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${ noResults }
359 Commits (58ea074f1433abdd5de792e47ae84c1e56c263f9)
Author | SHA1 | Message | Date |
---|---|---|---|
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94150513ec |
Don't pass the grouping target around unnecessarily.
Since commit
|
8 years ago |
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bb94ce4d26 |
Teach reparameterize_path() to handle AppendPaths.
If we're inside a lateral subquery, there may be no unparameterized paths for a particular child relation of an appendrel, in which case we *must* be able to create similarly-parameterized paths for each other child relation, else the planner will fail with "could not devise a query plan for the given query". This means that there are situations where we'd better be able to reparameterize at least one path for each child. This calls into question the assumption in reparameterize_path() that it can just punt if it feels like it. However, the only case that is known broken right now is where the child is itself an appendrel so that all its paths are AppendPaths. (I think possibly I disregarded that in the original coding on the theory that nested appendrels would get folded together --- but that only happens *after* reparameterize_path(), so it's not excused from handling a child AppendPath.) Given that this code's been like this since 9.3 when LATERAL was introduced, it seems likely we'd have heard of other cases by now if there were a larger problem. Per report from Elvis Pranskevichus. Back-patch to 9.3. Discussion: https://postgr.es/m/5981018.zdth1YWmNy@hammer.magicstack.net |
8 years ago |
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2f17844104 |
Allow UPDATE to move rows between partitions.
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 |
8 years ago |
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f033462d8f |
Reorder C includes
Reorder header files in joinrels.c and pathnode.c in alphabetical order, removing unnecessary ones. Author: Etsuro Fujita |
8 years ago |
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624e440a47 |
Improve the heuristic for ordering child paths of a parallel append.
Commit
|
8 years ago |
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9d4649ca49 |
Update copyright for 2018
Backpatch-through: certain files through 9.3 |
8 years ago |
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1804284042 |
Add parallel-aware hash joins.
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 |
8 years ago |
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ab72716778 |
Support Parallel Append plan nodes.
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 |
8 years ago |
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1761653bbb |
Make create_unique_path manage memory like mark_dummy_rel.
Put the unique path in the same context as the owning RelOptInfo, rather than the toplevel planner context. This is how this function worked originally, but commit |
8 years ago |
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eaedf0df71 |
Update typedefs.list and re-run pgindent
Discussion: http://postgr.es/m/CA+TgmoaA9=1RWKtBWpDaj+sF3Stgc8sHgf5z=KGtbjwPLQVDMA@mail.gmail.com |
8 years ago |
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44ae64c388 |
Push target list evaluation through Gather Merge.
We already do this for Gather, but it got overlooked for Gather Merge. Amit Kapila, with review and minor revisions by Rushabh Lathia and by me. Discussion: http://postgr.es/m/CAA4eK1KUC5Uyu7qaifxrjpHxbSeoQh3yzwN3bThnJsmJcZ-qtA@mail.gmail.com |
8 years ago |
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7b6c075471 |
Teach planner to account for HAVING quals in aggregation plan nodes.
For some reason, we have never accounted for either the evaluation cost or the selectivity of filter conditions attached to Agg and Group nodes (which, in practice, are always conditions from a HAVING clause). Applying our regular selectivity logic to post-grouping conditions is a bit bogus, but it's surely better than taking the selectivity as 1.0. Perhaps someday the extended-statistics mechanism can be taught to provide statistics that would help us in getting non-default estimates here. Per a gripe from Benjamin Coutu. This is surely a bug fix, but I'm hesitant to back-patch because of the prospect of destabilizing existing plan choices. Given that it took us this long to notice the bug, it's probably not hurting too many people in the field. Discussion: https://postgr.es/m/20968.1509486337@sss.pgh.pa.us |
8 years ago |
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f49842d1ee |
Basic partition-wise join functionality.
Instead of joining two partitioned tables in their entirety we can, if it is an equi-join on the partition keys, join the matching partitions individually. This involves teaching the planner about "other join" rels, which are related to regular join rels in the same way that other member rels are related to baserels. This can use significantly more CPU time and memory than regular join planning, because there may now be a set of "other" rels not only for every base relation but also for every join relation. In most practical cases, this probably shouldn't be a problem, because (1) it's probably unusual to join many tables each with many partitions using the partition keys for all joins and (2) if you do that scenario then you probably have a big enough machine to handle the increased memory cost of planning and (3) the resulting plan is highly likely to be better, so what you spend in planning you'll make up on the execution side. All the same, for now, turn this feature off by default. Currently, we can only perform joins between two tables whose partitioning schemes are absolutely identical. It would be nice to cope with other scenarios, such as extra partitions on one side or the other with no match on the other side, but that will have to wait for a future patch. Ashutosh Bapat, reviewed and tested by Rajkumar Raghuwanshi, Amit Langote, Rafia Sabih, Thomas Munro, Dilip Kumar, Antonin Houska, Amit Khandekar, and by me. A few final adjustments by me. Discussion: http://postgr.es/m/CAFjFpRfQ8GrQvzp3jA2wnLqrHmaXna-urjm_UY9BqXj=EaDTSA@mail.gmail.com Discussion: http://postgr.es/m/CAFjFpRcitjfrULr5jfuKWRPsGUX0LQ0k8-yG0Qw2+1LBGNpMdw@mail.gmail.com |
8 years ago |
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e139f1953f |
Assorted preparatory refactoring for partition-wise join.
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 |
8 years ago |
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6af9f1bd4b |
Document partitioned_rels in create_modifytable_path header comment.
Etsuro Fujita, slightly adjusted by me. Discussion: http://postgr.es/m/e87c4a6d-23d7-5e7c-e8db-44ed418eb5d1@lab.ntt.co.jp |
8 years ago |
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382ceffdf7 |
Phase 3 of pgindent updates.
Don't move parenthesized lines to the left, even if that means they flow past the right margin. By default, BSD indent lines up statement continuation lines that are within parentheses so that they start just to the right of the preceding left parenthesis. However, traditionally, if that resulted in the continuation line extending to the right of the desired right margin, then indent would push it left just far enough to not overrun the margin, if it could do so without making the continuation line start to the left of the current statement indent. That makes for a weird mix of indentations unless one has been completely rigid about never violating the 80-column limit. This behavior has been pretty universally panned by Postgres developers. Hence, disable it with indent's new -lpl switch, so that parenthesized lines are always lined up with the preceding left paren. 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 |
8 years ago |
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c7b8998ebb |
Phase 2 of pgindent updates.
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
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8 years ago |
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b522759508 |
Copy partitioned_rels lists to avoid shared substructure.
Otherwise, set_plan_refs() can get applied to the same list multiple times through different references, leading to chaos. Amit Langote, Dilip Kumar, and Robert Haas, reviewed by Ashutosh Bapat. Original report by Sveinn Sveinsson. Discussion: http://postgr.es/m/20170517141151.1435.79890@wrigleys.postgresql.org |
8 years ago |
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a6fd7b7a5f |
Post-PG 10 beta1 pgindent run
perltidy run not included. |
8 years ago |
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9c7f5229ad |
Optimize joins when the inner relation can be proven unique.
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 |
9 years ago |
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18ce3a4ab2 |
Add infrastructure to support EphemeralNamedRelation references.
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 |
9 years ago |
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7d8f6986b8 |
Fix parallel query so it doesn't spoil row estimates above Gather.
Commit
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9 years ago |
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b5635948ab |
Support hashed aggregation with grouping sets.
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 |
9 years ago |
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d3cc37f1d8 |
Don't scan partitioned tables.
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 |
9 years ago |
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355d3993c5 |
Add a Gather Merge executor node.
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 |
9 years ago |
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f35742ccb7 |
Support parallel bitmap heap scans.
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 |
9 years ago |
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fcec6caafa |
Support XMLTABLE query expression
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 |
9 years ago |
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5262f7a4fc |
Add optimizer and executor support for parallel index scans.
In combination with
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9 years ago |
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69f4b9c85f |
Move targetlist SRF handling from expression evaluation to new executor node.
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 |
9 years ago |
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1d25779284 |
Update copyright via script for 2017
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9 years ago |
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0832f2db68 |
Fix latent costing error in create_merge_append_path.
create_merge_append_path should use the path rowcount it just computed, not rel->tuples, for costing purposes. Those numbers should always be the same at present, but if we ever support parameterized MergeAppend paths (a case this function is otherwise prepared for), the former would be right and the latter wrong. No need for back-patch since the problem is only latent. Ashutosh Bapat Discussion: <CAFjFpRek+cLCnTo24youuGtsq4zRphEB8EUUPjDxZjnL4n4HYQ@mail.gmail.com> |
9 years ago |
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da1c91631e |
Speed up planner's scanning for parallel-query hazards.
We need to scan the whole parse tree for parallel-unsafe functions. If there are none, we'll later need to determine whether particular subtrees contain any parallel-restricted functions. The previous coding retained no knowledge from the first scan, even though this is very wasteful in the common case where the query contains only parallel-safe functions. We can bypass all of the later scans by remembering that fact. This provides a small but measurable speed improvement when the case applies, and shouldn't cost anything when it doesn't. Patch by me, reviewed by Robert Haas Discussion: <3740.1471538387@sss.pgh.pa.us> |
9 years ago |
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5ce5e4a12e |
Set consider_parallel correctly for upper planner rels.
Commit |
9 years ago |
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19e972d558 |
Rethink node-level representation of partial-aggregation modes.
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
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9 years ago |
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8b9d323cb9 |
Refactor planning of projection steps that don't need a Result plan node.
The original upper-planner-pathification design (commit |
9 years ago |
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54f5c5150f |
Try again to fix the way the scanjoin_target is used with partial paths.
Commit
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9 years ago |
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c9ce4a1c61 |
Eliminate "parallel degree" terminology.
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). |
9 years ago |
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c45bf5751b |
Fix planner crash from pfree'ing a partial path that a GatherPath uses.
We mustn't run generate_gather_paths() during add_paths_to_joinrel(), because that function can be invoked multiple times for the same target joinrel. Not only is it wasteful to build GatherPaths repeatedly, but a later add_partial_path() could delete the partial path that a previously created GatherPath depends on. Instead establish the convention that we do generate_gather_paths() for a rel only just before set_cheapest(). The code was accidentally not broken for baserels, because as of today there never is more than one partial path for a baserel. But that assumption obviously has a pretty short half-life, so move the generate_gather_paths() calls for those cases as well. Also add some generic comments explaining how and why this all works. Per fuzz testing by Andreas Seltenreich. Report: <871t5pgwdt.fsf@credativ.de> |
10 years ago |
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5fe5a2cee9 |
Allow aggregate transition states to be serialized and deserialized.
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. |
10 years ago |
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e06a38965b |
Support parallel aggregation.
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. |
10 years ago |
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992b5ba30d |
Push scan/join target list beneath Gather when possible.
This means that, for example, "SELECT expensive_func(a) FROM bigtab WHERE something" can compute expensive_func(a) in the workers rather than the leader if it happens to be parallel-safe, which figures to be a big win in some practical cases. Currently, we can only do this if the entire target list is parallel-safe. If we worked harder, we might be able to evaluate parallel-safe targets in the worker and any parallel-restricted targets in the leader, but that would be more complicated, and there aren't that many parallel-restricted functions that people are likely to use in queries anyway. I think. So just do the simple thing for the moment. Robert Haas, Amit Kapila, and Tom Lane |
10 years ago |
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101fd9349e |
Add a GetForeignUpperPaths callback function for FDWs.
This is basically like the just-added create_upper_paths_hook, but control is funneled only to the FDW responsible for all the baserels of the current query; so providing such a callback is much less likely to add useless overhead than using the hook function is. The documentation is a bit sketchy. We'll likely want to improve it, and/or adjust the call conventions, when we get some experience with actually using this callback. Hopefully somebody will find time to experiment with it before 9.6 feature freeze. |
10 years ago |
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28048cbaa2 |
Allow callers of create_foreignscan_path to specify nondefault PathTarget.
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. |
10 years ago |
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307c78852f |
Rethink representation of PathTargets.
In commit
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10 years ago |
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9e8b99420f |
Improve handling of group-column indexes in GroupingSetsPath.
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. |
10 years ago |
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8c314b9853 |
Finish refactoring make_foo() functions in createplan.c.
This patch removes some redundant cost calculations that I left for later
cleanup in commit
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10 years ago |
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3fc6e2d7f5 |
Make the upper part of the planner work by generating and comparing Paths.
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. |
10 years ago |
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19a541143a |
Add an explicit representation of the output targetlist to Paths.
Up to now, there's been an assumption that all Paths for a given relation compute the same output column set (targetlist). However, there are good reasons to remove that assumption. For example, an indexscan on an expression index might be able to return the value of an expensive function "for free". While we have the ability to generate such a plan today in simple cases, we don't have a way to model that it's cheaper than a plan that computes the function from scratch, nor a way to create such a plan in join cases (where the function computation would normally happen at the topmost join node). Also, we need this so that we can have Paths representing post-scan/join steps, where the targetlist may well change from one step to the next. Therefore, invent a "struct PathTarget" representing the columns we expect a plan step to emit. It's convenient to include the output tuple width and tlist evaluation cost in this struct, and there will likely be additional fields in future. While Path nodes that actually do have custom outputs will need their own PathTargets, it will still be true that most Paths for a given relation will compute the same tlist. To reduce the overhead added by this patch, keep a "default PathTarget" in RelOptInfo, and allow Paths that compute that column set to just point to their parent RelOptInfo's reltarget. (In the patch as committed, actually every Path is like that, since we do not yet have any cases of custom PathTargets.) I took this opportunity to provide some more-honest costing of PlaceHolderVar evaluation. Up to now, the assumption that "scan/join reltargetlists have cost zero" was applied not only to Vars, where it's reasonable, but also PlaceHolderVars where it isn't. Now, we add the eval cost of a PlaceHolderVar's expression to the first plan level where it can be computed, by including it in the PathTarget cost field and adding that to the cost estimates for Paths. This isn't perfect yet but it's much better than before, and there is a way forward to improve it more. This costing change affects the join order chosen for a couple of the regression tests, changing expected row ordering. |
10 years ago |
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45be99f8cd |
Support parallel joins, and make related improvements.
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. |
10 years ago |
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ee94300446 |
Update copyright for 2016
Backpatch certain files through 9.1 |
10 years ago |