91e9e89dc modified nodeSort.c so that it used datum sorts when the
targetlist of the outer node contained only a single column. That commit
failed to recognise that the Datum returned by tuplesort_getdatum() must
be pfree'd when the type is a byref type. Ronan Dunklau did originally
propose the patch with that restriction, but that, probably through my own
fault, got lost during further development work.
Due to the timing of this report (PG15 RC1 is almost out the door), let's
just restrict the datum sort optimization to apply for byval types only.
We might want to look harder into making this work for byref types in
PG16.
Reported-by: Önder Kalacı
Diagnosis-by: Tom Lane
Discussion: https://postgr.es/m/CACawEhVxe0ufR26UcqtU7GYGRuubq3p6ZWPGXL4cxy_uexpAAQ@mail.gmail.com
Backpatch-through: 15, where 91e9e89dc was introduced.
The general usage pattern when we store tuples in tuplesort.c is that
we store a series of tuples one by one then either perform a sort or spill
them to disk. In the common case, there is no pfreeing of already stored
tuples. For the common case since we do not individually pfree tuples, we
have very little need for aset.c memory allocation behavior which
maintains freelists and always rounds allocation sizes up to the next
power of 2 size.
Here we conditionally use generation.c contexts for storing tuples in
tuplesort.c when the sort will never be bounded. Unfortunately, the
memory context to store tuples is already created by the time any calls
would be made to tuplesort_set_bound(), so here we add a new sort option
that allows callers to specify if they're going to need a bounded sort or
not. We'll use a standard aset.c allocator when this sort option is not
set.
Extension authors must ensure that the TUPLESORT_ALLOWBOUNDED flag is
used when calling tuplesort_begin_* for any sorts that make a call to
tuplesort_set_bound().
Author: David Rowley
Reviewed-by: Andy Fan
Discussion: https://postgr.es/m/CAApHDvoH4ASzsAOyHcxkuY01Qf++8JJ0paw+03dk+W25tQEcNQ@mail.gmail.com
This replaces the bool flag for randomAccess. An upcoming patch requires
adding another option, so instead of breaking the API for that, then
breaking it again one day if we add more options, let's just break it
once. Any boolean options we add in the future will just make use of an
unused bit in the flags.
Any extensions making use of tuplesorts will need to update their code
to pass TUPLESORT_RANDOMACCESS instead of true for randomAccess.
TUPLESORT_NONE can be used for a set of empty options.
Author: David Rowley
Reviewed-by: Justin Pryzby
Discussion: https://postgr.es/m/CAApHDvoH4ASzsAOyHcxkuY01Qf%2B%2B8JJ0paw%2B03dk%2BW25tQEcNQ%40mail.gmail.com
Datum sorts can be significantly faster than tuple sorts, especially when
the data type being sorted is a pass-by-value type. Something in the
region of 50-70% performance improvements appear to be possible.
Just in case there's any confusion; the Datum sort is only used when the
targetlist of the Sort node contains a single column, not when there's a
single column in the sort key and multiple items in the target list.
Author: Ronan Dunklau
Reviewed-by: James Coleman, David Rowley, Ranier Vilela, Hou Zhijie
Tested-by: John Naylor
Discussion: https://postgr.es/m/3177670.itZtoPt7T5@aivenronan
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
Upcoming work intends to allow pluggable ways to introduce new ways of
storing table data. Accessing those table access methods from the
executor requires TupleTableSlots to be carry tuples in the native
format of such storage methods; otherwise there'll be a significant
conversion overhead.
Different access methods will require different data to store tuples
efficiently (just like virtual, minimal, heap already require fields
in TupleTableSlot). To allow that without requiring additional pointer
indirections, we want to have different structs (embedding
TupleTableSlot) for different types of slots. Thus different types of
slots are needed, which requires adapting creators of slots.
The slot that most efficiently can represent a type of tuple in an
executor node will often depend on the type of slot a child node
uses. Therefore we need to track the type of slot is returned by
nodes, so parent slots can create slots based on that.
Relatedly, JIT compilation of tuple deforming needs to know which type
of slot a certain expression refers to, so it can create an
appropriate deforming function for the type of tuple in the slot.
But not all nodes will only return one type of slot, e.g. an append
node will potentially return different types of slots for each of its
subplans.
Therefore add function that allows to query the type of a node's
result slot, and whether it'll always be the same type (whether it's
fixed). This can be queried using ExecGetResultSlotOps().
The scan, result, inner, outer type of slots are automatically
inferred from ExecInitScanTupleSlot(), ExecInitResultSlot(),
left/right subtrees respectively. If that's not correct for a node,
that can be overwritten using new fields in PlanState.
This commit does not introduce the actually abstracted implementation
of different kind of TupleTableSlots, that will be left for a followup
commit. The different types of slots introduced will, for now, still
use the same backing implementation.
While this already partially invalidates the big comment in
tuptable.h, it seems to make more sense to update it later, when the
different TupleTableSlot implementations actually exist.
Author: Ashutosh Bapat and Andres Freund, with changes by Amit Khandekar
Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
In a lot of nodes the return slot is not required. That can either be
because the node doesn't do any projection (say an Append node), or
because the node does perform projections but the projection is
optimized away because the projection would yield an identical row.
Slots aren't that small, especially for wide rows, so it's worthwhile
to avoid creating them. It's not possible to just skip creating the
slot - it's currently used to determine the tuple descriptor returned
by ExecGetResultType(). So separate the determination of the result
type from the slot creation. The work previously done internally
ExecInitResultTupleSlotTL() can now also be done separately with
ExecInitResultTypeTL() and ExecInitResultSlot(). That way nodes that
aren't guaranteed to need a result slot, can use
ExecInitResultTypeTL() to determine the result type of the node, and
ExecAssignScanProjectionInfo() (via
ExecConditionalAssignProjectionInfo()) determines that a result slot
is needed, it is created with ExecInitResultSlot().
Besides the advantage of avoiding to create slots that then are
unused, this is necessary preparation for later patches around tuple
table slot abstraction. In particular separating the return descriptor
and slot is a prerequisite to allow JITing of tuple deforming with
knowledge of the underlying tuple format, and to avoid unnecessarily
creating JITed tuple deforming for virtual slots.
This commit removes a redundant argument from
ExecInitResultTupleSlotTL(). While this commit touches a lot of the
relevant lines anyway, it'd normally still not worthwhile to cause
breakage, except that aforementioned later commits will touch *all*
ExecInitResultTupleSlotTL() callers anyway (but fits worse
thematically).
Author: Andres Freund
Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
The reason for doing so is that it will allow expression evaluation to
optimize based on the underlying tupledesc. In particular it will
allow to JIT tuple deforming together with the expression itself.
For that expression initialization needs to be moved after the
relevant slots are initialized - mostly unproblematic, except in the
case of nodeWorktablescan.c.
After doing so there's no need for ExecAssignResultType() and
ExecAssignResultTypeFromTL() anymore, as all former callers have been
converted to create a slot with a fixed descriptor.
When creating a slot with a fixed descriptor, tts_values/isnull can be
allocated together with the main slot, reducing allocation overhead
and increasing cache density a bit.
Author: Andres Freund
Discussion: https://postgr.es/m/20171206093717.vqdxe5icqttpxs3p@alap3.anarazel.de
To make this work, tuplesort.c and logtape.c must also support
parallelism, so this patch adds that infrastructure and then applies
it to the particular case of parallel btree index builds. Testing
to date shows that this can often be 2-3x faster than a serial
index build.
The model for deciding how many workers to use is fairly primitive
at present, but it's better than not having the feature. We can
refine it as we get more experience.
Peter Geoghegan with some help from Rushabh Lathia. While Heikki
Linnakangas is not an author of this patch, he wrote other patches
without which this feature would not have been possible, and
therefore the release notes should possibly credit him as an author
of this feature. Reviewed by Claudio Freire, Heikki Linnakangas,
Thomas Munro, Tels, Amit Kapila, me.
Discussion: http://postgr.es/m/CAM3SWZQKM=Pzc=CAHzRixKjp2eO5Q0Jg1SoFQqeXFQ647JiwqQ@mail.gmail.com
Discussion: http://postgr.es/m/CAH2-Wz=AxWqDoVvGU7dq856S4r6sJAj6DBn7VMtigkB33N5eyg@mail.gmail.com
When a Gather or Gather Merge node is started and stopped multiple
times, accumulate instrumentation data only once, at the end, instead
of after each execution, to avoid recording inflated totals.
Commit 778e78ae9f, the previous attempt
at a fix, instead reset the state after every execution, which worked
for the general instrumentation data but had problems for the additional
instrumentation specific to Sort and Hash nodes.
Report by hubert depesz lubaczewski. Analysis and fix by Amit Kapila,
following a design proposal from Thomas Munro, with a comment tweak
by me.
Discussion: http://postgr.es/m/20171127175631.GA405@depesz.com
Previously, executor nodes running in parallel worker processes didn't
have access to the dsm_segment object used for parallel execution. In
order to support resource management based on DSM segment lifetime,
they need that. So create a ParallelWorkerContext object to hold it
and pass it to all InitializeWorker functions.
Author: Thomas Munro
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/CAEepm=2W=cOkiZxcg6qiFQP-dHUe09aqTrEMM7yJDrHMhDv_RA@mail.gmail.com
Previously, the parallel executor logic did reinitialization of shared
state within the ExecReScan code for parallel-aware scan nodes. This is
problematic, because it means that the ExecReScan call has to occur
synchronously (ie, during the parent Gather node's ReScan call). That is
swimming very much against the tide so far as the ExecReScan machinery is
concerned; the fact that it works at all today depends on a lot of fragile
assumptions, such as that no plan node between Gather and a parallel-aware
scan node is parameterized. Another objection is that because ExecReScan
might be called in workers as well as the leader, hacky extra tests are
needed in some places to prevent unwanted shared-state resets.
Hence, let's separate this code into two functions, a ReInitializeDSM
call and the ReScan call proper. ReInitializeDSM is called only in
the leader and is guaranteed to run before we start new workers.
ReScan is returned to its traditional function of resetting only local
state, which means that ExecReScan's usual habits of delaying or
eliminating child rescan calls are safe again.
As with the preceding commit 7df2c1f8d, it doesn't seem to be necessary
to make these changes in 9.6, which is a good thing because the FDW and
CustomScan APIs are impacted.
Discussion: https://postgr.es/m/CAA4eK1JkByysFJNh9M349u_nNjqETuEnY_y1VUc_kJiU0bxtaQ@mail.gmail.com
Up until now, when parallel query was used, no details about the
sort method or space used by the workers were available; details
were shown only for any sorting done by the leader. Fix that.
Commit 1177ab1dab forced the test case
added by commit 1f6d515a67 to run
without parallelism; now that we have this infrastructure, allow
that again, with a little tweaking to make it pass with and without
force_parallel_mode.
Robert Haas and Tom Lane
Discussion: http://postgr.es/m/CA+Tgmoa2VBZW6S8AAXfhpHczb=Rf6RqQ2br+zJvEgwJ0uoD_tQ@mail.gmail.com
This allows us to add stack-depth checks the first time an executor
node is called, and skip that overhead on following
calls. Additionally it yields a nice speedup.
While it'd probably have been a good idea to have that check all
along, it has become more important after the new expression
evaluation framework in b8d7f053c5 - there's no stack depth
check in common paths anymore now. We previously relied on
ExecEvalExpr() being executed somewhere.
We should move towards that model for further routines, but as this is
required for v10, it seems better to only do the necessary (which
already is quite large).
Author: Andres Freund, Tom Lane
Reported-By: Julien Rouhaud
Discussion:
https://postgr.es/m/22833.1490390175@sss.pgh.pa.ushttps://postgr.es/m/b0af9eaa-130c-60d0-9e4e-7a135b1e0c76@dalibo.com
In a followup commit ExecProcNode(), and especially the large switch
it contains, will largely be replaced by a function pointer directly
to the correct node. The node functions will then get invoked by a
thin inline function wrapper. To avoid having to include miscadmin.h
in headers - CHECK_FOR_INTERRUPTS() - move the interrupt checks into
the individual executor routines.
While looking through all executor nodes, I noticed a number of
arguably missing interrupt checks, add these too.
Author: Andres Freund, Tom Lane
Reviewed-By: Tom Lane
Discussion:
https://postgr.es/m/22833.1490390175@sss.pgh.pa.us
Add a "copy" argument to make it optional to receive a copy of caller
tuple that is safe to use following a subsequent manipulating of
tuplesort's state. This is a performance optimization. Most existing
tuplesort_gettupleslot() callers are made to opt out of copying.
Existing callers that happen to rely on the validity of tuple memory
beyond subsequent manipulations of the tuplesort request their own
copy.
This brings tuplesort_gettupleslot() in line with
tuplestore_gettupleslot(). In the future, a "copy"
tuplesort_getdatum() argument may be added, that similarly allows
callers to opt out of receiving their own copy of tuple.
In passing, clarify assumptions that callers of other tuplesort fetch
routines may make about tuple memory validity, per gripe from Tom
Lane.
Author: Peter Geoghegan
Discussion: CAM3SWZQWZZ_N=DmmL7tKy_OUjGH_5mN=N=A6h7kHyyDvEhg2DA@mail.gmail.com
When processing ordered aggregates following a sort that could make use
of the abbreviated key optimization, only call the equality operator to
compare successive pairs of tuples when their abbreviated keys were not
equal.
Peter Geoghegan, reviewd by Andreas Karlsson and by me.
This makes the executor code more consistent. It also removes
an apparently superfluous NULL test in nodeGroup.c.
Qingqing Zhou, reviewed by Tom Lane, and further revised by me.
This adds collation support for columns and domains, a COLLATE clause
to override it per expression, and B-tree index support.
Peter Eisentraut
reviewed by Pavel Stehule, Itagaki Takahiro, Robert Haas, Noah Misch
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.
need be returned. We keep a heap of the current best N tuples and sift-up
new tuples into it as we scan the input. For M input tuples this means
only about M*log(N) comparisons instead of M*log(M), not to mention a lot
less workspace when N is small --- avoiding spill-to-disk for large M
is actually the most attractive thing about it. Patch includes planner
and executor support for invoking this facility in ORDER BY ... LIMIT
queries. Greg Stark, with some editorialization by moi.
per-column options for btree indexes. The planner's support for this is still
pretty rudimentary; it does not yet know how to plan mergejoins with
nondefault ordering options. The documentation is pretty rudimentary, too.
I'll work on improving that stuff later.
Note incompatible change from prior behavior: ORDER BY ... USING will now be
rejected if the operator is not a less-than or greater-than member of some
btree opclass. This prevents less-than-sane behavior if an operator that
doesn't actually define a proper sort ordering is selected.
per-tuple space overhead for sorts in memory. I chose to replace the
previous patch that tried to write out the bare minimum amount of data
when sorting on disk; instead, just dump the MinimalTuples as-is. This
wastes 3 to 10 bytes per tuple depending on architecture and null-bitmap
length, but the simplification in the writetup/readtup routines seems
worth it.
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
each tuple, as per my proposal of several days ago. Also, clean up
sort memory management by keeping all working data in a separate memory
context, and refine the handling of low-memory conditions.
David Rowley