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9eacee2e62d89cab7b004f97c206c4fba4f1d745
postgresql/src/include/optimizer/pathnode.h
David Rowley 9eacee2e62 Add Result Cache executor node (take 2) 
Here we add a new executor node type named "Result Cache".  The planner
can include this node type in the plan to have the executor cache the
results from the inner side of parameterized nested loop joins.  This
allows caching of tuples for sets of parameters so that in the event that
the node sees the same parameter values again, it can just return the
cached tuples instead of rescanning the inner side of the join all over
again.  Internally, result cache uses a hash table in order to quickly
find tuples that have been previously cached.

For certain data sets, this can significantly improve the performance of
joins.  The best cases for using this new node type are for join problems
where a large portion of the tuples from the inner side of the join have
no join partner on the outer side of the join.  In such cases, hash join
would have to hash values that are never looked up, thus bloating the hash
table and possibly causing it to multi-batch.  Merge joins would have to
skip over all of the unmatched rows.  If we use a nested loop join with a
result cache, then we only cache tuples that have at least one join
partner on the outer side of the join.  The benefits of using a
parameterized nested loop with a result cache increase when there are
fewer distinct values being looked up and the number of lookups of each
value is large.  Also, hash probes to lookup the cache can be much faster
than the hash probe in a hash join as it's common that the result cache's
hash table is much smaller than the hash join's due to result cache only
caching useful tuples rather than all tuples from the inner side of the
join.  This variation in hash probe performance is more significant when
the hash join's hash table no longer fits into the CPU's L3 cache, but the
result cache's hash table does.  The apparent "random" access of hash
buckets with each hash probe can cause a poor L3 cache hit ratio for large
hash tables.  Smaller hash tables generally perform better.

The hash table used for the cache limits itself to not exceeding work_mem
* hash_mem_multiplier in size.  We maintain a dlist of keys for this cache
and when we're adding new tuples and realize we've exceeded the memory
budget, we evict cache entries starting with the least recently used ones
until we have enough memory to add the new tuples to the cache.

For parameterized nested loop joins, we now consider using one of these
result cache nodes in between the nested loop node and its inner node.  We
determine when this might be useful based on cost, which is primarily
driven off of what the expected cache hit ratio will be.  Estimating the
cache hit ratio relies on having good distinct estimates on the nested
loop's parameters.

For now, the planner will only consider using a result cache for
parameterized nested loop joins.  This works for both normal joins and
also for LATERAL type joins to subqueries.  It is possible to use this new
node for other uses in the future.  For example, to cache results from
correlated subqueries.  However, that's not done here due to some
difficulties obtaining a distinct estimation on the outer plan to
calculate the estimated cache hit ratio.  Currently we plan the inner plan
before planning the outer plan so there is no good way to know if a result
cache would be useful or not since we can't estimate the number of times
the subplan will be called until the outer plan is generated.

The functionality being added here is newly introducing a dependency on
the return value of estimate_num_groups() during the join search.
Previously, during the join search, we only ever needed to perform
selectivity estimations.  With this commit, we need to use
estimate_num_groups() in order to estimate what the hit ratio on the
result cache will be.   In simple terms, if we expect 10 distinct values
and we expect 1000 outer rows, then we'll estimate the hit ratio to be
99%.  Since cache hits are very cheap compared to scanning the underlying
nodes on the inner side of the nested loop join, then this will
significantly reduce the planner's cost for the join.   However, it's
fairly easy to see here that things will go bad when estimate_num_groups()
incorrectly returns a value that's significantly lower than the actual
number of distinct values.  If this happens then that may cause us to make
use of a nested loop join with a result cache instead of some other join
type, such as a merge or hash join.  Our distinct estimations have been
known to be a source of trouble in the past, so the extra reliance on them
here could cause the planner to choose slower plans than it did previous
to having this feature.  Distinct estimations are also fairly hard to
estimate accurately when several tables have been joined already or when a
WHERE clause filters out a set of values that are correlated to the
expressions we're estimating the number of distinct value for.

For now, the costing we perform during query planning for result caches
does put quite a bit of faith in the distinct estimations being accurate.
When these are accurate then we should generally see faster execution
times for plans containing a result cache.  However, in the real world, we
may find that we need to either change the costings to put less trust in
the distinct estimations being accurate or perhaps even disable this
feature by default.  There's always an element of risk when we teach the
query planner to do new tricks that it decides to use that new trick at
the wrong time and causes a regression.  Users may opt to get the old
behavior by turning the feature off using the enable_resultcache GUC.
Currently, this is enabled by default.  It remains to be seen if we'll
maintain that setting for the release.

Additionally, the name "Result Cache" is the best name I could think of
for this new node at the time I started writing the patch.  Nobody seems
to strongly dislike the name. A few people did suggest other names but no
other name seemed to dominate in the brief discussion that there was about
names. Let's allow the beta period to see if the current name pleases
enough people.  If there's some consensus on a better name, then we can
change it before the release.  Please see the 2nd discussion link below
for the discussion on the "Result Cache" name.

Author: David Rowley
Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu, Hou Zhijie
Tested-By: Konstantin Knizhnik
Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com
2021-04-02 14:10:56 +13:00

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/*-------------------------------------------------------------------------
*
* pathnode.h
* prototypes for pathnode.c, relnode.c.
*
*
* Portions Copyright (c) 1996-2021, PostgreSQL Global Development Group
* Portions Copyright (c) 1994, Regents of the University of California
*
* src/include/optimizer/pathnode.h
*
*-------------------------------------------------------------------------
*/
#ifndef PATHNODE_H
#define PATHNODE_H
#include "nodes/bitmapset.h"
#include "nodes/pathnodes.h"
/*
* prototypes for pathnode.c
*/
extern int compare_path_costs(Path *path1, Path *path2,
CostSelector criterion);
extern int compare_fractional_path_costs(Path *path1, Path *path2,
double fraction);
extern void set_cheapest(RelOptInfo *parent_rel);
extern void add_path(RelOptInfo *parent_rel, Path *new_path);
extern bool add_path_precheck(RelOptInfo *parent_rel,
Cost startup_cost, Cost total_cost,
List *pathkeys, Relids required_outer);
extern void add_partial_path(RelOptInfo *parent_rel, Path *new_path);
extern bool add_partial_path_precheck(RelOptInfo *parent_rel,
Cost total_cost, List *pathkeys);
extern Path *create_seqscan_path(PlannerInfo *root, RelOptInfo *rel,
Relids required_outer, int parallel_workers);
extern Path *create_samplescan_path(PlannerInfo *root, RelOptInfo *rel,
Relids required_outer);
extern IndexPath *create_index_path(PlannerInfo *root,
IndexOptInfo *index,
List *indexclauses,
List *indexorderbys,
List *indexorderbycols,
List *pathkeys,
ScanDirection indexscandir,
bool indexonly,
Relids required_outer,
double loop_count,
bool partial_path);
extern BitmapHeapPath *create_bitmap_heap_path(PlannerInfo *root,
RelOptInfo *rel,
Path *bitmapqual,
Relids required_outer,
double loop_count,
int parallel_degree);
extern BitmapAndPath *create_bitmap_and_path(PlannerInfo *root,
RelOptInfo *rel,
List *bitmapquals);
extern BitmapOrPath *create_bitmap_or_path(PlannerInfo *root,
RelOptInfo *rel,
List *bitmapquals);
extern TidPath *create_tidscan_path(PlannerInfo *root, RelOptInfo *rel,
List *tidquals, Relids required_outer);
extern TidRangePath *create_tidrangescan_path(PlannerInfo *root,
RelOptInfo *rel,
List *tidrangequals,
Relids required_outer);
extern AppendPath *create_append_path(PlannerInfo *root, RelOptInfo *rel,
List *subpaths, List *partial_subpaths,
List *pathkeys, Relids required_outer,
int parallel_workers, bool parallel_aware,
double rows);
extern MergeAppendPath *create_merge_append_path(PlannerInfo *root,
RelOptInfo *rel,
List *subpaths,
List *pathkeys,
Relids required_outer);
extern GroupResultPath *create_group_result_path(PlannerInfo *root,
RelOptInfo *rel,
PathTarget *target,
List *havingqual);
extern MaterialPath *create_material_path(RelOptInfo *rel, Path *subpath);
extern ResultCachePath *create_resultcache_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
List *param_exprs,
List *hash_operators,
bool singlerow,
double calls);
extern UniquePath *create_unique_path(PlannerInfo *root, RelOptInfo *rel,
Path *subpath, SpecialJoinInfo *sjinfo);
extern GatherPath *create_gather_path(PlannerInfo *root,
RelOptInfo *rel, Path *subpath, PathTarget *target,
Relids required_outer, double *rows);
extern GatherMergePath *create_gather_merge_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
PathTarget *target,
List *pathkeys,
Relids required_outer,
double *rows);
extern SubqueryScanPath *create_subqueryscan_path(PlannerInfo *root,
RelOptInfo *rel, Path *subpath,
List *pathkeys, Relids required_outer);
extern Path *create_functionscan_path(PlannerInfo *root, RelOptInfo *rel,
List *pathkeys, Relids required_outer);
extern Path *create_valuesscan_path(PlannerInfo *root, RelOptInfo *rel,
Relids required_outer);
extern Path *create_tablefuncscan_path(PlannerInfo *root, RelOptInfo *rel,
Relids required_outer);
extern Path *create_ctescan_path(PlannerInfo *root, RelOptInfo *rel,
Relids required_outer);
extern Path *create_namedtuplestorescan_path(PlannerInfo *root, RelOptInfo *rel,
Relids required_outer);
extern Path *create_resultscan_path(PlannerInfo *root, RelOptInfo *rel,
Relids required_outer);
extern Path *create_worktablescan_path(PlannerInfo *root, RelOptInfo *rel,
Relids required_outer);
extern ForeignPath *create_foreignscan_path(PlannerInfo *root, RelOptInfo *rel,
PathTarget *target,
double rows, Cost startup_cost, Cost total_cost,
List *pathkeys,
Relids required_outer,
Path *fdw_outerpath,
List *fdw_private);
extern ForeignPath *create_foreign_join_path(PlannerInfo *root, RelOptInfo *rel,
PathTarget *target,
double rows, Cost startup_cost, Cost total_cost,
List *pathkeys,
Relids required_outer,
Path *fdw_outerpath,
List *fdw_private);
extern ForeignPath *create_foreign_upper_path(PlannerInfo *root, RelOptInfo *rel,
PathTarget *target,
double rows, Cost startup_cost, Cost total_cost,
List *pathkeys,
Path *fdw_outerpath,
List *fdw_private);
extern Relids calc_nestloop_required_outer(Relids outerrelids,
Relids outer_paramrels,
Relids innerrelids,
Relids inner_paramrels);
extern Relids calc_non_nestloop_required_outer(Path *outer_path, Path *inner_path);
extern NestPath *create_nestloop_path(PlannerInfo *root,
RelOptInfo *joinrel,
JoinType jointype,
JoinCostWorkspace *workspace,
JoinPathExtraData *extra,
Path *outer_path,
Path *inner_path,
List *restrict_clauses,
List *pathkeys,
Relids required_outer);
extern MergePath *create_mergejoin_path(PlannerInfo *root,
RelOptInfo *joinrel,
JoinType jointype,
JoinCostWorkspace *workspace,
JoinPathExtraData *extra,
Path *outer_path,
Path *inner_path,
List *restrict_clauses,
List *pathkeys,
Relids required_outer,
List *mergeclauses,
List *outersortkeys,
List *innersortkeys);
extern HashPath *create_hashjoin_path(PlannerInfo *root,
RelOptInfo *joinrel,
JoinType jointype,
JoinCostWorkspace *workspace,
JoinPathExtraData *extra,
Path *outer_path,
Path *inner_path,
bool parallel_hash,
List *restrict_clauses,
Relids required_outer,
List *hashclauses);
extern ProjectionPath *create_projection_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
PathTarget *target);
extern Path *apply_projection_to_path(PlannerInfo *root,
RelOptInfo *rel,
Path *path,
PathTarget *target);
extern ProjectSetPath *create_set_projection_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
PathTarget *target);
extern SortPath *create_sort_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
List *pathkeys,
double limit_tuples);
extern IncrementalSortPath *create_incremental_sort_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
List *pathkeys,
int presorted_keys,
double limit_tuples);
extern GroupPath *create_group_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
List *groupClause,
List *qual,
double numGroups);
extern UpperUniquePath *create_upper_unique_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
int numCols,
double numGroups);
extern AggPath *create_agg_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
PathTarget *target,
AggStrategy aggstrategy,
AggSplit aggsplit,
List *groupClause,
List *qual,
const AggClauseCosts *aggcosts,
double numGroups);
extern GroupingSetsPath *create_groupingsets_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
List *having_qual,
AggStrategy aggstrategy,
List *rollups,
const AggClauseCosts *agg_costs,
double numGroups);
extern MinMaxAggPath *create_minmaxagg_path(PlannerInfo *root,
RelOptInfo *rel,
PathTarget *target,
List *mmaggregates,
List *quals);
extern WindowAggPath *create_windowagg_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
PathTarget *target,
List *windowFuncs,
WindowClause *winclause);
extern SetOpPath *create_setop_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
SetOpCmd cmd,
SetOpStrategy strategy,
List *distinctList,
AttrNumber flagColIdx,
int firstFlag,
double numGroups,
double outputRows);
extern RecursiveUnionPath *create_recursiveunion_path(PlannerInfo *root,
RelOptInfo *rel,
Path *leftpath,
Path *rightpath,
PathTarget *target,
List *distinctList,
int wtParam,
double numGroups);
extern LockRowsPath *create_lockrows_path(PlannerInfo *root, RelOptInfo *rel,
Path *subpath, List *rowMarks, int epqParam);
extern ModifyTablePath *create_modifytable_path(PlannerInfo *root,
RelOptInfo *rel,
Path *subpath,
CmdType operation, bool canSetTag,
Index nominalRelation, Index rootRelation,
bool partColsUpdated,
List *resultRelations,
List *updateColnosLists,
List *withCheckOptionLists, List *returningLists,
List *rowMarks, OnConflictExpr *onconflict,
int epqParam);
extern LimitPath *create_limit_path(PlannerInfo *root, RelOptInfo *rel,
Path *subpath,
Node *limitOffset, Node *limitCount,
LimitOption limitOption,
int64 offset_est, int64 count_est);
extern void adjust_limit_rows_costs(double *rows,
Cost *startup_cost, Cost *total_cost,
int64 offset_est, int64 count_est);
extern Path *reparameterize_path(PlannerInfo *root, Path *path,
Relids required_outer,
double loop_count);
extern Path *reparameterize_path_by_child(PlannerInfo *root, Path *path,
RelOptInfo *child_rel);
/*
* prototypes for relnode.c
*/
extern void setup_simple_rel_arrays(PlannerInfo *root);
extern void expand_planner_arrays(PlannerInfo *root, int add_size);
extern RelOptInfo *build_simple_rel(PlannerInfo *root, int relid,
RelOptInfo *parent);
extern RelOptInfo *find_base_rel(PlannerInfo *root, int relid);
extern RelOptInfo *find_join_rel(PlannerInfo *root, Relids relids);
extern RelOptInfo *build_join_rel(PlannerInfo *root,
Relids joinrelids,
RelOptInfo *outer_rel,
RelOptInfo *inner_rel,
SpecialJoinInfo *sjinfo,
List **restrictlist_ptr);
extern Relids min_join_parameterization(PlannerInfo *root,
Relids joinrelids,
RelOptInfo *outer_rel,
RelOptInfo *inner_rel);
extern RelOptInfo *fetch_upper_rel(PlannerInfo *root, UpperRelationKind kind,
Relids relids);
extern Relids find_childrel_parents(PlannerInfo *root, RelOptInfo *rel);
extern ParamPathInfo *get_baserel_parampathinfo(PlannerInfo *root,
RelOptInfo *baserel,
Relids required_outer);
extern ParamPathInfo *get_joinrel_parampathinfo(PlannerInfo *root,
RelOptInfo *joinrel,
Path *outer_path,
Path *inner_path,
SpecialJoinInfo *sjinfo,
Relids required_outer,
List **restrict_clauses);
extern ParamPathInfo *get_appendrel_parampathinfo(RelOptInfo *appendrel,
Relids required_outer);
extern ParamPathInfo *find_param_path_info(RelOptInfo *rel,
Relids required_outer);
extern RelOptInfo *build_child_join_rel(PlannerInfo *root,
RelOptInfo *outer_rel, RelOptInfo *inner_rel,
RelOptInfo *parent_joinrel, List *restrictlist,
SpecialJoinInfo *sjinfo, JoinType jointype);
#endif /* PATHNODE_H */
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