2000-09-29 19:17:41 +02:00
# ----------
2010-09-20 22:08:53 +02:00
# src/test/regress/parallel_schedule
2007-08-21 03:11:32 +02:00
#
# By convention, we put no more than twenty tests in any one parallel group;
# this limits the number of connections needed to run the tests.
# ----------
2009-08-24 05:10:16 +02:00
# run tablespace by itself, and first, because it forces a checkpoint;
# we'd prefer not to have checkpoints later in the tests because that
# interferes with crash-recovery testing.
test: tablespace
2007-08-21 03:11:32 +02:00
# ----------
# The first group of parallel tests
2000-09-29 19:17:41 +02:00
# ----------
2014-04-08 16:27:56 +02:00
test: boolean char name varchar text int2 int4 int8 oid float4 float8 bit numeric txid uuid enum money rangetypes pg_lsn regproc
2000-09-29 19:17:41 +02:00
# ----------
2007-08-21 03:11:32 +02:00
# The second group of parallel tests
Re-order some regression test scripts for more parallelism.
Move the strings, numerology, insert, insert_conflict, select and
errors tests to be parts of nearby parallel groups, instead of
executing by themselves. (Moving "select" required adjusting the
constraints test, which uses a table named "tmp" as select also
does. There don't seem to be any other conflicts.)
Move psql and stats_ext to the next parallel group, where the rules
test also has a long runtime. To make it safe to run stats_ext in
parallel with rules, I adjusted the latter to only dump views/rules
from the pg_catalog and public schemas, which was what it was doing
anyway. stats_ext makes some views in a transient schema, which now
will not affect rules.
Reorder serial_schedule to match parallel_schedule.
Discussion: https://postgr.es/m/735.1554935715@sss.pgh.pa.us
2019-04-12 00:16:50 +02:00
# strings depends on char, varchar and text
# numerology depends on int2, int4, int8, float4, float8
Multirange datatypes
Multiranges are basically sorted arrays of non-overlapping ranges with
set-theoretic operations defined over them.
Since v14, each range type automatically gets a corresponding multirange
datatype. There are both manual and automatic mechanisms for naming multirange
types. Once can specify multirange type name using multirange_type_name
attribute in CREATE TYPE. Otherwise, a multirange type name is generated
automatically. If the range type name contains "range" then we change that to
"multirange". Otherwise, we add "_multirange" to the end.
Implementation of multiranges comes with a space-efficient internal
representation format, which evades extra paddings and duplicated storage of
oids. Altogether this format allows fetching a particular range by its index
in O(n).
Statistic gathering and selectivity estimation are implemented for multiranges.
For this purpose, stored multirange is approximated as union range without gaps.
This field will likely need improvements in the future.
Catversion is bumped.
Discussion: https://postgr.es/m/CALNJ-vSUpQ_Y%3DjXvTxt1VYFztaBSsWVXeF1y6gTYQ4bOiWDLgQ%40mail.gmail.com
Discussion: https://postgr.es/m/a0b8026459d1e6167933be2104a6174e7d40d0ab.camel%40j-davis.com#fe7218c83b08068bfffb0c5293eceda0
Author: Paul Jungwirth, revised by me
Reviewed-by: David Fetter, Corey Huinker, Jeff Davis, Pavel Stehule
Reviewed-by: Alvaro Herrera, Tom Lane, Isaac Morland, David G. Johnston
Reviewed-by: Zhihong Yu, Alexander Korotkov
2020-12-20 05:20:33 +01:00
# multirangetypes depends on rangetypes
# multirangetypes shouldn't be in the one group with type_sanity
2000-09-29 19:17:41 +02:00
# ----------
Multirange datatypes
Multiranges are basically sorted arrays of non-overlapping ranges with
set-theoretic operations defined over them.
Since v14, each range type automatically gets a corresponding multirange
datatype. There are both manual and automatic mechanisms for naming multirange
types. Once can specify multirange type name using multirange_type_name
attribute in CREATE TYPE. Otherwise, a multirange type name is generated
automatically. If the range type name contains "range" then we change that to
"multirange". Otherwise, we add "_multirange" to the end.
Implementation of multiranges comes with a space-efficient internal
representation format, which evades extra paddings and duplicated storage of
oids. Altogether this format allows fetching a particular range by its index
in O(n).
Statistic gathering and selectivity estimation are implemented for multiranges.
For this purpose, stored multirange is approximated as union range without gaps.
This field will likely need improvements in the future.
Catversion is bumped.
Discussion: https://postgr.es/m/CALNJ-vSUpQ_Y%3DjXvTxt1VYFztaBSsWVXeF1y6gTYQ4bOiWDLgQ%40mail.gmail.com
Discussion: https://postgr.es/m/a0b8026459d1e6167933be2104a6174e7d40d0ab.camel%40j-davis.com#fe7218c83b08068bfffb0c5293eceda0
Author: Paul Jungwirth, revised by me
Reviewed-by: David Fetter, Corey Huinker, Jeff Davis, Pavel Stehule
Reviewed-by: Alvaro Herrera, Tom Lane, Isaac Morland, David G. Johnston
Reviewed-by: Zhihong Yu, Alexander Korotkov
2020-12-20 05:20:33 +01:00
test: strings numerology point lseg line box path polygon circle date time timetz timestamp timestamptz interval inet macaddr macaddr8 tstypes multirangetypes
2000-09-29 19:17:41 +02:00
2007-08-21 03:11:32 +02:00
# ----------
# Another group of parallel tests
# geometry depends on point, lseg, box, path, polygon and circle
2018-09-29 00:21:48 +02:00
# horology depends on interval, timetz, timestamp, timestamptz
2007-08-21 03:11:32 +02:00
# ----------
2021-04-06 18:24:50 +02:00
test: geometry horology regex type_sanity opr_sanity misc_sanity comments expressions unicode xid mvcc
2000-09-29 19:17:41 +02:00
# ----------
# These four each depend on the previous one
# ----------
test: create_function_1
test: create_type
test: create_table
test: create_function_2
# ----------
# Load huge amounts of data
# We should split the data files into single files and then
# execute two copy tests parallel, to check that copy itself
# is concurrent safe.
# ----------
Re-order some regression test scripts for more parallelism.
Move the strings, numerology, insert, insert_conflict, select and
errors tests to be parts of nearby parallel groups, instead of
executing by themselves. (Moving "select" required adjusting the
constraints test, which uses a table named "tmp" as select also
does. There don't seem to be any other conflicts.)
Move psql and stats_ext to the next parallel group, where the rules
test also has a long runtime. To make it safe to run stats_ext in
parallel with rules, I adjusted the latter to only dump views/rules
from the pg_catalog and public schemas, which was what it was doing
anyway. stats_ext makes some views in a transient schema, which now
will not affect rules.
Reorder serial_schedule to match parallel_schedule.
Discussion: https://postgr.es/m/735.1554935715@sss.pgh.pa.us
2019-04-12 00:16:50 +02:00
test: copy copyselect copydml insert insert_conflict
2000-09-29 19:17:41 +02:00
# ----------
2011-11-09 05:05:14 +01:00
# More groups of parallel tests
2000-09-29 19:17:41 +02:00
# ----------
2017-11-30 14:46:13 +01:00
test: create_misc create_operator create_procedure
Re-order some regression test scripts for more parallelism.
Move the strings, numerology, insert, insert_conflict, select and
errors tests to be parts of nearby parallel groups, instead of
executing by themselves. (Moving "select" required adjusting the
constraints test, which uses a table named "tmp" as select also
does. There don't seem to be any other conflicts.)
Move psql and stats_ext to the next parallel group, where the rules
test also has a long runtime. To make it safe to run stats_ext in
parallel with rules, I adjusted the latter to only dump views/rules
from the pg_catalog and public schemas, which was what it was doing
anyway. stats_ext makes some views in a transient schema, which now
will not affect rules.
Reorder serial_schedule to match parallel_schedule.
Discussion: https://postgr.es/m/735.1554935715@sss.pgh.pa.us
2019-04-12 00:16:50 +02:00
# These depend on create_misc and create_operator
Split up a couple of long-running regression test scripts.
The point of this change is to increase the potential for parallelism
while running the core regression tests. Most people these days are
using parallel testing modes on multi-core machines, so we might as
well try a bit harder to keep multiple cores busy. Hence, a test that
runs much longer than others in its parallel group is a candidate to
be sub-divided.
In this patch, create_index.sql and join.sql are split up.
I haven't changed the content of the tests in any way, just
moved them.
I moved create_index.sql's SP-GiST-related tests into a new script
create_index_spgist, and moved its btree multilevel page deletion test
over to the existing script btree_index. (btree_index is a more natural
home for that test, and it's shorter than others in its parallel group,
so this doesn't hurt total runtime of that group.) There might be
room for more aggressive splitting of create_index, but this is enough
to improve matters considerably.
Likewise, I moved join.sql's "exercises for the hash join code" into
a new file join_hash. Those exercises contributed three-quarters of
the script's runtime. Which might well be excessive ... but for the
moment, I'm satisfied with shoving them into a different parallel
group, where they can share runtime with the roughly-equally-lengthy
gist test.
(Note for anybody following along at home: there are interesting
interactions between the runtimes of create_index and anything running
in parallel with it, because the tests of CREATE INDEX CONCURRENTLY
in that file will repeatedly block waiting for concurrent transactions
to commit. As committed in this patch, create_index and
create_index_spgist have roughly equal runtimes, but that's mostly an
artifact of forced synchronization of the CONCURRENTLY tests; when run
serially, create_index is much faster. A followup patch will reduce
the runtime of create_index_spgist and thereby also create_index.)
Discussion: https://postgr.es/m/735.1554935715@sss.pgh.pa.us
2019-04-11 22:15:54 +02:00
test: create_index create_index_spgist create_view index_including index_including_gist
2000-09-29 19:17:41 +02:00
2011-11-09 05:05:14 +01:00
# ----------
# Another group of parallel tests
# ----------
2020-10-13 23:44:56 +02:00
test: create_aggregate create_function_3 create_cast constraints triggers select inherit typed_table vacuum drop_if_exists updatable_views roleattributes create_am hash_func errors infinite_recurse
2011-11-09 05:05:14 +01:00
2000-09-29 19:17:41 +02:00
# ----------
# sanity_check does a vacuum, affecting the sort order of SELECT *
# results. So it should not run parallel to other tests.
# ----------
test: sanity_check
# ----------
2007-08-21 03:11:32 +02:00
# Another group of parallel tests
Re-order some regression test scripts for more parallelism.
Move the strings, numerology, insert, insert_conflict, select and
errors tests to be parts of nearby parallel groups, instead of
executing by themselves. (Moving "select" required adjusting the
constraints test, which uses a table named "tmp" as select also
does. There don't seem to be any other conflicts.)
Move psql and stats_ext to the next parallel group, where the rules
test also has a long runtime. To make it safe to run stats_ext in
parallel with rules, I adjusted the latter to only dump views/rules
from the pg_catalog and public schemas, which was what it was doing
anyway. stats_ext makes some views in a transient schema, which now
will not affect rules.
Reorder serial_schedule to match parallel_schedule.
Discussion: https://postgr.es/m/735.1554935715@sss.pgh.pa.us
2019-04-12 00:16:50 +02:00
# Note: the ignore: line does not run random, just mark it as ignorable
2000-09-29 19:17:41 +02:00
# ----------
Re-order some regression test scripts for more parallelism.
Move the strings, numerology, insert, insert_conflict, select and
errors tests to be parts of nearby parallel groups, instead of
executing by themselves. (Moving "select" required adjusting the
constraints test, which uses a table named "tmp" as select also
does. There don't seem to be any other conflicts.)
Move psql and stats_ext to the next parallel group, where the rules
test also has a long runtime. To make it safe to run stats_ext in
parallel with rules, I adjusted the latter to only dump views/rules
from the pg_catalog and public schemas, which was what it was doing
anyway. stats_ext makes some views in a transient schema, which now
will not affect rules.
Reorder serial_schedule to match parallel_schedule.
Discussion: https://postgr.es/m/735.1554935715@sss.pgh.pa.us
2019-04-12 00:16:50 +02:00
ignore: random
test: select_into select_distinct select_distinct_on select_implicit select_having subselect union case join aggregates transactions random portals arrays btree_index hash_index update delete namespace prepared_xacts
2000-09-29 19:17:41 +02:00
2011-03-20 19:35:39 +01:00
# ----------
# Another group of parallel tests
# ----------
Split up a couple of long-running regression test scripts.
The point of this change is to increase the potential for parallelism
while running the core regression tests. Most people these days are
using parallel testing modes on multi-core machines, so we might as
well try a bit harder to keep multiple cores busy. Hence, a test that
runs much longer than others in its parallel group is a candidate to
be sub-divided.
In this patch, create_index.sql and join.sql are split up.
I haven't changed the content of the tests in any way, just
moved them.
I moved create_index.sql's SP-GiST-related tests into a new script
create_index_spgist, and moved its btree multilevel page deletion test
over to the existing script btree_index. (btree_index is a more natural
home for that test, and it's shorter than others in its parallel group,
so this doesn't hurt total runtime of that group.) There might be
room for more aggressive splitting of create_index, but this is enough
to improve matters considerably.
Likewise, I moved join.sql's "exercises for the hash join code" into
a new file join_hash. Those exercises contributed three-quarters of
the script's runtime. Which might well be excessive ... but for the
moment, I'm satisfied with shoving them into a different parallel
group, where they can share runtime with the roughly-equally-lengthy
gist test.
(Note for anybody following along at home: there are interesting
interactions between the runtimes of create_index and anything running
in parallel with it, because the tests of CREATE INDEX CONCURRENTLY
in that file will repeatedly block waiting for concurrent transactions
to commit. As committed in this patch, create_index and
create_index_spgist have roughly equal runtimes, but that's mostly an
artifact of forced synchronization of the CONCURRENTLY tests; when run
serially, create_index is much faster. A followup patch will reduce
the runtime of create_index_spgist and thereby also create_index.)
Discussion: https://postgr.es/m/735.1554935715@sss.pgh.pa.us
2019-04-11 22:15:54 +02:00
test: brin gin gist spgist privileges init_privs security_label collate matview lock replica_identity rowsecurity object_address tablesample groupingsets drop_operator password identity generated join_hash
2012-10-15 18:18:52 +02:00
2021-03-26 13:35:29 +01:00
# ----------
# Additional BRIN tests
# ----------
2021-03-26 13:54:29 +01:00
test: brin_bloom brin_multi
2021-03-26 13:35:29 +01:00
2012-10-15 18:18:52 +02:00
# ----------
# Another group of parallel tests
# ----------
2021-02-27 10:59:36 +01:00
test: create_table_like alter_generic alter_operator misc async dbsize misc_functions sysviews tsrf tid tidscan tidrangescan collate.icu.utf8 incremental_sort
2011-03-20 19:35:39 +01:00
Re-order some regression test scripts for more parallelism.
Move the strings, numerology, insert, insert_conflict, select and
errors tests to be parts of nearby parallel groups, instead of
executing by themselves. (Moving "select" required adjusting the
constraints test, which uses a table named "tmp" as select also
does. There don't seem to be any other conflicts.)
Move psql and stats_ext to the next parallel group, where the rules
test also has a long runtime. To make it safe to run stats_ext in
parallel with rules, I adjusted the latter to only dump views/rules
from the pg_catalog and public schemas, which was what it was doing
anyway. stats_ext makes some views in a transient schema, which now
will not affect rules.
Reorder serial_schedule to match parallel_schedule.
Discussion: https://postgr.es/m/735.1554935715@sss.pgh.pa.us
2019-04-12 00:16:50 +02:00
# rules cannot run concurrently with any test that creates
# a view or rule in the public schema
2019-07-31 09:42:15 +02:00
# collate.*.utf8 tests cannot be run in parallel with each other
test: rules psql psql_crosstab amutils stats_ext collate.linux.utf8
2016-08-22 18:00:00 +02:00
# run by itself so it can run parallel workers
test: select_parallel
2017-10-05 17:34:38 +02:00
test: write_parallel
2000-09-29 19:17:41 +02:00
2017-01-19 18:00:00 +01:00
# no relation related tests can be put in this group
test: publication subscription
2000-09-29 19:17:41 +02:00
# ----------
2007-08-21 03:11:32 +02:00
# Another group of parallel tests
2000-09-29 19:17:41 +02:00
# ----------
Partial implementation of SQL/JSON path language
SQL 2016 standards among other things contains set of SQL/JSON features for
JSON processing inside of relational database. The core of SQL/JSON is JSON
path language, allowing access parts of JSON documents and make computations
over them. This commit implements partial support JSON path language as
separate datatype called "jsonpath". The implementation is partial because
it's lacking datetime support and suppression of numeric errors. Missing
features will be added later by separate commits.
Support of SQL/JSON features requires implementation of separate nodes, and it
will be considered in subsequent patches. This commit includes following
set of plain functions, allowing to execute jsonpath over jsonb values:
* jsonb_path_exists(jsonb, jsonpath[, jsonb, bool]),
* jsonb_path_match(jsonb, jsonpath[, jsonb, bool]),
* jsonb_path_query(jsonb, jsonpath[, jsonb, bool]),
* jsonb_path_query_array(jsonb, jsonpath[, jsonb, bool]).
* jsonb_path_query_first(jsonb, jsonpath[, jsonb, bool]).
This commit also implements "jsonb @? jsonpath" and "jsonb @@ jsonpath", which
are wrappers over jsonpath_exists(jsonb, jsonpath) and jsonpath_predicate(jsonb,
jsonpath) correspondingly. These operators will have an index support
(implemented in subsequent patches).
Catversion bumped, to add new functions and operators.
Code was written by Nikita Glukhov and Teodor Sigaev, revised by me.
Documentation was written by Oleg Bartunov and Liudmila Mantrova. The work
was inspired by Oleg Bartunov.
Discussion: https://postgr.es/m/fcc6fc6a-b497-f39a-923d-aa34d0c588e8%402ndQuadrant.com
Author: Nikita Glukhov, Teodor Sigaev, Alexander Korotkov, Oleg Bartunov, Liudmila Mantrova
Reviewed-by: Tomas Vondra, Andrew Dunstan, Pavel Stehule, Alexander Korotkov
2019-03-16 10:15:37 +01:00
test: select_views portals_p2 foreign_key cluster dependency guc bitmapops combocid tsearch tsdicts foreign_data window xmlmap functional_deps advisory_lock indirect_toast equivclass
# ----------
# Another group of parallel tests (JSON related)
# ----------
2019-03-25 13:43:56 +01:00
test: json jsonb json_encoding jsonpath jsonpath_encoding jsonb_jsonpath
Basic partition-wise join functionality.
Instead of joining two partitioned tables in their entirety we can, if
it is an equi-join on the partition keys, join the matching partitions
individually. This involves teaching the planner about "other join"
rels, which are related to regular join rels in the same way that
other member rels are related to baserels. This can use significantly
more CPU time and memory than regular join planning, because there may
now be a set of "other" rels not only for every base relation but also
for every join relation. In most practical cases, this probably
shouldn't be a problem, because (1) it's probably unusual to join many
tables each with many partitions using the partition keys for all
joins and (2) if you do that scenario then you probably have a big
enough machine to handle the increased memory cost of planning and (3)
the resulting plan is highly likely to be better, so what you spend in
planning you'll make up on the execution side. All the same, for now,
turn this feature off by default.
Currently, we can only perform joins between two tables whose
partitioning schemes are absolutely identical. It would be nice to
cope with other scenarios, such as extra partitions on one side or the
other with no match on the other side, but that will have to wait for
a future patch.
Ashutosh Bapat, reviewed and tested by Rajkumar Raghuwanshi, Amit
Langote, Rafia Sabih, Thomas Munro, Dilip Kumar, Antonin Houska, Amit
Khandekar, and by me. A few final adjustments by me.
Discussion: http://postgr.es/m/CAFjFpRfQ8GrQvzp3jA2wnLqrHmaXna-urjm_UY9BqXj=EaDTSA@mail.gmail.com
Discussion: http://postgr.es/m/CAFjFpRcitjfrULr5jfuKWRPsGUX0LQ0k8-yG0Qw2+1LBGNpMdw@mail.gmail.com
2017-10-06 17:11:10 +02:00
2000-09-29 19:17:41 +02:00
# ----------
2007-08-21 03:11:32 +02:00
# Another group of parallel tests
2008-12-30 18:11:26 +01:00
# NB: temp.sql does a reconnect which transiently uses 2 connections,
# so keep this parallel group to at most 19 tests
2000-09-29 19:17:41 +02:00
# ----------
Remove WITH OIDS support, change oid catalog column visibility.
Previously tables declared WITH OIDS, including a significant fraction
of the catalog tables, stored the oid column not as a normal column,
but as part of the tuple header.
This special column was not shown by default, which was somewhat odd,
as it's often (consider e.g. pg_class.oid) one of the more important
parts of a row. Neither pg_dump nor COPY included the contents of the
oid column by default.
The fact that the oid column was not an ordinary column necessitated a
significant amount of special case code to support oid columns. That
already was painful for the existing, but upcoming work aiming to make
table storage pluggable, would have required expanding and duplicating
that "specialness" significantly.
WITH OIDS has been deprecated since 2005 (commit ff02d0a05280e0).
Remove it.
Removing includes:
- CREATE TABLE and ALTER TABLE syntax for declaring the table to be
WITH OIDS has been removed (WITH (oids[ = true]) will error out)
- pg_dump does not support dumping tables declared WITH OIDS and will
issue a warning when dumping one (and ignore the oid column).
- restoring an pg_dump archive with pg_restore will warn when
restoring a table with oid contents (and ignore the oid column)
- COPY will refuse to load binary dump that includes oids.
- pg_upgrade will error out when encountering tables declared WITH
OIDS, they have to be altered to remove the oid column first.
- Functionality to access the oid of the last inserted row (like
plpgsql's RESULT_OID, spi's SPI_lastoid, ...) has been removed.
The syntax for declaring a table WITHOUT OIDS (or WITH (oids = false)
for CREATE TABLE) is still supported. While that requires a bit of
support code, it seems unnecessary to break applications / dumps that
do not use oids, and are explicit about not using them.
The biggest user of WITH OID columns was postgres' catalog. This
commit changes all 'magic' oid columns to be columns that are normally
declared and stored. To reduce unnecessary query breakage all the
newly added columns are still named 'oid', even if a table's column
naming scheme would indicate 'reloid' or such. This obviously
requires adapting a lot code, mostly replacing oid access via
HeapTupleGetOid() with access to the underlying Form_pg_*->oid column.
The bootstrap process now assigns oids for all oid columns in
genbki.pl that do not have an explicit value (starting at the largest
oid previously used), only oids assigned later by oids will be above
FirstBootstrapObjectId. As the oid column now is a normal column the
special bootstrap syntax for oids has been removed.
Oids are not automatically assigned during insertion anymore, all
backend code explicitly assigns oids with GetNewOidWithIndex(). For
the rare case that insertions into the catalog via SQL are called for
the new pg_nextoid() function can be used (which only works on catalog
tables).
The fact that oid columns on system tables are now normal columns
means that they will be included in the set of columns expanded
by * (i.e. SELECT * FROM pg_class will now include the table's oid,
previously it did not). It'd not technically be hard to hide oid
column by default, but that'd mean confusing behavior would either
have to be carried forward forever, or it'd cause breakage down the
line.
While it's not unlikely that further adjustments are needed, the
scope/invasiveness of the patch makes it worthwhile to get merge this
now. It's painful to maintain externally, too complicated to commit
after the code code freeze, and a dependency of a number of other
patches.
Catversion bump, for obvious reasons.
Author: Andres Freund, with contributions by John Naylor
Discussion: https://postgr.es/m/20180930034810.ywp2c7awz7opzcfr@alap3.anarazel.de
2018-11-21 00:36:57 +01:00
test: plancache limit plpgsql copy2 temp domain rangefuncs prepare conversion truncate alter_table sequence polymorphism rowtypes returning largeobject with xml
2004-01-27 01:50:33 +01:00
2017-04-06 14:33:16 +02:00
# ----------
# Another group of parallel tests
# ----------
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 03:10:56 +02:00
test: partition_join partition_prune reloptions hash_part indexing partition_aggregate partition_info tuplesort explain compression resultcache
2017-04-06 14:33:16 +02:00
2014-12-07 16:55:28 +01:00
# event triggers cannot run concurrently with any test that runs DDL
Build in some knowledge about foreign-key relationships in the catalogs.
This follows in the spirit of commit dfb75e478, which created primary
key and uniqueness constraints to improve the visibility of constraints
imposed on the system catalogs. While our catalogs contain many
foreign-key-like relationships, they don't quite follow SQL semantics,
in that the convention for an omitted reference is to write zero not
NULL. Plus, we have some cases in which there are arrays each of whose
elements is supposed to be an FK reference; SQL has no way to model that.
So we can't create actual foreign key constraints to describe the
situation. Nonetheless, we can collect and use knowledge about these
relationships.
This patch therefore adds annotations to the catalog header files to
declare foreign-key relationships. (The BKI_LOOKUP annotations cover
simple cases, but we weren't previously distinguishing which such
columns are allowed to contain zeroes; we also need new markings for
multi-column FK references.) Then, Catalog.pm and genbki.pl are
taught to collect this information into a table in a new generated
header "system_fk_info.h". The only user of that at the moment is
a new SQL function pg_get_catalog_foreign_keys(), which exposes the
table to SQL. The oidjoins regression test is rewritten to use
pg_get_catalog_foreign_keys() to find out which columns to check.
Aside from removing the need for manual maintenance of that test
script, this allows it to cover numerous relationships that were not
checked by the old implementation based on findoidjoins. (As of this
commit, 217 relationships are checked by the test, versus 181 before.)
Discussion: https://postgr.es/m/3240355.1612129197@sss.pgh.pa.us
2021-02-02 23:11:55 +01:00
# oidjoins is read-only, though, and should run late for best coverage
test: event_trigger oidjoins
2018-04-20 23:27:56 +02:00
# this test also uses event triggers, so likewise run it by itself
test: fast_default
2014-12-07 16:55:28 +01:00
2004-01-27 01:50:33 +01:00
# run stats by itself because its delay may be insufficient under heavy load
test: stats