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) 1996-2024, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
* IDENTIFICATION
* src/backend/executor/nodeGatherMerge.c
*
*-------------------------------------------------------------------------
*/
#include "postgres.h"
#include "executor/executor.h"
#include "executor/execParallel.h"
#include "executor/nodeGatherMerge.h"
#include "executor/tqueue.h"
#include "lib/binaryheap.h"
#include "miscadmin.h"
#include "optimizer/optimizer.h"
/*
* 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.
* We'll read up to MAX_TUPLE_STORE tuples (in addition to the first one).
*/
#define MAX_TUPLE_STORE 10
/*
* Pending-tuple array for each worker. This holds additional tuples that
* we were able to fetch from the worker, but can't process yet. In addition,
* this struct holds the "done" flag indicating the worker is known to have
* no more tuples. (We do not use this struct for the leader; we don't keep
* any pending tuples for the leader, and the need_to_scan_locally flag serves
* as its "done" indicator.)
*/
typedef struct GMReaderTupleBuffer
{
MinimalTuple *tuple; /* array of length MAX_TUPLE_STORE */
int nTuples; /* number of tuples currently stored */
int readCounter; /* index of next tuple to extract */
bool done; /* true if reader is known exhausted */
} GMReaderTupleBuffer;
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 MinimalTuple gm_readnext_tuple(GatherMergeState *gm_state, int nreader,
bool nowait, bool *done);
static void ExecShutdownGatherMergeWorkers(GatherMergeState *node);
static void gather_merge_setup(GatherMergeState *gm_state);
static void gather_merge_init(GatherMergeState *gm_state);
static void gather_merge_clear_tuples(GatherMergeState *gm_state);
static bool gather_merge_readnext(GatherMergeState *gm_state, int reader,
bool nowait);
static void load_tuple_array(GatherMergeState *gm_state, int reader);
/* ----------------------------------------------------------------
* ExecInitGather
* ----------------------------------------------------------------
*/
GatherMergeState *
ExecInitGatherMerge(GatherMerge *node, EState *estate, int eflags)
{
GatherMergeState *gm_state;
Plan *outerNode;
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;
gm_state->initialized = false;
gm_state->gm_initialized = false;
gm_state->tuples_needed = -1;
/*
* Miscellaneous initialization
*
* create expression context for node
*/
ExecAssignExprContext(estate, &gm_state->ps);
/*
* GatherMerge doesn't support checking a qual (it's always more efficient
* to do it in the child node).
*/
Assert(!node->plan.qual);
/*
* now initialize outer plan
*/
outerNode = outerPlan(node);
outerPlanState(gm_state) = ExecInitNode(outerNode, estate, eflags);
/*
* Leader may access ExecProcNode result directly (if
* need_to_scan_locally), or from workers via tuple queue. So we can't
* trivially rely on the slot type being fixed for expressions evaluated
* within this node.
*/
gm_state->ps.outeropsset = true;
gm_state->ps.outeropsfixed = false;
/*
* Store the tuple descriptor into gather merge state, so we can use it
* while initializing the gather merge slots.
*/
tupDesc = ExecGetResultType(outerPlanState(gm_state));
gm_state->tupDesc = tupDesc;
/*
Don't require return slots for nodes without projection. In a lot of nodes the return slot is not required. That can either be because the node doesn't do any projection (say an Append node), or because the node does perform projections but the projection is optimized away because the projection would yield an identical row. Slots aren't that small, especially for wide rows, so it's worthwhile to avoid creating them. It's not possible to just skip creating the slot - it's currently used to determine the tuple descriptor returned by ExecGetResultType(). So separate the determination of the result type from the slot creation. The work previously done internally ExecInitResultTupleSlotTL() can now also be done separately with ExecInitResultTypeTL() and ExecInitResultSlot(). That way nodes that aren't guaranteed to need a result slot, can use ExecInitResultTypeTL() to determine the result type of the node, and ExecAssignScanProjectionInfo() (via ExecConditionalAssignProjectionInfo()) determines that a result slot is needed, it is created with ExecInitResultSlot(). Besides the advantage of avoiding to create slots that then are unused, this is necessary preparation for later patches around tuple table slot abstraction. In particular separating the return descriptor and slot is a prerequisite to allow JITing of tuple deforming with knowledge of the underlying tuple format, and to avoid unnecessarily creating JITed tuple deforming for virtual slots. This commit removes a redundant argument from ExecInitResultTupleSlotTL(). While this commit touches a lot of the relevant lines anyway, it'd normally still not worthwhile to cause breakage, except that aforementioned later commits will touch *all* ExecInitResultTupleSlotTL() callers anyway (but fits worse thematically). Author: Andres Freund Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
2018-11-10 02:19:39 +01:00
* Initialize result type and projection.
*/
Don't require return slots for nodes without projection. In a lot of nodes the return slot is not required. That can either be because the node doesn't do any projection (say an Append node), or because the node does perform projections but the projection is optimized away because the projection would yield an identical row. Slots aren't that small, especially for wide rows, so it's worthwhile to avoid creating them. It's not possible to just skip creating the slot - it's currently used to determine the tuple descriptor returned by ExecGetResultType(). So separate the determination of the result type from the slot creation. The work previously done internally ExecInitResultTupleSlotTL() can now also be done separately with ExecInitResultTypeTL() and ExecInitResultSlot(). That way nodes that aren't guaranteed to need a result slot, can use ExecInitResultTypeTL() to determine the result type of the node, and ExecAssignScanProjectionInfo() (via ExecConditionalAssignProjectionInfo()) determines that a result slot is needed, it is created with ExecInitResultSlot(). Besides the advantage of avoiding to create slots that then are unused, this is necessary preparation for later patches around tuple table slot abstraction. In particular separating the return descriptor and slot is a prerequisite to allow JITing of tuple deforming with knowledge of the underlying tuple format, and to avoid unnecessarily creating JITed tuple deforming for virtual slots. This commit removes a redundant argument from ExecInitResultTupleSlotTL(). While this commit touches a lot of the relevant lines anyway, it'd normally still not worthwhile to cause breakage, except that aforementioned later commits will touch *all* ExecInitResultTupleSlotTL() callers anyway (but fits worse thematically). Author: Andres Freund Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
2018-11-10 02:19:39 +01:00
ExecInitResultTypeTL(&gm_state->ps);
ExecConditionalAssignProjectionInfo(&gm_state->ps, tupDesc, OUTER_VAR);
/*
* Without projections result slot type is not trivially known, see
* comment above.
*/
Introduce notion of different types of slots (without implementing them). Upcoming work intends to allow pluggable ways to introduce new ways of storing table data. Accessing those table access methods from the executor requires TupleTableSlots to be carry tuples in the native format of such storage methods; otherwise there'll be a significant conversion overhead. Different access methods will require different data to store tuples efficiently (just like virtual, minimal, heap already require fields in TupleTableSlot). To allow that without requiring additional pointer indirections, we want to have different structs (embedding TupleTableSlot) for different types of slots. Thus different types of slots are needed, which requires adapting creators of slots. The slot that most efficiently can represent a type of tuple in an executor node will often depend on the type of slot a child node uses. Therefore we need to track the type of slot is returned by nodes, so parent slots can create slots based on that. Relatedly, JIT compilation of tuple deforming needs to know which type of slot a certain expression refers to, so it can create an appropriate deforming function for the type of tuple in the slot. But not all nodes will only return one type of slot, e.g. an append node will potentially return different types of slots for each of its subplans. Therefore add function that allows to query the type of a node's result slot, and whether it'll always be the same type (whether it's fixed). This can be queried using ExecGetResultSlotOps(). The scan, result, inner, outer type of slots are automatically inferred from ExecInitScanTupleSlot(), ExecInitResultSlot(), left/right subtrees respectively. If that's not correct for a node, that can be overwritten using new fields in PlanState. This commit does not introduce the actually abstracted implementation of different kind of TupleTableSlots, that will be left for a followup commit. The different types of slots introduced will, for now, still use the same backing implementation. While this already partially invalidates the big comment in tuptable.h, it seems to make more sense to update it later, when the different TupleTableSlot implementations actually exist. Author: Ashutosh Bapat and Andres Freund, with changes by Amit Khandekar Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
2018-11-16 07:00:30 +01:00
if (gm_state->ps.ps_ProjInfo == NULL)
{
gm_state->ps.resultopsset = true;
gm_state->ps.resultopsfixed = 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);
}
}
/* Now allocate the workspace for gather merge */
gather_merge_setup(gm_state);
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;
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 = castNode(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 && estate->es_use_parallel_mode)
{
ParallelContext *pcxt;
/* Initialize, or re-initialize, shared state needed by workers. */
if (!node->pei)
node->pei = ExecInitParallelPlan(outerPlanState(node),
estate,
gm->initParam,
gm->num_workers,
node->tuples_needed);
else
ExecParallelReinitialize(outerPlanState(node),
node->pei,
gm->initParam);
/* Try to launch workers. */
pcxt = node->pei->pcxt;
LaunchParallelWorkers(pcxt);
/* We save # workers launched for the benefit of EXPLAIN */
node->nworkers_launched = pcxt->nworkers_launched;
/* Set up tuple queue readers to read the results. */
if (pcxt->nworkers_launched > 0)
{
ExecParallelCreateReaders(node->pei);
/* Make a working array showing the active readers */
node->nreaders = pcxt->nworkers_launched;
node->reader = (TupleQueueReader **)
palloc(node->nreaders * sizeof(TupleQueueReader *));
memcpy(node->reader, node->pei->reader,
node->nreaders * sizeof(TupleQueueReader *));
}
else
{
/* No workers? Then never mind. */
node->nreaders = 0;
node->reader = NULL;
}
}
/* allow leader to participate if enabled or no choice */
if (parallel_leader_participation || node->nreaders == 0)
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;
/* If no projection is required, we're done. */
if (node->ps.ps_ProjInfo == NULL)
return slot;
/*
* Form the result tuple using ExecProject(), and return it.
*/
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);
}
/* ----------------------------------------------------------------
* ExecShutdownGatherMerge
*
* Destroy the setup for parallel workers including parallel context.
* ----------------------------------------------------------------
*/
void
ExecShutdownGatherMerge(GatherMergeState *node)
{
ExecShutdownGatherMergeWorkers(node);
/* Now destroy the parallel context. */
if (node->pei != NULL)
{
ExecParallelCleanup(node->pei);
node->pei = NULL;
}
}
/* ----------------------------------------------------------------
* ExecShutdownGatherMergeWorkers
*
* Stop all the parallel workers.
* ----------------------------------------------------------------
*/
static void
ExecShutdownGatherMergeWorkers(GatherMergeState *node)
{
if (node->pei != NULL)
ExecParallelFinish(node->pei);
/* Flush local copy of reader array */
if (node->reader)
pfree(node->reader);
node->reader = NULL;
}
/* ----------------------------------------------------------------
* 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 15:29:55 +02:00
GatherMerge *gm = (GatherMerge *) node->ps.plan;
PlanState *outerPlan = outerPlanState(node);
/* Make sure any existing workers are gracefully shut down */
ExecShutdownGatherMergeWorkers(node);
/* Free any unused tuples, so we don't leak memory across rescans */
gather_merge_clear_tuples(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 15:29:55 +02:00
/*
* 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 15:29:55 +02:00
*/
if (outerPlan->chgParam == NULL)
ExecReScan(outerPlan);
}
/*
* Set up the data structures that we'll need for Gather Merge.
*
* We allocate these once on the basis of gm->num_workers, which is an
* upper bound for the number of workers we'll actually have. During
* a rescan, we reset the structures to empty. This approach simplifies
* not leaking memory across rescans.
*
* In the gm_slots[] array, index 0 is for the leader, and indexes 1 to n
* are for workers. The values placed into gm_heap correspond to indexes
* in gm_slots[]. The gm_tuple_buffers[] array, however, is indexed from
* 0 to n-1; it has no entry for the leader.
*/
static void
gather_merge_setup(GatherMergeState *gm_state)
{
GatherMerge *gm = castNode(GatherMerge, gm_state->ps.plan);
int nreaders = gm->num_workers;
int i;
/*
* Allocate gm_slots for the number of workers + one more slot for leader.
* Slot 0 is always for the leader. Leader always calls ExecProcNode() to
* read the tuple, and then stores it directly into its gm_slots entry.
* For other slots, code below will call ExecInitExtraTupleSlot() to
* create a slot for the worker's results. Note that during any single
* scan, we might have fewer than num_workers available workers, in which
* case the extra array entries go unused.
*/
gm_state->gm_slots = (TupleTableSlot **)
palloc0((nreaders + 1) * sizeof(TupleTableSlot *));
/* Allocate the tuple slot and tuple array for each worker */
gm_state->gm_tuple_buffers = (GMReaderTupleBuffer *)
palloc0(nreaders * sizeof(GMReaderTupleBuffer));
for (i = 0; i < nreaders; i++)
{
/* Allocate the tuple array with length MAX_TUPLE_STORE */
gm_state->gm_tuple_buffers[i].tuple =
(MinimalTuple *) palloc0(sizeof(MinimalTuple) * MAX_TUPLE_STORE);
/* Initialize tuple slot for worker */
gm_state->gm_slots[i + 1] =
Introduce notion of different types of slots (without implementing them). Upcoming work intends to allow pluggable ways to introduce new ways of storing table data. Accessing those table access methods from the executor requires TupleTableSlots to be carry tuples in the native format of such storage methods; otherwise there'll be a significant conversion overhead. Different access methods will require different data to store tuples efficiently (just like virtual, minimal, heap already require fields in TupleTableSlot). To allow that without requiring additional pointer indirections, we want to have different structs (embedding TupleTableSlot) for different types of slots. Thus different types of slots are needed, which requires adapting creators of slots. The slot that most efficiently can represent a type of tuple in an executor node will often depend on the type of slot a child node uses. Therefore we need to track the type of slot is returned by nodes, so parent slots can create slots based on that. Relatedly, JIT compilation of tuple deforming needs to know which type of slot a certain expression refers to, so it can create an appropriate deforming function for the type of tuple in the slot. But not all nodes will only return one type of slot, e.g. an append node will potentially return different types of slots for each of its subplans. Therefore add function that allows to query the type of a node's result slot, and whether it'll always be the same type (whether it's fixed). This can be queried using ExecGetResultSlotOps(). The scan, result, inner, outer type of slots are automatically inferred from ExecInitScanTupleSlot(), ExecInitResultSlot(), left/right subtrees respectively. If that's not correct for a node, that can be overwritten using new fields in PlanState. This commit does not introduce the actually abstracted implementation of different kind of TupleTableSlots, that will be left for a followup commit. The different types of slots introduced will, for now, still use the same backing implementation. While this already partially invalidates the big comment in tuptable.h, it seems to make more sense to update it later, when the different TupleTableSlot implementations actually exist. Author: Ashutosh Bapat and Andres Freund, with changes by Amit Khandekar Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
2018-11-16 07:00:30 +01:00
ExecInitExtraTupleSlot(gm_state->ps.state, gm_state->tupDesc,
&TTSOpsMinimalTuple);
}
/* Allocate the resources for the merge */
gm_state->gm_heap = binaryheap_allocate(nreaders + 1,
heap_compare_slots,
false,
gm_state);
}
/*
* Initialize the Gather Merge.
*
* Reset data structures to ensure they're empty. Then pull at least one
* tuple from leader + each worker (or set its "done" indicator), and set up
* the heap.
*/
static void
gather_merge_init(GatherMergeState *gm_state)
{
int nreaders = gm_state->nreaders;
bool nowait = true;
int i;
/* Assert that gather_merge_setup made enough space */
Assert(nreaders <= castNode(GatherMerge, gm_state->ps.plan)->num_workers);
/* Reset leader's tuple slot to empty */
gm_state->gm_slots[0] = NULL;
/* Reset the tuple slot and tuple array for each worker */
for (i = 0; i < nreaders; i++)
{
/* Reset tuple array to empty */
gm_state->gm_tuple_buffers[i].nTuples = 0;
gm_state->gm_tuple_buffers[i].readCounter = 0;
/* Reset done flag to not-done */
gm_state->gm_tuple_buffers[i].done = false;
/* Ensure output slot is empty */
ExecClearTuple(gm_state->gm_slots[i + 1]);
}
/* Reset binary heap to empty */
binaryheap_reset(gm_state->gm_heap);
/*
* First, try to read a tuple from each worker (including leader) in
* nowait mode. After this, if not all workers were able to produce a
* tuple (or a "done" indication), then re-read from remaining workers,
* this time using wait mode. Add all live readers (those producing at
* least one tuple) to the heap.
*/
reread:
for (i = 0; i <= nreaders; i++)
{
CHECK_FOR_INTERRUPTS();
/* skip this source if already known done */
if ((i == 0) ? gm_state->need_to_scan_locally :
!gm_state->gm_tuple_buffers[i - 1].done)
{
if (TupIsNull(gm_state->gm_slots[i]))
{
/* Don't have a tuple yet, try to get one */
if (gather_merge_readnext(gm_state, i, nowait))
binaryheap_add_unordered(gm_state->gm_heap,
Int32GetDatum(i));
}
else
{
/*
* We already got at least one tuple from this worker, but
* might as well see if it has any more ready by now.
*/
load_tuple_array(gm_state, i);
}
}
}
/* need not recheck leader, since nowait doesn't matter for it */
for (i = 1; i <= nreaders; i++)
{
if (!gm_state->gm_tuple_buffers[i - 1].done &&
TupIsNull(gm_state->gm_slots[i]))
{
nowait = false;
goto reread;
}
}
/* Now heapify the heap. */
binaryheap_build(gm_state->gm_heap);
gm_state->gm_initialized = true;
}
/*
* Clear out the tuple table slot, and any unused pending tuples,
* for each gather merge input.
*/
static void
gather_merge_clear_tuples(GatherMergeState *gm_state)
{
int i;
for (i = 0; i < gm_state->nreaders; i++)
{
GMReaderTupleBuffer *tuple_buffer = &gm_state->gm_tuple_buffers[i];
while (tuple_buffer->readCounter < tuple_buffer->nTuples)
pfree(tuple_buffer->tuple[tuple_buffer->readCounter++]);
ExecClearTuple(gm_state->gm_slots[i + 1]);
}
}
/*
* 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
{
/* reader exhausted, remove it from heap */
(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_tuples(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 tuple(s) for given reader in nowait mode, and load into its tuple
* array, until we have MAX_TUPLE_STORE of them or would have to block.
*/
static void
load_tuple_array(GatherMergeState *gm_state, int reader)
{
GMReaderTupleBuffer *tuple_buffer;
int i;
/* Don't do anything if this is the leader. */
if (reader == 0)
return;
tuple_buffer = &gm_state->gm_tuple_buffers[reader - 1];
/* If there's nothing in the array, reset the counters to zero. */
if (tuple_buffer->nTuples == tuple_buffer->readCounter)
tuple_buffer->nTuples = tuple_buffer->readCounter = 0;
/* Try to fill additional slots in the array. */
for (i = tuple_buffer->nTuples; i < MAX_TUPLE_STORE; i++)
{
MinimalTuple tuple;
tuple = gm_readnext_tuple(gm_state,
reader,
true,
&tuple_buffer->done);
if (!tuple)
break;
tuple_buffer->tuple[i] = tuple;
tuple_buffer->nTuples++;
}
}
/*
* Store the next tuple for a given reader into the appropriate slot.
*
* Returns true if successful, false if not (either reader is exhausted,
* or we didn't want to wait for a tuple). Sets done flag if reader
* is found to be exhausted.
*/
static bool
gather_merge_readnext(GatherMergeState *gm_state, int reader, bool nowait)
{
GMReaderTupleBuffer *tuple_buffer;
MinimalTuple tup;
/*
* If we're being asked to generate a tuple from the leader, then we just
* call ExecProcNode as normal to produce one.
*/
if (reader == 0)
{
if (gm_state->need_to_scan_locally)
{
PlanState *outerPlan = outerPlanState(gm_state);
TupleTableSlot *outerTupleSlot;
EState *estate = gm_state->ps.state;
/* Install our DSA area while executing the plan. */
estate->es_query_dsa = gm_state->pei ? gm_state->pei->area : NULL;
outerTupleSlot = ExecProcNode(outerPlan);
estate->es_query_dsa = NULL;
if (!TupIsNull(outerTupleSlot))
{
gm_state->gm_slots[0] = outerTupleSlot;
return true;
}
/* need_to_scan_locally serves as "done" flag for leader */
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 - 1];
if (tuple_buffer->nTuples > tuple_buffer->readCounter)
{
/* Return any tuple previously read that is still buffered. */
tup = tuple_buffer->tuple[tuple_buffer->readCounter++];
}
else if (tuple_buffer->done)
{
/* Reader is known to be exhausted. */
return false;
}
else
{
/* Read and buffer next tuple. */
tup = gm_readnext_tuple(gm_state,
reader,
nowait,
&tuple_buffer->done);
if (!tup)
return false;
/*
* Attempt to read more tuples in nowait mode and store them in the
* pending-tuple array for the reader.
*/
load_tuple_array(gm_state, reader);
}
Assert(tup);
/* Build the TupleTableSlot for the given tuple */
ExecStoreMinimalTuple(tup, /* tuple to store */
gm_state->gm_slots[reader], /* slot in which to
* store the tuple */
true); /* pfree tuple when done with it */
return true;
}
/*
* Attempt to read a tuple from given worker.
*/
static MinimalTuple
gm_readnext_tuple(GatherMergeState *gm_state, int nreader, bool nowait,
bool *done)
{
TupleQueueReader *reader;
MinimalTuple tup;
/* Check for async events, particularly messages from workers. */
CHECK_FOR_INTERRUPTS();
/*
* Attempt to read a tuple.
*
* Note that TupleQueueReaderNext will just return NULL for a worker which
* fails to initialize. We'll treat that worker as having produced no
* tuples; WaitForParallelWorkersToFinish will error out when we get
* there.
*/
reader = gm_state->reader[nreader - 1];
tup = TupleQueueReaderNext(reader, nowait, done);
/*
* Since we'll be buffering these across multiple calls, we need to make a
* copy.
*/
return tup ? heap_copy_minimal_tuple(tup) : NULL;
}
/*
* 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)
{
INVERT_COMPARE_RESULT(compare);
return compare;
}
}
return 0;
}