(s2, attno, &isNull2);
compare = ApplySortComparator(datum1, isNull1,
datum2, isNull2,
sortKey);
if (compare != 0)
return -compare;
}
return 0;
}