| Commit message (Collapse) | Author | Age |
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Backpatch-through: 10
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Commit 4ace45677 failed to fix the problem fully, because the
same issue of attempting to fetch a non-returnable index column
can occur when rechecking the indexqual after using a lossy index
operator. Moreover, it broke EXPLAIN for such indexquals (which
indicates a gap in our test cases :-().
Revert the code changes of 4ace45677 in favor of adding a new field
to struct IndexOnlyScan, containing a version of the indexqual that
can be executed against the index-returned tuple without using any
non-returnable columns. (The restrictions imposed by check_index_only
guarantee this is possible, although we may have to recompute indexed
expressions.) Support construction of that during setrefs.c
processing by marking IndexOnlyScan.indextlist entries as resjunk
if they can't be returned, rather than removing them entirely.
(We could alternatively require setrefs.c to look up the IndexOptInfo
again, but abusing resjunk this way seems like a reasonably safe way
to avoid needing to do that.)
This solution isn't great from an API-stability standpoint: if there
are any extensions out there that build IndexOnlyScan structs directly,
they'll be broken in the next minor releases. However, only a very
invasive extension would be likely to do such a thing. There's no
change in the Path representation, so typical planner extensions
shouldn't have a problem.
As before, back-patch to all supported branches.
Discussion: https://postgr.es/m/3179992.1641150853@sss.pgh.pa.us
Discussion: https://postgr.es/m/17350-b5bdcf476e5badbb@postgresql.org
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If an index has both returnable and non-returnable columns, and one of
the non-returnable columns is an expression using a Var that is in a
returnable column, then a query returning that expression could result
in an index-only scan plan that attempts to read the non-returnable
column, instead of recomputing the expression from the returnable
column as intended.
To fix, redefine the "indextlist" list of an IndexOnlyScan plan node
as containing null Consts in place of any non-returnable columns.
This solves the problem by preventing setrefs.c from falsely matching
to such entries. The executor is happy since it only cares about the
exposed types of the entries, and ruleutils.c doesn't care because a
correct plan won't reference those entries. I considered some other
ways to prevent setrefs.c from doing the wrong thing, but this way
seems good since (a) it allows a very localized fix, (b) it makes
the indextlist structure more compact in many cases, and (c) the
indextlist is now a more faithful representation of what the index AM
will actually produce, viz. nulls for any non-returnable columns.
This is easier to hit since we introduced included columns, but it's
possible to construct failing examples without that, as per the
added regression test. Hence, back-patch to all supported branches.
Per bug #17350 from Louis Jachiet.
Discussion: https://postgr.es/m/17350-b5bdcf476e5badbb@postgresql.org
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It's possible that a subplan below a Memoize node contains a parameter
from above the Memoize node. If this parameter changes then cache entries
may become out-dated due to the new parameter value.
Previously Memoize was mistakenly not aware of this. We fix this here by
flushing the cache whenever a parameter that's not part of the cache
key changes.
Bug: #17213
Reported by: Elvis Pranskevichus
Author: David Rowley
Discussion: https://postgr.es/m/17213-988ed34b225a2862@postgresql.org
Backpatch-through: 14, where Memoize was added
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This reverts commit 1050048a315790a505465bfcceb26eaf8dbc7e2e.
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It's possible that a subplan below a Memoize node contains a parameter
from above the Memoize node. If this parameter changes then cache entries
may become out-dated due to the new parameter value.
Previously Memoize was mistakenly not aware of this. We fix this here by
flushing the cache whenever a parameter that's not part of the cache
key changes.
Bug: #17213
Reported by: Elvis Pranskevichus
Author: David Rowley
Discussion: https://postgr.es/m/17213-988ed34b225a2862@postgresql.org
Backpatch-through: 14, where Memoize was added
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Memoize would always use the hash equality operator for the cache key
types to determine if the current set of parameters were the same as some
previously cached set. Certain types such as floating points where -0.0
and +0.0 differ in their binary representation but are classed as equal by
the hash equality operator may cause problems as unless the join uses the
same operator it's possible that whichever join operator is being used
would be able to distinguish the two values. In which case we may
accidentally return in the incorrect rows out of the cache.
To fix this here we add a binary mode to Memoize to allow it to the
current set of parameters to previously cached values by comparing
bit-by-bit rather than logically using the hash equality operator. This
binary mode is always used for LATERAL joins and it's used for normal
joins when any of the join operators are not hashable.
Reported-by: Tom Lane
Author: David Rowley
Discussion: https://postgr.es/m/3004308.1632952496@sss.pgh.pa.us
Backpatch-through: 14, where Memoize was added
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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
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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
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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
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"Result Cache" was never a great name for this node, but nobody managed
to come up with another name that anyone liked enough. That was until
David Johnston mentioned "Node Memoization", which Tom Lane revised to
just "Memoize". People seem to like "Memoize", so let's do the rename.
Reviewed-by: Justin Pryzby
Discussion: https://postgr.es/m/20210708165145.GG1176@momjian.us
Backpatch-through: 14, where Result Cache was introduced
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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
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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
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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.
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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
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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
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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
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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
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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
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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
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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
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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
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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 a929e17e5a8 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
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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 a929e17e5a8 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
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Backpatch-through: 9.5
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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
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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
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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
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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
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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
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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
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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
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This reverts commit 4cad2534da6d17067d98cf04be2dfc1bda8f2cd0 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
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pgperltidy and reformat-dat-files too, though those didn't
find anything to change.
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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
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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
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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
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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
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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
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Backpatch-through: update all files in master, backpatch legal files through 9.4
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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
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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
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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
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In 5f32b29c1819 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-
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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
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Author: Alexander Lakhin
Discussion: https://postgr.es/m/af27d1b3-a128-9d62-46e0-88f424397f44@gmail.com
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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
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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
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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
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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
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