ORDER BY / DISTINCT aggreagtes have, since implemented in Postgres, been
executed by always performing a sort in nodeAgg.c to sort the tuples in
the current group into the correct order before calling the transition
function on the sorted tuples. This was not great as often there might be
an index that could have provided pre-sorted input and allowed the
transition functions to be called as the rows come in, rather than having
to store them in a tuplestore in order to sort them once all the tuples
for the group have arrived.
Here we change the planner so it requests a path with a sort order which
supports the most amount of ORDER BY / DISTINCT aggregate functions and
add new code to the executor to allow it to support the processing of
ORDER BY / DISTINCT aggregates where the tuples are already sorted in the
correct order.
Since there can be many ORDER BY / DISTINCT aggregates in any given query
level, it's very possible that we can't find an order that suits all of
these aggregates. The sort order that the planner chooses is simply the
one that suits the most aggregate functions. We take the most strictly
sorted variation of each order and see how many aggregate functions can
use that, then we try again with the order of the remaining aggregates to
see if another order would suit more aggregate functions. For example:
SELECT agg(a ORDER BY a),agg2(a ORDER BY a,b) ...
would request the sort order to be {a, b} because {a} is a subset of the
sort order of {a,b}, but;
SELECT agg(a ORDER BY a),agg2(a ORDER BY c) ...
would just pick a plan ordered by {a} (we give precedence to aggregates
which are earlier in the targetlist).
SELECT agg(a ORDER BY a),agg2(a ORDER BY b),agg3(a ORDER BY b) ...
would choose to order by {b} since two aggregates suit that vs just one
that requires input ordered by {a}.
Author: David Rowley
Reviewed-by: Ronan Dunklau, James Coleman, Ranier Vilela, Richard Guo, Tom Lane
Discussion: https://postgr.es/m/CAApHDvpHzfo92%3DR4W0%2BxVua3BUYCKMckWAmo-2t_KiXN-wYH%3Dw%40mail.gmail.com
Commit 964d01ae9 marked a lot of fields as read_write_ignore
to stay consistent with what was dumped by the manually-maintained
outfuncs.c code. However, it seems that a pretty fair number
of those omissions were either flat-out oversights, or a shortcut
taken because hand-written code seemed like it'd be too much trouble.
Let's upgrade things where it seems to make sense to dump.
To do this, we need to add support to gen_node_support.pl and
outfuncs.c for variable-length arrays of Node pointers. That's
pretty straightforward given the model of the existing code
for arrays of scalars, but I found I needed to tighten the
type-recognizing regexes in gen_node_support.pl. (As they
stood, they mistook "foo **" for "foo *". Make sure they're
all fully anchored to prevent additional problems.)
The main thing left un-done here is that a lot of partitioning-related
structs are still not dumped, because they are bare structs not Nodes.
I'm not sure about the wisdom of that choice ... but changing it would
be fairly invasive, so it probably requires more justification than
just making planner node dumps more complete.
Discussion: https://postgr.es/m/1295668.1658258637@sss.pgh.pa.us
This is mostly just to get outfuncs.c support for them, so that
the agginfos and aggtransinfos lists can be dumped when dumping
the contents of PlannerInfo.
While here, improve some related comments; notably, clean up
obsolete comments left over from when preprocess_minmax_aggregates
had to make its own scan of the query tree.
Discussion: https://postgr.es/m/742479.1658160504@sss.pgh.pa.us
Teach this script to handle function pointer fields honestly.
Previously they were just silently ignored, but that's not likely to
be a behavior we can accept indefinitely. This mostly entails fixing
it so that a field declaration spanning multiple lines can be parsed,
because we have a bunch of such fields that're laid out that way.
But that's a good improvement in its own right.
With that change and a minor regex adjustment, the only struct it
fails to parse in the node-defining headers is A_Const, because
of the embedded union. The path of least resistance is to move
that union declaration outside the struct.
Having done those things, we can make it error out if it finds
any within-struct syntax it doesn't understand, which seems like
a pretty important property for robustness.
This commit doesn't change the output files at all; it's just in
the way of future-proofing.
Discussion: https://postgr.es/m/2593369.1657759779@sss.pgh.pa.us
The initial version of gen_node_support.pl manually excluded most
utility statement node types from having out/read support, and
also some raw-parse-tree-only node types. That was mostly to keep
the output comparable to the old hand-maintained code. We'd like
to have out/read support for utility statements, for debugging
purposes and so that they can be included in new-style SQL functions;
so it's time to lift that restriction.
Most if not all of the previously-excluded raw-parse-tree-only node
types can appear in expression subtrees of utility statements, so
they have to be handled too.
We don't quite have full read support yet; certain custom_read_write
node types need to have their handwritten read functions implemented
before that will work.
Doing this allows us to drop the previous hack in _outQuery to not
dump the utilityStmt field in most cases, which means we no longer
need manually-maintained out/read functions for Query, so get rid
of those in favor of auto-generating them.
Fix a couple of omissions in gen_node_support.pl that are exposed
through having to handle more node types.
catversion bump forced because somebody was sloppy about the field
order in the manually-maintained Query out/read functions.
(Committers should note that almost all changes in parsenodes.h
are now grounds for a catversion bump.)
Previously, the STORAGE specification was only available in ALTER
TABLE. This makes it available in CREATE TABLE as well.
Also make the code and the documentation for STORAGE and COMPRESSION
attributes consistent.
Author: Teodor Sigaev <teodor@sigaev.ru>
Author: Aleksander Alekseev <aleksander@timescale.com>
Reviewed-by: Peter Eisentraut <peter.eisentraut@enterprisedb.com>
Reviewed-by: wenjing zeng <wjzeng2012@gmail.com>
Reviewed-by: Matthias van de Meent <boekewurm+postgres@gmail.com>
Reviewed-by: Kyotaro Horiguchi <horikyota.ntt@gmail.com>
Discussion: https://postgr.es/m/de83407a-ae3d-a8e1-a788-920eb334f25b@sigaev.ru
There are a few things that we could do a little better within
get_cheapest_group_keys_order():
1. We should be using list_free() rather than pfree() on a List.
2. We should use for_each_from() instead of manually coding a for loop to
skip the first n elements of a List
3. list_truncate(list_copy(...), n) is not a great way to copy the first n
elements of a list. Let's invent list_copy_head() for that. That way we
don't need to copy the entire list just to truncate it directly
afterwards.
4. We can simplify finding the cheapest cost by setting the cheapest cost
variable to DBL_MAX. That allows us to skip special-casing the initial
iteration of the loop.
Author: David Rowley
Discussion: https://postgr.es/m/CAApHDvrGyL3ft8waEkncG9y5HDMu5TFFJB1paoTC8zi9YK97Nw@mail.gmail.com
Backpatch-through: 15, where get_cheapest_group_keys_order was added.
Having different build systems producing different contents of the
NodeTag enum would be catastrophic for extension ABI stability.
But that ordering depends on the order in which gen_node_support.pl
processes its input files. It seems too fragile to let the Makefiles,
MSVC build scripts, and soon meson build scripts all set this order
independently. As a klugy but serviceable solution, put a canonical
copy of the file list into gen_node_support.pl itself, and check that
against the files given on the command line.
Also, while it's fine to add and delete node tags during development,
we must not let the assigned NodeTag values change unexpectedly in
stable branches. Add a cross-check that can be enabled when a branch
is forked off (or later, but that is a time when we're unlikely to
miss doing it). It just checks that the last auto-assigned number
doesn't change, which is simplistic but will catch the most likely
sorts of mistakes.
From time to time we do need to add a node tag in a stable branch.
To support doing that without changing the branch's auto-assigned
tag numbers, invent pg_node_attr(nodetag_number(VALUE)) which can
be used to give such a node a hand-assigned tag above the last
auto-assigned one.
Discussion: https://postgr.es/m/1249010.1657574337@sss.pgh.pa.us
This allows explaining gen_node_support.pl's handling of execnodes.h
and some other input files as being a shortcut for explicit marking
of all their node declarations as pg_node_attr(nodetag_only).
I foresee that someday we might need to be more fine-grained about
that, and this change provides the infrastructure needed to do so.
For now, it just allows removal of the script's klugy special case
for CallContext and InlineCodeBlock.
Discussion: https://postgr.es/m/75063.1657410615@sss.pgh.pa.us
copyfuncs.c and friends no longer seem like great places to put
high-level remarks about what's covered and what isn't. Move that
material to backend/nodes/README and other more-prominent places.
Add back (versions of) some remarks that disappeared in 2be87f092.
Discussion: https://postgr.es/m/3843645.1657385930@sss.pgh.pa.us
In the same vein as commit 251154beb, make it clear that we never
instantiate PlanState.
Also mark MemoryContextData as abstract. This has no effect right now,
since memnodes.h isn't one of the files fed to gen_node_support.pl.
But it seems like good documentation and future-proofing.
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
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
Use it for RelationSyncEntry->streamed_txns, which is currently using an
integer list.
The API support is not complete, not because it is hard to write but
because it's unclear that it's worth the code space, there being so
little use of XID lists.
Discussion: https://postgr.es/m/202205130830.g5ntonhztspb@alvherre.pgsql
Reviewed-by: Amit Kapila <amit.kapila16@gmail.com>
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
inline_cte() expected to find exactly as many references to the
target CTE as its cterefcount indicates. While that should be
accurate for the tree as emitted by the parser, there are some
optimizations that occur upstream of here that could falsify it,
notably removal of unused subquery output expressions.
Trying to make the accounting 100% accurate seems expensive and
doomed to future breakage. It's not really worth it, because
all this code is protecting is downstream assumptions that every
referenced CTE has a plan. Let's convert those assertions to
regular test-and-elog just in case there's some actual problem,
and then drop the failing assertion.
Per report from Tomas Vondra (thanks also to Richard Guo for
analysis). Back-patch to v12 where the faulty code came in.
Discussion: https://postgr.es/m/29196a1e-ed47-c7ca-9be2-b1c636816183@enterprisedb.com
Up until now, we've had a policy of only marking certain variables
in the PostgreSQL header files with PGDLLIMPORT, but now we've
decided to mark them all. This means that extensions running on
Windows should no longer operate at a disadvantage as compared to
extensions running on Linux: if the variable is present in a header
file, it should be accessible.
Discussion: http://postgr.es/m/CA+TgmoYanc1_FSfimhgiWSqVyP5KKmh5NP2BWNwDhO8Pg2vGYQ@mail.gmail.com
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
This patch allows "PGC_SUSET" parameters to be set by non-superusers
if they have been explicitly granted the privilege to do so.
The privilege to perform ALTER SYSTEM SET/RESET on a specific parameter
can also be granted.
Such privileges are cluster-wide, not per database. They are tracked
in a new shared catalog, pg_parameter_acl.
Granting and revoking these new privileges works as one would expect.
One caveat is that PGC_USERSET GUCs are unaffected by the SET privilege
--- one could wish that those were handled by a revocable grant to
PUBLIC, but they are not, because we couldn't make it robust enough
for GUCs defined by extensions.
Mark Dilger, reviewed at various times by Andrew Dunstan, Robert Haas,
Joshua Brindle, and myself
Discussion: https://postgr.es/m/3D691E20-C1D5-4B80-8BA5-6BEB63AF3029@enterprisedb.com
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
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
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
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
When evaluating a query with a multi-column GROUP BY clause using sort,
the cost may be heavily dependent on the order in which the keys are
compared when building the groups. Grouping does not imply any ordering,
so we're allowed to compare the keys in arbitrary order, and a Hash Agg
leverages this. But for Group Agg, we simply compared keys in the order
as specified in the query. This commit explores alternative ordering of
the keys, trying to find a cheaper one.
In principle, we might generate grouping paths for all permutations of
the keys, and leave the rest to the optimizer. But that might get very
expensive, so we try to pick only a couple interesting orderings based
on both local and global information.
When planning the grouping path, we explore statistics (number of
distinct values, cost of the comparison function) for the keys and
reorder them to minimize comparison costs. Intuitively, it may be better
to perform more expensive comparisons (for complex data types etc.)
last, because maybe the cheaper comparisons will be enough. Similarly,
the higher the cardinality of a key, the lower the probability we’ll
need to compare more keys. The patch generates and costs various
orderings, picking the cheapest ones.
The ordering of group keys may interact with other parts of the query,
some of which may not be known while planning the grouping. E.g. there
may be an explicit ORDER BY clause, or some other ordering-dependent
operation, higher up in the query, and using the same ordering may allow
using either incremental sort or even eliminate the sort entirely.
The patch generates orderings and picks those minimizing the comparison
cost (for various pathkeys), and then adds orderings that might be
useful for operations higher up in the plan (ORDER BY, etc.). Finally,
it always keeps the ordering specified in the query, on the assumption
the user might have additional insights.
This introduces a new GUC enable_group_by_reordering, so that the
optimization may be disabled if needed.
The original patch was proposed by Teodor Sigaev, and later improved and
reworked by Dmitry Dolgov. Reviews by a number of people, including me,
Andrey Lepikhov, Claudio Freire, Ibrar Ahmed and Zhihong Yu.
Author: Dmitry Dolgov, Teodor Sigaev, Tomas Vondra
Reviewed-by: Tomas Vondra, Andrey Lepikhov, Claudio Freire, Ibrar Ahmed, Zhihong Yu
Discussion: https://postgr.es/m/7c79e6a5-8597-74e8-0671-1c39d124c9d6%40sigaev.ru
Discussion: https://postgr.es/m/CA%2Bq6zcW_4o2NC0zutLkOJPsFt80megSpX_dVRo6GK9PC-Jx_Ag%40mail.gmail.com
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
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
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
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
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
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
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
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
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
This feature allows skipping the transaction on subscriber nodes.
If incoming change violates any constraint, logical replication stops
until it's resolved. Currently, users need to either manually resolve the
conflict by updating a subscriber-side database or by using function
pg_replication_origin_advance() to skip the conflicting transaction. This
commit introduces a simpler way to skip the conflicting transactions.
The user can specify LSN by ALTER SUBSCRIPTION ... SKIP (lsn = XXX),
which allows the apply worker to skip the transaction finished at
specified LSN. The apply worker skips all data modification changes within
the transaction.
Author: Masahiko Sawada
Reviewed-by: Takamichi Osumi, Hou Zhijie, Peter Eisentraut, Amit Kapila, Shi Yu, Vignesh C, Greg Nancarrow, Haiying Tang, Euler Taveira
Discussion: https://postgr.es/m/CAD21AoDeScrsHhLyEPYqN3sydg6PxAPVBboK=30xJfUVihNZDA@mail.gmail.com
When an update on a partitioned table referenced in foreign key
constraints causes a row to move from one partition to another,
the fact that the move is implemented as a delete followed by an insert
on the target partition causes the foreign key triggers to have
surprising behavior. For example, a given foreign key's delete trigger
which implements the ON DELETE CASCADE clause of that key will delete
any referencing rows when triggered for that internal DELETE, although
it should not, because the referenced row is simply being moved from one
partition of the referenced root partitioned table into another, not
being deleted from it.
This commit teaches trigger.c to skip queuing such delete trigger events
on the leaf partitions in favor of an UPDATE event fired on the root
target relation. Doing so is sensible because both the old and the new
tuple "logically" belong to the root relation.
The after trigger event queuing interface now allows passing the source
and the target partitions of a particular cross-partition update when
registering the update event for the root partitioned table. Along with
the two ctids of the old and the new tuple, the after trigger event now
also stores the OIDs of those partitions. The tuples fetched from the
source and the target partitions are converted into the root table
format, if necessary, before they are passed to the trigger function.
The implementation currently has a limitation that only the foreign keys
pointing into the query's target relation are considered, not those of
its sub-partitioned partitions. That seems like a reasonable
limitation, because it sounds rare to have distinct foreign keys
pointing to sub-partitioned partitions instead of to the root table.
This misbehavior stems from commit f56f8f8da6 (which added support for
foreign keys to reference partitioned tables) not paying sufficient
attention to commit 2f17844104 (which had introduced cross-partition
updates a year earlier). Even though the former commit goes back to
Postgres 12, we're not backpatching this fix at this time for fear of
destabilizing things too much, and because there are a few ABI breaks in
it that we'd have to work around in older branches. It also depends on
commit f4566345cf, which had its own share of backpatchability issues
as well.
Author: Amit Langote <amitlangote09@gmail.com>
Reviewed-by: Masahiko Sawada <sawada.mshk@gmail.com>
Reviewed-by: Álvaro Herrera <alvherre@alvh.no-ip.org>
Reported-by: Eduard Català <eduard.catala@gmail.com>
Discussion: https://postgr.es/m/CA+HiwqFvkBCmfwkQX_yBqv2Wz8ugUGiBDxum8=WvVbfU1TXaNg@mail.gmail.com
Discussion: https://postgr.es/m/CAL54xNZsLwEM1XCk5yW9EqaRzsZYHuWsHQkA2L5MOSKXAwviCQ@mail.gmail.com
If a RowExpr is marked as returning a named composite type, we aren't
going to consult its colnames list; we'll use the attribute names
shown for the type in pg_attribute. Hence, skip storing that list,
to save a few nanoseconds when copying the expression tree around.
Discussion: https://postgr.es/m/2950001.1638729947@sss.pgh.pa.us
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
David Rowley
Tom Lane
Peter Eisentraut
Robert Haas
Alvaro Herrera
Tomas Vondra
Etsuro Fujita
Andrew Dunstan
Amit Kapila