postgresql/src/test/regress/parallel_schedule

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# ----------
2010-09-20 22:08:53 +02:00
# src/test/regress/parallel_schedule
#
# Most test scripts can be run after running just test_setup and possibly
# create_index. Exceptions to this rule are documented below.
#
# 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.
# ----------
# required setup steps
test: test_setup
# ----------
# The first group of parallel tests
# ----------
test: boolean char name varchar text int2 int4 int8 oid float4 float8 bit numeric txid uuid enum money rangetypes pg_lsn regproc
# ----------
# The second group of parallel tests
2020-12-20 05:20:33 +01:00
# multirangetypes depends on rangetypes
Replace opr_sanity test's binary_coercible() function with C code. opr_sanity's binary_coercible() function has always been meant to match the parser's notion of binary coercibility, but it also has always been a rather poor approximation of the parser's real rules (as embodied in IsBinaryCoercible()). That hasn't bit us so far, but it's predictable that it will eventually. It also now emerges that implementing this check in plpgsql performs absolutely horribly in clobber-cache-always testing. (Perhaps we could do something about that, but I suspect it just means that plpgsql is exploiting catalog caching to the hilt.) Hence, let's replace binary_coercible() with a C shim that directly invokes IsBinaryCoercible(), eliminating both the semantic hazard and the performance issue. Most of regress.c's C functions are declared in create_function_1, but we can't simply move that to before opr_sanity/type_sanity since those tests would complain about the resulting shell types. I chose to split it into create_function_0 and create_function_1. Since create_function_0 now runs as part of a parallel group while create_function_1 doesn't, reduce the latter to create just those functions that opr_sanity and type_sanity would whine about. To make room for create_function_0 in the second parallel group of tests, move tstypes to the third parallel group. In passing, clean up some ordering deviations between parallel_schedule and serial_schedule. Discussion: https://postgr.es/m/292305.1620503097@sss.pgh.pa.us
2021-05-11 20:28:11 +02:00
# multirangetypes shouldn't run concurrently with type_sanity
# ----------
test: strings md5 numerology point lseg line box path polygon circle date time timetz timestamp timestamptz interval inet macaddr macaddr8 multirangetypes
# ----------
# Another group of parallel tests
# geometry depends on point, lseg, line, box, path, polygon, circle
# horology depends on date, time, timetz, timestamp, timestamptz, interval
# ----------
Replace opr_sanity test's binary_coercible() function with C code. opr_sanity's binary_coercible() function has always been meant to match the parser's notion of binary coercibility, but it also has always been a rather poor approximation of the parser's real rules (as embodied in IsBinaryCoercible()). That hasn't bit us so far, but it's predictable that it will eventually. It also now emerges that implementing this check in plpgsql performs absolutely horribly in clobber-cache-always testing. (Perhaps we could do something about that, but I suspect it just means that plpgsql is exploiting catalog caching to the hilt.) Hence, let's replace binary_coercible() with a C shim that directly invokes IsBinaryCoercible(), eliminating both the semantic hazard and the performance issue. Most of regress.c's C functions are declared in create_function_1, but we can't simply move that to before opr_sanity/type_sanity since those tests would complain about the resulting shell types. I chose to split it into create_function_0 and create_function_1. Since create_function_0 now runs as part of a parallel group while create_function_1 doesn't, reduce the latter to create just those functions that opr_sanity and type_sanity would whine about. To make room for create_function_0 in the second parallel group of tests, move tstypes to the third parallel group. In passing, clean up some ordering deviations between parallel_schedule and serial_schedule. Discussion: https://postgr.es/m/292305.1620503097@sss.pgh.pa.us
2021-05-11 20:28:11 +02:00
test: geometry horology tstypes regex type_sanity opr_sanity misc_sanity comments expressions unicode xid mvcc
# ----------
# Load huge amounts of data
# We should split the data files into single files and then
# execute two copy tests in parallel, to check that copy itself
# is concurrent safe.
# ----------
test: copy copyselect copydml insert insert_conflict
# ----------
# More groups of parallel tests
# Note: many of the tests in later groups depend on create_index
# ----------
Fix crashes with CREATE SCHEMA AUTHORIZATION and schema elements CREATE SCHEMA AUTHORIZATION with appended schema elements can lead to crashes when comparing the schema name of the query with the schemas used in the qualification of some clauses in the elements' queries. The origin of the problem is that the transformation routine for the elements listed in a CREATE SCHEMA query uses as new, expected, schema name the one listed in CreateSchemaStmt itself. However, depending on the query, CreateSchemaStmt.schemaname may be NULL, being computed instead from the role specification of the query given by the AUTHORIZATION clause, that could be either: - A user name string, with the new schema name being set to the same value as the role given. - Guessed from CURRENT_ROLE, SESSION_ROLE or CURRENT_ROLE, with a new schema name computed from the security context where CREATE SCHEMA is running. Regression tests are added for CREATE SCHEMA with some appended elements (some of them with schema qualifications), covering also some role specification patterns. While on it, this simplifies the context structure used during the transformation of the elements listed in a CREATE SCHEMA query by removing the fields for the role specification and the role type. They were not used, and for the role specification this could be confusing as the schema name may by extracted from that at the beginning of CreateSchemaCommand(). This issue exists for a long time, so backpatch down to all the versions supported. Reported-by: Song Hongyu Author: Michael Paquier Reviewed-by: Richard Guo Discussion: https://postgr.es/m/17909-f65c12dfc5f0451d@postgresql.org Backpatch-through: 11
2023-04-28 12:29:12 +02:00
test: create_function_c create_misc create_operator create_procedure create_table create_type create_schema
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
# ----------
# Another group of parallel tests
# ----------
test: create_aggregate create_function_sql create_cast constraints triggers select inherit typed_table vacuum drop_if_exists updatable_views roleattributes create_am hash_func errors infinite_recurse
# ----------
# sanity_check does a vacuum, affecting the sort order of SELECT *
# results. So it should not run parallel to other tests.
# ----------
test: sanity_check
# ----------
# Another group of parallel tests
# aggregates depends on create_aggregate
# join depends on create_misc
# ----------
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
# ----------
# 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
BRIN bloom indexes Adds a BRIN opclass using a Bloom filter to summarize the range. Indexes using the new opclasses allow only equality queries (similar to hash indexes), but that works fine for data like UUID, MAC addresses etc. for which range queries are not very common. This also means the indexes work for data that is not well correlated to physical location within the table, or perhaps even entirely random (which is a common issue with existing BRIN minmax opclasses). It's possible to specify opclass parameters with the usual Bloom filter parameters, i.e. the desired false-positive rate and the expected number of distinct values per page range. CREATE TABLE t (a int); CREATE INDEX ON t USING brin (a int4_bloom_ops(false_positive_rate = 0.05, n_distinct_per_range = 100)); The opclasses do not operate on the indexed values directly, but compute a 32-bit hash first, and the Bloom filter is built on the hash value. Collisions should not be a huge issue though, as the number of distinct values in a page ranges is usually fairly small. Bump catversion, due to various catalog changes. Author: Tomas Vondra <tomas.vondra@postgresql.org> Reviewed-by: Alvaro Herrera <alvherre@alvh.no-ip.org> Reviewed-by: Alexander Korotkov <aekorotkov@gmail.com> Reviewed-by: Sokolov Yura <y.sokolov@postgrespro.ru> Reviewed-by: Nico Williams <nico@cryptonector.com> Reviewed-by: John Naylor <john.naylor@enterprisedb.com> Discussion: https://postgr.es/m/c1138ead-7668-f0e1-0638-c3be3237e812@2ndquadrant.com Discussion: https://postgr.es/m/5d78b774-7e9c-c94e-12cf-fef51cc89b1a%402ndquadrant.com
2021-03-26 13:35:29 +01:00
# ----------
# Additional BRIN tests
# ----------
test: brin_bloom brin_multi
BRIN bloom indexes Adds a BRIN opclass using a Bloom filter to summarize the range. Indexes using the new opclasses allow only equality queries (similar to hash indexes), but that works fine for data like UUID, MAC addresses etc. for which range queries are not very common. This also means the indexes work for data that is not well correlated to physical location within the table, or perhaps even entirely random (which is a common issue with existing BRIN minmax opclasses). It's possible to specify opclass parameters with the usual Bloom filter parameters, i.e. the desired false-positive rate and the expected number of distinct values per page range. CREATE TABLE t (a int); CREATE INDEX ON t USING brin (a int4_bloom_ops(false_positive_rate = 0.05, n_distinct_per_range = 100)); The opclasses do not operate on the indexed values directly, but compute a 32-bit hash first, and the Bloom filter is built on the hash value. Collisions should not be a huge issue though, as the number of distinct values in a page ranges is usually fairly small. Bump catversion, due to various catalog changes. Author: Tomas Vondra <tomas.vondra@postgresql.org> Reviewed-by: Alvaro Herrera <alvherre@alvh.no-ip.org> Reviewed-by: Alexander Korotkov <aekorotkov@gmail.com> Reviewed-by: Sokolov Yura <y.sokolov@postgrespro.ru> Reviewed-by: Nico Williams <nico@cryptonector.com> Reviewed-by: John Naylor <john.naylor@enterprisedb.com> Discussion: https://postgr.es/m/c1138ead-7668-f0e1-0638-c3be3237e812@2ndquadrant.com Discussion: https://postgr.es/m/5d78b774-7e9c-c94e-12cf-fef51cc89b1a%402ndquadrant.com
2021-03-26 13:35:29 +01:00
# ----------
# Another group of parallel tests
# psql depends on create_am
# amutils depends on geometry, create_index_spgist, hash_index, brin
# ----------
test: create_table_like alter_generic alter_operator misc async dbsize merge misc_functions sysviews tsrf tid tidscan tidrangescan collate.utf8 collate.icu.utf8 incremental_sort create_role without_overlaps
# collate.linux.utf8 and collate.icu.utf8 tests cannot be run in parallel with each other
test: rules psql psql_crosstab amutils stats_ext collate.linux.utf8 collate.windows.win1252
# ----------
# Run these alone so they don't run out of parallel workers
# select_parallel depends on create_misc
# ----------
test: select_parallel
test: write_parallel
Don't overlook indexes during parallel VACUUM. Commit b4af70cb, which simplified state managed by VACUUM, performed refactoring of parallel VACUUM in passing. Confusion about the exact details of the tasks that the leader process is responsible for led to code that made it possible for parallel VACUUM to miss a subset of the table's indexes entirely. Specifically, indexes that fell under the min_parallel_index_scan_size size cutoff were missed. These indexes are supposed to be vacuumed by the leader (alongside any parallel unsafe indexes), but weren't vacuumed at all. Affected indexes could easily end up with duplicate heap TIDs, once heap TIDs were recycled for new heap tuples. This had generic symptoms that might be seen with almost any index corruption involving structural inconsistencies between an index and its table. To fix, make sure that the parallel VACUUM leader process performs any required index vacuuming for indexes that happen to be below the size cutoff. Also document the design of parallel VACUUM with these below-size-cutoff indexes. It's unclear how many users might be affected by this bug. There had to be at least three indexes on the table to hit the bug: a smaller index, plus at least two additional indexes that themselves exceed the size cutoff. Cases with just one additional index would not run into trouble, since the parallel VACUUM cost model requires two larger-than-cutoff indexes on the table to apply any parallel processing. Note also that autovacuum was not affected, since it never uses parallel processing. Test case based on tests from a larger patch to test parallel VACUUM by Masahiko Sawada. Many thanks to Kamigishi Rei for her invaluable help with tracking this problem down. Author: Peter Geoghegan <pg@bowt.ie> Author: Masahiko Sawada <sawada.mshk@gmail.com> Reported-By: Kamigishi Rei <iijima.yun@koumakan.jp> Reported-By: Andrew Gierth <andrew@tao11.riddles.org.uk> Diagnosed-By: Andres Freund <andres@anarazel.de> Bug: #17245 Discussion: https://postgr.es/m/17245-ddf06aaf85735f36@postgresql.org Discussion: https://postgr.es/m/20211030023740.qbnsl2xaoh2grq3d@alap3.anarazel.de Backpatch: 14-, where the refactoring commit appears.
2021-11-02 20:06:17 +01:00
test: vacuum_parallel
# no relation related tests can be put in this group
test: publication subscription
# ----------
# Another group of parallel tests
# select_views depends on create_view
# ----------
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)
# ----------
Add basic JSON_TABLE() functionality JSON_TABLE() allows JSON data to be converted into a relational view and thus used, for example, in a FROM clause, like other tabular data. Data to show in the view is selected from a source JSON object using a JSON path expression to get a sequence of JSON objects that's called a "row pattern", which becomes the source to compute the SQL/JSON values that populate the view's output columns. Column values themselves are computed using JSON path expressions applied to each of the JSON objects comprising the "row pattern", for which the SQL/JSON query functions added in 6185c9737cf4 are used. To implement JSON_TABLE() as a table function, this augments the TableFunc and TableFuncScanState nodes that are currently used to support XMLTABLE() with some JSON_TABLE()-specific fields. Note that the JSON_TABLE() spec includes NESTED COLUMNS and PLAN clauses, which are required to provide more flexibility to extract data out of nested JSON objects, but they are not implemented here to keep this commit of manageable size. Author: Nikita Glukhov <n.gluhov@postgrespro.ru> Author: Teodor Sigaev <teodor@sigaev.ru> Author: Oleg Bartunov <obartunov@gmail.com> Author: Alexander Korotkov <aekorotkov@gmail.com> Author: Andrew Dunstan <andrew@dunslane.net> Author: Amit Langote <amitlangote09@gmail.com> Author: Jian He <jian.universality@gmail.com> Reviewers have included (in no particular order): Andres Freund, Alexander Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zihong Yu, Himanshu Upadhyaya, Daniel Gustafsson, Justin Pryzby, Álvaro Herrera, Jian He Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru Discussion: https://postgr.es/m/20220616233130.rparivafipt6doj3@alap3.anarazel.de Discussion: https://postgr.es/m/abd9b83b-aa66-f230-3d6d-734817f0995d%40postgresql.org Discussion: https://postgr.es/m/CA+HiwqE4XTdfb1nW=Ojoy_tQSRhYt-q_kb6i5d4xcKyrLC1Nbg@mail.gmail.com
2024-04-04 12:57:08 +02:00
test: json jsonb json_encoding jsonpath jsonpath_encoding jsonb_jsonpath sqljson sqljson_queryfuncs sqljson_jsontable
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
# ----------
# Another group of parallel tests
# with depends on create_misc
# NB: temp.sql does a reconnect which transiently uses 2 connections,
# so keep this parallel group to at most 19 tests
# ----------
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
# ----------
# Another group of parallel tests
#
# The stats test resets stats, so nothing else needing stats access can be in
# this group.
# ----------
test: partition_merge partition_split partition_join partition_prune reloptions hash_part indexing partition_aggregate partition_info tuplesort explain compression memoize stats predicate
# event_trigger depends on create_am and cannot run concurrently with
# any test that runs DDL
# oidjoins is read-only, though, and should run late for best coverage
test: oidjoins event_trigger
# event_trigger_login cannot run concurrently with any other tests because
# on-login event handling could catch connection of a concurrent test.
test: event_trigger_login
# this test also uses event triggers, so likewise run it by itself
test: fast_default
# run tablespace test at the end because it drops the tablespace created during
# setup that other tests may use.
test: tablespace