Commit Graph

10 Commits

Author SHA1 Message Date
Bruce Momjian 29275b1d17 Update copyright for 2024
Reported-by: Michael Paquier

Discussion: https://postgr.es/m/ZZKTDPxBBMt3C0J9@paquier.xyz

Backpatch-through: 12
2024-01-03 20:49:05 -05:00
Bruce Momjian c8e1ba736b Update copyright for 2023
Backpatch-through: 11
2023-01-02 15:00:37 -05:00
David Rowley ed1a88ddac Allow window functions to adjust their frameOptions
WindowFuncs such as row_number() don't care if it's called with ROWS
UNBOUNDED PRECEDING AND CURRENT ROW or with RANGE UNBOUNDED PRECEDING AND
CURRENT ROW.  The latter is less efficient as the RANGE option requires
that the executor check for peer rows, so using the ROW option instead
would cause less overhead.  Because RANGE is part of the default frame
options for WindowClauses, it means WindowAgg is, by default, working much
harder than it needs to for window functions where the ROWS / RANGE option
has no effect on the window function's result.

On a test query from the discussion thread, a performance improvement of
344% was seen by using ROWS instead of RANGE.

Here we add a new support function node type to allow support functions to
be called for window functions so that the most optimal version of the
frame options can be set.  The planner has been adjusted so that the frame
options are changed only if all window functions sharing the same window
clause agree on what the optimized frame options are.

Here we give the ability for row_number(), rank(), dense_rank(),
percent_rank(), cume_dist() and ntile() to alter their WindowClause's
frameOptions.

Reviewed-by: Vik Fearing, Erwin Brandstetter, Zhihong Yu
Discussion: https://postgr.es/m/CAGHENJ7LBBszxS+SkWWFVnBmOT2oVsBhDMB1DFrgerCeYa_DyA@mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvohAKEtTXxq7Pc-ic2dKT8oZfbRKeEJP64M0B6+S88z+A@mail.gmail.com
2022-12-23 12:43:52 +13:00
David Rowley 9d9c02ccd1 Teach planner and executor about monotonic window funcs
Window functions such as row_number() always return a value higher than
the previously returned value for tuples in any given window partition.

Traditionally queries such as;

SELECT * FROM (
   SELECT *, row_number() over (order by c) rn
   FROM t
) t WHERE rn <= 10;

were executed fairly inefficiently.  Neither the query planner nor the
executor knew that once rn made it to 11 that nothing further would match
the outer query's WHERE clause.  It would blindly continue until all
tuples were exhausted from the subquery.

Here we implement means to make the above execute more efficiently.

This is done by way of adding a pg_proc.prosupport function to various of
the built-in window functions and adding supporting code to allow the
support function to inform the planner if the window function is
monotonically increasing, monotonically decreasing, both or neither.  The
planner is then able to make use of that information and possibly allow
the executor to short-circuit execution by way of adding a "run condition"
to the WindowAgg to allow it to determine if some of its execution work
can be skipped.

This "run condition" is not like a normal filter.  These run conditions
are only built using quals comparing values to monotonic window functions.
For monotonic increasing functions, quals making use of the btree
operators for <, <= and = can be used (assuming the window function column
is on the left). You can see here that once such a condition becomes false
that a monotonic increasing function could never make it subsequently true
again.  For monotonically decreasing functions the >, >= and = btree
operators for the given type can be used for run conditions.

The best-case situation for this is when there is a single WindowAgg node
without a PARTITION BY clause.  Here when the run condition becomes false
the WindowAgg node can simply return NULL.  No more tuples will ever match
the run condition.  It's a little more complex when there is a PARTITION
BY clause.  In this case, we cannot return NULL as we must still process
other partitions.  To speed this case up we pull tuples from the outer
plan to check if they're from the same partition and simply discard them
if they are.  When we find a tuple belonging to another partition we start
processing as normal again until the run condition becomes false or we run
out of tuples to process.

When there are multiple WindowAgg nodes to evaluate then this complicates
the situation.  For intermediate WindowAggs we must ensure we always
return all tuples to the calling node.  Any filtering done could lead to
incorrect results in WindowAgg nodes above.  For all intermediate nodes,
we can still save some work when the run condition becomes false.  We've
no need to evaluate the WindowFuncs anymore.  Other WindowAgg nodes cannot
reference the value of these and these tuples will not appear in the final
result anyway.  The savings here are small in comparison to what can be
saved in the top-level WingowAgg, but still worthwhile.

Intermediate WindowAgg nodes never filter out tuples, but here we change
WindowAgg so that the top-level WindowAgg filters out tuples that don't
match the intermediate WindowAgg node's run condition.  Such filters
appear in the "Filter" clause in EXPLAIN for the top-level WindowAgg node.

Here we add prosupport functions to allow the above to work for;
row_number(), rank(), dense_rank(), count(*) and count(expr).  It appears
technically possible to do the same for min() and max(), however, it seems
unlikely to be useful enough, so that's not done here.

Bump catversion

Author: David Rowley
Reviewed-by: Andy Fan, Zhihong Yu
Discussion: https://postgr.es/m/CAApHDvqvp3At8++yF8ij06sdcoo1S_b2YoaT9D4Nf+MObzsrLQ@mail.gmail.com
2022-04-08 10:34:36 +12:00
Bruce Momjian 27b77ecf9f Update copyright for 2022
Backpatch-through: 10
2022-01-07 19:04:57 -05:00
Bruce Momjian ca3b37487b Update copyright for 2021
Backpatch-through: 9.5
2021-01-02 13:06:25 -05:00
Bruce Momjian 7559d8ebfa Update copyrights for 2020
Backpatch-through: update all files in master, backpatch legal files through 9.4
2020-01-01 12:21:45 -05:00
Tom Lane 74dfe58a59 Allow extensions to generate lossy index conditions.
For a long time, indxpath.c has had the ability to extract derived (lossy)
index conditions from certain operators such as LIKE.  For just as long,
it's been obvious that we really ought to make that capability available
to extensions.  This commit finally accomplishes that, by adding another
API for planner support functions that lets them create derived index
conditions for their functions.  As proof of concept, the hardwired
"special index operator" code formerly present in indxpath.c is pushed
out to planner support functions attached to LIKE and other relevant
operators.

A weak spot in this design is that an extension needs to know OIDs for
the operators, datatypes, and opfamilies involved in the transformation
it wants to make.  The core-code prototypes use hard-wired OID references
but extensions don't have that option for their own operators etc.  It's
usually possible to look up the required info, but that may be slow and
inconvenient.  However, improving that situation is a separate task.

I want to do some additional refactorization around selfuncs.c, but
that also seems like a separate task.

Discussion: https://postgr.es/m/15193.1548028093@sss.pgh.pa.us
2019-02-11 21:26:14 -05:00
Tom Lane a391ff3c3d Build out the planner support function infrastructure.
Add support function requests for estimating the selectivity, cost,
and number of result rows (if a SRF) of the target function.

The lack of a way to estimate selectivity of a boolean-returning
function in WHERE has been a recognized deficiency of the planner
since Berkeley days.  This commit finally fixes it.

In addition, non-constant estimates of cost and number of output
rows are now possible.  We still fall back to looking at procost
and prorows if the support function doesn't service the request,
of course.

To make concrete use of the possibility of estimating output rowcount
for SRFs, this commit adds support functions for array_unnest(anyarray)
and the integer variants of generate_series; the lack of plausible
rowcount estimates for those, even when it's obvious to a human,
has been a repeated subject of complaints.  Obviously, much more
could now be done in this line, but I'm mostly just trying to get
the infrastructure in place.

Discussion: https://postgr.es/m/15193.1548028093@sss.pgh.pa.us
2019-02-09 18:32:23 -05:00
Tom Lane 1fb57af920 Create the infrastructure for planner support functions.
Rename/repurpose pg_proc.protransform as "prosupport".  The idea is
still that it names an internal function that provides knowledge to
the planner about the behavior of the function it's attached to;
but redesign the API specification so that it's not limited to doing
just one thing, but can support an extensible set of requests.

The original purpose of simplifying a function call is handled by
the first request type to be invented, SupportRequestSimplify.
Adjust all the existing transform functions to handle this API,
and rename them fron "xxx_transform" to "xxx_support" to reflect
the potential generalization of what they do.  (Since we never
previously provided any way for extensions to add transform functions,
this change doesn't create an API break for them.)

Also add DDL and pg_dump support for attaching a support function to a
user-defined function.  Unfortunately, DDL access has to be restricted
to superusers, at least for now; but seeing that support functions
will pretty much have to be written in C, that limitation is just
theoretical.  (This support is untested in this patch, but a follow-on
patch will add cases that exercise it.)

Discussion: https://postgr.es/m/15193.1548028093@sss.pgh.pa.us
2019-02-09 18:08:48 -05:00