| Commit message (Collapse) | Author | Age |
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Existing partition pruning is only able to work at plan time, for query
quals that appear in the parsed query. This is good but limiting, as
there can be parameters that appear later that can be usefully used to
further prune partitions.
This commit adds support for pruning subnodes of Append which cannot
possibly contain any matching tuples, during execution, by evaluating
Params to determine the minimum set of subnodes that can possibly match.
We support more than just simple Params in WHERE clauses. Support
additionally includes:
1. Parameterized Nested Loop Joins: The parameter from the outer side of the
join can be used to determine the minimum set of inner side partitions to
scan.
2. Initplans: Once an initplan has been executed we can then determine which
partitions match the value from the initplan.
Partition pruning is performed in two ways. When Params external to the plan
are found to match the partition key we attempt to prune away unneeded Append
subplans during the initialization of the executor. This allows us to bypass
the initialization of non-matching subplans meaning they won't appear in the
EXPLAIN or EXPLAIN ANALYZE output.
For parameters whose value is only known during the actual execution
then the pruning of these subplans must wait. Subplans which are
eliminated during this stage of pruning are still visible in the EXPLAIN
output. In order to determine if pruning has actually taken place, the
EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never
executed due to the elimination of the partition then the execution
timing area will state "(never executed)". Whereas, if, for example in
the case of parameterized nested loops, the number of loops stated in
the EXPLAIN ANALYZE output for certain subplans may appear lower than
others due to the subplan having been scanned fewer times. This is due
to the list of matching subnodes having to be evaluated whenever a
parameter which was found to match the partition key changes.
This commit required some additional infrastructure that permits the
building of a data structure which is able to perform the translation of
the matching partition IDs, as returned by get_matching_partitions, into
the list index of a subpaths list, as exist in node types such as
Append, MergeAppend and ModifyTable. This allows us to translate a list
of clauses into a Bitmapset of all the subpath indexes which must be
included to satisfy the clause list.
Author: David Rowley, based on an earlier effort by Beena Emerson
Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi,
Jesper Pedersen
Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
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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 other require multiple PL statements.
e.g.
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 and partitioned tables, including
column and row security enforcement, as well as support for
row, statement and transition triggers.
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 statically from PL/pgSQL.
MERGE does not yet support inheritance, write rules,
RETURNING clauses, updatable views or foreign tables.
MERGE follows SQL Standard per the most recent SQL:2016.
Includes full tests and documentation, including full
isolation tests to demonstrate the concurrent behavior.
This version written from scratch in 2017 by Simon Riggs,
using docs and tests originally written in 2009. Later work
from Pavan Deolasee has been both complex and deep, leaving
the lead author credit now in his hands.
Extensive discussion of concurrency from Peter Geoghegan,
with thanks for the time and effort contributed.
Various issues reported via sqlsmith by Andreas Seltenreich
Authors: Pavan Deolasee, Simon Riggs
Reviewer: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs
Discussion:
https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.com
https://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
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This reverts commit 354f13855e6381d288dfaa52bcd4f2cb0fd4a5eb.
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Since commit 4f15e5d09de276fb77326be5567dd9796008ca2e made grouped_rel
set reltarget, a variety of other functions can just get it from
grouped_rel instead of having to pass it around explicitly. Simplify
accordingly.
Patch by me, reviewed by Ashutosh Bapat.
Discussion: http://postgr.es/m/CA+TgmoZ+ZJTVad-=vEq393N99KTooxv9k7M+z73qnTAqkb49BQ@mail.gmail.com
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When an UPDATE causes a row to no longer match the partition
constraint, try to move it to a different partition where it does
match the partition constraint. In essence, the UPDATE is split into
a DELETE from the old partition and an INSERT into the new one. This
can lead to surprising behavior in concurrency scenarios because
EvalPlanQual rechecks won't work as they normally did; the known
problems are documented. (There is a pending patch to improve the
situation further, but it needs more review.)
Amit Khandekar, reviewed and tested by Amit Langote, David Rowley,
Rajkumar Raghuwanshi, Dilip Kumar, Amul Sul, Thomas Munro, Álvaro
Herrera, Amit Kapila, and me. A few final revisions by me.
Discussion: http://postgr.es/m/CAJ3gD9do9o2ccQ7j7+tSgiE1REY65XRiMb=yJO3u3QhyP8EEPQ@mail.gmail.com
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Backpatch-through: certain files through 9.3
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Introduce parallel-aware hash joins that appear in EXPLAIN plans as Parallel
Hash Join with Parallel Hash. While hash joins could already appear in
parallel queries, they were previously always parallel-oblivious and had a
partial subplan only on the outer side, meaning that the work of the inner
subplan was duplicated in every worker.
After this commit, the planner will consider using a partial subplan on the
inner side too, using the Parallel Hash node to divide the work over the
available CPU cores and combine its results in shared memory. If the join
needs to be split into multiple batches in order to respect work_mem, then
workers process different batches as much as possible and then work together
on the remaining batches.
The advantages of a parallel-aware hash join over a parallel-oblivious hash
join used in a parallel query are that it:
* avoids wasting memory on duplicated hash tables
* avoids wasting disk space on duplicated batch files
* divides the work of building the hash table over the CPUs
One disadvantage is that there is some communication between the participating
CPUs which might outweigh the benefits of parallelism in the case of small
hash tables. This is avoided by the planner's existing reluctance to supply
partial plans for small scans, but it may be necessary to estimate
synchronization costs in future if that situation changes. Another is that
outer batch 0 must be written to disk if multiple batches are required.
A potential future advantage of parallel-aware hash joins is that right and
full outer joins could be supported, since there is a single set of matched
bits for each hashtable, but that is not yet implemented.
A new GUC enable_parallel_hash is defined to control the feature, defaulting
to on.
Author: Thomas Munro
Reviewed-By: Andres Freund, Robert Haas
Tested-By: Rafia Sabih, Prabhat Sahu
Discussion:
https://postgr.es/m/CAEepm=2W=cOkiZxcg6qiFQP-dHUe09aqTrEMM7yJDrHMhDv_RA@mail.gmail.com
https://postgr.es/m/CAEepm=37HKyJ4U6XOLi=JgfSHM3o6B-GaeO-6hkOmneTDkH+Uw@mail.gmail.com
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When we create an Append node, we can spread out the workers over the
subplans instead of piling on to each subplan one at a time, which
should typically be a bit more efficient, both because the startup
cost of any plan executed entirely by one worker is paid only once and
also because of reduced contention. We can also construct Append
plans using a mix of partial and non-partial subplans, which may allow
for parallelism in places that otherwise couldn't support it.
Unfortunately, this patch doesn't handle the important case of
parallelizing UNION ALL by running each branch in a separate worker;
the executor infrastructure is added here, but more planner work is
needed.
Amit Khandekar, Robert Haas, Amul Sul, reviewed and tested by
Ashutosh Bapat, Amit Langote, Rafia Sabih, Amit Kapila, and
Rajkumar Raghuwanshi.
Discussion: http://postgr.es/m/CAJ3gD9dy0K_E8r727heqXoBmWZ83HwLFwdcaSSmBQ1+S+vRuUQ@mail.gmail.com
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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
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Instead of duplicating the logic to search for a matching
ParamPathInfo in multiple places, factor it out into a separate
function.
Pass only the relevant bits of the PartitionKey to
partition_bounds_equal instead of the whole thing, because
partition-wise join will want to call this without having a
PartitionKey available.
Adjust allow_star_schema_join and calc_nestloop_required_outer
to take relevant Relids rather than the entire Path, because
partition-wise join will want to call it with the top-parent
relids to determine whether a child join is allowable.
Ashutosh Bapat. Review and testing of the larger patch set of which
this is a part by Amit Langote, Rajkumar Raghuwanshi, Rafia Sabih,
Thomas Munro, Dilip Kumar, and me.
Discussion: http://postgr.es/m/CA+TgmobQK80vtXjAsPZWWXd7c8u13G86gmuLupN+uUJjA+i4nA@mail.gmail.com
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Change pg_bsd_indent to follow upstream rules for placement of comments
to the right of code, and remove pgindent hack that caused comments
following #endif to not obey the general rule.
Commit e3860ffa4dd0dad0dd9eea4be9cc1412373a8c89 wasn't actually using
the published version of pg_bsd_indent, but a hacked-up version that
tried to minimize the amount of movement of comments to the right of
code. The situation of interest is where such a comment has to be
moved to the right of its default placement at column 33 because there's
code there. BSD indent has always moved right in units of tab stops
in such cases --- but in the previous incarnation, indent was working
in 8-space tab stops, while now it knows we use 4-space tabs. So the
net result is that in about half the cases, such comments are placed
one tab stop left of before. This is better all around: it leaves
more room on the line for comment text, and it means that in such
cases the comment uniformly starts at the next 4-space tab stop after
the code, rather than sometimes one and sometimes two tabs after.
Also, ensure that comments following #endif are indented the same
as comments following other preprocessor commands such as #else.
That inconsistency turns out to have been self-inflicted damage
from a poorly-thought-through post-indent "fixup" in pgindent.
This patch is much less interesting than the first round of indent
changes, but also bulkier, so I thought it best to separate the effects.
Discussion: https://postgr.es/m/E1dAmxK-0006EE-1r@gemulon.postgresql.org
Discussion: https://postgr.es/m/30527.1495162840@sss.pgh.pa.us
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perltidy run not included.
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If there can certainly be no more than one matching inner row for a given
outer row, then the executor can move on to the next outer row as soon as
it's found one match; there's no need to continue scanning the inner
relation for this outer row. This saves useless scanning in nestloop
and hash joins. In merge joins, it offers the opportunity to skip
mark/restore processing, because we know we have not advanced past the
first possible match for the next outer row.
Of course, the devil is in the details: the proof of uniqueness must
depend only on joinquals (not otherquals), and if we want to skip
mergejoin mark/restore then it must depend only on merge clauses.
To avoid adding more planning overhead than absolutely necessary,
the present patch errs in the conservative direction: there are cases
where inner_unique or skip_mark_restore processing could be used, but
it will not do so because it's not sure that the uniqueness proof
depended only on "safe" clauses. This could be improved later.
David Rowley, reviewed and rather heavily editorialized on by me
Discussion: https://postgr.es/m/CAApHDvqF6Sw-TK98bW48TdtFJ+3a7D2mFyZ7++=D-RyPsL76gw@mail.gmail.com
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Currently, the only type of child relation is an "other member rel",
which is the child of a baserel, but in the future joins and even
upper relations may have child rels. To facilitate that, introduce
macros that test to test for particular RelOptKind values, and use
them in various places where they help to clarify the sense of a test.
(For example, a test may allow RELOPT_OTHER_MEMBER_REL either because
it intends to allow child rels, or because it intends to allow simple
rels.)
Also, remove find_childrel_top_parent, which will not work for a
child rel that is not a baserel. Instead, add a new RelOptInfo
member top_parent_relids to track the same kind of information in a
more generic manner.
Ashutosh Bapat, slightly tweaked by me. Review and testing of the
patch set from which this was taken by Rajkumar Raghuwanshi and Rafia
Sabih.
Discussion: http://postgr.es/m/CA+TgmoagTnF2yqR3PT2rv=om=wJiZ4-A+ATwdnriTGku1CLYxA@mail.gmail.com
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A QueryEnvironment concept is added, which allows new types of
objects to be passed into queries from parsing on through
execution. At this point, the only thing implemented is a
collection of EphemeralNamedRelation objects -- relations which
can be referenced by name in queries, but do not exist in the
catalogs. The only type of ENR implemented is NamedTuplestore, but
provision is made to add more types fairly easily.
An ENR can carry its own TupleDesc or reference a relation in the
catalogs by relid.
Although these features can be used without SPI, convenience
functions are added to SPI so that ENRs can easily be used by code
run through SPI.
The initial use of all this is going to be transition tables in
AFTER triggers, but that will be added to each PL as a separate
commit.
An incidental effect of this patch is to produce a more informative
error message if an attempt is made to modify the contents of a CTE
from a referencing DML statement. No tests previously covered that
possibility, so one is added.
Kevin Grittner and Thomas Munro
Reviewed by Heikki Linnakangas, David Fetter, and Thomas Munro
with valuable comments and suggestions from many others
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This extends the Aggregate node with two new features: HashAggregate
can now run multiple hashtables concurrently, and a new strategy
MixedAggregate populates hashtables while doing sorted grouping.
The planner will now attempt to save as many sorts as possible when
planning grouping sets queries, while not exceeding work_mem for the
estimated combined sizes of all hashtables used. No SQL-level changes
are required. There should be no user-visible impact other than the
new EXPLAIN output and possible changes to result ordering when ORDER
BY was not used (which affected a few regression tests). The
enable_hashagg option is respected.
Author: Andrew Gierth
Reviewers: Mark Dilger, Andres Freund
Discussion: https://postgr.es/m/87vatszyhj.fsf@news-spur.riddles.org.uk
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Partitioned tables do not contain any data; only their unpartitioned
descendents need to be scanned. However, the partitioned tables still
need to be locked, even though they're not scanned. To make that
work, Append and MergeAppend relations now need to carry a list of
(unscanned) partitioned relations that must be locked, and InitPlan
must lock all partitioned result relations.
Aside from the obvious advantage of avoiding some work at execution
time, this has two other advantages. First, it may improve the
planner's decision-making in some cases since the empty relation
might throw things off. Second, it paves the way to getting rid of
the storage for partitioned tables altogether.
Amit Langote, reviewed by me.
Discussion: http://postgr.es/m/6837c359-45c4-8044-34d1-736756335a15@lab.ntt.co.jp
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Like Gather, we spawn multiple workers and run the same plan in each
one; however, Gather Merge is used when each worker produces the same
output ordering and we want to preserve that output ordering while
merging together the streams of tuples from various workers. (In a
way, Gather Merge is like a hybrid of Gather and MergeAppend.)
This works out to a win if it saves us from having to perform an
expensive Sort. In cases where only a small amount of data would need
to be sorted, it may actually be faster to use a regular Gather node
and then sort the results afterward, because Gather Merge sometimes
needs to wait synchronously for tuples whereas a pure Gather generally
doesn't. But if this avoids an expensive sort then it's a win.
Rushabh Lathia, reviewed and tested by Amit Kapila, Thomas Munro,
and Neha Sharma, and reviewed and revised by me.
Discussion: http://postgr.es/m/CAGPqQf09oPX-cQRpBKS0Gq49Z+m6KBxgxd_p9gX8CKk_d75HoQ@mail.gmail.com
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The index is scanned by a single process, but then all cooperating
processes can iterate jointly over the resulting set of heap blocks.
In the future, we might also want to support using a parallel bitmap
index scan to set up for a parallel bitmap heap scan, but that's a
job for another day.
Dilip Kumar, with some corrections and cosmetic changes by me. The
larger patch set of which this is a part has been reviewed and tested
by (at least) Andres Freund, Amit Khandekar, Tushar Ahuja, Rafia
Sabih, Haribabu Kommi, Thomas Munro, and me.
Discussion: http://postgr.es/m/CAFiTN-uc4=0WxRGfCzs-xfkMYcSEWUC-Fon6thkJGjkh9i=13A@mail.gmail.com
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XMLTABLE is defined by the SQL/XML standard as a feature that allows
turning XML-formatted data into relational form, so that it can be used
as a <table primary> in the FROM clause of a query.
This new construct provides significant simplicity and performance
benefit for XML data processing; what in a client-side custom
implementation was reported to take 20 minutes can be executed in 400ms
using XMLTABLE. (The same functionality was said to take 10 seconds
using nested PostgreSQL XPath function calls, and 5 seconds using
XMLReader under PL/Python).
The implemented syntax deviates slightly from what the standard
requires. First, the standard indicates that the PASSING clause is
optional and that multiple XML input documents may be given to it; we
make it mandatory and accept a single document only. Second, we don't
currently support a default namespace to be specified.
This implementation relies on a new executor node based on a hardcoded
method table. (Because the grammar is fixed, there is no extensibility
in the current approach; further constructs can be implemented on top of
this such as JSON_TABLE, but they require changes to core code.)
Author: Pavel Stehule, Álvaro Herrera
Extensively reviewed by: Craig Ringer
Discussion: https://postgr.es/m/CAFj8pRAgfzMD-LoSmnMGybD0WsEznLHWap8DO79+-GTRAPR4qA@mail.gmail.com
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In combination with 569174f1be92be93f5366212cc46960d28a5c5cd, which
taught the btree AM how to perform parallel index scans, this allows
parallel index scan plans on btree indexes. This infrastructure
should be general enough to support parallel index scans for other
index AMs as well, if someone updates them to support parallel
scans.
Amit Kapila, reviewed and tested by Anastasia Lubennikova, Tushar
Ahuja, and Haribabu Kommi, and me.
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Evaluation of set returning functions (SRFs_ in the targetlist (like SELECT
generate_series(1,5)) so far was done in the expression evaluation (i.e.
ExecEvalExpr()) and projection (i.e. ExecProject/ExecTargetList) code.
This meant that most executor nodes performing projection, and most
expression evaluation functions, had to deal with the possibility that an
evaluated expression could return a set of return values.
That's bad because it leads to repeated code in a lot of places. It also,
and that's my (Andres's) motivation, made it a lot harder to implement a
more efficient way of doing expression evaluation.
To fix this, introduce a new executor node (ProjectSet) that can evaluate
targetlists containing one or more SRFs. To avoid the complexity of the old
way of handling nested expressions returning sets (e.g. having to pass up
ExprDoneCond, and dealing with arguments to functions returning sets etc.),
those SRFs can only be at the top level of the node's targetlist. The
planner makes sure (via split_pathtarget_at_srfs()) that SRF evaluation is
only necessary in ProjectSet nodes and that SRFs are only present at the
top level of the node's targetlist. If there are nested SRFs the planner
creates multiple stacked ProjectSet nodes. The ProjectSet nodes always get
input from an underlying node.
We also discussed and prototyped evaluating targetlist SRFs using ROWS
FROM(), but that turned out to be more complicated than we'd hoped.
While moving SRF evaluation to ProjectSet would allow to retain the old
"least common multiple" behavior when multiple SRFs are present in one
targetlist (i.e. continue returning rows until all SRFs are at the end of
their input at the same time), we decided to instead only return rows till
all SRFs are exhausted, returning NULL for already exhausted ones. We
deemed the previous behavior to be too confusing, unexpected and actually
not particularly useful.
As a side effect, the previously prohibited case of multiple set returning
arguments to a function, is now allowed. Not because it's particularly
desirable, but because it ends up working and there seems to be no argument
for adding code to prohibit it.
Currently the behavior for COALESCE and CASE containing SRFs has changed,
returning multiple rows from the expression, even when the SRF containing
"arm" of the expression is not evaluated. That's because the SRFs are
evaluated in a separate ProjectSet node. As that's quite confusing, we're
likely to instead prohibit SRFs in those places. But that's still being
discussed, and the code would reside in places not touched here, so that's
a task for later.
There's a lot of, now superfluous, code dealing with set return expressions
around. But as the changes to get rid of those are verbose largely boring,
it seems better for readability to keep the cleanup as a separate commit.
Author: Tom Lane and Andres Freund
Discussion: https://postgr.es/m/20160822214023.aaxz5l4igypowyri@alap3.anarazel.de
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The original coding had three separate booleans representing partial
aggregation behavior, which was confusing, unreadable, and error-prone,
not least because the booleans weren't always listed in the same order.
It was also inadequate for the allegedly-desirable future extension to
support intermediate partial aggregation, because we'd need separate
markers for serialization and deserialization in such a case.
Merge these bools into an enum "AggSplit" to provide symbolic names for
the supported operating modes (and document what those are). By assigning
the values of the enum constants carefully, we can treat AggSplit values
as options bitmasks so that tests of what to do aren't noticeably more
expensive than before.
While at it, get rid of Aggref.aggoutputtype. That's not needed since
commit 59a3795c2 got rid of setrefs.c's special-purpose Aggref comparison
code, and it likewise seemed more confusing than helpful.
Assorted comment cleanup as well (there's still more that I want to do
in that line).
catversion bump for change in Aggref node contents. Should be the last
one for partial-aggregation changes.
Discussion: <29309.1466699160@sss.pgh.pa.us>
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The original upper-planner-pathification design (commit 3fc6e2d7f5b652b4)
assumed that we could always determine during Path formation whether or not
we would need a Result plan node to perform projection of a targetlist.
That turns out not to work very well, though, because createplan.c still
has some responsibilities for choosing the specific target list associated
with sorting/grouping nodes (in particular it might choose to add resjunk
columns for sorting). We might not ever refactor that --- doing so would
push more work into Path formation, which isn't attractive --- and we
certainly won't do so for 9.6. So, while create_projection_path and
apply_projection_to_path can tell for sure what will happen if the subpath
is projection-capable, they can't tell for sure when it isn't. This is at
least a latent bug in apply_projection_to_path, which might think it can
apply a target to a non-projecting node when the node will end up computing
something different.
Also, I'd tied the creation of a ProjectionPath node to whether or not a
Result is needed, but it turns out that we sometimes need a ProjectionPath
node anyway to avoid modifying a possibly-shared subpath node. Callers had
to use create_projection_path for such cases, and we added code to them
that knew about the potential omission of a Result node and attempted to
adjust the cost estimates for that. That was uncertainly correct and
definitely ugly/unmaintainable.
To fix, have create_projection_path explicitly check whether a Result
is needed and adjust its cost estimate accordingly, though it creates
a ProjectionPath in either case. apply_projection_to_path is now mostly
just an optimized version that can avoid creating an extra Path node when
the input is known to not be shared with any other live path. (There
is one case that create_projection_path doesn't handle, which is pushing
parallel-safe expressions below a Gather node. We could make it do that
by duplicating the GatherPath, but there seems no need as yet.)
create_projection_plan still has to recheck the tlist-match condition,
which means that if the matching situation does get changed by createplan.c
then we'll have made a slightly incorrect cost estimate. But there seems
no help for that in the near term, and I doubt it occurs often enough,
let alone would change planning decisions often enough, to be worth
stressing about.
I added a "dummypp" field to ProjectionPath to track whether
create_projection_path thinks a Result is needed. This is not really
necessary as-committed because create_projection_plan doesn't look at the
flag; but it seems like a good idea to remember what we thought when
forming the cost estimate, if only for debugging purposes.
In passing, get rid of the target_parallel parameter added to
apply_projection_to_path by commit 54f5c5150. I don't think that's a good
idea because it involves callers in what should be an internal decision,
and opens us up to missing optimization opportunities if callers think they
don't need to provide a valid flag, as most don't. For the moment, this
just costs us an extra has_parallel_hazard call when planning a Gather.
If that starts to look expensive, I think a better solution would be to
teach PathTarget to carry/cache knowledge of parallel-safety of its
contents.
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Commit 04ae11f62e643e07c411c4935ea6af46cb112aa9 removed some broken
code to apply the scan/join target to partial paths, but its theory
that this processing step is totally unnecessary turns out to be wrong.
Put similar code back again, but this time, check for parallel-safety
and avoid in-place modifications to paths that may already have been
used as part of some other path.
(This is not an entirely elegant solution to this problem; it might
be better, for example, to postpone generate_gather_paths for the
topmost scan/join rel until after the scan/join target has been
applied. But this is not the time for such redesign work.)
Amit Kapila and Robert Haas
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This terminology provoked widespread complaints. So, instead, rename
the GUC max_parallel_degree to max_parallel_workers_per_gather
(leaving room for a possible future GUC max_parallel_workers that acts
as a system-wide limit), and rename the parallel_degree reloption to
parallel_workers. Rename structure members to match.
These changes create a dump/restore hazard for users of PostgreSQL
9.6beta1 who have set the reloption (or applied the GUC using ALTER
USER or ALTER DATABASE).
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This is necessary infrastructure for supporting parallel aggregation
for aggregates whose transition type is "internal". Such values
can't be passed between cooperating processes, because they are
just pointers.
David Rowley, reviewed by Tomas Vondra and by me.
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Parallel workers can now partially aggregate the data and pass the
transition values back to the leader, which can combine the partial
results to produce the final answer.
David Rowley, based on earlier work by Haribabu Kommi. Reviewed by
Álvaro Herrera, Tomas Vondra, Amit Kapila, James Sewell, and me.
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Although the default choice of rel->reltarget should typically be
sufficient for scan or join paths, it's not at all sufficient for the
purposes PathTargets were invented for; in particular not for
upper-relation Paths. So break API compatibility by adding a PathTarget
argument to create_foreignscan_path(). To ease updating of existing
code, accept a NULL value of the argument as selecting rel->reltarget.
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Instead of having planner.c compute a groupColIdx array and store it in
GroupingSetsPaths, make create_groupingsets_plan() find the grouping
columns by searching in the child plan node's tlist. Although that's
probably a bit slower for create_groupingsets_plan(), it's more like
the way every other plan node type does this, and it provides positive
confirmation that we know which child output columns we're supposed to be
grouping on. (Indeed, looking at this now, I'm not at all sure that it
wasn't broken before, because create_groupingsets_plan() isn't demanding
an exact tlist match from its child node.) Also, this allows substantial
simplification in planner.c, because it no longer needs to compute the
groupColIdx array at all; no other cases were using it.
I'd intended to put off this refactoring until later (like 9.7), but
in view of the likely bug fix and the need to rationalize planner.c's
tlist handling so we can do something sane with Konstantin Knizhnik's
function-evaluation-postponement patch, I think it can't wait.
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This patch removes some redundant cost calculations that I left for later
cleanup in commit 3fc6e2d7f5b652b4. There's now a uniform policy that the
make_foo() convenience functions don't do any cost calculations. Most of
their callers copy costs from the source Path node, and for those that
don't, the calculation in the make_foo() function wasn't necessarily right
anyhow. (make_result() was particularly a mess, as it was serving multiple
callers using cost calcs designed for only the first one or two that had
ever existed.) Aside from saving a few cycles, this ensures that what
EXPLAIN prints matches the costs we used for planning purposes. It does
not change any planner decisions, since the decisions are already made.
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I've been saying we needed to do this for more than five years, and here it
finally is. This patch removes the ever-growing tangle of spaghetti logic
that grouping_planner() used to use to try to identify the best plan for
post-scan/join query steps. Now, there is (nearly) independent
consideration of each execution step, and entirely separate construction of
Paths to represent each of the possible ways to do that step. We choose
the best Path or set of Paths using the same add_path() logic that's been
used inside query_planner() for years.
In addition, this patch removes the old restriction that subquery_planner()
could return only a single Plan. It now returns a RelOptInfo containing a
set of Paths, just as query_planner() does, and the parent query level can
use each of those Paths as the basis of a SubqueryScanPath at its level.
This allows finding some optimizations that we missed before, wherein a
subquery was capable of returning presorted data and thereby avoiding a
sort in the parent level, making the overall cost cheaper even though
delivering sorted output was not the cheapest plan for the subquery in
isolation. (A couple of regression test outputs change in consequence of
that. However, there is very little change in visible planner behavior
overall, because the point of this patch is not to get immediate planning
benefits but to create the infrastructure for future improvements.)
There is a great deal left to do here. This patch unblocks a lot of
planner work that was basically impractical in the old code structure,
such as allowing FDWs to implement remote aggregation, or rewriting
plan_set_operations() to allow consideration of multiple implementation
orders for set operations. (The latter will likely require a full
rewrite of plan_set_operations(); what I've done here is only to fix it
to return Paths not Plans.) I have also left unfinished some localized
refactoring in createplan.c and planner.c, because it was not necessary
to get this patch to a working state.
Thanks to Robert Haas, David Rowley, and Amit Kapila for review.
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The core innovation of this patch is the introduction of the concept
of a partial path; that is, a path which if executed in parallel will
generate a subset of the output rows in each process. Gathering a
partial path produces an ordinary (complete) path. This allows us to
generate paths for parallel joins by joining a partial path for one
side (which at the baserel level is currently always a Partial Seq
Scan) to an ordinary path on the other side. This is subject to
various restrictions at present, especially that this strategy seems
unlikely to be sensible for merge joins, so only nested loops and
hash joins paths are generated.
This also allows an Append node to be pushed below a Gather node in
the case of a partitioned table.
Testing revealed that early versions of this patch made poor decisions
in some cases, which turned out to be caused by the fact that the
original cost model for Parallel Seq Scan wasn't very good. So this
patch tries to make some modest improvements in that area.
There is much more to be done in the area of generating good parallel
plans in all cases, but this seems like a useful step forward.
Patch by me, reviewed by Dilip Kumar and Amit Kapila.
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Backpatch certain files through 9.1
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More fuzz testing by Andreas Seltenreich exposed that the planner did not
cope well with chains of lateral references. If relation X references Y
laterally, and Y references Z laterally, then we will have to scan X on the
inside of a nestloop with Z, so for all intents and purposes X is laterally
dependent on Z too. The planner did not understand this and would generate
intermediate joins that could not be used. While that was usually harmless
except for wasting some planning cycles, under the right circumstances it
would lead to "failed to build any N-way joins" or "could not devise a
query plan" planner failures.
To fix that, convert the existing per-relation lateral_relids and
lateral_referencers relid sets into their transitive closures; that is,
they now show all relations on which a rel is directly or indirectly
laterally dependent. This not only fixes the chained-reference problem
but allows some of the relevant tests to be made substantially simpler
and faster, since they can be reduced to simple bitmap manipulations
instead of searches of the LateralJoinInfo list.
Also, when a PlaceHolderVar that is due to be evaluated at a join contains
lateral references, we should treat those references as indirect lateral
dependencies of each of the join's base relations. This prevents us from
trying to join any individual base relations to the lateral reference
source before the join is formed, which again cannot work.
Andreas' testing also exposed another oversight in the "dangerous
PlaceHolderVar" test added in commit 85e5e222b1dd02f1. Simply rejecting
unsafe join paths in joinpath.c is insufficient, because in some cases
we will end up rejecting *all* possible paths for a particular join, again
leading to "could not devise a query plan" failures. The restriction has
to be known also to join_is_legal and its cohort functions, so that they
will not select a join for which that will happen. I chose to move the
supporting logic into joinrels.c where the latter functions are.
Back-patch to 9.3 where LATERAL support was introduced.
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Commit e7cb7ee14555cc9c5773e2c102efd6371f6f2005 provided basic
infrastructure for allowing a foreign data wrapper or custom scan
provider to replace a join of one or more tables with a scan.
However, this infrastructure failed to take into account the need
for possible EvalPlanQual rechecks, and ExecScanFetch would fail
an assertion (or just overwrite memory) if such a check was attempted
for a plan containing a pushed-down join. To fix, adjust the EPQ
machinery to skip some processing steps when scanrelid == 0, making
those the responsibility of scan's recheck method, which also has
the responsibility in this case of correctly populating the relevant
slot.
To allow foreign scans to gain control in the right place to make
use of this new facility, add a new, optional RecheckForeignScan
method. Also, allow a foreign scan to have a child plan, which can
be used to correctly populate the slot (or perhaps for something
else, but this is the only use currently envisioned).
KaiGai Kohei, reviewed by Robert Haas, Etsuro Fujita, and Kyotaro
Horiguchi.
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It was possible for the planner to decide to join a LATERAL subquery to
the outer side of an outer join before the outer join itself is completed.
Normally that's fine because of the associativity rules, but it doesn't
work if the subquery contains a lateral reference to the inner side of the
outer join. In such a situation the outer join *must* be done first.
join_is_legal() missed this consideration and would allow the join to be
attempted, but the actual path-building code correctly decided that no
valid join path could be made, sometimes leading to planner errors such as
"failed to build any N-way joins".
Per report from Andreas Seltenreich. Back-patch to 9.3 where LATERAL
support was added.
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In addition, this path fills in a number of missing bits and pieces in
the parallel infrastructure. Paths and plans now have a parallel_aware
flag indicating whether whatever parallel-aware logic they have should
be engaged. It is believed that we will need this flag for a number of
path/plan types, not just sequential scans, which is why the flag is
generic rather than part of the SeqScan structures specifically.
Also, execParallel.c now gives parallel nodes a chance to initialize
their PlanState nodes from the DSM during parallel worker startup.
Amit Kapila, with a fair amount of adjustment by me. Review of previous
patch versions by Haribabu Kommi and others.
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A Gather executor node runs any number of copies of a plan in an equal
number of workers and merges all of the results into a single tuple
stream. It can also run the plan itself, if the workers are
unavailable or haven't started up yet. It is intended to work with
the Partial Seq Scan node which will be added in future commits.
It could also be used to implement parallel query of a different sort
by itself, without help from Partial Seq Scan, if the single_copy mode
is used. In that mode, a worker executes the plan, and the parallel
leader does not, merely collecting the worker's results. So, a Gather
node could be inserted into a plan to split the execution of that plan
across two processes. Nested Gather nodes aren't currently supported,
but we might want to add support for that in the future.
There's nothing in the planner to actually generate Gather nodes yet,
so it's not quite time to break out the champagne. But we're getting
close.
Amit Kapila. Some designs suggestions were provided by me, and I also
reviewed the patch. Single-copy mode, documentation, and other minor
changes also by me.
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Add a TABLESAMPLE clause to SELECT statements that allows
user to specify random BERNOULLI sampling or block level
SYSTEM sampling. Implementation allows for extensible
sampling functions to be written, using a standard API.
Basic version follows SQLStandard exactly. Usable
concrete use cases for the sampling API follow in later
commits.
Petr Jelinek
Reviewed by Michael Paquier and Simon Riggs
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Backpatch certain files through 9.0
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Instead of register_custom_path_provider and a CreateCustomScanPath
callback, let's just provide a standard function hook in set_rel_pathlist.
This is more flexible than what was previously committed, is more like the
usual conventions for planner hooks, and requires less support code in the
core. We had discussed this design (including centralizing the
set_cheapest() calls) back in March or so, so I'm not sure why it wasn't
done like this already.
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Get rid of the pernicious entanglement between planner and executor headers
introduced by commit 0b03e5951bf0a1a8868db13f02049cf686a82165.
Also, rearrange the CustomFoo struct/typedef definitions so that all the
typedef names are seen as used by the compiler. Without this pgindent
will mess things up a bit, which is not so important perhaps, but it also
removes a bizarre discrepancy between the declaration arrangement used for
CustomExecMethods and that used for CustomScanMethods and
CustomPathMethods.
Clean up the commentary around ExecSupportsMarkRestore to reflect the
rather large change in its API.
Const-ify register_custom_path_provider's argument. This necessitates
casting away const in the function, but that seems better than forcing
callers of the function to do so (or else not const-ify their method
pointer structs, which was sort of the whole point).
De-export fix_expr_common. I don't like the exporting of fix_scan_expr
or replace_nestloop_params either, but this one surely has got little
excuse.
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This allows extension modules to define their own methods for
scanning a relation, and get the core code to use them. It's
unclear as yet how much use this capability will find, but we
won't find out if we never commit it.
KaiGai Kohei, reviewed at various times and in various levels
of detail by Shigeru Hanada, Tom Lane, Andres Freund, Álvaro
Herrera, and myself.
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As of commit a87c72915 (which later got backpatched as far as 9.1),
we're explicitly supporting the notion that append relations can be
nested; this can occur when UNION ALL constructs are nested, or when
a UNION ALL contains a table with inheritance children.
Bug #11457 from Nelson Page, as well as an earlier report from Elvis
Pranskevichus, showed that there were still nasty bugs associated with such
cases: in particular the EquivalenceClass mechanism could try to generate
"join" clauses connecting an appendrel child to some grandparent appendrel,
which would result in assertion failures or bogus plans.
Upon investigation I concluded that all current callers of
find_childrel_appendrelinfo() need to be fixed to explicitly consider
multiple levels of parent appendrels. The most complex fix was in
processing of "broken" EquivalenceClasses, which are ECs for which we have
been unable to generate all the derived equality clauses we would like to
because of missing cross-type equality operators in the underlying btree
operator family. That code path is more or less entirely untested by
the regression tests to date, because no standard opfamilies have such
holes in them. So I wrote a new regression test script to try to exercise
it a bit, which turned out to be quite a worthwhile activity as it exposed
existing bugs in all supported branches.
The present patch is essentially the same as far back as 9.2, which is
where parameterized paths were introduced. In 9.0 and 9.1, we only need
to back-patch a small fragment of commit 5b7b5518d, which fixes failure to
propagate out the original WHERE clauses when a broken EC contains constant
members. (The regression test case results show that these older branches
are noticeably stupider than 9.2+ in terms of the quality of the plans
generated; but we don't really care about plan quality in such cases,
only that the plan not be outright wrong. A more invasive fix in the
older branches would not be a good idea anyway from a plan-stability
standpoint.)
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Update all files in head, and files COPYRIGHT and legal.sgml in all back
branches.
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This patch adds the ability to write TABLE( function1(), function2(), ...)
as a single FROM-clause entry. The result is the concatenation of the
first row from each function, followed by the second row from each
function, etc; with NULLs inserted if any function produces fewer rows than
others. This is believed to be a much more useful behavior than what
Postgres currently does with multiple SRFs in a SELECT list.
This syntax also provides a reasonable way to combine use of column
definition lists with WITH ORDINALITY: put the column definition list
inside TABLE(), where it's clear that it doesn't control the ordinality
column as well.
Also implement SQL-compliant multiple-argument UNNEST(), by turning
UNNEST(a,b,c) into TABLE(unnest(a), unnest(b), unnest(c)).
The SQL standard specifies TABLE() with only a single function, not
multiple functions, and it seems to require an implicit UNNEST() which is
not what this patch does. There may be something wrong with that reading
of the spec, though, because if it's right then the spec's TABLE() is just
a pointless alternative spelling of UNNEST(). After further review of
that, we might choose to adopt a different syntax for what this patch does,
but in any case this functionality seems clearly worthwhile.
Andrew Gierth, reviewed by Zoltán Böszörményi and Heikki Linnakangas, and
significantly revised by me
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