This commit changes index-only scans so that data is read directly from the
index tuple without first generating a faux heap tuple. The only immediate
benefit is that indexes on system columns (such as OID) can be used in
index-only scans, but this is necessary infrastructure if we are ever to
support index-only scans on expression indexes. The executor is now ready
for that, though the planner still needs substantial work to recognize
the possibility.
To do this, Vars in index-only plan nodes have to refer to index columns
not heap columns. I introduced a new special varno, INDEX_VAR, to mark
such Vars to avoid confusion. (In passing, this commit renames the two
existing special varnos to OUTER_VAR and INNER_VAR.) This allows
ruleutils.c to handle them with logic similar to what we use for subplan
reference Vars.
Since index-only scans are now fundamentally different from regular
indexscans so far as their expression subtrees are concerned, I also chose
to change them to have their own plan node type (and hence, their own
executor source file).
This provides information about the numbers of tuples that were visited
but not returned by table scans, as well as the numbers of join tuples
that were considered and discarded within a join plan node.
There is still some discussion going on about the best way to report counts
for outer-join situations, but I think most of what's in the patch would
not change if we revise that, so I'm going to go ahead and commit it as-is.
Documentation changes to follow (they weren't in the submitted patch
either).
Marko Tiikkaja, reviewed by Marc Cousin, somewhat revised by Tom
This is advantageous first because it allows us to hash the smaller table
regardless of the outer-join type, and second because hash join can be more
flexible than merge join in dealing with arbitrary join quals in a FULL
join. For merge join all the join quals have to be mergejoinable, but hash
join will work so long as there's at least one hashjoinable qual --- the
others can be any condition. (This is true essentially because we don't
keep per-inner-tuple match flags in merge join, while hash join can do so.)
To do this, we need a has-it-been-matched flag for each tuple in the
hashtable, not just one for the current outer tuple. The key idea that
makes this practical is that we can store the match flag in the tuple's
infomask, since there are lots of bits there that are of no interest for a
MinimalTuple. So we aren't increasing the size of the hashtable at all for
the feature.
To write this without turning the hash code into even more of a pile of
spaghetti than it already was, I rewrote ExecHashJoin in a state-machine
style, similar to ExecMergeJoin. Other than that decision, it was pretty
straightforward.
relation using the general PARAM_EXEC executor parameter mechanism, rather
than the ad-hoc kluge of passing the outer tuple down through ExecReScan.
The previous method was hard to understand and could never be extended to
handle parameters coming from multiple join levels. This patch doesn't
change the set of possible plans nor have any significant performance effect,
but it's necessary infrastructure for future generalization of the concept
of an inner indexscan plan.
ExecReScan's second parameter is now unused, so it's removed.
The purpose of this change is to eliminate the need for every caller
of SearchSysCache, SearchSysCacheCopy, SearchSysCacheExists,
GetSysCacheOid, and SearchSysCacheList to know the maximum number
of allowable keys for a syscache entry (currently 4). This will
make it far easier to increase the maximum number of keys in a
future release should we choose to do so, and it makes the code
shorter, too.
Design and review by Tom Lane.
We show the number of buckets, the number of batches (and also the original
number if it has changed), and the peak space used by the hash table. Minor
executor changes to track peak space used.
"column < constant", and the comparison value is in the first or last
histogram bin or outside the histogram entirely, try to fetch the actual
column min or max value using an index scan (if there is an index on the
column). If successful, replace the lower or upper histogram bound with
that value before carrying on with the estimate. This limits the
estimation error caused by moving min/max values when the comparison
value is close to the min or max. Per a complaint from Josh Berkus.
It is tempting to consider using this mechanism for mergejoinscansel as well,
but that would inject index fetches into main-line join estimation not just
endpoint cases. I'm refraining from that until we can get a better handle
on the costs of doing this type of lookup.
and teach ANALYZE to compute such stats for tables that have subclasses.
Per my proposal of yesterday.
autovacuum still needs to be taught about running ANALYZE on parent tables
when their subclasses change, but the feature is useful even without that.
The original coding ensured nbuckets and nbatch didn't exceed INT_MAX,
which while not insane on its own terms did nothing to protect subsequent
code like "palloc(nbatch * sizeof(BufFile *))". Since enormous join size
estimates might well be planner error rather than reality, it seems best
to constrain the initial sizes to be not more than work_mem/sizeof(pointer),
thus ensuring the allocated arrays don't exceed work_mem. We will allow
nbatch to get bigger than that during subsequent ExecHashIncreaseNumBatches
calls, but we should still guard against integer overflow in those palloc
requests. Per bug #5145 from Bernt Marius Johnsen.
Although the given test case only seems to fail back to 8.2, previous
releases have variants of this issue, so patch all supported branches.
distribution, by creating a special fast path for the (first few) most common
values of the outer relation. Tuples having hashvalues matching the MCVs
are effectively forced to be in the first batch, so that we never write
them out to the batch temp files.
Bryce Cutt and Ramon Lawrence, with some editorialization by me.
for each temp file, rather than once per sort or hashjoin; this allows
spreading the data of a large sort or join across multiple tablespaces.
(I remain dubious that this will make any difference in practice, but certain
people insisted.) Arrange to cache the results of parsing the GUC variable
instead of recomputing from scratch on every demand, and push usage of the
cache down to the bottommost fd.c level.
tablespace(s) in which to store temp tables and temporary files. This is a
list to allow spreading the load across multiple tablespaces (a random list
element is chosen each time a temp object is to be created). Temp files are
not stored in per-database pgsql_tmp/ directories anymore, but per-tablespace
directories.
Jaime Casanova and Albert Cervera, with review by Bernd Helmle and Tom Lane.
selecting power-of-2, rather than prime, numbers of buckets in hash joins.
If the hash functions are doing their jobs properly by making all hash bits
equally random, this is good enough, and it saves expensive integer division
and modulus operations.
Hashing for aggregation purposes still needs work, so it's not time to
mark any cross-type operators as hashable for general use, but these cases
work if the operators are so marked by hand in the system catalogs.
match because they contain a null join key (and the join operator is
known strict). Improves performance significantly when the inner
relation contains a lot of nulls, as per bug #2930.
any use in the past many years, we'd have made some effort to include
them in all executor node types; but in fact they were only in
nodeAppend.c and nodeIndexscan.c, up until I copied nodeIndexscan.c's
occurrence into the new bitmap node types. Remove some other unused
macros in execdebug.h, too. Some day the whole header probably ought to
go away in favor of better-designed facilities.
bits indicating which optional capabilities can actually be exercised
at runtime. This will allow Sort and Material nodes, and perhaps later
other nodes, to avoid unnecessary overhead in common cases.
This commit just adds the infrastructure and arranges to pass the correct
flag values down to plan nodes; none of the actual optimizations are here
yet. I'm committing this separately in case anyone wants to measure the
added overhead. (It should be negligible.)
Simon Riggs and Tom Lane
generate their output tuple descriptors from their target lists (ie, using
ExecAssignResultTypeFromTL()). We long ago fixed things so that all node
types have minimally valid tlists, so there's no longer any good reason to
have two different ways of doing it. This change is needed to fix bug
reported by Hayden James: the fix of 2005-11-03 to emit the correct column
names after optimizing away a SubqueryScan node didn't work if the new
top-level plan node used ExecAssignResultTypeFromOuterPlan to generate its
tupdesc, since the next plan node down won't have the correct column labels.
comment line where output as too long, and update typedefs for /lib
directory. Also fix case where identifiers were used as variable names
in the backend, but as typedefs in ecpg (favor the backend for
indenting).
Backpatch to 8.1.X.
outer relation is empty did not work, per test case from Patrick Welche.
It tried to use nodeHashjoin.c's high-level mechanisms for fetching an
outer-relation tuple, but that code expected the hash table to be filled
already. As patched, the code failed in corner cases such as having no
outer-relation tuples for the first hash batch. Revert and rewrite.
work if either of the join relations are empty. The logic is:
(1) if the inner relation's startup cost is less than the outer
relation's startup cost and this is not an outer join, read
a single tuple from the inner relation via ExecHash()
- if NULL, we're done
(2) read a single tuple from the outer relation
- if NULL, we're done
(3) build the hash table on the inner relation
- if hash table is empty and this is not an outer join,
we're done
(4) otherwise, do hash join as usual
The implementation uses the new MultiExecProcNode API, per a
suggestion from Tom: invoking ExecHash() now produces the first
tuple from the Hash node's child node, whereas MultiExecHash()
builds the hash table.
I had to put in a bit of a kludge to get the row count returned
for EXPLAIN ANALYZE to be correct: since ExecHash() is invoked to
return a tuple, and then MultiExecHash() is invoked, we would
return one too many tuples to EXPLAIN ANALYZE. I hacked around
this by just manually detecting this situation and subtracting 1
from the EXPLAIN ANALYZE row count.
return just a single tuple at a time. Currently the only such node
type is Hash, but I expect we will soon have indexscans that can return
tuple bitmaps. A side benefit is that EXPLAIN ANALYZE now shows the
correct tuple count for a Hash node.
old comment in the code claimed that this was necessary. Since it is not
actually necessary any more, it is clearer to remove the comment and
just return NULL instead -- the return value of ExecHash() is not used.
of tuples when passing data up through multiple plan nodes. A slot can now
hold either a normal "physical" HeapTuple, or a "virtual" tuple consisting
of Datum/isnull arrays. Upper plan levels can usually just copy the Datum
arrays, avoiding heap_formtuple() and possible subsequent nocachegetattr()
calls to extract the data again. This work extends Atsushi Ogawa's earlier
patch, which provided the key idea of adding Datum arrays to TupleTableSlots.
(I believe however that something like this was foreseen way back in Berkeley
days --- see the old comment on ExecProject.) A test case involving many
levels of join of fairly wide tables (about 80 columns altogether) showed
about 3x overall speedup, though simple queries will probably not be
helped very much.
I have also duplicated some code in heaptuple.c in order to provide versions
of heap_formtuple and friends that use "bool" arrays to indicate null
attributes, instead of the old convention of "char" arrays containing either
'n' or ' '. This provides a better match to the convention used by
ExecEvalExpr. While I have not made a concerted effort to get rid of uses
of the old routines, I think they should be deprecated and eventually removed.
on-the-fly, and thereby avoid blowing out memory when the planner has
underestimated the hash table size. Hash join will now obey the
work_mem limit with some faithfulness. Per my recent proposal
(hash aggregate part isn't done yet though).
Bruce Momjian
Tom Lane
Magnus Hagander
Robert Haas
Neil Conway