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Remove a number of (char *) casts that are unnecessary. Or in some
cases, rewrite the code to make the purpose of the cast clearer.
Reviewed-by: Dagfinn Ilmari Mannsåker <ilmari@ilmari.org>
Discussion: https://www.postgresql.org/message-id/flat/fd1fcedb-3492-4fc8-9e3e-74b97f2db6c7%40eisentraut.org
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Backpatch-through: 13
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Reported-by: Michael Paquier
Discussion: https://postgr.es/m/ZZKTDPxBBMt3C0J9@paquier.xyz
Backpatch-through: 12
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Backpatch-through: 11
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Add a NodeTag field to struct Bitmapset. This is free because of
alignment considerations on 64-bit hardware. While it adds some
space on 32-bit machines, we aren't optimizing for that case anymore.
The advantage is that data structures such as Lists of Bitmapsets
are now first-class objects to the Node infrastructure, and don't
require special-case code to handle.
This patch includes removal of one such special case, in indxpath.c:
bms_equal_any() can now be replaced by list_member(). There may be
more existing code that could be simplified, but I didn't look very
hard. We also get to drop the read_write_ignore annotations on a
couple of RelOptInfo fields.
The outfuncs/readfuncs support is arranged so that nothing changes
in the string representation of a Bitmapset field; therefore, this
doesn't need a catversion bump.
Amit Langote and Tom Lane
Discussion: https://postgr.es/m/109089.1668197158@sss.pgh.pa.us
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Commit f10a025cfe97 added support for List to store Xids, but didn't
handle the new type in all cases. Add some obviously necessary pieces.
As far as I am aware, this is all dead code as far as core code is
concerned, but it seems unacceptable not to have it in case third-party
code wants to rely on this type of list. (Some parts of the List API
remain unimplemented, but that can be fixed as and when needed -- see
lack of list_intersection_oid, list_deduplicate_int as precedents.)
Discussion: https://postgr.es/m/20220708164534.nbejhgt4ajz35p65@alvherre.pgsql
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This removes the code sections that were ifdef'ed out by
964d01ae90c314eb31132c2e7712d5d9fc237331.
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Add a script to automatically generate the node support functions
(copy, equal, out, and read, as well as the node tags enum) from the
struct definitions.
For each of the four node support files, it creates two include files,
e.g., copyfuncs.funcs.c and copyfuncs.switch.c, to include in the main
file. All the scaffolding of the main file stays in place.
I have tried to mostly make the coverage of the output match what is
currently there. For example, one could now do out/read coverage of
utility statement nodes, but I have manually excluded those for now.
The reason is mainly that it's easier to diff the before and after,
and adding a bunch of stuff like this might require a separate
analysis and review.
Subtyping (TidScan -> Scan) is supported.
For the hard cases, you can just write a manual function and exclude
generating one. For the not so hard cases, there is a way of
annotating struct fields to get special behaviors. For example,
pg_node_attr(equal_ignore) has the field ignored in equal functions.
(In this patch, I have only ifdef'ed out the code to could be removed,
mainly so that it won't constantly have merge conflicts. It will be
deleted in a separate patch. All the code comments that are worth
keeping from those sections have already been moved to the header
files where the structs are defined.)
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://www.postgresql.org/message-id/flat/c1097590-a6a4-486a-64b1-e1f9cc0533ce%40enterprisedb.com
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These are abstract node types that don't need to have a node tag
defined.
Discussion: https://www.postgresql.org/message-id/2592455.1657140387%40sss.pgh.pa.us
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We have been using the term RelFileNode to refer to either (1) the
integer that is used to name the sequence of files for a certain relation
within the directory set aside for that tablespace/database combination;
or (2) that value plus the OIDs of the tablespace and database; or
occasionally (3) the whole series of files created for a relation
based on those values. Using the same name for more than one thing is
confusing.
Replace RelFileNode with RelFileNumber when we're talking about just the
single number, i.e. (1) from above, and with RelFileLocator when we're
talking about all the things that are needed to locate a relation's files
on disk, i.e. (2) from above. In the places where we refer to (3) as
a relfilenode, instead refer to "relation storage".
Since there is a ton of SQL code in the world that knows about
pg_class.relfilenode, don't change the name of that column, or of other
SQL-facing things that derive their name from it.
On the other hand, do adjust closely-related internal terminology. For
example, the structure member names dbNode and spcNode appear to be
derived from the fact that the structure itself was called RelFileNode,
so change those to dbOid and spcOid. Likewise, various variables with
names like rnode and relnode get renamed appropriately, according to
how they're being used in context.
Hopefully, this is clearer than before. It is also preparation for
future patches that intend to widen the relfilenumber fields from its
current width of 32 bits. Variables that store a relfilenumber are now
declared as type RelFileNumber rather than type Oid; right now, these
are the same, but that can now more easily be changed.
Dilip Kumar, per an idea from me. Reviewed also by Andres Freund.
I fixed some whitespace issues, changed a couple of words in a
comment, and made one other minor correction.
Discussion: http://postgr.es/m/CA+TgmoamOtXbVAQf9hWFzonUo6bhhjS6toZQd7HZ-pmojtAmag@mail.gmail.com
Discussion: http://postgr.es/m/CA+Tgmobp7+7kmi4gkq7Y+4AM9fTvL+O1oQ4-5gFTT+6Ng-dQ=g@mail.gmail.com
Discussion: http://postgr.es/m/CAFiTN-vTe79M8uDH1yprOU64MNFE+R3ODRuA+JWf27JbhY4hJw@mail.gmail.com
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Noted while comparing existing code to the output of the proposed
patch to automate creation of these functions. Some of the changes
are just cosmetic, but others represent real bugs. I've not
attempted to analyze the user-visible impact.
Back-patch to v15 where this code came in.
Discussion: https://postgr.es/m/1794155.1656984188@sss.pgh.pa.us
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I started out with the intention to rename value_type to item_type to
avoid a collision with a typedef name that appears on some platforms.
Along the way, I noticed that the adjacent field "format" was not being
correctly handled by the backend/nodes/ infrastructure functions:
copyfuncs.c erroneously treated it as a scalar, while equalfuncs,
outfuncs, and readfuncs omitted handling it at all. This looks like
it might be cosmetic at the moment because the field is always NULL
after parse analysis; but that's likely a bug in itself, and the code's
certainly not very future-proof. Let's fix it while we can still do so
without forcing an initdb on beta testers.
Further study found a few other inconsistencies in the backend/nodes/
infrastructure for the recently-added JSON node types, so fix those too.
catversion bumped because of potential change in stored rules.
Discussion: https://postgr.es/m/526703.1652385613@sss.pgh.pa.us
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Run pgindent, pgperltidy, and reformat-dat-files.
I manually fixed a couple of comments that pgindent uglified.
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Window functions such as row_number() always return a value higher than
the previously returned value for tuples in any given window partition.
Traditionally queries such as;
SELECT * FROM (
SELECT *, row_number() over (order by c) rn
FROM t
) t WHERE rn <= 10;
were executed fairly inefficiently. Neither the query planner nor the
executor knew that once rn made it to 11 that nothing further would match
the outer query's WHERE clause. It would blindly continue until all
tuples were exhausted from the subquery.
Here we implement means to make the above execute more efficiently.
This is done by way of adding a pg_proc.prosupport function to various of
the built-in window functions and adding supporting code to allow the
support function to inform the planner if the window function is
monotonically increasing, monotonically decreasing, both or neither. The
planner is then able to make use of that information and possibly allow
the executor to short-circuit execution by way of adding a "run condition"
to the WindowAgg to allow it to determine if some of its execution work
can be skipped.
This "run condition" is not like a normal filter. These run conditions
are only built using quals comparing values to monotonic window functions.
For monotonic increasing functions, quals making use of the btree
operators for <, <= and = can be used (assuming the window function column
is on the left). You can see here that once such a condition becomes false
that a monotonic increasing function could never make it subsequently true
again. For monotonically decreasing functions the >, >= and = btree
operators for the given type can be used for run conditions.
The best-case situation for this is when there is a single WindowAgg node
without a PARTITION BY clause. Here when the run condition becomes false
the WindowAgg node can simply return NULL. No more tuples will ever match
the run condition. It's a little more complex when there is a PARTITION
BY clause. In this case, we cannot return NULL as we must still process
other partitions. To speed this case up we pull tuples from the outer
plan to check if they're from the same partition and simply discard them
if they are. When we find a tuple belonging to another partition we start
processing as normal again until the run condition becomes false or we run
out of tuples to process.
When there are multiple WindowAgg nodes to evaluate then this complicates
the situation. For intermediate WindowAggs we must ensure we always
return all tuples to the calling node. Any filtering done could lead to
incorrect results in WindowAgg nodes above. For all intermediate nodes,
we can still save some work when the run condition becomes false. We've
no need to evaluate the WindowFuncs anymore. Other WindowAgg nodes cannot
reference the value of these and these tuples will not appear in the final
result anyway. The savings here are small in comparison to what can be
saved in the top-level WingowAgg, but still worthwhile.
Intermediate WindowAgg nodes never filter out tuples, but here we change
WindowAgg so that the top-level WindowAgg filters out tuples that don't
match the intermediate WindowAgg node's run condition. Such filters
appear in the "Filter" clause in EXPLAIN for the top-level WindowAgg node.
Here we add prosupport functions to allow the above to work for;
row_number(), rank(), dense_rank(), count(*) and count(expr). It appears
technically possible to do the same for min() and max(), however, it seems
unlikely to be useful enough, so that's not done here.
Bump catversion
Author: David Rowley
Reviewed-by: Andy Fan, Zhihong Yu
Discussion: https://postgr.es/m/CAApHDvqvp3At8++yF8ij06sdcoo1S_b2YoaT9D4Nf+MObzsrLQ@mail.gmail.com
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This reverts a sequence of commits, implementing features related to
logical decoding and replication of sequences:
- 0da92dc530c9251735fc70b20cd004d9630a1266
- 80901b32913ffa59bf157a4d88284b2b3a7511d9
- b779d7d8fdae088d70da5ed9fcd8205035676df3
- d5ed9da41d96988d905b49bebb273a9b2d6e2915
- a180c2b34de0989269fdb819bff241a249bf5380
- 75b1521dae1ff1fde17fda2e30e591f2e5d64b6a
- 2d2232933b02d9396113662e44dca5f120d6830e
- 002c9dd97a0c874fd1693a570383e2dd38cd40d5
- 05843b1aa49df2ecc9b97c693b755bd1b6f856a9
The implementation has issues, mostly due to combining transactional and
non-transactional behavior of sequences. It's not clear how this could
be fixed, but it'll require reworking significant part of the patch.
Discussion: https://postgr.es/m/95345a19-d508-63d1-860a-f5c2f41e8d40@enterprisedb.com
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In commit 27e1f1456, create_append_plan() only allowed the subplan
created from a given subpath to be executed asynchronously when it was
an async-capable ForeignPath. To extend coverage, this patch handles
cases when the given subpath includes some other Path types as well that
can be omitted in the plan processing, such as a ProjectionPath directly
atop an async-capable ForeignPath, allowing asynchronous execution in
partitioned-scan/partitioned-join queries with non-Var tlist expressions
and more UNION queries.
Andrey Lepikhov and Etsuro Fujita, reviewed by Alexander Pyhalov and
Zhihong Yu.
Discussion: https://postgr.es/m/659c37a8-3e71-0ff2-394c-f04428c76f08%40postgrespro.ru
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These clauses allow the user to specify how data from nested paths are
joined, allowing considerable freedom in shaping the tabular output of
JSON_TABLE.
PLAN DEFAULT allows the user to specify the global strategies when
dealing with sibling or child nested paths. The is often sufficient to
achieve the necessary goal, and is considerably simpler than the full
PLAN clause, which allows the user to specify the strategy to be used
for each named nested path.
Nikita Glukhov
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zhihong Yu,
Himanshu Upadhyaya, Daniel Gustafsson, Justin Pryzby.
Discussion: https://postgr.es/m/7e2cb85d-24cf-4abb-30a5-1a33715959bd@postgrespro.ru
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This feature allows jsonb data to be treated as a table and thus used in
a FROM clause like other tabular data. Data can be selected from the
jsonb using jsonpath expressions, and hoisted out of nested structures
in the jsonb to form multiple rows, more or less like an outer join.
Nikita Glukhov
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup, Erik Rijkers, Zhihong Yu (whose
name I previously misspelled), Himanshu Upadhyaya, Daniel Gustafsson,
Justin Pryzby.
Discussion: https://postgr.es/m/7e2cb85d-24cf-4abb-30a5-1a33715959bd@postgrespro.ru
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This patch is extracted from a larger patch that allowed setting the
default returned value from these functions to json or jsonb. That had
problems, but this piece of it is fine. For these functions only json or
jsonb can be specified in the RETURNING clause.
Extracted from an original patch from Nikita Glukhov
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.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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This Patch introduces three SQL standard JSON functions:
JSON() (incorrectly mentioned in my commit message for f4fb45d15c)
JSON_SCALAR()
JSON_SERIALIZE()
JSON() produces json values from text, bytea, json or jsonb values, and
has facilitites for handling duplicate keys.
JSON_SCALAR() produces a json value from any scalar sql value, including
json and jsonb.
JSON_SERIALIZE() produces text or bytea from input which containis or
represents json or jsonb;
For the most part these functions don't add any significant new
capabilities, but they will be of use to users wanting standard
compliant JSON handling.
Nikita Glukhov
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.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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This introduces the SQL/JSON functions for querying JSON data using
jsonpath expressions. The functions are:
JSON_EXISTS()
JSON_QUERY()
JSON_VALUE()
All of these functions only operate on jsonb. The workaround for now is
to cast the argument to jsonb.
JSON_EXISTS() tests if the jsonpath expression applied to the jsonb
value yields any values. JSON_VALUE() must return a single value, and an
error occurs if it tries to return multiple values. JSON_QUERY() must
return a json object or array, and there are various WRAPPER options for
handling scalar or multi-value results. Both these functions have
options for handling EMPTY and ERROR conditions.
Nikita Glukhov
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.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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This patch intrdocuces the SQL standard IS JSON predicate. It operates
on text and bytea values representing JSON as well as on the json and
jsonb types. Each test has an IS and IS NOT variant. The tests are:
IS JSON [VALUE]
IS JSON ARRAY
IS JSON OBJECT
IS JSON SCALAR
IS JSON WITH | WITHOUT UNIQUE KEYS
These are mostly self-explanatory, but note that IS JSON WITHOUT UNIQUE
KEYS is true whenever IS JSON is true, and IS JSON WITH UNIQUE KEYS is
true whenever IS JSON is true except it IS JSON OBJECT is true and there
are duplicate keys (which is never the case when applied to jsonb values).
Nikita Glukhov
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.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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MERGE performs actions that modify rows in the target table using a
source table or query. MERGE provides a single SQL statement that can
conditionally INSERT/UPDATE/DELETE rows -- a task that would otherwise
require multiple PL statements. For example,
MERGE INTO target AS t
USING source AS s
ON t.tid = s.sid
WHEN MATCHED AND t.balance > s.delta THEN
UPDATE SET balance = t.balance - s.delta
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED AND s.delta > 0 THEN
INSERT VALUES (s.sid, s.delta)
WHEN NOT MATCHED THEN
DO NOTHING;
MERGE works with regular tables, partitioned tables and inheritance
hierarchies, including column and row security enforcement, as well as
support for row and statement triggers and transition tables therein.
MERGE is optimized for OLTP and is parameterizable, though also useful
for large scale ETL/ELT. MERGE is not intended to be used in preference
to existing single SQL commands for INSERT, UPDATE or DELETE since there
is some overhead. MERGE can be used from PL/pgSQL.
MERGE does not support targetting updatable views or foreign tables, and
RETURNING clauses are not allowed either. These limitations are likely
fixable with sufficient effort. Rewrite rules are also not supported,
but it's not clear that we'd want to support them.
Author: Pavan Deolasee <pavan.deolasee@gmail.com>
Author: Álvaro Herrera <alvherre@alvh.no-ip.org>
Author: Amit Langote <amitlangote09@gmail.com>
Author: Simon Riggs <simon.riggs@enterprisedb.com>
Reviewed-by: Peter Eisentraut <peter.eisentraut@enterprisedb.com>
Reviewed-by: Andres Freund <andres@anarazel.de> (earlier versions)
Reviewed-by: Peter Geoghegan <pg@bowt.ie> (earlier versions)
Reviewed-by: Robert Haas <robertmhaas@gmail.com> (earlier versions)
Reviewed-by: Japin Li <japinli@hotmail.com>
Reviewed-by: Justin Pryzby <pryzby@telsasoft.com>
Reviewed-by: Tomas Vondra <tomas.vondra@enterprisedb.com>
Reviewed-by: Zhihong Yu <zyu@yugabyte.com>
Discussion: https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.com
Discussion: https://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
Discussion: https://postgr.es/m/20201231134736.GA25392@alvherre.pgsql
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This patch introduces the SQL/JSON standard constructors for JSON:
JSON()
JSON_ARRAY()
JSON_ARRAYAGG()
JSON_OBJECT()
JSON_OBJECTAGG()
For the most part these functions provide facilities that mimic
existing json/jsonb functions. However, they also offer some useful
additional functionality. In addition to text input, the JSON() function
accepts bytea input, which it will decode and constuct a json value from.
The other functions provide useful options for handling duplicate keys
and null values.
This series of patches will be followed by a consolidated documentation
patch.
Nikita Glukhov
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.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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This introduces some of the building blocks used by the SQL/JSON
constructor and query functions. Specifically, it provides node
executor and grammar support for the FORMAT JSON [ENCODING foo]
clause, and values decorated with it, and for the RETURNING clause.
The following SQL/JSON patches will leverage these.
Nikita Glukhov (who probably deserves an award for perseverance).
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.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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This allows specifying an optional column list when adding a table to
logical replication. The column list may be specified after the table
name, enclosed in parentheses. Columns not included in this list are not
sent to the subscriber, allowing the schema on the subscriber to be a
subset of the publisher schema.
For UPDATE/DELETE publications, the column list needs to cover all
REPLICA IDENTITY columns. For INSERT publications, the column list is
arbitrary and may omit some REPLICA IDENTITY columns. Furthermore, if
the table uses REPLICA IDENTITY FULL, column list is not allowed.
The column list can contain only simple column references. Complex
expressions, function calls etc. are not allowed. This restriction could
be relaxed in the future.
During the initial table synchronization, only columns included in the
column list are copied to the subscriber. If the subscription has
several publications, containing the same table with different column
lists, columns specified in any of the lists will be copied.
This means all columns are replicated if the table has no column list
at all (which is treated as column list with all columns), or when of
the publications is defined as FOR ALL TABLES (possibly IN SCHEMA that
matches the schema of the table).
For partitioned tables, publish_via_partition_root determines whether
the column list for the root or the leaf relation will be used. If the
parameter is 'false' (the default), the list defined for the leaf
relation is used. Otherwise, the column list for the root partition
will be used.
Psql commands \dRp+ and \d <table-name> now display any column lists.
Author: Tomas Vondra, Alvaro Herrera, Rahila Syed
Reviewed-by: Peter Eisentraut, Alvaro Herrera, Vignesh C, Ibrar Ahmed,
Amit Kapila, Hou zj, Peter Smith, Wang wei, Tang, Shi yu
Discussion: https://postgr.es/m/CAH2L28vddB_NFdRVpuyRBJEBWjz4BSyTB=_ektNRH8NJ1jf95g@mail.gmail.com
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This commit adds support for decoding of sequences to the built-in
replication (the infrastructure was added by commit 0da92dc530).
The syntax and behavior mostly mimics handling of tables, i.e. a
publication may be defined as FOR ALL SEQUENCES (replicating all
sequences in a database), FOR ALL SEQUENCES IN SCHEMA (replicating
all sequences in a particular schema) or individual sequences.
To publish sequence modifications, the publication has to include
'sequence' action. The protocol is extended with a new message,
describing sequence increments.
A new system view pg_publication_sequences lists all the sequences
added to a publication, both directly and indirectly. Various psql
commands (\d and \dRp) are improved to also display publications
including a given sequence, or sequences included in a publication.
Author: Tomas Vondra, Cary Huang
Reviewed-by: Peter Eisentraut, Amit Kapila, Hannu Krosing, Andres
Freund, Petr Jelinek
Discussion: https://postgr.es/m/d045f3c2-6cfb-06d3-5540-e63c320df8bc@enterprisedb.com
Discussion: https://postgr.es/m/1710ed7e13b.cd7177461430746.3372264562543607781@highgo.ca
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This reverts commit 865fe4d5df560a6f5353da652018ff876978ad2d.
This has caused issues with a significant number of buildfarm members
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This introduces some of the building blocks used by the SQL/JSON
constructor and query functions. Specifically, it provides node
executor and grammar support for the FORMAT JSON [ENCODING foo]
clause, and values decorated with it, and for the RETURNING clause.
The following SQL/JSON patches will leverage these.
Nikita Glukhov (who probably deserves an award for perseverance).
Reviewers have included (in no particular order) Andres Freund, Alexander
Korotkov, Pavel Stehule, Andrew Alsup. Erik Rijkers, Zihong Yu and
Himanshu Upadhyaya.
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
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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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forgotten in 37851a8b83d3d57ca48736093b10aa5f3bc0c177
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The SQL standard has been ambiguous about whether null values in
unique constraints should be considered equal or not. Different
implementations have different behaviors. In the SQL:202x draft, this
has been formalized by making this implementation-defined and adding
an option on unique constraint definitions UNIQUE [ NULLS [NOT]
DISTINCT ] to choose a behavior explicitly.
This patch adds this option to PostgreSQL. The default behavior
remains UNIQUE NULLS DISTINCT. Making this happen in the btree code
is pretty easy; most of the patch is just to carry the flag around to
all the places that need it.
The CREATE UNIQUE INDEX syntax extension is not from the standard,
it's my own invention.
I named all the internal flags, catalog columns, etc. in the negative
("nulls not distinct") so that the default PostgreSQL behavior is the
default if the flag is false.
Reviewed-by: Maxim Orlov <orlovmg@gmail.com>
Reviewed-by: Pavel Borisov <pashkin.elfe@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/84e5ee1b-387e-9a54-c326-9082674bde78@enterprisedb.com
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Before, SQL-level boolean constants were represented by a string with
a cast, and internal Boolean values in DDL commands were usually
represented by Integer nodes. This takes the place of both of these
uses, making the intent clearer and having some amount of type safety.
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/8c1a2e37-c68d-703c-5a83-7a6077f4f997@enterprisedb.com
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For the formerly-Value node types, rename the "val" field to a name
specific to the node type, namely "ival", "fval", "sval", and "bsval".
This makes some code clearer and catches mixups better.
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/8c1a2e37-c68d-703c-5a83-7a6077f4f997@enterprisedb.com
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Backpatch-through: 10
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Commit 4ace45677 failed to fix the problem fully, because the
same issue of attempting to fetch a non-returnable index column
can occur when rechecking the indexqual after using a lossy index
operator. Moreover, it broke EXPLAIN for such indexquals (which
indicates a gap in our test cases :-().
Revert the code changes of 4ace45677 in favor of adding a new field
to struct IndexOnlyScan, containing a version of the indexqual that
can be executed against the index-returned tuple without using any
non-returnable columns. (The restrictions imposed by check_index_only
guarantee this is possible, although we may have to recompute indexed
expressions.) Support construction of that during setrefs.c
processing by marking IndexOnlyScan.indextlist entries as resjunk
if they can't be returned, rather than removing them entirely.
(We could alternatively require setrefs.c to look up the IndexOptInfo
again, but abusing resjunk this way seems like a reasonably safe way
to avoid needing to do that.)
This solution isn't great from an API-stability standpoint: if there
are any extensions out there that build IndexOnlyScan structs directly,
they'll be broken in the next minor releases. However, only a very
invasive extension would be likely to do such a thing. There's no
change in the Path representation, so typical planner extensions
shouldn't have a problem.
As before, back-patch to all supported branches.
Discussion: https://postgr.es/m/3179992.1641150853@sss.pgh.pa.us
Discussion: https://postgr.es/m/17350-b5bdcf476e5badbb@postgresql.org
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Extend the foreign key ON DELETE actions SET NULL and SET DEFAULT by
allowing the specification of a column list, like
CREATE TABLE posts (
...
FOREIGN KEY (tenant_id, author_id) REFERENCES users ON DELETE SET NULL (author_id)
);
If a column list is specified, only those columns are set to
null/default, instead of all the columns in the foreign-key
constraint.
This is useful for multitenant or sharded schemas, where the tenant or
shard ID is included in the primary key of all tables but shouldn't be
set to null.
Author: Paul Martinez <paulmtz@google.com>
Discussion: https://www.postgresql.org/message-id/flat/CACqFVBZQyMYJV=njbSMxf+rbDHpx=W=B7AEaMKn8dWn9OZJY7w@mail.gmail.com
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It's possible that a subplan below a Memoize node contains a parameter
from above the Memoize node. If this parameter changes then cache entries
may become out-dated due to the new parameter value.
Previously Memoize was mistakenly not aware of this. We fix this here by
flushing the cache whenever a parameter that's not part of the cache
key changes.
Bug: #17213
Reported by: Elvis Pranskevichus
Author: David Rowley
Discussion: https://postgr.es/m/17213-988ed34b225a2862@postgresql.org
Backpatch-through: 14, where Memoize was added
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Memoize would always use the hash equality operator for the cache key
types to determine if the current set of parameters were the same as some
previously cached set. Certain types such as floating points where -0.0
and +0.0 differ in their binary representation but are classed as equal by
the hash equality operator may cause problems as unless the join uses the
same operator it's possible that whichever join operator is being used
would be able to distinguish the two values. In which case we may
accidentally return in the incorrect rows out of the cache.
To fix this here we add a binary mode to Memoize to allow it to the
current set of parameters to previously cached values by comparing
bit-by-bit rather than logically using the hash equality operator. This
binary mode is always used for LATERAL joins and it's used for normal
joins when any of the join operators are not hashable.
Reported-by: Tom Lane
Author: David Rowley
Discussion: https://postgr.es/m/3004308.1632952496@sss.pgh.pa.us
Backpatch-through: 14, where Memoize was added
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In v14, because we don't have a field in RestrictInfo to cache both the
left and right type's hash equality operator, we just restrict the scope
of Memoize to only when the left and right types of a RestrictInfo are the
same.
In master we add another field to RestrictInfo and cache both hash
equality operators.
Reported-by: Jaime Casanova
Author: David Rowley
Discussion: https://postgr.es/m/20210929185544.GB24346%40ahch-to
Backpatch-through: 14
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A new option "FOR ALL TABLES IN SCHEMA" in Create/Alter Publication allows
one or more schemas to be specified, whose tables are selected by the
publisher for sending the data to the subscriber.
The new syntax allows specifying both the tables and schemas. For example:
CREATE PUBLICATION pub1 FOR TABLE t1,t2,t3, ALL TABLES IN SCHEMA s1,s2;
OR
ALTER PUBLICATION pub1 ADD TABLE t1,t2,t3, ALL TABLES IN SCHEMA s1,s2;
A new system table "pg_publication_namespace" has been added, to maintain
the schemas that the user wants to publish through the publication.
Modified the output plugin (pgoutput) to publish the changes if the
relation is part of schema publication.
Updates pg_dump to identify and dump schema publications. Updates the \d
family of commands to display schema publications and \dRp+ variant will
now display associated schemas if any.
Author: Vignesh C, Hou Zhijie, Amit Kapila
Syntax-Suggested-by: Tom Lane, Alvaro Herrera
Reviewed-by: Greg Nancarrow, Masahiko Sawada, Hou Zhijie, Amit Kapila, Haiying Tang, Ajin Cherian, Rahila Syed, Bharath Rupireddy, Mark Dilger
Tested-by: Haiying Tang
Discussion: https://www.postgresql.org/message-id/CALDaNm0OANxuJ6RXqwZsM1MSY4s19nuH3734j4a72etDwvBETQ@mail.gmail.com
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Move support functions for new PublicationTable node to more sensible
locations in the files.
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These handle node fields that are inline arrays (as opposed to
dynamically allocated arrays handled by COPY_POINTER_FIELD and
COMPARE_POINTER_FIELD). These cases were hand-coded until now.
Reviewed-by: Jacob Champion <pchampion@vmware.com>
Discussion: https://www.postgresql.org/message-id/c091e5cd-45f8-69ee-6a9b-de86912cc7e7@enterprisedb.com
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The Value node struct is a weird construct. It is its own node type,
but most of the time, it actually has a node type of Integer, Float,
String, or BitString. As a consequence, the struct name and the node
type don't match most of the time, and so it has to be treated
specially a lot. There doesn't seem to be any value in the special
construct. There is very little code that wants to accept all Value
variants but nothing else (and even if it did, this doesn't provide
any convenient way to check it), and most code wants either just one
particular node type (usually String), or it accepts a broader set of
node types besides just Value.
This change removes the Value struct and node type and replaces them
by separate Integer, Float, String, and BitString node types that are
proper node types and structs of their own and behave mostly like
normal node types.
Also, this removes the T_Null node tag, which was previously also a
possible variant of Value but wasn't actually used outside of the
Value contained in A_Const. Replace that by an isnull field in
A_Const.
Reviewed-by: Dagfinn Ilmari Mannsåker <ilmari@ilmari.org>
Reviewed-by: Kyotaro Horiguchi <horikyota.ntt@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/5ba6bc5b-3f95-04f2-2419-f8ddb4c046fb@enterprisedb.com
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These encapsulate a relation when referred from replication DDL.
Currently they don't do anything useful (they're just wrappers around
RangeVar and Relation respectively) but in the future they'll be used to
carry column lists.
Extracted from a larger patch by Rahila Syed.
Author: Rahila Syed <rahilasyed90@gmail.com>
Reviewed-by: Álvaro Herrera <alvherre@alvh.no-ip.org>
Reviewed-by: Tomas Vondra <tomas.vondra@enterprisedb.com>
Reviewed-by: Amit Kapila <amit.kapila16@gmail.com>
Discussion: https://postgr.es/m/CAH2L28vddB_NFdRVpuyRBJEBWjz4BSyTB=_ektNRH8NJ1jf95g@mail.gmail.com
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instead of making each caller do it.
Discussion: https://www.postgresql.org/message-id/flat/c1097590-a6a4-486a-64b1-e1f9cc0533ce@enterprisedb.com
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Some node function names didn't match their node type names exactly.
Fix those for consistency.
Discussion: https://www.postgresql.org/message-id/flat/c1097590-a6a4-486a-64b1-e1f9cc0533ce@enterprisedb.com
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"Result Cache" was never a great name for this node, but nobody managed
to come up with another name that anyone liked enough. That was until
David Johnston mentioned "Node Memoization", which Tom Lane revised to
just "Memoize". People seem to like "Memoize", so let's do the rename.
Reviewed-by: Justin Pryzby
Discussion: https://postgr.es/m/20210708165145.GG1176@momjian.us
Backpatch-through: 14, where Result Cache was introduced
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Similar to 50e17ad28, which allowed hash tables to be used for IN clauses
with a set of constants, here we add the same feature for NOT IN clauses.
NOT IN evaluates the same as: WHERE a <> v1 AND a <> v2 AND a <> v3.
Obviously, if we're using a hash table we must be exactly equivalent to
that and return the same result taking into account that either side of
the condition could contain a NULL. This requires a little bit of
special handling to make work with the hash table version.
When processing NOT IN, the ScalarArrayOpExpr's operator will be the <>
operator. To be able to build and lookup a hash table we must use the
<>'s negator operator. The planner checks if that exists and is hashable
and sets the relevant fields in ScalarArrayOpExpr to instruct the executor
to use hashing.
Author: David Rowley, James Coleman
Reviewed-by: James Coleman, Zhihong Yu
Discussion: https://postgr.es/m/CAApHDvoF1mum_FRk6D621edcB6KSHBi2+GAgWmioj5AhOu2vwQ@mail.gmail.com
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Commit 2453ea142 redefined pg_proc.proargtypes to include the types of
OUT parameters, for procedures only. While that had some advantages
for implementing the SQL-spec behavior of DROP PROCEDURE, it was pretty
disastrous from a number of other perspectives. Notably, since the
primary key of pg_proc is name + proargtypes, this made it possible to
have multiple procedures with identical names + input arguments and
differing output argument types. That would make it impossible to call
any one of the procedures by writing just NULL (or "?", or any other
data-type-free notation) for the output argument(s). The change also
seems likely to cause grave confusion for client applications that
examine pg_proc and expect the traditional definition of proargtypes.
Hence, revert the definition of proargtypes to what it was, and
undo a number of complications that had been added to support that.
To support the SQL-spec behavior of DROP PROCEDURE, when there are
no argmode markers in the command's parameter list, we perform the
lookup both ways (that is, matching against both proargtypes and
proallargtypes), succeeding if we get just one unique match.
In principle this could result in ambiguous-function failures
that would not happen when using only one of the two rules.
However, overloading of procedure names is thought to be a pretty
rare usage, so this shouldn't cause many problems in practice.
Postgres-specific code such as pg_dump can defend against any
possibility of such failures by being careful to specify argmodes
for all procedure arguments.
This also fixes a few other bugs in the area of CALL statements
with named parameters, and improves the documentation a little.
catversion bump forced because the representation of procedures
with OUT arguments changes.
Discussion: https://postgr.es/m/3742981.1621533210@sss.pgh.pa.us
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