This SQL standard functionality allows to aggregate data by different
GROUP BY clauses at once. Each grouping set returns rows with columns
grouped by in other sets set to NULL.
This could previously be achieved by doing each grouping as a separate
query, conjoined by UNION ALLs. Besides being considerably more concise,
grouping sets will in many cases be faster, requiring only one scan over
the underlying data.
The current implementation of grouping sets only supports using sorting
for input. Individual sets that share a sort order are computed in one
pass. If there are sets that don't share a sort order, additional sort &
aggregation steps are performed. These additional passes are sourced by
the previous sort step; thus avoiding repeated scans of the source data.
The code is structured in a way that adding support for purely using
hash aggregation or a mix of hashing and sorting is possible. Sorting
was chosen to be supported first, as it is the most generic method of
implementation.
Instead of, as in an earlier versions of the patch, representing the
chain of sort and aggregation steps as full blown planner and executor
nodes, all but the first sort are performed inside the aggregation node
itself. This avoids the need to do some unusual gymnastics to handle
having to return aggregated and non-aggregated tuples from underlying
nodes, as well as having to shut down underlying nodes early to limit
memory usage. The optimizer still builds Sort/Agg node to describe each
phase, but they're not part of the plan tree, but instead additional
data for the aggregation node. They're a convenient and preexisting way
to describe aggregation and sorting. The first (and possibly only) sort
step is still performed as a separate execution step. That retains
similarity with existing group by plans, makes rescans fairly simple,
avoids very deep plans (leading to slow explains) and easily allows to
avoid the sorting step if the underlying data is sorted by other means.
A somewhat ugly side of this patch is having to deal with a grammar
ambiguity between the new CUBE keyword and the cube extension/functions
named cube (and rollup). To avoid breaking existing deployments of the
cube extension it has not been renamed, neither has cube been made a
reserved keyword. Instead precedence hacking is used to make GROUP BY
cube(..) refer to the CUBE grouping sets feature, and not the function
cube(). To actually group by a function cube(), unlikely as that might
be, the function name has to be quoted.
Needs a catversion bump because stored rules may change.
Author: Andrew Gierth and Atri Sharma, with contributions from Andres Freund
Reviewed-By: Andres Freund, Noah Misch, Tom Lane, Svenne Krap, Tomas
Vondra, Erik Rijkers, Marti Raudsepp, Pavel Stehule
Discussion: CAOeZVidmVRe2jU6aMk_5qkxnB7dfmPROzM7Ur8JPW5j8Y5X-Lw@mail.gmail.com
This SQL-standard feature allows a sub-SELECT yielding multiple columns
(but only one row) to be used to compute the new values of several columns
to be updated. While the same results can be had with an independent
sub-SELECT per column, such a workaround can require a great deal of
duplicated computation.
The standard actually says that the source for a multi-column assignment
could be any row-valued expression. The implementation used here is
tightly tied to our existing sub-SELECT support and can't handle other
cases; the Bison grammar would have some issues with them too. However,
I don't feel too bad about this since other cases can be converted into
sub-SELECTs. For instance, "SET (a,b,c) = row_valued_function(x)" could
be written "SET (a,b,c) = (SELECT * FROM row_valued_function(x))".
It's possible that inlining of SQL functions (or perhaps other changes?)
has exposed typmod information not known at parse time. In such cases,
Vars generated by query_planner might have valid typmod values while the
original grouping columns only have typmod -1. This isn't a semantic
problem since the behavior of grouping only depends on type not typmod,
but it breaks locate_grouping_columns' use of tlist_member to locate the
matching entry in query_planner's result tlist.
We can fix this without an excessive amount of new code or complexity by
relying on the fact that locate_grouping_columns only gets called when
make_subplanTargetList has set need_tlist_eval == false, and that can only
happen if all the grouping columns are simple Vars. Therefore we only need
to search the sub_tlist for a matching Var, and we can reasonably define a
"match" as being a match of the Var identity fields
varno/varattno/varlevelsup. The code still Asserts that vartype matches,
but ignores vartypmod.
Per bug #8393 from Evan Martin. The added regression test case is
basically the same as his example. This has been broken for a very long
time, so back-patch to all supported branches.
The planner sometimes inserts Result nodes to perform column projections
(ie, arbitrary scalar calculations) above plan nodes that lack projection
logic of their own. However, we did that even if the lower plan node was
in fact producing the required column set already; which is a pretty common
case given the popularity of "SELECT * FROM ...". Measurements show that
the useless plan node adds non-negligible overhead, especially when there
are many columns in the result. So add a check to avoid inserting a Result
node unless there's something useful for it to do.
There are a couple of remaining places where unnecessary Result nodes
could get inserted, but they are (a) much less performance-critical,
and (b) coded in such a way that it's hard to avoid inserting a Result,
because the desired tlist is changed on-the-fly in subsequent logic.
We'll leave those alone for now.
Kyotaro Horiguchi; reviewed and further hacked on by Amit Kapila and
Tom Lane.
Regular aggregate functions in combination with, or within the arguments
of, window functions are OK per spec; they have the semantics that the
aggregate output rows are computed and then we run the window functions
over that row set. (Thus, this combination is not really useful unless
there's a GROUP BY so that more than one aggregate output row is possible.)
The case without GROUP BY could fail, as recently reported by Jeff Davis,
because sloppy construction of the Agg node's targetlist resulted in extra
references to possibly-ungrouped Vars appearing outside the aggregate
function calls themselves. See the added regression test case for an
example.
Fixing this requires modifying the API of flatten_tlist and its underlying
function pull_var_clause. I chose to make pull_var_clause's API for
aggregates identical to what it was already doing for placeholders, since
the useful behaviors turn out to be the same (error, report node as-is, or
recurse into it). I also tightened the error checking in this area a bit:
if it was ever valid to see an uplevel Var, Aggref, or PlaceHolderVar here,
that was a long time ago, so complain instead of ignoring them.
Backpatch into 9.1. The failure exists in 8.4 and 9.0 as well, but seeing
that it only occurs in a basically-useless corner case, it doesn't seem
worth the risks of changing a function API in a minor release. There might
be third-party code using pull_var_clause.
This area was a few bricks shy of a load, and badly under-commented too.
We have to ensure that the generated targetlist entries for a set-operation
node expose the correct collation for each entry, since higher-level
processing expects the tlist to reflect the true ordering of the plan's
output.
This hackery wouldn't be necessary if SortGroupClause carried collation
info ... but making it do so would inject more pain in the parser than
would be saved here. Still, we might want to rethink that sometime.
hashtable entries for tuples that are found only in the second input: they
can never contribute to the output. Furthermore, this implies that the
planner should endeavor to put first the smaller (in number of groups) input
relation for an INTERSECT. Implement that, and upgrade prepunion's estimation
of the number of rows returned by setops so that there's some amount of sanity
in the estimate of which one is smaller.
but seem like a separate patch since most of the remaining work is on the
executor side.) I took the opportunity to push selection of the grouping
operators for set operations into the parser where it belongs. Otherwise this
is just a small exercise in making prepunion.c consider both alternatives.
As with the recent DISTINCT patch, this means we can UNION on datatypes that
can hash but not sort, and it means that UNION without ORDER BY is no longer
certain to produce sorted output.
as per my recent proposal:
1. Fold SortClause and GroupClause into a single node type SortGroupClause.
We were already relying on them to be struct-equivalent, so using two node
tags wasn't accomplishing much except to get in the way of comparing items
with equal().
2. Add an "eqop" field to SortGroupClause to carry the associated equality
operator. This is cheap for the parser to get at the same time it's looking
up the sort operator, and storing it eliminates the need for repeated
not-so-cheap lookups during planning. In future this will also let us
represent GROUP/DISTINCT operations on datatypes that have hash opclasses
but no btree opclasses (ie, they have equality but no natural sort order).
The previous representation simply didn't work for that, since its only
indicator of comparison semantics was a sort operator.
3. Add a hasDistinctOn boolean to struct Query to explicitly record whether
the distinctClause came from DISTINCT or DISTINCT ON. This allows removing
some complicated and not 100% bulletproof code that attempted to figure
that out from the distinctClause alone.
This patch doesn't in itself create any new capability, but it's necessary
infrastructure for future attempts to use hash-based grouping for DISTINCT
and UNION/INTERSECT/EXCEPT.
predictable manner; in particular that if you say ORDER BY output-column-ref,
it will in fact sort by that specific column even if there are multiple
syntactic matches. An example is
SELECT random() AS a, random() AS b FROM ... ORDER BY b, a;
While the use-case for this might be a bit debatable, it worked as expected
in earlier releases, so we should preserve the behavior for 8.3. Per my
recent proposal.
While at it, fix convert_subquery_pathkeys() to handle RelabelType stripping
in both directions; it needs this for the same reasons make_sort_from_pathkeys
does.
to be able to discard top-level RelabelType nodes on *both* sides of the
equivalence-class-to-target-list comparison, since make_pathkey_from_sortinfo
might either add or remove a RelabelType. Also fix the latter to do the
removal case cleanly. Per example from Peter.
thereby sharing code with the inheritance case. This puts the UNION-ALL-view
approach to partitioned tables on par with inheritance, so far as constraint
exclusion is concerned: it works either way. (Still need to update the docs
to say so.) The definition of "simple UNION ALL" is a little simpler than
I would like --- basically the union arms can only be SELECT * FROM foo
--- but it's good enough for partitioned-table cases.
few palloc's. I also chose to eliminate the restype and restypmod fields
entirely, since they are redundant with information stored in the node's
contained expression; re-examining the expression at need seems simpler
and more reliable than trying to keep restype/restypmod up to date.
initdb forced due to change in contents of stored rules.
Also performed an initial run through of upgrading our Copyright date to
extend to 2005 ... first run here was very simple ... change everything
where: grep 1996-2004 && the word 'Copyright' ... scanned through the
generated list with 'less' first, and after, to make sure that I only
picked up the right entries ...
node emits only those vars that are actually needed above it in the
plan tree. (There were comments in the code suggesting that this was
done at some point in the dim past, but for a long time we have just
made join nodes emit everything that either input emitted.) Aside from
being marginally more efficient, this fixes the problem noted by Peter
Eisentraut where a join above an IN-implemented-as-join might fail,
because the subplan targetlist constructed in the latter case didn't
meet the expectation of including everything.
Along the way, fix some places that were O(N^2) in the targetlist
length. This is not all the trouble spots for wide queries by any
means, but it's a step forward.
the column by table OID and column number, if it's a simple column
reference. Along the way, get rid of reskey/reskeyop fields in Resdoms.
Turns out that representation was not convenient for either the planner
or the executor; we can make the planner deliver exactly what the
executor wants with no more effort.
initdb forced due to change in stored rule representation.
the outer query. (The implementation is a bit klugy, but it would take
nontrivial restructuring to make it nicer, which this is probably not
worth.) This avoids unnecessary sort steps in examples like
SELECT foo,count(*) FROM (SELECT ... ORDER BY foo,bar) sub GROUP BY foo
which means there is now a reasonable technique for controlling the
order of inputs to custom aggregates, even in the grouping case.
There are two implementation techniques: the executor understands a new
JOIN_IN jointype, which emits at most one matching row per left-hand row,
or the result of the IN's sub-select can be fed through a DISTINCT filter
and then joined as an ordinary relation.
Along the way, some minor code cleanup in the optimizer; notably, break
out most of the jointree-rearrangement preprocessing in planner.c and
put it in a new file prep/prepjointree.c.
as both a GROUP BY item and an output expression, the top-level Group
node should just copy up the evaluated expression value from its input,
rather than re-evaluating the expression. Aside from any performance
benefit this might offer, this avoids a crash when there is a sub-SELECT
in said expression.
SELECT DISTINCT ON (expr [, expr ...]) targetlist ...
and there is a check to make sure that the user didn't specify an ORDER BY
that's incompatible with the DISTINCT operation.
Reimplement nodeUnique and nodeGroup to use the proper datatype-specific
equality function for each column being compared --- they used to do
bitwise comparisons or convert the data to text strings and strcmp().
(To add insult to injury, they'd look up the conversion functions once
for each tuple...) Parse/plan representation of DISTINCT is now a list
of SortClause nodes.
initdb forced by querytree change...
and fix_opids processing to a single recursive pass over the plan tree
executed at the very tail end of planning, rather than haphazardly here
and there at different places. Now that tlist Vars do not get modified
until the very end, it's possible to get rid of the klugy var_equal and
match_varid partial-matching routines, and just use plain equal()
throughout the optimizer. This is a step towards allowing merge and
hash joins to be done on expressions instead of only Vars ...
sort order down into planner, instead of handling it only at the very top
level of the planner. This fixes many things. An explicit sort is now
avoided if there is a cheaper alternative (typically an indexscan) not
only for ORDER BY, but also for the internal sort of GROUP BY. It works
even when there is no other reason (such as a WHERE condition) to consider
the indexscan. It works for indexes on functions. It works for indexes
on functions, backwards. It's just so cool...
CAUTION: I have changed the representation of SortClause nodes, therefore
THIS UPDATE BREAKS STORED RULES. You will need to initdb.
store all ordering information in pathkeys lists (which are now lists of
lists of PathKeyItem nodes, not just lists of lists of vars). This was
a big win --- the code is smaller and IMHO more understandable than it
was, even though it handles more cases. I believe the node changes will
not force an initdb for anyone; planner nodes don't show up in stored
rules.
Bruce Momjian
Andres Freund
Tom Lane
Magnus Hagander
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