Previously materializing a slot always returned a HeapTuple. As
current work aims to reduce the reliance on HeapTuples (so other
storage systems can work efficiently), that needs to change. Thus
split the tasks of materializing a slot (i.e. making it independent
from the underlying storage / other memory contexts) from fetching a
HeapTuple from the slot. For brevity, allow to fetch a HeapTuple from
a slot and materializing the slot at the same time, controlled by a
parameter.
For now some callers of ExecFetchSlotHeapTuple, with materialize =
true, expect that changes to the heap tuple will be reflected in the
underlying slot. Those places will be adapted in due course, so while
not pretty, that's OK for now.
Also rename ExecFetchSlotTuple to ExecFetchSlotHeapTupleDatum and
ExecFetchSlotTupleDatum to ExecFetchSlotHeapTupleDatum, as it's likely
that future storage methods will need similar methods. There already
is ExecFetchSlotMinimalTuple, so the new names make the naming scheme
more coherent.
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
This mainly de-duplicates code. As evaluating a system variable isn't
the hottest path and the current inline implementation ends up calling
out to an external function anyway, this is OK from a performance POV.
The main motivation for de-duplicating is the upcoming slot
abstraction work, after which there's not guaranteed to be a HeapTuple
backing the slot.
Author: Andres Freund, Amit Khandekar
Discussion: https://postgr.es/m/20181105210039.hh4vvi4vwoq5ba2q@alap3.anarazel.de
There's several reasons for this change:
1) It reduces the total size of TupleTableSlot / reduces alignment
padding, making the commonly accessed members fit into a single
cacheline (but we currently do not force proper alignment, so
that's not yet guaranteed to be helpful)
2) Combining the booleans into a flag allows to combine read/writes
from memory.
3) With the upcoming slot abstraction changes, it allows to have core
and extended flags, in a memory efficient way.
Author: Ashutosh Bapat and Andres Freund
Discussion: https://postgr.es/m/20180220224318.gw4oe5jadhpmcdnm@alap3.anarazel.de
heaptuple.c was never a particular good fit for slot_getattr(),
slot_getsomeattrs() and slot_getmissingattrs(), but in upcoming
changes slots will be made more abstract (allowing slots that contain
different types of tuples), making it clearly the wrong place.
Note that slot_deform_tuple() remains in it's current place, as it
clearly deals with a HeapTuple. getmissingattrs() also remains, but
it's less clear that that's correct - but execTuples.c wouldn't be the
right place.
Author: Ashutosh Bapat.
Discussion: https://postgr.es/m/20180220224318.gw4oe5jadhpmcdnm@alap3.anarazel.de
We already have appropriate locks on every relation listed in the
query's rangetable before we reach the executor. Take the next step
in exploiting that knowledge by removing code that worries about
taking locks on non-leaf result relations in a partitioned table.
In particular, get rid of ExecLockNonLeafAppendTables and a stanza in
InitPlan that asserts we already have locks on certain such tables.
In passing, clean up some now-obsolete comments in InitPlan.
Amit Langote, reviewed by David Rowley and Jesper Pedersen,
and whacked around a bit more by me
Discussion: https://postgr.es/m/468c85d9-540e-66a2-1dde-fec2b741e688@lab.ntt.co.jp
Instead of doing a lot of list_nth() accesses to es_range_table,
create a flattened pointer array during executor startup and index
into that to get at individual RangeTblEntrys.
This eliminates one source of O(N^2) behavior with lots of partitions.
(I'm not exactly convinced that it's the most important source, but
it's an easy one to fix.)
Amit Langote and David Rowley
Discussion: https://postgr.es/m/468c85d9-540e-66a2-1dde-fec2b741e688@lab.ntt.co.jp
Create an array estate->es_relations[] paralleling the es_range_table,
and store references to Relations (relcache entries) there, so that any
given RT entry is opened and closed just once per executor run. Scan
nodes typically still call ExecOpenScanRelation, but ExecCloseScanRelation
is no more; relation closing is now done centrally in ExecEndPlan.
This is slightly more complex than one would expect because of the
interactions with relcache references held in ResultRelInfo nodes.
The general convention is now that ResultRelInfo->ri_RelationDesc does
not represent a separate relcache reference and so does not need to be
explicitly closed; but there is an exception for ResultRelInfos in the
es_trig_target_relations list, which are manufactured by
ExecGetTriggerResultRel and have to be cleaned up by
ExecCleanUpTriggerState. (That much was true all along, but these
ResultRelInfos are now more different from others than they used to be.)
To allow the partition pruning logic to make use of es_relations[] rather
than having its own relcache references, adjust PartitionedRelPruneInfo
to store an RT index rather than a relation OID.
Amit Langote, reviewed by David Rowley and Jesper Pedersen,
some mods by me
Discussion: https://postgr.es/m/468c85d9-540e-66a2-1dde-fec2b741e688@lab.ntt.co.jp
It's inefficient to use a single slot for mapping between tuple
descriptors for multiple tuples, as previously done when using
ConvertPartitionTupleSlot(), as that means the slot's tuple descriptors
change for every tuple.
Previously we also, via ConvertPartitionTupleSlot(), built new tuples
after the mapping even in cases where we, immediately afterwards,
access individual columns again.
Refactor the code so one slot, on demand, is used for each
partition. That avoids having to change the descriptor (and allows to
use the more efficient "fixed" tuple slots). Then use slot->slot
mapping, to avoid unnecessarily forming a tuple.
As the naming between the tuple and slot mapping functions wasn't
consistent, rename them to execute_attr_map_{tuple,slot}. It's likely
that we'll also rename convert_tuples_by_* to denote that these
functions "only" build a map, but that's left for later.
Author: Amit Khandekar and Amit Langote, editorialized by me
Reviewed-By: Amit Langote, Amit Khandekar, Andres Freund
Discussion:
https://postgr.es/m/CAJ3gD9fR0wRNeAE8VqffNTyONS_UfFPRpqxhnD9Q42vZB+Jvpg@mail.gmail.comhttps://postgr.es/m/e4f9d743-cd4b-efb0-7574-da21d86a7f36%40lab.ntt.co.jp
Backpatch: -
Upcoming changes introduce further types of tuple table slots, in
preparation of making table storage pluggable. New storage methods
will have different representation of tuples, therefore the slot
accessor should refer explicitly to heap tuples.
Instead of just renaming the functions, split it into one function
that accepts heap tuples not residing in buffers, and one accepting
ones in buffers. Previously one function was used for both, but that
was a bit awkward already, and splitting will allow us to represent
slot types for tuples in buffers and normal memory separately.
This is split out from the patch introducing abstract slots, as this
largely consists out of mechanical changes.
Author: Ashutosh Bapat
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/20180220224318.gw4oe5jadhpmcdnm@alap3.anarazel.de
Previously it was an int / 4 bytes. The maximum number of attributes
in a tuple is restricted by the maximum value Var->varattno, which is
an AttrNumber/int16. Hence use the same data type for
TupleTableSlot->tts_nvalid.
Author: Ashutosh Bapat
Discussion: https://postgr.es/m/20180220224318.gw4oe5jadhpmcdnm@alap3.anarazel.de
Previously, when using parallel query, EXPLAIN (ANALYZE)'s JIT
compilation timings did not include the overhead from doing so on the
workers. Fix that.
We do so by simply aggregating the cost of doing JIT compilation on
workers and the leader together. Arguably that's not quite accurate,
because the total time spend doing so is spent in parallel - but it's
hard to do much better. For additional detail, when VERBOSE is
specified, the stats for workers are displayed separately.
Author: Amit Khandekar and Andres Freund
Discussion: https://postgr.es/m/CAJ3gD9eLrz51RK_gTkod+71iDcjpB_N8eC6vU2AW-VicsAERpQ@mail.gmail.com
Backpatch: 11-
The EvalPlanQual machinery assumes that any initplans (that is,
uncorrelated sub-selects) used during an EPQ recheck would have already
been evaluated during the main query; this is implicit in the fact that
execPlan pointers are not copied into the EPQ estate's es_param_exec_vals.
But it's possible for that assumption to fail, if the initplan is only
reached conditionally. For example, a sub-select inside a CASE expression
could be reached during a recheck when it had not been previously, if the
CASE test depends on a column that was just updated.
This bug is old, appearing to date back to my rewrite of EvalPlanQual in
commit 9f2ee8f28, but was not detected until Kyle Samson reported a case.
To fix, force all not-yet-evaluated initplans used within the EPQ plan
subtree to be evaluated at the start of the recheck, before entering the
EPQ environment. This could be inefficient, if such an initplan is
expensive and goes unused again during the recheck --- but that's piling
one layer of improbability atop another. It doesn't seem worth adding
more complexity to prevent that, at least not in the back branches.
It was convenient to use the new-in-v11 ExecEvalParamExecParams function
to implement this, but I didn't like either its name or the specifics of
its API, so revise that.
Back-patch all the way. Rather than rewrite the patch to avoid depending
on bms_next_member() in the oldest branches, I chose to back-patch that
function into 9.4 and 9.3. (This isn't the first time back-patches have
needed that, and it exhausted my patience.) I also chose to back-patch
some test cases added by commits 71404af2a and 342a1ffa2 into 9.4 and 9.3,
so that the 9.x versions of eval-plan-qual.spec are all the same.
Andrew Gierth diagnosed the problem and contributed the added test cases,
though the actual code changes are by me.
Discussion: https://postgr.es/m/A033A40A-B234-4324-BE37-272279F7B627@tripadvisor.com
For some reason pg_waldump is including tuptable.h, and the recent
addition of a static inline function to it is causing problems on
older buildfarm members that fail to optimize such functions away
completely. I wonder if this situation doesn't mean that some header
refactoring is called for ... but as a band-aid, wrap the static
function in "#ifndef FRONTEND".
Discussion: https://postgr.es/m/20180824154237.mabsv6fsz5q37bma@alap3.anarazel.de
This patch removes two sources of interference between nominally
independent functions when one SPI-using function calls another,
perhaps without knowing that it does so.
Chapman Flack pointed out that xml.c's query_to_xml_internal() expects
SPI_tuptable and SPI_processed to stay valid across datatype output
function calls; but it's possible that such a call could involve
re-entrant use of SPI. It seems likely that there are similar hazards
elsewhere, if not in the core code then in third-party SPI users.
Previously SPI_finish() reset SPI's API globals to zeroes/nulls, which
would typically make for a crash in such a situation. Restoring them
to the values they had at SPI_connect() seems like a considerably more
useful behavior, and it still meets the design goal of not leaving any
dangling pointers to tuple tables of the function being exited.
Also, cause SPI_connect() to reset these variables to zeroes/nulls after
saving them. This prevents interference in the opposite direction: it's
possible that a SPI-using function that's only ever been tested standalone
contains assumptions that these variables start out as zeroes. That was
the case as long as you were the outermost SPI user, but not so much for
an inner user. Now it's consistent.
Report and fix suggestion by Chapman Flack, actual patch by me.
Back-patch to all supported branches.
Discussion: https://postgr.es/m/9fa25bef-2e4f-1c32-22a4-3ad0723c4a17@anastigmatix.net
Code in slot_getallattrs() is the same as if slot_getsomeattrs() is
called with number of attributes specified in the tuple
descriptor. Implement it that way instead of duplicating the code
between those two functions.
This is part of a patchseries abstracting TupleTableSlots so they can
store arbitrary forms of tuples, but is a nice enough cleanup on its
own.
Author: Ashutosh Bapat
Reviewed-By: Andres Freund
Discussion: https://postgr.es/m/20180220224318.gw4oe5jadhpmcdnm@alap3.anarazel.de
The previous coding here supposed that if run-time partitioning applied to
a particular Append/MergeAppend plan, then all child plans of that node
must be members of a single partitioning hierarchy. This is totally wrong,
since an Append could be formed from a UNION ALL: we could have multiple
hierarchies sharing the same Append, or child plans that aren't part of any
hierarchy.
To fix, restructure the related plan-time and execution-time data
structures so that we can have a separate list or array for each
partitioning hierarchy. Also track subplans that are not part of any
hierarchy, and make sure they don't get pruned.
Per reports from Phil Florent and others. Back-patch to v11, since
the bug originated there.
David Rowley, with a lot of cosmetic adjustments by me; thanks also
to Amit Langote for review.
Discussion: https://postgr.es/m/HE1PR03MB17068BB27404C90B5B788BCABA7B0@HE1PR03MB1706.eurprd03.prod.outlook.com
CopyFrom allows multi-inserts to be used for non-partitioned tables, but
this was disabled for partitioned tables. The reason for this appeared
to be that the tuple may not belong to the same partition as the
previous tuple did. Not allowing multi-inserts here greatly slowed down
imports into partitioned tables. These could take twice as long as a
copy to an equivalent non-partitioned table. It seems wise to do
something about this, so this change allows the multi-inserts by
flushing the so-far inserted tuples to the partition when the next tuple
does not belong to the same partition, or when the buffer fills. This
improves performance when the next tuple in the stream commonly belongs
to the same partition as the previous tuple.
In cases where the target partition changes on every tuple, using
multi-inserts slightly slows the performance. To get around this we
track the average size of the batches that have been inserted and
adaptively enable or disable multi-inserts based on the size of the
batch. Some testing was done and the regression only seems to exist
when the average size of the insert batch is close to 1, so let's just
enable multi-inserts when the average size is at least 1.3. More
performance testing might reveal a better number for, this, but since
the slowdown was only 1-2% it does not seem critical enough to spend too
much time calculating it. In any case it may depend on other factors
rather than just the size of the batch.
Allowing multi-inserts for partitions required a bit of work around the
per-tuple memory contexts as we must flush the tuples when the next
tuple does not belong the same partition. In which case there is no
good time to reset the per-tuple context, as we've already built the new
tuple by this time. In order to work around this we maintain two
per-tuple contexts and just switch between them every time the partition
changes and reset the old one. This does mean that the first of each
batch of tuples is not allocated in the same memory context as the
others, but that does not matter since we only reset the context once
the previous batch has been inserted.
Author: David Rowley <david.rowley@2ndquadrant.com>
Reviewed-by: Melanie Plageman <melanieplageman@gmail.com>
The previous coding saved pointers into the partitioned table's relcache
entry, but then closed the relcache entry, causing those pointers to
nominally become dangling. Actual trouble would be seen in the field
only if a relcache flush occurred mid-query, but that's hardly out of
the question.
While we could fix this by copying all the data in question at query
start, it seems better to just hold the relcache entry open for the
whole query.
While at it, improve the handling of support-function lookups: do that
once per query not once per pruning test. There's still something to be
desired here, in that we fail to exploit the possibility of caching data
across queries in the fn_extra fields of the relcache's FmgrInfo structs,
which could happen if we just used those structs in-place rather than
copying them. However, combining that with the possibility of per-query
lookups of cross-type comparison functions seems to require changes in the
APIs of a lot of the pruning support functions, so it's too invasive to
consider as part of this patch. A win would ensue only for complex
partition key data types (e.g. arrays), so it may not be worth the
trouble.
David Rowley and Tom Lane
Discussion: https://postgr.es/m/17850.1528755844@sss.pgh.pa.us
Starting with commit f0e44751d7, ExecConstraints was in charge of
running the partition constraint; commit 19c47e7c82 modified that so
that caller could request to skip that checking depending on some
conditions, but that commit and 15ce775faa together introduced a small
bug there which caused ExecInsert to request skipping the constraint
check but have this not be honored -- in effect doing the check twice.
This could have been fixed in a very small patch, but on further
analysis of the involved function and its callsites, it turns out to be
simpler to give the responsibility of checking the partition constraint
fully to the caller, and return ExecConstraints to its original
(pre-partitioning) shape where it only checked tuple descriptor-related
constraints. Each caller must do partition constraint checking on its
own schedule, which is more convenient after commit 2f17844104 anyway.
Reported-by: David Rowley
Author: David Rowley, Álvaro Herrera
Reviewed-by: Amit Langote, Amit Khandekar, Simon Riggs
Discussion: https://postgr.es/m/CAKJS1f8w8+awsxgea8wt7_UX8qzOQ=Tm1LD+U1fHqBAkXxkW2w@mail.gmail.com
The initial coding of the run-time-pruning feature only coped with cases
where the partition key(s) are compared to Params. That is a bit silly;
we can allow it to work with any non-Var-containing stable expression, as
long as we take special care with expressions containing PARAM_EXEC Params.
The code is hardly any longer this way, and it's considerably clearer
(IMO at least). Per gripe from Pavel Stehule.
David Rowley, whacked around a bit by me
Discussion: https://postgr.es/m/CAFj8pRBjrufA3ocDm8o4LPGNye9Y+pm1b9kCwode4X04CULG3g@mail.gmail.com
Since the SPI stack has been moved from TopTransactionContext to
TopMemoryContext, setting _SPI_stack to NULL in AtEOXact_SPI() leaks
memory. In fact, we don't need to do that anymore: We just leave the
allocated stack around for the next SPI use.
Also, refactor the SPI cleanup so that it is run both at transaction end
and when returning to the main loop on an exception. The latter is
necessary when a procedure calls a COMMIT or ROLLBACK command that
itself causes an error.
This reverts commits d204ef6377,
83454e3c2b and a few more commits thereafter
(complete list at the end) related to MERGE feature.
While the feature was fully functional, with sufficient test coverage and
necessary documentation, it was felt that some parts of the executor and
parse-analyzer can use a different design and it wasn't possible to do that in
the available time. So it was decided to revert the patch for PG11 and retry
again in the future.
Thanks again to all reviewers and bug reporters.
List of commits reverted, in reverse chronological order:
f1464c5380 Improve parse representation for MERGE
ddb4158579 MERGE syntax diagram correction
530e69e59b Allow cpluspluscheck to pass by renaming variable
01b88b4df5 MERGE minor errata
3af7b2b0d4 MERGE fix variable warning in non-assert builds
a5d86181ec MERGE INSERT allows only one VALUES clause
4b2d44031f MERGE post-commit review
4923550c20 Tab completion for MERGE
aa3faa3c7a WITH support in MERGE
83454e3c2b New files for MERGE
d204ef6377 MERGE SQL Command following SQL:2016
Author: Pavan Deolasee
Reviewed-by: Michael Paquier
The HeapFetches counter was using a simple value in IndexOnlyScanState,
which fails to propagate values from parallel workers; so the counts are
wrong when IndexOnlyScan runs in parallel. Move it to Instrumentation,
like all the other counters.
While at it, change INSERT ON CONFLICT conflicting tuple counter to use
the new ntuples2 instead of nfiltered2, which is a blatant misuse.
Discussion: https://postgr.es/m/20180409215851.idwc75ct2bzi6tea@alvherre.pgsql
Existing partition pruning is only able to work at plan time, for query
quals that appear in the parsed query. This is good but limiting, as
there can be parameters that appear later that can be usefully used to
further prune partitions.
This commit adds support for pruning subnodes of Append which cannot
possibly contain any matching tuples, during execution, by evaluating
Params to determine the minimum set of subnodes that can possibly match.
We support more than just simple Params in WHERE clauses. Support
additionally includes:
1. Parameterized Nested Loop Joins: The parameter from the outer side of the
join can be used to determine the minimum set of inner side partitions to
scan.
2. Initplans: Once an initplan has been executed we can then determine which
partitions match the value from the initplan.
Partition pruning is performed in two ways. When Params external to the plan
are found to match the partition key we attempt to prune away unneeded Append
subplans during the initialization of the executor. This allows us to bypass
the initialization of non-matching subplans meaning they won't appear in the
EXPLAIN or EXPLAIN ANALYZE output.
For parameters whose value is only known during the actual execution
then the pruning of these subplans must wait. Subplans which are
eliminated during this stage of pruning are still visible in the EXPLAIN
output. In order to determine if pruning has actually taken place, the
EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never
executed due to the elimination of the partition then the execution
timing area will state "(never executed)". Whereas, if, for example in
the case of parameterized nested loops, the number of loops stated in
the EXPLAIN ANALYZE output for certain subplans may appear lower than
others due to the subplan having been scanned fewer times. This is due
to the list of matching subnodes having to be evaluated whenever a
parameter which was found to match the partition key changes.
This commit required some additional infrastructure that permits the
building of a data structure which is able to perform the translation of
the matching partition IDs, as returned by get_matching_partitions, into
the list index of a subpaths list, as exist in node types such as
Append, MergeAppend and ModifyTable. This allows us to translate a list
of clauses into a Bitmapset of all the subpath indexes which must be
included to satisfy the clause list.
Author: David Rowley, based on an earlier effort by Beena Emerson
Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi,
Jesper Pedersen
Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com
When an update moves a row between partitions (supported since
2f17844104), our normal logic for following update chains in READ
COMMITTED mode doesn't work anymore. Cross partition updates are
modeled as an delete from the old and insert into the new
partition. No ctid chain exists across partitions, and there's no
convenient space to introduce that link.
Not throwing an error in a partitioned context when one would have
been thrown without partitioning is obviously problematic. This commit
introduces infrastructure to detect when a tuple has been moved, not
just plainly deleted. That allows to throw an error when encountering
a deletion that's actually a move, while attempting to following a
ctid chain.
The row deleted as part of a cross partition update is marked by
pointing it's t_ctid to an invalid block, instead of self as a normal
update would. That was deemed to be the least invasive and most
future proof way to represent the knowledge, given how few infomask
bits are there to be recycled (there's also some locking issues with
using infomask bits).
External code following ctid chains should be updated to check for
moved tuples. The most likely consequence of not doing so is a missed
error.
Author: Amul Sul, editorialized by me
Reviewed-By: Amit Kapila, Pavan Deolasee, Andres Freund, Robert Haas
Discussion: http://postgr.es/m/CAAJ_b95PkwojoYfz0bzXU8OokcTVGzN6vYGCNVUukeUDrnF3dw@mail.gmail.com
Also enable this for postgres_fdw.
Etsuro Fujita, based on an earlier patch by Amit Langote. The larger
patch series of which this is a part has been reviewed by Amit
Langote, David Fetter, Maksim Milyutin, Álvaro Herrera, Stephen Frost,
and me. Minor documentation changes to the final version by me.
Discussion: http://postgr.es/m/29906a26-da12-8c86-4fb9-d8f88442f2b9@lab.ntt.co.jp
Review comments from Andres Freund
* Consolidate code into AfterTriggerGetTransitionTable()
* Rename nodeMerge.c to execMerge.c
* Rename nodeMerge.h to execMerge.h
* Move MERGE handling in ExecInitModifyTable()
into a execMerge.c ExecInitMerge()
* Move mt_merge_subcommands flags into execMerge.h
* Rename opt_and_condition to opt_merge_when_and_condition
* Wordsmith various comments
Author: Pavan Deolasee
Reviewer: Simon Riggs
MERGE performs actions that modify rows in the target table
using a source table or query. MERGE provides a single SQL
statement that can conditionally INSERT/UPDATE/DELETE rows
a task that would other require multiple PL statements.
e.g.
MERGE INTO target AS t
USING source AS s
ON t.tid = s.sid
WHEN MATCHED AND t.balance > s.delta THEN
UPDATE SET balance = t.balance - s.delta
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED AND s.delta > 0 THEN
INSERT VALUES (s.sid, s.delta)
WHEN NOT MATCHED THEN
DO NOTHING;
MERGE works with regular and partitioned tables, including
column and row security enforcement, as well as support for
row, statement and transition triggers.
MERGE is optimized for OLTP and is parameterizable, though
also useful for large scale ETL/ELT. MERGE is not intended
to be used in preference to existing single SQL commands
for INSERT, UPDATE or DELETE since there is some overhead.
MERGE can be used statically from PL/pgSQL.
MERGE does not yet support inheritance, write rules,
RETURNING clauses, updatable views or foreign tables.
MERGE follows SQL Standard per the most recent SQL:2016.
Includes full tests and documentation, including full
isolation tests to demonstrate the concurrent behavior.
This version written from scratch in 2017 by Simon Riggs,
using docs and tests originally written in 2009. Later work
from Pavan Deolasee has been both complex and deep, leaving
the lead author credit now in his hands.
Extensive discussion of concurrency from Peter Geoghegan,
with thanks for the time and effort contributed.
Various issues reported via sqlsmith by Andreas Seltenreich
Authors: Pavan Deolasee, Simon Riggs
Reviewer: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs
Discussion:
https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.comhttps://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
MERGE performs actions that modify rows in the target table
using a source table or query. MERGE provides a single SQL
statement that can conditionally INSERT/UPDATE/DELETE rows
a task that would other require multiple PL statements.
e.g.
MERGE INTO target AS t
USING source AS s
ON t.tid = s.sid
WHEN MATCHED AND t.balance > s.delta THEN
UPDATE SET balance = t.balance - s.delta
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED AND s.delta > 0 THEN
INSERT VALUES (s.sid, s.delta)
WHEN NOT MATCHED THEN
DO NOTHING;
MERGE works with regular and partitioned tables, including
column and row security enforcement, as well as support for
row, statement and transition triggers.
MERGE is optimized for OLTP and is parameterizable, though
also useful for large scale ETL/ELT. MERGE is not intended
to be used in preference to existing single SQL commands
for INSERT, UPDATE or DELETE since there is some overhead.
MERGE can be used statically from PL/pgSQL.
MERGE does not yet support inheritance, write rules,
RETURNING clauses, updatable views or foreign tables.
MERGE follows SQL Standard per the most recent SQL:2016.
Includes full tests and documentation, including full
isolation tests to demonstrate the concurrent behavior.
This version written from scratch in 2017 by Simon Riggs,
using docs and tests originally written in 2009. Later work
from Pavan Deolasee has been both complex and deep, leaving
the lead author credit now in his hands.
Extensive discussion of concurrency from Peter Geoghegan,
with thanks for the time and effort contributed.
Various issues reported via sqlsmith by Andreas Seltenreich
Authors: Pavan Deolasee, Simon Riggs
Reviewers: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs
Discussion:
https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.comhttps://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
So far, a nested CALL or DO in PL/pgSQL would not establish a context
where transaction control statements were allowed. This fixes that by
handling CALL and DO specially in PL/pgSQL, passing the atomic/nonatomic
execution context through and doing the required management around
transaction boundaries.
Reviewed-by: Tomas Vondra <tomas.vondra@2ndquadrant.com>
Instead using memset to set tts_isnull, call the new
slot_getmissingattrs().
Also fix a bug (= instead of >=) in the code generation. Normally = is
correct, but when repeatedly deforming fields not in a
tuple (e.g. deform up to natts + 1 and then natts + 2) >= is needed.
Discussion: https://postgr.es/m/20180328010053.i2qvsuuusst4lgmc@alap3.anarazel.de
Performing JIT compilation for deforming gains performance benefits
over unJITed deforming from compile-time knowledge of the tuple
descriptor. Fixed column widths, NOT NULLness, etc can be taken
advantage of.
Right now the JITed deforming is only used when deforming tuples as
part of expression evaluation (and obviously only if the descriptor is
known). It's likely to be beneficial in other cases, too.
By default tuple deforming is JITed whenever an expression is JIT
compiled. There's a separate boolean GUC controlling it, but that's
expected to be primarily useful for development and benchmarking.
Docs will follow in a later commit containing docs for the whole JIT
feature.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
For any interesting JIT target, fields inside structs need to be
accessed. b96d550e contains infrastructure for syncing the definition
of types between postgres C code and runtime code generation with
LLVM. But that doesn't sync the number or names of fields inside
structs, just the types (including padding etc).
One option would be to hardcode the offset numbers in the JIT code,
but that'd be hard to keep in sync. Instead add macros indicating the
field offset to the fields that need to be accessed. Not pretty, but
manageable.
Author: Andres Freund
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
"UPDATE/DELETE WHERE CURRENT OF cursor_name" failed, with an error message
like "cannot extract system attribute from virtual tuple", if the cursor
was using a index-only scan for the target table. Fix it by digging the
current TID out of the indexscan state.
It seems likely that the same failure could occur for CustomScan plans
and perhaps some FDW plan types, so that leaving this to be treated as an
internal error with an obscure message isn't as good an idea as it first
seemed. Hence, add a bit of heaptuple.c infrastructure to let us deliver
a more on-topic message. I chose to make the message match what you get
for the case where execCurrentOf can't identify the target scan node at
all, "cursor "foo" is not a simply updatable scan of table "bar"".
Perhaps it should be different, but we can always adjust that later.
In the future, it might be nice to provide hooks that would let custom
scan providers and/or FDWs deal with this in other ways; but that's
not a suitable topic for a back-patchable bug fix.
It's been like this all along, so back-patch to all supported branches.
Yugo Nagata and Tom Lane
Discussion: https://postgr.es/m/20180201013349.937dfc5f.nagata@sraoss.co.jp
In a top-level CALL, the values of INOUT arguments will be returned as a
result row. In PL/pgSQL, the values are assigned back to the input
arguments. In other languages, the same convention as for return a
record from a function is used. That does not require any code changes
in the PL implementations.
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
Andres Freund
Tom Lane
Alvaro Herrera
Peter Eisentraut
Bruce Momjian
Simon Riggs
Robert Haas