508 Commits (e3ec3c00d85bd2844ffddee83df2bd67c4f8297f)

Author	SHA1	Message	Date
Tom Lane	e3ec3c00d8	Remove arbitrary 64K-or-so limit on rangetable size. ... Up to now the size of a query's rangetable has been limited by the constants INNER_VAR et al, which mustn't be equal to any real rangetable index. 65000 doubtless seemed like enough for anybody, and it still is orders of magnitude larger than the number of joins we can realistically handle. However, we need a rangetable entry for each child partition that is (or might be) processed by a query. Queries with a few thousand partitions are getting more realistic, so that the day when that limit becomes a problem is in sight, even if it's not here yet. Hence, let's raise the limit. Rather than just increase the values of INNER_VAR et al, this patch adopts the approach of making them small negative values, so that rangetables could theoretically become as long as INT_MAX. The bulk of the patch is concerned with changing Var.varno and some related variables from "Index" (unsigned int) to plain "int". This is basically cosmetic, with little actual effect other than to help debuggers print their values nicely. As such, I've only bothered with changing places that could actually see INNER_VAR et al, which the parser and most of the planner don't. We do have to be careful in places that are performing less/greater comparisons on varnos, but there are very few such places, other than the IS_SPECIAL_VARNO macro itself. A notable side effect of this patch is that while it used to be possible to add INNER_VAR et al to a Bitmapset, that will now draw an error. I don't see any likelihood that it wouldn't be a bug to include these fake varnos in a bitmapset of real varnos, so I think this is all to the good. Although this touches outfuncs/readfuncs, I don't think a catversion bump is required, since stored rules would never contain Vars with these fake varnos. Andrey Lepikhov and Tom Lane, after a suggestion by Peter Eisentraut Discussion: https://postgr.es/m/43c7f2f5-1e27-27aa-8c65-c91859d15190@postgrespro.ru	4 years ago
Peter Eisentraut	18fea737b5	Change NestPath node to contain JoinPath node ... This makes the structure of all JoinPath-derived nodes the same, independent of whether they have additional fields. Discussion: https://www.postgresql.org/message-id/flat/c1097590-a6a4-486a-64b1-e1f9cc0533ce@enterprisedb.com	4 years ago
Peter Eisentraut	2226b4189b	Change SeqScan node to contain Scan node ... This makes the structure of all Scan-derived nodes the same, independent of whether they have additional fields. Discussion: https://www.postgresql.org/message-id/flat/c1097590-a6a4-486a-64b1-e1f9cc0533ce@enterprisedb.com	4 years ago
David Rowley	83f4fcc655	Change the name of the Result Cache node to Memoize ... "Result Cache" was never a great name for this node, but nobody managed to come up with another name that anyone liked enough. That was until David Johnston mentioned "Node Memoization", which Tom Lane revised to just "Memoize". People seem to like "Memoize", so let's do the rename. Reviewed-by: Justin Pryzby Discussion: https://postgr.es/m/20210708165145.GG1176@momjian.us Backpatch-through: 14, where Result Cache was introduced	4 years ago
Tom Lane	955b3e0f92	Allow CustomScan providers to say whether they support projections. ... Previously, all CustomScan providers had to support projections, but there may be cases where this is inconvenient. Add a flag bit to say if it's supported. Important item for the release notes: this is non-backwards-compatible since the default is now to assume that CustomScan providers can't project, instead of assuming that they can. It's fail-soft, but could result in visible performance penalties due to adding unnecessary Result nodes. Sven Klemm, reviewed by Aleksander Alekseev; some cosmetic fiddling by me. Discussion: https://postgr.es/m/CAMCrgp1kyakOz6c8aKhNDJXjhQ1dEjEnp+6KNT3KxPrjNtsrDg@mail.gmail.com	4 years ago
Tom Lane	6ee41a301e	Fix mis-planning of repeated application of a projection. ... create_projection_plan contains a hidden assumption (here made explicit by an Assert) that a projection-capable Path will yield a projection-capable Plan. Unfortunately, that assumption is violated only a few lines away, by create_projection_plan itself. This means that two stacked ProjectionPaths can yield an outcome where we try to jam the upper path's tlist into a non-projection-capable child node, resulting in an invalid plan. There isn't any good reason to have stacked ProjectionPaths; indeed the whole concept is faulty, since the set of Vars/Aggs/etc needed by the upper one wouldn't necessarily be available in the output of the lower one, nor could the lower one create such values if they weren't available from its input. Hence, we can fix this by adjusting create_projection_path to strip any top-level ProjectionPath from the subpath it's given. (This amounts to saying "oh, we changed our minds about what we need to project here".) The test case added here only fails in v13 and HEAD; before that, we don't attempt to shove the Sort into the parallel part of the plan, for reasons that aren't entirely clear to me. However, all the directly-related code looks generally the same as far back as v11, where the hazard was introduced (by d7c19e62a). So I've got no faith that the same type of bug doesn't exist in v11 and v12, given the right test case. Hence, back-patch the code changes, but not the irrelevant test case, into those branches. Per report from Bas Poot. Discussion: https://postgr.es/m/534fca83789c4a378c7de379e9067d4f@politie.nl	4 years ago
Tom Lane	def5b065ff	Initial pgindent and pgperltidy run for v14. ... Also "make reformat-dat-files". The only change worthy of note is that pgindent messed up the formatting of launcher.c's struct LogicalRepWorkerId, which led me to notice that that struct wasn't used at all anymore, so I just took it out.	4 years ago
Tom Lane	049e1e2edb	Fix mishandling of resjunk columns in ON CONFLICT ... UPDATE tlists. ... It's unusual to have any resjunk columns in an ON CONFLICT ... UPDATE list, but it can happen when MULTIEXPR_SUBLINK SubPlans are present. If it happens, the ON CONFLICT UPDATE code path would end up storing tuples that include the values of the extra resjunk columns. That's fairly harmless in the short run, but if new columns are added to the table then the values would become accessible, possibly leading to malfunctions if they don't match the datatypes of the new columns. This had escaped notice through a confluence of missing sanity checks, including * There's no cross-check that a tuple presented to heap_insert or heap_update matches the table rowtype. While it's difficult to check that fully at reasonable cost, we can easily add assertions that there aren't too many columns. * The output-column-assignment cases in execExprInterp.c lacked any sanity checks on the output column numbers, which seems like an oversight considering there are plenty of assertion checks on input column numbers. Add assertions there too. * We failed to apply nodeModifyTable's ExecCheckPlanOutput() to the ON CONFLICT UPDATE tlist. That wouldn't have caught this specific error, since that function is chartered to ignore resjunk columns; but it sure seems like a bad omission now that we've seen this bug. In HEAD, the right way to fix this is to make the processing of ON CONFLICT UPDATE tlists work the same as regular UPDATE tlists now do, that is don't add "SET x = x" entries, and use ExecBuildUpdateProjection to evaluate the tlist and combine it with old values of the not-set columns. This adds a little complication to ExecBuildUpdateProjection, but allows removal of a comparable amount of now-dead code from the planner. In the back branches, the most expedient solution seems to be to (a) use an output slot for the ON CONFLICT UPDATE projection that actually matches the target table, and then (b) invent a variant of ExecBuildProjectionInfo that can be told to not store values resulting from resjunk columns, so it doesn't try to store into nonexistent columns of the output slot. (We can't simply ignore the resjunk columns altogether; they have to be evaluated for MULTIEXPR_SUBLINK to work.) This works back to v10. In 9.6, projections work much differently and we can't cheaply give them such an option. The 9.6 version of this patch works by inserting a JunkFilter when it's necessary to get rid of resjunk columns. In addition, v11 and up have the reverse problem when trying to perform ON CONFLICT UPDATE on a partitioned table. Through a further oversight, adjust_partition_tlist() discarded resjunk columns when re-ordering the ON CONFLICT UPDATE tlist to match a partition. This accidentally prevented the storing-bogus-tuples problem, but at the cost that MULTIEXPR_SUBLINK cases didn't work, typically crashing if more than one row has to be updated. Fix by preserving resjunk columns in that routine. (I failed to resist the temptation to add more assertions there too, and to do some minor code beautification.) Per report from Andres Freund. Back-patch to all supported branches. Security: CVE-2021-32028	4 years ago
Tom Lane	3753982441	Fix planner failure in some cases of sorting by an aggregate. ... An oversight introduced by the incremental-sort patches caused "could not find pathkey item to sort" errors in some situations where a sort key involves an aggregate or window function. The basic problem here is that find_em_expr_usable_for_sorting_rel isn't properly modeling what prepare_sort_from_pathkeys will do later. Rather than hoping we can keep those functions in sync, let's refactor so that they actually share the code for identifying a suitable sort expression. With this refactoring, tlist.c's tlist_member_ignore_relabel is unused. I removed it in HEAD but left it in place in v13, in case any extensions are using it. Per report from Luc Vlaming. Back-patch to v13 where the problem arose. James Coleman and Tom Lane Discussion: https://postgr.es/m/91f3ec99-85a4-fa55-ea74-33f85a5c651f@swarm64.com	4 years ago
David Rowley	9eacee2e62	Add Result Cache executor node (take 2) ... Here we add a new executor node type named "Result Cache". The planner can include this node type in the plan to have the executor cache the results from the inner side of parameterized nested loop joins. This allows caching of tuples for sets of parameters so that in the event that the node sees the same parameter values again, it can just return the cached tuples instead of rescanning the inner side of the join all over again. Internally, result cache uses a hash table in order to quickly find tuples that have been previously cached. For certain data sets, this can significantly improve the performance of joins. The best cases for using this new node type are for join problems where a large portion of the tuples from the inner side of the join have no join partner on the outer side of the join. In such cases, hash join would have to hash values that are never looked up, thus bloating the hash table and possibly causing it to multi-batch. Merge joins would have to skip over all of the unmatched rows. If we use a nested loop join with a result cache, then we only cache tuples that have at least one join partner on the outer side of the join. The benefits of using a parameterized nested loop with a result cache increase when there are fewer distinct values being looked up and the number of lookups of each value is large. Also, hash probes to lookup the cache can be much faster than the hash probe in a hash join as it's common that the result cache's hash table is much smaller than the hash join's due to result cache only caching useful tuples rather than all tuples from the inner side of the join. This variation in hash probe performance is more significant when the hash join's hash table no longer fits into the CPU's L3 cache, but the result cache's hash table does. The apparent "random" access of hash buckets with each hash probe can cause a poor L3 cache hit ratio for large hash tables. Smaller hash tables generally perform better. The hash table used for the cache limits itself to not exceeding work_mem * hash_mem_multiplier in size. We maintain a dlist of keys for this cache and when we're adding new tuples and realize we've exceeded the memory budget, we evict cache entries starting with the least recently used ones until we have enough memory to add the new tuples to the cache. For parameterized nested loop joins, we now consider using one of these result cache nodes in between the nested loop node and its inner node. We determine when this might be useful based on cost, which is primarily driven off of what the expected cache hit ratio will be. Estimating the cache hit ratio relies on having good distinct estimates on the nested loop's parameters. For now, the planner will only consider using a result cache for parameterized nested loop joins. This works for both normal joins and also for LATERAL type joins to subqueries. It is possible to use this new node for other uses in the future. For example, to cache results from correlated subqueries. However, that's not done here due to some difficulties obtaining a distinct estimation on the outer plan to calculate the estimated cache hit ratio. Currently we plan the inner plan before planning the outer plan so there is no good way to know if a result cache would be useful or not since we can't estimate the number of times the subplan will be called until the outer plan is generated. The functionality being added here is newly introducing a dependency on the return value of estimate_num_groups() during the join search. Previously, during the join search, we only ever needed to perform selectivity estimations. With this commit, we need to use estimate_num_groups() in order to estimate what the hit ratio on the result cache will be. In simple terms, if we expect 10 distinct values and we expect 1000 outer rows, then we'll estimate the hit ratio to be 99%. Since cache hits are very cheap compared to scanning the underlying nodes on the inner side of the nested loop join, then this will significantly reduce the planner's cost for the join. However, it's fairly easy to see here that things will go bad when estimate_num_groups() incorrectly returns a value that's significantly lower than the actual number of distinct values. If this happens then that may cause us to make use of a nested loop join with a result cache instead of some other join type, such as a merge or hash join. Our distinct estimations have been known to be a source of trouble in the past, so the extra reliance on them here could cause the planner to choose slower plans than it did previous to having this feature. Distinct estimations are also fairly hard to estimate accurately when several tables have been joined already or when a WHERE clause filters out a set of values that are correlated to the expressions we're estimating the number of distinct value for. For now, the costing we perform during query planning for result caches does put quite a bit of faith in the distinct estimations being accurate. When these are accurate then we should generally see faster execution times for plans containing a result cache. However, in the real world, we may find that we need to either change the costings to put less trust in the distinct estimations being accurate or perhaps even disable this feature by default. There's always an element of risk when we teach the query planner to do new tricks that it decides to use that new trick at the wrong time and causes a regression. Users may opt to get the old behavior by turning the feature off using the enable_resultcache GUC. Currently, this is enabled by default. It remains to be seen if we'll maintain that setting for the release. Additionally, the name "Result Cache" is the best name I could think of for this new node at the time I started writing the patch. Nobody seems to strongly dislike the name. A few people did suggest other names but no other name seemed to dominate in the brief discussion that there was about names. Let's allow the beta period to see if the current name pleases enough people. If there's some consensus on a better name, then we can change it before the release. Please see the 2nd discussion link below for the discussion on the "Result Cache" name. Author: David Rowley Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu, Hou Zhijie Tested-By: Konstantin Knizhnik Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com	5 years ago
David Rowley	28b3e3905c	Revert b6002a796 ... This removes "Add Result Cache executor node". It seems that something weird is going on with the tracking of cache hits and misses as highlighted by many buildfarm animals. It's not yet clear what the problem is as other parts of the plan indicate that the cache did work correctly, it's just the hits and misses that were being reported as 0. This is especially a bad time to have the buildfarm so broken, so reverting before too many more animals go red. Discussion: https://postgr.es/m/CAApHDvq_hydhfovm4=izgWs+C5HqEeRScjMbOgbpC-jRAeK3Yw@mail.gmail.com	5 years ago
David Rowley	b6002a796d	Add Result Cache executor node ... Here we add a new executor node type named "Result Cache". The planner can include this node type in the plan to have the executor cache the results from the inner side of parameterized nested loop joins. This allows caching of tuples for sets of parameters so that in the event that the node sees the same parameter values again, it can just return the cached tuples instead of rescanning the inner side of the join all over again. Internally, result cache uses a hash table in order to quickly find tuples that have been previously cached. For certain data sets, this can significantly improve the performance of joins. The best cases for using this new node type are for join problems where a large portion of the tuples from the inner side of the join have no join partner on the outer side of the join. In such cases, hash join would have to hash values that are never looked up, thus bloating the hash table and possibly causing it to multi-batch. Merge joins would have to skip over all of the unmatched rows. If we use a nested loop join with a result cache, then we only cache tuples that have at least one join partner on the outer side of the join. The benefits of using a parameterized nested loop with a result cache increase when there are fewer distinct values being looked up and the number of lookups of each value is large. Also, hash probes to lookup the cache can be much faster than the hash probe in a hash join as it's common that the result cache's hash table is much smaller than the hash join's due to result cache only caching useful tuples rather than all tuples from the inner side of the join. This variation in hash probe performance is more significant when the hash join's hash table no longer fits into the CPU's L3 cache, but the result cache's hash table does. The apparent "random" access of hash buckets with each hash probe can cause a poor L3 cache hit ratio for large hash tables. Smaller hash tables generally perform better. The hash table used for the cache limits itself to not exceeding work_mem * hash_mem_multiplier in size. We maintain a dlist of keys for this cache and when we're adding new tuples and realize we've exceeded the memory budget, we evict cache entries starting with the least recently used ones until we have enough memory to add the new tuples to the cache. For parameterized nested loop joins, we now consider using one of these result cache nodes in between the nested loop node and its inner node. We determine when this might be useful based on cost, which is primarily driven off of what the expected cache hit ratio will be. Estimating the cache hit ratio relies on having good distinct estimates on the nested loop's parameters. For now, the planner will only consider using a result cache for parameterized nested loop joins. This works for both normal joins and also for LATERAL type joins to subqueries. It is possible to use this new node for other uses in the future. For example, to cache results from correlated subqueries. However, that's not done here due to some difficulties obtaining a distinct estimation on the outer plan to calculate the estimated cache hit ratio. Currently we plan the inner plan before planning the outer plan so there is no good way to know if a result cache would be useful or not since we can't estimate the number of times the subplan will be called until the outer plan is generated. The functionality being added here is newly introducing a dependency on the return value of estimate_num_groups() during the join search. Previously, during the join search, we only ever needed to perform selectivity estimations. With this commit, we need to use estimate_num_groups() in order to estimate what the hit ratio on the result cache will be. In simple terms, if we expect 10 distinct values and we expect 1000 outer rows, then we'll estimate the hit ratio to be 99%. Since cache hits are very cheap compared to scanning the underlying nodes on the inner side of the nested loop join, then this will significantly reduce the planner's cost for the join. However, it's fairly easy to see here that things will go bad when estimate_num_groups() incorrectly returns a value that's significantly lower than the actual number of distinct values. If this happens then that may cause us to make use of a nested loop join with a result cache instead of some other join type, such as a merge or hash join. Our distinct estimations have been known to be a source of trouble in the past, so the extra reliance on them here could cause the planner to choose slower plans than it did previous to having this feature. Distinct estimations are also fairly hard to estimate accurately when several tables have been joined already or when a WHERE clause filters out a set of values that are correlated to the expressions we're estimating the number of distinct value for. For now, the costing we perform during query planning for result caches does put quite a bit of faith in the distinct estimations being accurate. When these are accurate then we should generally see faster execution times for plans containing a result cache. However, in the real world, we may find that we need to either change the costings to put less trust in the distinct estimations being accurate or perhaps even disable this feature by default. There's always an element of risk when we teach the query planner to do new tricks that it decides to use that new trick at the wrong time and causes a regression. Users may opt to get the old behavior by turning the feature off using the enable_resultcache GUC. Currently, this is enabled by default. It remains to be seen if we'll maintain that setting for the release. Additionally, the name "Result Cache" is the best name I could think of for this new node at the time I started writing the patch. Nobody seems to strongly dislike the name. A few people did suggest other names but no other name seemed to dominate in the brief discussion that there was about names. Let's allow the beta period to see if the current name pleases enough people. If there's some consensus on a better name, then we can change it before the release. Please see the 2nd discussion link below for the discussion on the "Result Cache" name. Author: David Rowley Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu Tested-By: Konstantin Knizhnik Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com	5 years ago
Tom Lane	86dc90056d	Rework planning and execution of UPDATE and DELETE. ... This patch makes two closely related sets of changes: 1. For UPDATE, the subplan of the ModifyTable node now only delivers the new values of the changed columns (i.e., the expressions computed in the query's SET clause) plus row identity information such as CTID. ModifyTable must re-fetch the original tuple to merge in the old values of any unchanged columns. The core advantage of this is that the changed columns are uniform across all tables of an inherited or partitioned target relation, whereas the other columns might not be. A secondary advantage, when the UPDATE involves joins, is that less data needs to pass through the plan tree. The disadvantage of course is an extra fetch of each tuple to be updated. However, that seems to be very nearly free in context; even worst-case tests don't show it to add more than a couple percent to the total query cost. At some point it might be interesting to combine the re-fetch with the tuple access that ModifyTable must do anyway to mark the old tuple dead; but that would require a good deal of refactoring and it seems it wouldn't buy all that much, so this patch doesn't attempt it. 2. For inherited UPDATE/DELETE, instead of generating a separate subplan for each target relation, we now generate a single subplan that is just exactly like a SELECT's plan, then stick ModifyTable on top of that. To let ModifyTable know which target relation a given incoming row refers to, a tableoid junk column is added to the row identity information. This gets rid of the horrid hack that was inheritance_planner(), eliminating O(N^2) planning cost and memory consumption in cases where there were many unprunable target relations. Point 2 of course requires point 1, so that there is a uniform definition of the non-junk columns to be returned by the subplan. We can't insist on uniform definition of the row identity junk columns however, if we want to keep the ability to have both plain and foreign tables in a partitioning hierarchy. Since it wouldn't scale very far to have every child table have its own row identity column, this patch includes provisions to merge similar row identity columns into one column of the subplan result. In particular, we can merge the whole-row Vars typically used as row identity by FDWs into one column by pretending they are type RECORD. (It's still okay for the actual composite Datums to be labeled with the table's rowtype OID, though.) There is more that can be done to file down residual inefficiencies in this patch, but it seems to be committable now. FDW authors should note several API changes: * The argument list for AddForeignUpdateTargets() has changed, and so has the method it must use for adding junk columns to the query. Call add_row_identity_var() instead of manipulating the parse tree directly. You might want to reconsider exactly what you're adding, too. * PlanDirectModify() must now work a little harder to find the ForeignScan plan node; if the foreign table is part of a partitioning hierarchy then the ForeignScan might not be the direct child of ModifyTable. See postgres_fdw for sample code. * To check whether a relation is a target relation, it's no longer sufficient to compare its relid to root->parse->resultRelation. Instead, check it against all_result_relids or leaf_result_relids, as appropriate. Amit Langote and Tom Lane Discussion: https://postgr.es/m/CA+HiwqHpHdqdDn48yCEhynnniahH78rwcrv1rEX65-fsZGBOLQ@mail.gmail.com	5 years ago
Etsuro Fujita	27e1f14563	Add support for asynchronous execution. ... This implements asynchronous execution, which runs multiple parts of a non-parallel-aware Append concurrently rather than serially to improve performance when possible. Currently, the only node type that can be run concurrently is a ForeignScan that is an immediate child of such an Append. In the case where such ForeignScans access data on different remote servers, this would run those ForeignScans concurrently, and overlap the remote operations to be performed simultaneously, so it'll improve the performance especially when the operations involve time-consuming ones such as remote join and remote aggregation. We may extend this to other node types such as joins or aggregates over ForeignScans in the future. This also adds the support for postgres_fdw, which is enabled by the table-level/server-level option "async_capable". The default is false. Robert Haas, Kyotaro Horiguchi, Thomas Munro, and myself. This commit is mostly based on the patch proposed by Robert Haas, but also uses stuff from the patch proposed by Kyotaro Horiguchi and from the patch proposed by Thomas Munro. Reviewed by Kyotaro Horiguchi, Konstantin Knizhnik, Andrey Lepikhov, Movead Li, Thomas Munro, Justin Pryzby, and others. Discussion: https://postgr.es/m/CA%2BTgmoaXQEt4tZ03FtQhnzeDEMzBck%2BLrni0UWHVVgOTnA6C1w%40mail.gmail.com Discussion: https://postgr.es/m/CA%2BhUKGLBRyu0rHrDCMC4%3DRn3252gogyp1SjOgG8SEKKZv%3DFwfQ%40mail.gmail.com Discussion: https://postgr.es/m/20200228.170650.667613673625155850.horikyota.ntt%40gmail.com	5 years ago
David Rowley	bb437f995d	Add TID Range Scans to support efficient scanning ranges of TIDs ... This adds a new executor node named TID Range Scan. The query planner will generate paths for TID Range scans when quals are discovered on base relations which search for ranges on the table's ctid column. These ranges may be open at either end. For example, WHERE ctid >= '(10,0)'; will return all tuples on page 10 and over. To support this, two new optional callback functions have been added to table AM. scan_set_tidrange is used to set the scan range to just the given range of TIDs. scan_getnextslot_tidrange fetches the next tuple in the given range. For AMs were scanning ranges of TIDs would not make sense, these functions can be set to NULL in the TableAmRoutine. The query planner won't generate TID Range Scan Paths in that case. Author: Edmund Horner, David Rowley Reviewed-by: David Rowley, Tomas Vondra, Tom Lane, Andres Freund, Zhihong Yu Discussion: https://postgr.es/m/CAMyN-kB-nFTkF=VA_JPwFNo08S0d-Yk0F741S2B7LDmYAi8eyA@mail.gmail.com	5 years ago
Tom Lane	f003a7522b	Remove [Merge]AppendPath.partitioned_rels. ... It turns out that the calculation of [Merge]AppendPath.partitioned_rels in allpaths.c is faulty and sometimes omits relevant non-leaf partitions, allowing an assertion added by commit a929e17e5a to trigger. Rather than fix that, it seems better to get rid of those fields altogether. We don't really need the info until create_plan time, and calculating it once for the selected plan should be cheaper than calculating it for each append path we consider. The preceding two commits did away with all use of the partitioned_rels values; this commit just mechanically removes the fields and the code that calculated them. Discussion: https://postgr.es/m/87sg8tqhsl.fsf@aurora.ydns.eu Discussion: https://postgr.es/m/CAJKUy5gCXDSmFs2c=R+VGgn7FiYcLCsEFEuDNNLGfoha=pBE_g@mail.gmail.com	5 years ago
Tom Lane	5076f88bc9	Remove incidental dependencies on partitioned_rels lists. ... It turns out that the calculation of [Merge]AppendPath.partitioned_rels in allpaths.c is faulty and sometimes omits relevant non-leaf partitions, allowing an assertion added by commit a929e17e5a to trigger. Rather than fix that, it seems better to get rid of those fields altogether. We don't really need the info until create_plan time, and calculating it once for the selected plan should be cheaper than calculating it for each append path we consider. This patch undoes a couple of very minor uses of the partitioned_rels values. createplan.c was testing for nil-ness to optimize away the preparatory work for make_partition_pruneinfo(). That is worth doing if the check is nigh free, but it's not worth going to any great lengths to avoid. create_append_path() was testing for nil-ness as part of deciding how to set up ParamPathInfo for an AppendPath. I replaced that with a check for the appendrel's parent rel being partitioned. That's not quite the same thing but should cover most cases. If we note any interesting loss of optimizations, we can dumb this down to just always use the more expensive method when the parent is a baserel. Discussion: https://postgr.es/m/87sg8tqhsl.fsf@aurora.ydns.eu Discussion: https://postgr.es/m/CAJKUy5gCXDSmFs2c=R+VGgn7FiYcLCsEFEuDNNLGfoha=pBE_g@mail.gmail.com	5 years ago
Bruce Momjian	ca3b37487b	Update copyright for 2021 ... Backpatch-through: 9.5	5 years ago
Tomas Vondra	1ca2eb1031	Improve find_em_expr_usable_for_sorting_rel comment ... Clarify the relationship between find_em_expr_usable_for_sorting_rel and prepare_sort_from_pathkeys, i.e. what restrictions need to be shared between those two places. Author: James Coleman Reviewed-by: Tomas Vondra Backpatch-through: 13 Discussion: https://postgr.es/m/CAAaqYe8cK3g5CfLC4w7bs%3DhC0mSksZC%3DH5M8LSchj5e5OxpTAg%40mail.gmail.com	5 years ago
Tomas Vondra	6bc2769832	Error out when Gather Merge input is not sorted ... To build Gather Merge path, the input needs to be sufficiently sorted. Ensuring this is the responsibility of the code constructing the paths, but create_gather_merge_plan tried to handle unsorted paths by adding an explicit Sort. In light of the recent issues related to Incremental Sort, this is rather fragile. Some of the expressions may be volatile or parallel unsafe, in which case we can't add the Sort here. We could do more checks and add the Sort in at least some cases, but it seems cleaner to just error out and make it clear this is a bug in code constructing those paths. Author: James Coleman Reviewed-by: Tomas Vondra Discussion: https://postgr.es/m/CAAaqYe8cK3g5CfLC4w7bs%3DhC0mSksZC%3DH5M8LSchj5e5OxpTAg%40mail.gmail.com Discussion: https://postgr.es/m/CAJGNTeNaxpXgBVcRhJX%2B2vSbq%2BF2kJqGBcvompmpvXb7pq%2BoFA%40mail.gmail.com	5 years ago
David Rowley	a929e17e5a	Allow run-time pruning on nested Append/MergeAppend nodes ... Previously we only tagged on the required information to allow the executor to perform run-time partition pruning for Append/MergeAppend nodes belonging to base relations. It was thought that nested Append/MergeAppend nodes were just about always pulled up into the top-level Append/MergeAppend and that making the run-time pruning info for any sub Append/MergeAppend nodes was a waste of time. However, that was likely badly thought through. Some examples of cases we're unable to pullup nested Append/MergeAppends are: 1) Parallel Append nodes with a mix of parallel and non-parallel paths into a Parallel Append. 2) When planning an ordered Append scan a sub-partition which is unordered may require a nested MergeAppend path to ensure sub-partitions don't mix up the order of tuples being fed into the top-level Append. Unfortunately, it was not just as simple as removing the lines in createplan.c which were purposefully not building the run-time pruning info for anything but RELOPT_BASEREL relations. The code in add_paths_to_append_rel() was far too sloppy about which partitioned_rels it included for the Append/MergeAppend paths. The original code there would always assume accumulate_append_subpath() would pull each sub-Append and sub-MergeAppend path into the top-level path. While it does not appear that there were any actual bugs caused by having the additional partitioned table RT indexes recorded, what it did mean is that later in planning, when we built the run-time pruning info that we wasted effort and built PartitionedRelPruneInfos for partitioned tables that we had no subpaths for the executor to run-time prune. Here we tighten that up so that partitioned_rels only ever contains the RT index for partitioned tables which actually have subpaths in the given Append/MergeAppend. We can now Assert that every PartitionedRelPruneInfo has a non-empty present_parts. That should allow us to catch any weird corner cases that have been missed. In passing, it seems there is no longer a good reason to have the AppendPath and MergeAppendPath's partitioned_rel fields a List of IntList. We can simply have a List of Relids instead. This is more compact in memory and faster to add new members to. We still know which is the root level partition as these always have a lower relid than their children. Previously this field was used for more things, but run-time partition pruning now remains the only user of it and it has no need for a List of IntLists. Here we also get rid of the RelOptInfo partitioned_child_rels field. This is what was previously used to (sometimes incorrectly) set the Append/MergeAppend path's partitioned_rels field. That was the only usage of that field, so we can happily just remove it. I also couldn't resist changing some nearby code to make use of the newly added for_each_from macro so we can skip the first element in the list without checking if the current item was the first one on each iteration. A bug report from Andreas Kretschmer prompted all this work, however, after some consideration, I'm not personally classing this as a bug fix. So no backpatch. In Andreas' test case, it just wasn't that clear that there was a nested Append since the top-level Append just had a single sub-path which was pulled up a level, per 8edd0e794. Author: David Rowley Reviewed-by: Amit Langote Discussion: https://postgr.es/m/flat/CAApHDvqSchs%2BubdybcfFaSPB%2B%2BEA7kqMaoqajtP0GtZvzOOR3g%40mail.gmail.com	5 years ago
Heikki Linnakangas	178f2d560d	Include result relation info in direct modify ForeignScan nodes. ... FDWs that can perform an UPDATE/DELETE remotely using the "direct modify" set of APIs need to access the ResultRelInfo of the target table. That's currently available in EState.es_result_relation_info, but the next commit will remove that field. This commit adds a new resultRelation field in ForeignScan, to store the target relation's RT index, and the corresponding ResultRelInfo in ForeignScanState. The FDW's PlanDirectModify callback is expected to set 'resultRelation' along with 'operation'. The core code doesn't need them for anything, they are for the convenience of FDW's Begin- and IterateDirectModify callbacks. Authors: Amit Langote, Etsuro Fujita Discussion: https://www.postgresql.org/message-id/CA%2BHiwqGEmiib8FLiHMhKB%2BCH5dRgHSLc5N5wnvc4kym%2BZYpQEQ%40mail.gmail.com	5 years ago
Heikki Linnakangas	1375422c78	Create ResultRelInfos later in InitPlan, index them by RT index. ... Instead of allocating all the ResultRelInfos upfront in one big array, allocate them in ExecInitModifyTable(). es_result_relations is now an array of ResultRelInfo pointers, rather than an array of structs, and it is indexed by the RT index. This simplifies things: we get rid of the separate concept of a "result rel index", and don't need to set it in setrefs.c anymore. This also allows follow-up optimizations (not included in this commit yet) to skip initializing ResultRelInfos for target relations that were not needed at runtime, and removal of the es_result_relation_info pointer. The EState arrays of regular result rels and root result rels are merged into one array. Similarly, the resultRelations and rootResultRelations lists in PlannedStmt are merged into one. It's not actually clear to me why they were kept separate in the first place, but now that the es_result_relations array is indexed by RT index, it certainly seems pointless. The PlannedStmt->resultRelations list is now only needed for ExecRelationIsTargetRelation(). One visible effect of this change is that ExecRelationIsTargetRelation() will now return 'true' also for the partition root, if a partitioned table is updated. That seems like a good thing, although the function isn't used in core code, and I don't see any reason for an FDW to call it on a partition root. Author: Amit Langote Discussion: https://www.postgresql.org/message-id/CA%2BHiwqGEmiib8FLiHMhKB%2BCH5dRgHSLc5N5wnvc4kym%2BZYpQEQ%40mail.gmail.com	5 years ago
Tom Lane	56fe008996	Add for_each_from, to simplify loops starting from non-first list cells. ... We have a dozen or so places that need to iterate over all but the first cell of a List. Prior to v13 this was typically written as for_each_cell(lc, lnext(list_head(list))) Commit 1cff1b95a changed these to for_each_cell(lc, list, list_second_cell(list)) This patch introduces a new macro for_each_from() which expresses the start point as a list index, allowing these to be written as for_each_from(lc, list, 1) This is marginally more efficient, since ForEachState.i can be initialized directly instead of backing into it from a ListCell address. It also seems clearer and less typo-prone. Some of the remaining uses of for_each_cell() look like they could profitably be changed to for_each_from(), but here I confined myself to changing uses of list_second_cell(). Also, fix for_each_cell_setup() and for_both_cell_setup() to const-ify their arguments; that's a simple oversight in 1cff1b95a. Back-patch into v13, on the grounds that (1) the const-ification is a minor bug fix, and (2) it's better for back-patching purposes if we only have two ways to write these loops rather than three. In HEAD, also remove list_third_cell() and list_fourth_cell(), which were also introduced in 1cff1b95a, and are unused as of cc99baa43. It seems unlikely that any third-party code would have started to use them already; anyone who has can be directed to list_nth_cell instead. Discussion: https://postgr.es/m/CAApHDvpo1zj9KhEpU2cCRZfSM3Q6XGdhzuAS2v79PH7WJBkYVA@mail.gmail.com	5 years ago
Thomas Munro	cdc7169509	Use MinimalTuple for tuple queues. ... This representation saves 8 bytes per tuple compared to HeapTuple, and avoids the need to allocate, copy and free on the receiving side. Gather can emit the returned MinimalTuple directly, but GatherMerge now needs to make an explicit copy because it buffers multiple tuples at a time. That should be no worse than before. Reviewed-by: Soumyadeep Chakraborty <soumyadeep2007@gmail.com> Discussion: https://postgr.es/m/CA%2BhUKG%2B8T_ggoUTAE-U%3DA%2BOcPc4%3DB0nPPHcSfffuQhvXXjML6w%40mail.gmail.com	5 years ago
Jeff Davis	0babd10980	Revert "Use CP_SMALL_TLIST for hash aggregate" ... This reverts commit 4cad2534da due to a performance regression. It will be replaced by a new approach in an upcoming commit. Reported-by: Andres Freund Discussion: https://postgr.es/m/20200614181418.mx4bvljmfkkhoqzl@alap3.anarazel.de Backpatch-through: 13	5 years ago
Tom Lane	b5d69b7c22	pgindent run prior to branching v13. ... pgperltidy and reformat-dat-files too, though those didn't find anything to change.	5 years ago
Tomas Vondra	4cad2534da	Use CP_SMALL_TLIST for hash aggregate ... Commit 1f39bce021 added disk-based hash aggregation, which may spill incoming tuples to disk. It however did not request projection to make the tuples as narrow as possible, which may mean having to spill much more data than necessary (increasing I/O, pushing other stuff from page cache, etc.). This adds CP_SMALL_TLIST in places that may use hash aggregation - we do that only for AGG_HASHED. It's unnecessary for AGG_SORTED, because that either uses explicit Sort (which already does projection) or pre-sorted input (which does not need spilling to disk). Author: Tomas Vondra Reviewed-by: Jeff Davis Discussion: https://postgr.es/m/20200519151202.u2p2gpiawoaznsv2%40development	5 years ago
Alvaro Herrera	357889eb17	Support FETCH FIRST WITH TIES ... WITH TIES is an option to the FETCH FIRST N ROWS clause (the SQL standard's spelling of LIMIT), where you additionally get rows that compare equal to the last of those N rows by the columns in the mandatory ORDER BY clause. There was a proposal by Andrew Gierth to implement this functionality in a more powerful way that would yield more features, but the other patch had not been finished at this time, so we decided to use this one for now in the spirit of incremental development. Author: Surafel Temesgen <surafel3000@gmail.com> Reviewed-by: Álvaro Herrera <alvherre@alvh.no-ip.org> Reviewed-by: Tomas Vondra <tomas.vondra@2ndquadrant.com> Discussion: https://postgr.es/m/CALAY4q9ky7rD_A4vf=FVQvCGngm3LOes-ky0J6euMrg=_Se+ag@mail.gmail.com Discussion: https://postgr.es/m/87o8wvz253.fsf@news-spur.riddles.org.uk	6 years ago
Tomas Vondra	d2d8a229bc	Implement Incremental Sort ... Incremental Sort is an optimized variant of multikey sort for cases when the input is already sorted by a prefix of the requested sort keys. For example when the relation is already sorted by (key1, key2) and we need to sort it by (key1, key2, key3) we can simply split the input rows into groups having equal values in (key1, key2), and only sort/compare the remaining column key3. This has a number of benefits: - Reduced memory consumption, because only a single group (determined by values in the sorted prefix) needs to be kept in memory. This may also eliminate the need to spill to disk. - Lower startup cost, because Incremental Sort produce results after each prefix group, which is beneficial for plans where startup cost matters (like for example queries with LIMIT clause). We consider both Sort and Incremental Sort, and decide based on costing. The implemented algorithm operates in two different modes: - Fetching a minimum number of tuples without check of equality on the prefix keys, and sorting on all columns when safe. - Fetching all tuples for a single prefix group and then sorting by comparing only the remaining (non-prefix) keys. We always start in the first mode, and employ a heuristic to switch into the second mode if we believe it's beneficial - the goal is to minimize the number of unnecessary comparions while keeping memory consumption below work_mem. This is a very old patch series. The idea was originally proposed by Alexander Korotkov back in 2013, and then revived in 2017. In 2018 the patch was taken over by James Coleman, who wrote and rewrote most of the current code. There were many reviewers/contributors since 2013 - I've done my best to pick the most active ones, and listed them in this commit message. Author: James Coleman, Alexander Korotkov Reviewed-by: Tomas Vondra, Andreas Karlsson, Marti Raudsepp, Peter Geoghegan, Robert Haas, Thomas Munro, Antonin Houska, Andres Freund, Alexander Kuzmenkov Discussion: https://postgr.es/m/CAPpHfdscOX5an71nHd8WSUH6GNOCf=V7wgDaTXdDd9=goN-gfA@mail.gmail.com Discussion: https://postgr.es/m/CAPpHfds1waRZ=NOmueYq0sx1ZSCnt+5QJvizT8ndT2=etZEeAQ@mail.gmail.com	6 years ago
Jeff Davis	c11cb17dc5	Save calculated transitionSpace in Agg node. ... This will be useful in the upcoming Hash Aggregation work to improve estimates for hash table sizing. Discussion: https://postgr.es/m/37091115219dd522fd9ed67333ee8ed1b7e09443.camel%40j-davis.com	6 years ago
Alvaro Herrera	c9d2977519	Clean up newlines following left parentheses ... We used to strategically place newlines after some function call left parentheses to make pgindent move the argument list a few chars to the left, so that the whole line would fit under 80 chars. However, pgindent no longer does that, so the newlines just made the code vertically longer for no reason. Remove those newlines, and reflow some of those lines for some extra naturality. Reviewed-by: Michael Paquier, Tom Lane Discussion: https://postgr.es/m/20200129200401.GA6303@alvherre.pgsql	6 years ago
Bruce Momjian	7559d8ebfa	Update copyrights for 2020 ... Backpatch-through: update all files in master, backpatch legal files through 9.4	6 years ago
Tom Lane	6ef77cf46e	Further adjust EXPLAIN's choices of table alias names. ... This patch causes EXPLAIN to always assign a separate table alias to the parent RTE of an append relation (inheritance set); before, such RTEs were ignored if not actually scanned by the plan. Since the child RTEs now always have that same alias to start with (cf. commit 55a1954da), the net effect is that the parent RTE usually gets the alias used or implied by the query text, and the children all get that alias with "_N" appended. (The exception to "usually" is if there are duplicate aliases in different subtrees of the original query; then some of those original RTEs will also have "_N" appended.) This results in more uniform output for partitioned-table plans than we had before: the partitioned table itself gets the original alias, and all child tables have aliases with "_N", rather than the previous behavior where one of the children would get an alias without "_N". The reason for giving the parent RTE an alias, even if it isn't scanned by the plan, is that we now use the parent's alias to qualify Vars that refer to an appendrel output column and appear above the Append or MergeAppend that computes the appendrel. But below the append, Vars refer to some one of the child relations, and are displayed that way. This seems clearer than the old behavior where a Var that could carry values from any child relation was displayed as if it referred to only one of them. While at it, change ruleutils.c so that the code paths used by EXPLAIN deal in Plan trees not PlanState trees. This effectively reverts a decision made in commit 1cc29fe7c, which seemed like a good idea at the time to make ruleutils.c consistent with explain.c. However, it's problematic because we'd really like to allow executor startup pruning to remove all the children of an append node when possible, leaving no child PlanState to resolve Vars against. (That's not done here, but will be in the next patch.) This requires different handling of subplans and initplans than before, but is otherwise a pretty straightforward change. Discussion: https://postgr.es/m/001001d4f44b$2a2cca50$7e865ef0$@lab.ntt.co.jp	6 years ago
Andrew Gierth	a9056cc637	Request small targetlist for input to WindowAgg. ... WindowAgg will potentially store large numbers of input rows into tuplestores to allow access to other rows in the frame. If the input is coming via an explicit Sort node, then unneeded columns will already have been discarded (since Sort requests a small tlist); but there are idioms like COUNT(*) OVER () that result in the input not being sorted at all, and cases where the input is being sorted by some means other than a Sort; if we don't request a small tlist, then WindowAgg's storage requirement is inflated by the unneeded columns. Backpatch back to 9.6, where the current tlist handling was added. (Prior to that, WindowAgg would always use a small tlist.) Discussion: https://postgr.es/m/87a7ator8n.fsf@news-spur.riddles.org.uk	6 years ago
Tom Lane	5ee190f8ec	Rationalize use of list_concat + list_copy combinations. ... In the wake of commit 1cff1b95a, the result of list_concat no longer shares the ListCells of the second input. Therefore, we can replace "list_concat(x, list_copy(y))" with just "list_concat(x, y)". To improve call sites that were list_copy'ing the first argument, or both arguments, invent "list_concat_copy()" which produces a new list sharing no ListCells with either input. (This is a bit faster than "list_concat(list_copy(x), y)" because it makes the result list the right size to start with.) In call sites that were not list_copy'ing the second argument, the new semantics mean that we are usually leaking the second List's storage, since typically there is no remaining pointer to it. We considered inventing another list_copy variant that would list_free the second input, but concluded that for most call sites it isn't worth worrying about, given the relative compactness of the new List representation. (Note that in cases where such leakage would happen, the old code already leaked the second List's header; so we're only discussing the size of the leak not whether there is one. I did adjust two or three places that had been troubling to free that header so that they manually free the whole second List.) Patch by me; thanks to David Rowley for review. Discussion: https://postgr.es/m/11587.1550975080@sss.pgh.pa.us	6 years ago
Andres Freund	2abd7ae9b2	Fix representation of hash keys in Hash/HashJoin nodes. ... In 5f32b29c18 I changed the creation of HashState.hashkeys to actually use HashState as the parent (instead of HashJoinState, which was incorrect, as they were executed below HashState), to fix the problem of hashkeys expressions otherwise relying on slot types appropriate for HashJoinState, rather than HashState as would be correct. That reliance was only introduced in 12, which is why it previously worked to use HashJoinState as the parent (although I'd be unsurprised if there were problematic cases). Unfortunately that's not a sufficient solution, because before this commit, the to-be-hashed expressions referenced inner/outer as appropriate for the HashJoin, not Hash. That didn't have obvious bad consequences, because the slots containing the tuples were put into ecxt_innertuple when hashing a tuple for HashState (even though Hash doesn't have an inner plan). There are less common cases where this can cause visible problems however (rather than just confusion when inspecting such executor trees). E.g. "ERROR: bogus varno: 65000", when explaining queries containing a HashJoin where the subsidiary Hash node's hash keys reference a subplan. While normally hashkeys aren't displayed by EXPLAIN, if one of those expressions references a subplan, that subplan may be printed as part of the Hash node - which then failed because an inner plan was referenced, and Hash doesn't have that. It seems quite possible that there's other broken cases, too. Fix the problem by properly splitting the expression for the HashJoin and Hash nodes at plan time, and have them reference the proper subsidiary node. While other workarounds are possible, fixing this correctly seems easy enough. It was a pretty ugly hack to have ExecInitHashJoin put the expression into the already initialized HashState, in the first place. I decided to not just split inner/outer hashkeys inside make_hashjoin(), but also to separate out hashoperators and hashcollations at plan time. Otherwise we would have ended up having two very similar loops, one at plan time and the other during executor startup. The work seems to more appropriately belong to plan time, anyway. Reported-By: Nikita Glukhov, Alexander Korotkov Author: Andres Freund Reviewed-By: Tom Lane, in an earlier version Discussion: https://postgr.es/m/CAPpHfdvGVegF_TKKRiBrSmatJL2dR9uwFCuR+teQ_8tEXU8mxg@mail.gmail.com Backpatch: 12-	6 years ago
Tom Lane	1cff1b95ab	Represent Lists as expansible arrays, not chains of cons-cells. ... Originally, Postgres Lists were a more or less exact reimplementation of Lisp lists, which consist of chains of separately-allocated cons cells, each having a value and a next-cell link. We'd hacked that once before (commit d0b4399d8) to add a separate List header, but the data was still in cons cells. That makes some operations -- notably list_nth() -- O(N), and it's bulky because of the next-cell pointers and per-cell palloc overhead, and it's very cache-unfriendly if the cons cells end up scattered around rather than being adjacent. In this rewrite, we still have List headers, but the data is in a resizable array of values, with no next-cell links. Now we need at most two palloc's per List, and often only one, since we can allocate some values in the same palloc call as the List header. (Of course, extending an existing List may require repalloc's to enlarge the array. But this involves just O(log N) allocations not O(N).) Of course this is not without downsides. The key difficulty is that addition or deletion of a list entry may now cause other entries to move, which it did not before. For example, that breaks foreach() and sister macros, which historically used a pointer to the current cons-cell as loop state. We can repair those macros transparently by making their actual loop state be an integer list index; the exposed "ListCell *" pointer is no longer state carried across loop iterations, but is just a derived value. (In practice, modern compilers can optimize things back to having just one loop state value, at least for simple cases with inline loop bodies.) In principle, this is a semantics change for cases where the loop body inserts or deletes list entries ahead of the current loop index; but I found no such cases in the Postgres code. The change is not at all transparent for code that doesn't use foreach() but chases lists "by hand" using lnext(). The largest share of such code in the backend is in loops that were maintaining "prev" and "next" variables in addition to the current-cell pointer, in order to delete list cells efficiently using list_delete_cell(). However, we no longer need a previous-cell pointer to delete a list cell efficiently. Keeping a next-cell pointer doesn't work, as explained above, but we can improve matters by changing such code to use a regular foreach() loop and then using the new macro foreach_delete_current() to delete the current cell. (This macro knows how to update the associated foreach loop's state so that no cells will be missed in the traversal.) There remains a nontrivial risk of code assuming that a ListCell * pointer will remain good over an operation that could now move the list contents. To help catch such errors, list.c can be compiled with a new define symbol DEBUG_LIST_MEMORY_USAGE that forcibly moves list contents whenever that could possibly happen. This makes list operations significantly more expensive so it's not normally turned on (though it is on by default if USE_VALGRIND is on). There are two notable API differences from the previous code: * lnext() now requires the List's header pointer in addition to the current cell's address. * list_delete_cell() no longer requires a previous-cell argument. These changes are somewhat unfortunate, but on the other hand code using either function needs inspection to see if it is assuming anything it shouldn't, so it's not all bad. Programmers should be aware of these significant performance changes: * list_nth() and related functions are now O(1); so there's no major access-speed difference between a list and an array. * Inserting or deleting a list element now takes time proportional to the distance to the end of the list, due to moving the array elements. (However, it typically *doesn't* require palloc or pfree, so except in long lists it's probably still faster than before.) Notably, lcons() used to be about the same cost as lappend(), but that's no longer true if the list is long. Code that uses lcons() and list_delete_first() to maintain a stack might usefully be rewritten to push and pop at the end of the list rather than the beginning. * There are now list_insert_nth...() and list_delete_nth...() functions that add or remove a list cell identified by index. These have the data-movement penalty explained above, but there's no search penalty. * list_concat() and variants now copy the second list's data into storage belonging to the first list, so there is no longer any sharing of cells between the input lists. The second argument is now declared "const List *" to reflect that it isn't changed. This patch just does the minimum needed to get the new implementation in place and fix bugs exposed by the regression tests. As suggested by the foregoing, there's a fair amount of followup work remaining to do. Also, the ENABLE_LIST_COMPAT macros are finally removed in this commit. Code using those should have been gone a dozen years ago. Patch by me; thanks to David Rowley, Jesper Pedersen, and others for review. Discussion: https://postgr.es/m/11587.1550975080@sss.pgh.pa.us	6 years ago
Michael Paquier	c74d49d41c	Fix many typos and inconsistencies ... Author: Alexander Lakhin Discussion: https://postgr.es/m/af27d1b3-a128-9d62-46e0-88f424397f44@gmail.com	6 years ago
Tom Lane	8255c7a5ee	Phase 2 pgindent run for v12. ... Switch to 2.1 version of pg_bsd_indent. This formats multiline function declarations "correctly", that is with additional lines of parameter declarations indented to match where the first line's left parenthesis is. Discussion: https://postgr.es/m/CAEepm=0P3FeTXRcU5B2W3jv3PgRVZ-kGUXLGfd42FFhUROO3ug@mail.gmail.com	6 years ago
Tom Lane	24c19e9f66	Repair issues with faulty generation of merge-append plans. ... create_merge_append_plan failed to honor the CP_EXACT_TLIST flag: it would generate the expected targetlist but then it felt free to add resjunk sort targets to it. This demonstrably leads to assertion failures in v11 and HEAD, and it's probably just accidental that we don't see the same in older branches. I've not looked into whether there would be any real-world consequences in non-assert builds. In HEAD, create_append_plan has sprouted the same problem, so fix that too (although we do not have any test cases that seem able to reach that bug). This is an oversight in commit 3fc6e2d7f which invented the CP_EXACT_TLIST flag, so back-patch to 9.6 where that came in. convert_subquery_pathkeys would create pathkeys for subquery output values if they match any EquivalenceClass known in the outer query and are available in the subquery's syntactic targetlist. However, the second part of that condition is wrong, because such values might not appear in the subquery relation's reltarget list, which would mean that they couldn't be accessed above the level of the subquery scan. We must check that they appear in the reltarget list, instead. This can lead to dropping knowledge about the subquery's sort ordering, but I believe it's okay, because any sort key that the outer query actually has any interest in would appear in the reltarget list. This second issue is of very long standing, but right now there's no evidence that it causes observable problems before 9.6, so I refrained from back-patching further than that. We can revisit that choice if somebody finds a way to make it cause problems in older branches. (Developing useful test cases for these issues is really problematic; fixing convert_subquery_pathkeys removes the only known way to exhibit the create_merge_append_plan bug, and neither of the test cases added by this patch causes a problem in all branches, even when considering the issues separately.) The second issue explains bug #15795 from Suresh Kumar R ("could not find pathkey item to sort" with nested DISTINCT queries). I stumbled across the first issue while investigating that. Discussion: https://postgr.es/m/15795-fadb56c8e44ee73c@postgresql.org	6 years ago
Tom Lane	959d00e9db	Use Append rather than MergeAppend for scanning ordered partitions. ... If we need ordered output from a scan of a partitioned table, but the ordering matches the partition ordering, then we don't need to use a MergeAppend to combine the pre-ordered per-partition scan results: a plain Append will produce the same results. This both saves useless comparison work inside the MergeAppend proper, and allows us to start returning tuples after istarting up just the first child node not all of them. However, all is not peaches and cream, because if some of the child nodes have high startup costs then there will be big discontinuities in the tuples-returned-versus-elapsed-time curve. The planner's cost model cannot handle that (yet, anyway). If we model the Append's startup cost as being just the first child's startup cost, we may drastically underestimate the cost of fetching slightly more tuples than are available from the first child. Since we've had bad experiences with over-optimistic choices of "fast start" plans for ORDER BY LIMIT queries, that seems scary. As a klugy workaround, set the startup cost estimate for an ordered Append to be the sum of its children's startup costs (as MergeAppend would). This doesn't really describe reality, but it's less likely to cause a bad plan choice than an underestimated startup cost would. In practice, the cases where we really care about this optimization will have child plans that are IndexScans with zero startup cost, so that the overly conservative estimate is still just zero. David Rowley, reviewed by Julien Rouhaud and Antonin Houska Discussion: https://postgr.es/m/CAKJS1f-hAqhPLRk_RaSFTgYxd=Tz5hA7kQ2h4-DhJufQk8TGuw@mail.gmail.com	7 years ago
Peter Eisentraut	fc22b6623b	Generated columns ... This is an SQL-standard feature that allows creating columns that are computed from expressions rather than assigned, similar to a view or materialized view but on a column basis. This implements one kind of generated column: stored (computed on write). Another kind, virtual (computed on read), is planned for the future, and some room is left for it. Reviewed-by: Michael Paquier <michael@paquier.xyz> Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com> Discussion: https://www.postgresql.org/message-id/flat/b151f851-4019-bdb1-699e-ebab07d2f40a@2ndquadrant.com	7 years ago
Tom Lane	8edd0e7946	Suppress Append and MergeAppend plan nodes that have a single child. ... If there's only one child relation, the Append or MergeAppend isn't doing anything useful, and can be elided. It does have a purpose during planning though, which is to serve as a buffer between parent and child Var numbering. Therefore we keep it all the way through to setrefs.c, and get rid of it only after fixing references in the plan level(s) above it. This works largely the same as setrefs.c's ancient hack to get rid of no-op SubqueryScan nodes, and can even share some code with that. Note the change to make setrefs.c use apply_tlist_labeling rather than ad-hoc code. This has the effect of propagating the child's resjunk and ressortgroupref labels, which formerly weren't propagated when removing a SubqueryScan. Doing that is demonstrably necessary for the [Merge]Append cases, and seems harmless for SubqueryScan, if only because trivial_subqueryscan is afraid to collapse cases where the resjunk marking differs. (I suspect that restriction could now be removed, though it's unclear that it'd make any new matches possible, since the outer query can't have references to a child resjunk column.) David Rowley, reviewed by Alvaro Herrera and Tomas Vondra Discussion: https://postgr.es/m/CAKJS1f_7u8ATyJ1JGTMHFoKDvZdeF-iEBhs+sM_SXowOr9cArg@mail.gmail.com	7 years ago
Peter Eisentraut	5e1963fb76	Collations with nondeterministic comparison ... This adds a flag "deterministic" to collations. If that is false, such a collation disables various optimizations that assume that strings are equal only if they are byte-wise equal. That then allows use cases such as case-insensitive or accent-insensitive comparisons or handling of strings with different Unicode normal forms. This functionality is only supported with the ICU provider. At least glibc doesn't appear to have any locales that work in a nondeterministic way, so it's not worth supporting this for the libc provider. The term "deterministic comparison" in this context is from Unicode Technical Standard #10 (https://unicode.org/reports/tr10/#Deterministic_Comparison). This patch makes changes in three areas: - CREATE COLLATION DDL changes and system catalog changes to support this new flag. - Many executor nodes and auxiliary code are extended to track collations. Previously, this code would just throw away collation information, because the eventually-called user-defined functions didn't use it since they only cared about equality, which didn't need collation information. - String data type functions that do equality comparisons and hashing are changed to take the (non-)deterministic flag into account. For comparison, this just means skipping various shortcuts and tie breakers that use byte-wise comparison. For hashing, we first need to convert the input string to a canonical "sort key" using the ICU analogue of strxfrm(). Reviewed-by: Daniel Verite <daniel@manitou-mail.org> Reviewed-by: Peter Geoghegan <pg@bowt.ie> Discussion: https://www.postgresql.org/message-id/flat/1ccc668f-4cbc-0bef-af67-450b47cdfee7@2ndquadrant.com	7 years ago
Tom Lane	1d33858406	Fix handling of targetlist SRFs when scan/join relation is known empty. ... When we introduced separate ProjectSetPath nodes for application of set-returning functions in v10, we inadvertently broke some cases where we're supposed to recognize that the result of a subquery is known to be empty (contain zero rows). That's because IS_DUMMY_REL was just looking for a childless AppendPath without allowing for a ProjectSetPath being possibly stuck on top. In itself, this didn't do anything much worse than produce slightly worse plans for some corner cases. Then in v11, commit 11cf92f6e rearranged things to allow the scan/join targetlist to be applied directly to partial paths before they get gathered. But it inserted a short-circuit path for dummy relations that was a little too short: it failed to insert a ProjectSetPath node at all for a targetlist containing set-returning functions, resulting in bogus "set-valued function called in context that cannot accept a set" errors, as reported in bug #15669 from Madelaine Thibaut. The best way to fix this mess seems to be to reimplement IS_DUMMY_REL so that it drills down through any ProjectSetPath nodes that might be there (and it seems like we'd better allow for ProjectionPath as well). While we're at it, make it look at rel->pathlist not cheapest_total_path, so that it gives the right answer independently of whether set_cheapest has been done lately. That dependency looks pretty shaky in the context of code like apply_scanjoin_target_to_paths, and even if it's not broken today it'd certainly bite us at some point. (Nastily, unsafe use of the old coding would almost always work; the hazard comes down to possibly looking through a dangling pointer, and only once in a blue moon would you find something there that resulted in the wrong answer.) It now looks like it was a mistake for IS_DUMMY_REL to be a macro: if there are any extensions using it, they'll continue to use the old inadequate logic until they're recompiled, after which they'll fail to load into server versions predating this fix. Hopefully there are few such extensions. Having fixed IS_DUMMY_REL, the special path for dummy rels in apply_scanjoin_target_to_paths is unnecessary as well as being wrong, so we can just drop it. Also change a few places that were testing for partitioned-ness of a planner relation but not using IS_PARTITIONED_REL for the purpose; that seems unsafe as well as inconsistent, plus it required an ugly hack in apply_scanjoin_target_to_paths. In passing, save a few cycles in apply_scanjoin_target_to_paths by skipping processing of pre-existing paths for partitioned rels, and do some cosmetic cleanup and comment adjustment in that function. I renamed IS_DUMMY_PATH to IS_DUMMY_APPEND with the intention of breaking any code that might be using it, since in almost every case that would be wrong; IS_DUMMY_REL is what to be using instead. In HEAD, also make set_dummy_rel_pathlist static (since it's no longer used from outside allpaths.c), and delete is_dummy_plan, since it's no longer used anywhere. Back-patch as appropriate into v11 and v10. Tom Lane and Julien Rouhaud Discussion: https://postgr.es/m/15669-02fb3296cca26203@postgresql.org	7 years ago
Tom Lane	8fd3fdd85a	Simplify the planner's new representation of indexable clauses a little. ... In commit 1a8d5afb0, I thought it'd be a good idea to define IndexClause.indexquals as NIL in the most common case where the given clause (IndexClause.rinfo) is usable exactly as-is. It'd be more consistent to define the indexquals in that case as being a one-element list containing IndexClause.rinfo, but I thought saving the palloc overhead for making such a list would be worthwhile. In hindsight, that was a great example of "premature optimization is the root of all evil": it's complicated everyplace that needs to deal with the indexquals, requiring duplicative code to handle both the simple case and the not-simple case. I'd initially found that tolerable but it's getting less so as I mop up some areas that I'd not touched in 1a8d5afb0. In any case, two more pallocs during a planner run are surely at the noise level (a conclusion confirmed by a bit of microbenchmarking). So let's change this decision before it becomes set in stone, and insist that IndexClause.indexquals always be a valid list of the actual index quals for the clause. Discussion: https://postgr.es/m/24586.1550106354@sss.pgh.pa.us	7 years ago
Tom Lane	1a8d5afb0d	Refactor the representation of indexable clauses in IndexPaths. ... In place of three separate but interrelated lists (indexclauses, indexquals, and indexqualcols), an IndexPath now has one list "indexclauses" of IndexClause nodes. This holds basically the same information as before, but in a more useful format: in particular, there is now a clear connection between an indexclause (an original restriction clause from WHERE or JOIN/ON) and the indexquals (directly usable index conditions) derived from it. We also change the ground rules a bit by mandating that clause commutation, if needed, be done up-front so that what is stored in the indexquals list is always directly usable as an index condition. This gets rid of repeated re-determination of which side of the clause is the indexkey during costing and plan generation, as well as repeated lookups of the commutator operator. To minimize the added up-front cost, the typical case of commuting a plain OpExpr is handled by a new special-purpose function commute_restrictinfo(). For RowCompareExprs, generating the new clause properly commuted to begin with is not really any more complex than before, it's just different --- and we can save doing that work twice, as the pretty-klugy original implementation did. Tracking the connection between original and derived clauses lets us also track explicitly whether the derived clauses are an exact or lossy translation of the original. This provides a cheap solution to getting rid of unnecessary rechecks of boolean index clauses, which previously seemed like it'd be more expensive than it was worth. Another pleasant (IMO) side-effect is that EXPLAIN now always shows index clauses with the indexkey on the left; this seems less confusing. This commit leaves expand_indexqual_conditions() and some related functions in a slightly messy state. I didn't bother to change them any more than minimally necessary to work with the new data structure, because all that code is going to be refactored out of existence in a follow-on patch. Discussion: https://postgr.es/m/22182.1549124950@sss.pgh.pa.us	7 years ago
Tom Lane	f09346a9c6	Refactor planner's header files. ... Create a new header optimizer/optimizer.h, which exposes just the planner functions that can be used "at arm's length", without need to access Paths or the other planner-internal data structures defined in nodes/relation.h. This is intended to provide the whole planner API seen by most of the rest of the system; although FDWs still need to use additional stuff, and more thought is also needed about just what selfuncs.c should rely on. The main point of doing this now is to limit the amount of new #include baggage that will be needed by "planner support functions", which I expect to introduce later, and which will be in relevant datatype modules rather than anywhere near the planner. This commit just moves relevant declarations into optimizer.h from other header files (a couple of which go away because everything got moved), and adjusts #include lists to match. There's further cleanup that could be done if we want to decide that some stuff being exposed by optimizer.h doesn't belong in the planner at all, but I'll leave that for another day. Discussion: https://postgr.es/m/11460.1548706639@sss.pgh.pa.us	7 years ago
Tom Lane	4be058fe9e	In the planner, replace an empty FROM clause with a dummy RTE. ... The fact that "SELECT expression" has no base relations has long been a thorn in the side of the planner. It makes it hard to flatten a sub-query that looks like that, or is a trivial VALUES() item, because the planner generally uses relid sets to identify sub-relations, and such a sub-query would have an empty relid set if we flattened it. prepjointree.c contains some baroque logic that works around this in certain special cases --- but there is a much better answer. We can replace an empty FROM clause with a dummy RTE that acts like a table of one row and no columns, and then there are no such corner cases to worry about. Instead we need some logic to get rid of useless dummy RTEs, but that's simpler and covers more cases than what was there before. For really trivial cases, where the query is just "SELECT expression" and nothing else, there's a hazard that adding the extra RTE makes for a noticeable slowdown; even though it's not much processing, there's not that much for the planner to do overall. However testing says that the penalty is very small, close to the noise level. In more complex queries, this is able to find optimizations that we could not find before. The new RTE type is called RTE_RESULT, since the "scan" plan type it gives rise to is a Result node (the same plan we produced for a "SELECT expression" query before). To avoid confusion, rename the old ResultPath path type to GroupResultPath, reflecting that it's only used in degenerate grouping cases where we know the query produces just one grouped row. (It wouldn't work to unify the two cases, because there are different rules about where the associated quals live during query_planner.) Note: although this touches readfuncs.c, I don't think a catversion bump is required, because the added case can't occur in stored rules, only plans. Patch by me, reviewed by David Rowley and Mark Dilger Discussion: https://postgr.es/m/15944.1521127664@sss.pgh.pa.us	7 years ago