For a mergejoin, if the given outer path or inner path is not already
well enough ordered, we need to do an explicit sort. Currently, we
only consider explicit full sort and do not account for incremental
sort.
In this patch, for the outer path of a mergejoin, we choose to use
explicit incremental sort if it is enabled and there are presorted
keys. For the inner path, though, we cannot use incremental sort
because it does not support mark/restore at present.
The rationale is based on the assumption that incremental sort is
always faster than full sort when there are presorted keys, a premise
that has been applied in various parts of the code. In addition, the
current cost model tends to favor incremental sort as being cheaper
than full sort in the presence of presorted keys, making it reasonable
not to consider full sort in such cases.
It could be argued that what if a mergejoin with an incremental sort
as the outer path is selected as the inner path of another mergejoin.
However, this should not be a problem, because mergejoin itself does
not support mark/restore either, and we will add a Material node on
top of it anyway in this case (see final_cost_mergejoin).
There is one ensuing plan change in the regression tests, and we have
to modify that test case to ensure that it continues to test what it
is intended to.
No backpatch as this could result in plan changes.
Author: Richard Guo
Reviewed-by: David Rowley, Tomas Vondra
Discussion: https://postgr.es/m/CAMbWs49x425QrX7h=Ux05WEnt8GS757H-jOP3_xsX5t1FoUsZw@mail.gmail.com
Previously an "amcanorderbyop" index would only be used when the index
could provide sorted results which satisfied all query_pathkeys. Here
we relax this so that we also allow these indexes to be considered by the
planner when they only provide partially sorted results. This allows the
planner to later consider making use of an Incremental Sort to satisfy the
remaining pathkeys. This change is particularly useful for KNN-type
queries which contain a LIMIT clause and an additional ORDER BY clause for
a non-indexed column.
Author: Miroslav Bendik
Reviewed-by: Richard Guo, David Rowley
Discussion: https://postgr.es/m/CAPoEpV0QYDtzjwamwWUBqyWpaCVbJV2d6qOD7Uy09bWn47PJtw%40mail.gmail.com
When incremental sorts were added in v13 a 1.5x pessimism factor was added
to the cost modal. Seemingly this was done because the cost modal only
has an estimate of the total number of input rows and the number of
presorted groups. It assumes that the input rows will be evenly
distributed throughout the presorted groups. The 1.5x pessimism factor
was added to slightly reduce the likelihood of incremental sorts being
used in the hope to avoid performance regressions where an incremental
sort plan was picked and turned out slower due to a large skew in the
number of rows in the presorted groups.
An additional quirk with the path generation code meant that we could
consider both a sort and an incremental sort on paths with presorted keys.
This meant that with the pessimism factor, it was possible that we opted
to perform a sort rather than an incremental sort when the given path had
presorted keys.
Here we remove the 1.5x pessimism factor to allow incremental sorts to
have a fairer chance at being chosen against a full sort.
Previously we would generally create a sort path on the cheapest input
path (if that wasn't sorted already) and incremental sort paths on any
path which had presorted keys. This meant that if the cheapest input path
wasn't completely sorted but happened to have presorted keys, we would
create a full sort path *and* an incremental sort path on that input path.
Here we change this logic so that if there are presorted keys, we only
create an incremental sort path, and create sort paths only when a full
sort is required.
Both the removal of the cost pessimism factor and the changes made to the
path generation make it more likely that incremental sorts will now be
chosen. That, of course, as with teaching the planner any new tricks,
means an increased likelihood that the planner will perform an incremental
sort when it's not the best method. Our standard escape hatch for these
cases is an enable_* GUC. enable_incremental_sort already exists for
this.
This came out of a report by Pavel Luzanov where he mentioned that the
master branch was choosing to perform a Seq Scan -> Sort -> Group
Aggregate for his query with an ORDER BY aggregate function. The v15 plan
for his query performed an Index Scan -> Group Aggregate, of course, the
aggregate performed the final sort internally in nodeAgg.c for the
aggregate's ORDER BY. The ideal plan would have been to use the index,
which provided partially sorted input then use an incremental sort to
provide the aggregate with the sorted input. This was not being chosen
due to the pessimism in the incremental sort cost modal, so here we remove
that and rationalize the path generation so that sort and incremental sort
plans don't have to needlessly compete. We assume that it's senseless
to ever use a full sort on a given input path where an incremental sort
can be performed.
Reported-by: Pavel Luzanov
Reviewed-by: Richard Guo
Discussion: https://postgr.es/m/9f61ddbf-2989-1536-b31e-6459370a6baa%40postgrespro.ru
This reverts commit db0d67db24 and
several follow-on fixes. The idea of making a cost-based choice
of the order of the sorting columns is not fundamentally unsound,
but it requires cost information and data statistics that we don't
really have. For example, relying on procost to distinguish the
relative costs of different sort comparators is pretty pointless
so long as most such comparator functions are labeled with cost 1.0.
Moreover, estimating the number of comparisons done by Quicksort
requires more than just an estimate of the number of distinct values
in the input: you also need some idea of the sizes of the larger
groups, if you want an estimate that's good to better than a factor of
three or so. That's data that's often unknown or not very reliable.
Worse, to arrive at estimates of the number of calls made to the
lower-order-column comparison functions, the code needs to make
estimates of the numbers of distinct values of multiple columns,
which are necessarily even less trustworthy than per-column stats.
Even if all the inputs are perfectly reliable, the cost algorithm
as-implemented cannot offer useful information about how to order
sorting columns beyond the point at which the average group size
is estimated to drop to 1.
Close inspection of the code added by db0d67db2 shows that there
are also multiple small bugs. These could have been fixed, but
there's not much point if we don't trust the estimates to be
accurate in-principle.
Finally, the changes in cost_sort's behavior made for very large
changes (often a factor of 2 or so) in the cost estimates for all
sorting operations, not only those for multi-column GROUP BY.
That naturally changes plan choices in many situations, and there's
precious little evidence to show that the changes are for the better.
Given the above doubts about whether the new estimates are really
trustworthy, it's hard to summon much confidence that these changes
are better on the average.
Since we're hard up against the release deadline for v15, let's
revert these changes for now. We can always try again later.
Note: in v15, I left T_PathKeyInfo in place in nodes.h even though
it's unreferenced. Removing it would be an ABI break, and it seems
a bit late in the release cycle for that.
Discussion: https://postgr.es/m/TYAPR01MB586665EB5FB2C3807E893941F5579@TYAPR01MB5866.jpnprd01.prod.outlook.com
Remove the test case added by commit fac1b470a, which never actually
worked to expose the problem it claimed to test. Replace it with
a case that does expose the problem, and also covers the SRF-not-
at-the-top deficiency repaired in 1aa8dad41.
Richard Guo, with some editorialization by me
Discussion: https://postgr.es/m/17564-c7472c2f90ef2da3@postgresql.org
When evaluating a query with a multi-column GROUP BY clause using sort,
the cost may be heavily dependent on the order in which the keys are
compared when building the groups. Grouping does not imply any ordering,
so we're allowed to compare the keys in arbitrary order, and a Hash Agg
leverages this. But for Group Agg, we simply compared keys in the order
as specified in the query. This commit explores alternative ordering of
the keys, trying to find a cheaper one.
In principle, we might generate grouping paths for all permutations of
the keys, and leave the rest to the optimizer. But that might get very
expensive, so we try to pick only a couple interesting orderings based
on both local and global information.
When planning the grouping path, we explore statistics (number of
distinct values, cost of the comparison function) for the keys and
reorder them to minimize comparison costs. Intuitively, it may be better
to perform more expensive comparisons (for complex data types etc.)
last, because maybe the cheaper comparisons will be enough. Similarly,
the higher the cardinality of a key, the lower the probability we’ll
need to compare more keys. The patch generates and costs various
orderings, picking the cheapest ones.
The ordering of group keys may interact with other parts of the query,
some of which may not be known while planning the grouping. E.g. there
may be an explicit ORDER BY clause, or some other ordering-dependent
operation, higher up in the query, and using the same ordering may allow
using either incremental sort or even eliminate the sort entirely.
The patch generates orderings and picks those minimizing the comparison
cost (for various pathkeys), and then adds orderings that might be
useful for operations higher up in the plan (ORDER BY, etc.). Finally,
it always keeps the ordering specified in the query, on the assumption
the user might have additional insights.
This introduces a new GUC enable_group_by_reordering, so that the
optimization may be disabled if needed.
The original patch was proposed by Teodor Sigaev, and later improved and
reworked by Dmitry Dolgov. Reviews by a number of people, including me,
Andrey Lepikhov, Claudio Freire, Ibrar Ahmed and Zhihong Yu.
Author: Dmitry Dolgov, Teodor Sigaev, Tomas Vondra
Reviewed-by: Tomas Vondra, Andrey Lepikhov, Claudio Freire, Ibrar Ahmed, Zhihong Yu
Discussion: https://postgr.es/m/7c79e6a5-8597-74e8-0671-1c39d124c9d6%40sigaev.ru
Discussion: https://postgr.es/m/CA%2Bq6zcW_4o2NC0zutLkOJPsFt80megSpX_dVRo6GK9PC-Jx_Ag%40mail.gmail.com
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
The inner loop in switchToPresortedPrefixMode() can be implemented
as a conventional integer-counter for() loop, removing a couple of
redundant boolean state variables. The old logic here was a remnant
of earlier development, but as things now stand there's no reason
for extra complexity.
Also, annotate the test case added by 82e0e2930 to explain why it
manages to hit the corner case fixed in that commit, and add an
EXPLAIN to verify that it's creating an incremental-sort plan.
Back-patch to v13, like the previous patch.
James Coleman and Tom Lane
Discussion: https://postgr.es/m/16846-ae49f51ac379a4cb@postgresql.org
switchToPresortedPrefixMode() did the wrong thing if it detected
a batch boundary just at the last tuple of a fullsort group.
The initially-reported symptom was a "retrieved too many tuples in a
bounded sort" error, but the test case added here just silently gives
the wrong answer without this patch.
I (tgl) am not really happy about committing this patch without review
from the incremental-sort authors, but they seem AWOL and we are hard
against a release deadline. This does demonstrably make some cases
better, anyway.
Per bug #16846 from Yoran Heling. Back-patch to v13 where incremental
sort was introduced.
Neil Chen
Discussion: https://postgr.es/m/16846-ae49f51ac379a4cb@postgresql.org
While we do allow SRFs in ORDER BY, scan/join processing should not
consider such cases - such sorts should only happen via final Sort atop
a ProjectSet. So make sure we don't try adding such sorts below Gather
Merge, just like we do for expressions that are volatile and/or not
parallel safe.
Backpatch to PostgreSQL 13, where this code was introduced as part of
the Incremental Sort patch.
Author: James Coleman
Reviewed-by: Tomas Vondra
Backpatch-through: 13
Discussion: https://postgr.es/m/CAAaqYe8cK3g5CfLC4w7bs=hC0mSksZC=H5M8LSchj5e5OxpTAg@mail.gmail.com
Discussion: https://postgr.es/m/295524.1606246314%40sss.pgh.pa.us
Commit ebb7ae839d ensured we ignore pathkeys with volatile expressions
when considering adding a sort below a Gather Merge. Turns out we need
to care about parallel safety of the pathkeys too, otherwise we might
try sorting e.g. on results of a correlated subquery (as demonstrated
by a report from Luis Roberto).
Initial investigation by Tom Lane, patch by James Coleman. Backpatch
to 13, where the code was instroduced (as part of Incremental Sort).
Reported-by: Luis Roberto
Author: James Coleman
Reviewed-by: Tomas Vondra
Backpatch-through: 13
Discussion: https://postgr.es/m/622580997.37108180.1604080457319.JavaMail.zimbra%40siscobra.com.br
Discussion: https://postgr.es/m/CAAaqYe8cK3g5CfLC4w7bs=hC0mSksZC=H5M8LSchj5e5OxpTAg@mail.gmail.com
generate_useful_gather_paths used to skip unsorted paths (without any
pathkeys), but that is unnecessary - the later code actually can handle
such paths just fine by adding a Sort node. This is clearly a thinko,
preventing construction of useful plans.
Backpatch to 13, where Incremental Sort was introduced.
Author: James Coleman
Reviewed-by: Tomas Vondra
Backpatch-through: 13
Discussion: https://postgr.es/m/CAAaqYe8cK3g5CfLC4w7bs=hC0mSksZC=H5M8LSchj5e5OxpTAg@mail.gmail.com
When considering Incremental Sort below a Gather Merge, we need to be
a bit more careful when matching pathkeys to EC members. It's not enough
to find a member whose Vars are all in the current relation's target;
volatile expressions in particular need to be contained in the target,
otherwise it's too early to use the pathkey.
Reported-by: Jaime Casanova
Author: James Coleman
Reviewed-by: Tomas Vondra
Backpatch-through: 13, where the incremental sort code was added
Discussion: https://postgr.es/m/CAJGNTeNaxpXgBVcRhJX%2B2vSbq%2BF2kJqGBcvompmpvXb7pq%2BoFA%40mail.gmail.com
The explain format used by incremental sort was somewhat inconsistent
with other nodes, making it harder to parse and understand. This commit
addresses that by
- adding an extra space to better separate groups of values
- using colons instead of equal signs to separate key/value
- properly capitalizing first letter of a key
- using separate lines for full and pre-sorted groups
These changes were proposed by Justin Pryzby and mostly copy the final
explain format used to report WAL usage.
Author: Justin Pryzby
Reviewed-by: James Coleman
Discussion: https://postgr.es/m/20200419023625.GP26953@telsasoft.com
When estimating the number of pre-sorted groups in cost_incremental_sort
we must not pass Vars with varno 0 to estimate_num_groups, which would
cause failues in find_base_rel. This may happen when sorting output of
set operations, thanks to generate_append_tlist.
Unlike recurse_set_operations we can't easily access the original target
list, so if we find any Vars with varno 0, we fall back to the default
estimate DEFAULT_NUM_DISTINCT.
Reported-by: Justin Pryzby
Discussion: https://postgr.es/m/20200411214639.GK2228%40telsasoft.com
The test never did ANALYZE on the test table, so the plans depended on
various defaults (e.g. number of groups being 200). This worked most of
the time, but with CLOBBER_CACHE_ALWAYS the autoanalyze often managed
to build accurate stats, changing the plan.
Fixed by increasing the size of test tables a bit, making the Sort a bit
more expensive than Incremental Sort. The tests were constructed to test
transitions in the Incremental Sort algorithm, and this change does not
break that.
Reviewed-by: James Coleman
Discussion: https://postgr.es/m/CAPpHfds1waRZ=NOmueYq0sx1ZSCnt+5QJvizT8ndT2=etZEeAQ@mail.gmail.com
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
