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PostgreSQL 15 preview

记录PostgreSQL 15中的提交日志

GUC compute_query_id 增加 regress 模式

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commit ebf6c5249b7db525e59563fb149642665c88f747 (HEAD -> master, origin/master, origin/HEAD)
Author: Michael Paquier <michael@paquier.xyz>
Date: Tue Feb 22 10:22:15 2022 +0900

Add compute_query_id = regress

"regress" is a new mode added to compute_query_id aimed at facilitating
regression testing when a module computing query IDs is loaded into the
backend, like pg_stat_statements. It works the same way as "auto",
meaning that query IDs are computed if a module enables it, except that
query IDs are hidden in EXPLAIN outputs to ensure regression output
stability.

Like any GUCs of the kind (force_parallel_mode, etc.), this new
configuration can be added to an instance's postgresql.conf, or just
passed down with PGOPTIONS at command level. compute_query_id uses an
enum for its set of option values, meaning that this addition ensures
ABI compatibility.

Using this new configuration mode allows installcheck-world to pass when
running the tests on an instance with pg_stat_statements enabled,
stabilizing the test output while checking the paths doing query ID
computations.

Reported-by: Anton Melnikov
Reviewed-by: Julien Rouhaud
Discussion: https://postgr.es/m/1634283396.372373993@f75.i.mail.ru
Discussion: https://postgr.es/m/YgHlxgc/OimuPYhH@paquier.xyz
Backpatch-through: 14

逻辑复制支持row filters

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commit 52e4f0cd472d39d07732b99559989ea3b615be78 (HEAD -> master, origin/master, origin/HEAD)
Author: Amit Kapila <akapila@postgresql.org>
Date: Tue Feb 22 07:54:12 2022 +0530

Allow specifying row filters for logical replication of tables.

This feature adds row filtering for publication tables. When a publication
is defined or modified, an optional WHERE clause can be specified. Rows
that don't satisfy this WHERE clause will be filtered out. This allows a
set of tables to be partially replicated. The row filter is per table. A
new row filter can be added simply by specifying a WHERE clause after the
table name. The WHERE clause must be enclosed by parentheses.

The row filter WHERE clause for a table added to a publication that
publishes UPDATE and/or DELETE operations must contain only columns that
are covered by REPLICA IDENTITY. The row filter WHERE clause for a table
added to a publication that publishes INSERT can use any column. If the
row filter evaluates to NULL, it is regarded as "false". The WHERE clause
only allows simple expressions that don't have user-defined functions,
user-defined operators, user-defined types, user-defined collations,
non-immutable built-in functions, or references to system columns. These
restrictions could be addressed in the future.

If you choose to do the initial table synchronization, only data that
satisfies the row filters is copied to the subscriber. If the subscription
has several publications in which a table has been published with
different WHERE clauses, rows that satisfy ANY of the expressions will be
copied. If a subscriber is a pre-15 version, the initial table
synchronization won't use row filters even if they are defined in the
publisher.

The row filters are applied before publishing the changes. If the
subscription has several publications in which the same table has been
published with different filters (for the same publish operation), those
expressions get OR'ed together so that rows satisfying any of the
expressions will be replicated.

This means all the other filters become redundant if (a) one of the
publications have no filter at all, (b) one of the publications was
created using FOR ALL TABLES, (c) one of the publications was created
using FOR ALL TABLES IN SCHEMA and the table belongs to that same schema.

If your publication contains a partitioned table, the publication
parameter publish_via_partition_root determines if it uses the partition's
row filter (if the parameter is false, the default) or the root
partitioned table's row filter.

Psql commands \dRp+ and \d <table-name> will display any row filters.

Author: Hou Zhijie, Euler Taveira, Peter Smith, Ajin Cherian
Reviewed-by: Greg Nancarrow, Haiying Tang, Amit Kapila, Tomas Vondra, Dilip Kumar, Vignesh C, Alvaro Herrera, Andres Freund, Wei Wang
Discussion: https://www.postgresql.org/message-id/flat/CAHE3wggb715X%2BmK_DitLXF25B%3DjE6xyNCH4YOwM860JR7HarGQ%40mail.gmail.com
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