Specifically, add a per-node hook that is called after the per-node
information has been displayed but before we display children, and a
per-query hook that is called after existing query-level information
is printed. This assumes that extension-added information should
always go at the end rather than the beginning or the middle, but
that seems like an acceptable limitation for simplicity. It also
assumes that extensions will only want to add information, not remove
or reformat existing details; those also seem like acceptable
restrictions, at least for now.
If multiple EXPLAIN extensions are used, the order in which any
additional details are printed is likely to depend on the order in
which the modules are loaded. That seems OK, since the user may
have opinions about the order in which output should appear, and the
extension author can't really know whether their stuff is more or
less important to a particular user than some other extension.
Discussion: http://postgr.es/m/CA+TgmoYSzg58hPuBmei46o8D3SKX+SZoO4K_aGQGwiRzvRApLg@mail.gmail.com
Reviewed-by: Srinath Reddy <srinath2133@gmail.com>
Reviewed-by: Andrei Lepikhov <lepihov@gmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Sami Imseih <samimseih@gmail.com>
Modules can use RegisterExtensionExplainOption to register new
EXPLAIN options, and GetExplainExtensionId, GetExplainExtensionState,
and SetExplainExtensionState to store related state inside the
ExplainState object.
Since this substantially increases the amount of code that needs
to handle ExplainState-related tasks, move a few bits of existing
code to a new file explain_state.c and add the rest of this
infrastructure there.
See the comments at the top of explain_state.c for further
explanation of how this mechanism works.
This does not yet provide a way for such such options to do anything
useful. The intention is that we'll add hooks for that purpose in a
separate commit.
Discussion: http://postgr.es/m/CA+TgmoYSzg58hPuBmei46o8D3SKX+SZoO4K_aGQGwiRzvRApLg@mail.gmail.com
Reviewed-by: Srinath Reddy <srinath2133@gmail.com>
Reviewed-by: Andrei Lepikhov <lepihov@gmail.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: Sami Imseih <samimseih@gmail.com>
Up to now we just punted on showing the window definitions used
in a plan, with window function calls represented as "OVER (?)".
To improve that, show the window definition implemented by each
WindowAgg plan node, and reference their window names in OVER.
For nameless window clauses generated by "OVER (...)", assign
unique names w1, w2, etc.
In passing, re-order the properties shown for a WindowAgg node
so that the Run Condition (if any) appears after the Window
property and before the Filter (if any). This seems more
sensible since the Run Condition is associated with the Window
and acts before the Filter.
Thanks to David G. Johnston and Álvaro Herrera for design
suggestions.
Author: Tom Lane <tgl@sss.pgh.pa.us>
Reviewed-by: David Rowley <dgrowleyml@gmail.com>
Discussion: https://postgr.es/m/144530.1741469955@sss.pgh.pa.us
Expose the count of index searches/index descents in EXPLAIN ANALYZE's
output for index scan/index-only scan/bitmap index scan nodes. This
information is particularly useful with scans that use ScalarArrayOp
quals, where the number of index searches can be unpredictable due to
implementation details that interact with physical index characteristics
(at least with nbtree SAOP scans, since Postgres 17 commit 5bf748b8).
The information shown also provides useful context when EXPLAIN ANALYZE
runs a plan with an index scan node that successfully applied the skip
scan optimization (set to be added to nbtree by an upcoming patch).
The instrumentation works by teaching all index AMs to increment a new
nsearches counter whenever a new index search begins. The counter is
incremented at exactly the same point that index AMs already increment
the pg_stat_*_indexes.idx_scan counter (we're counting the same event,
but at the scan level rather than the relation level). Parallel queries
have workers copy their local counter struct into shared memory when an
index scan node ends -- even when it isn't a parallel aware scan node.
An earlier version of this patch that only worked with parallel aware
scans became commit 5ead85fb (though that was quickly reverted by commit
d00107cd following "debug_parallel_query=regress" buildfarm failures).
Our approach doesn't match the approach used when tracking other index
scan related costs (e.g., "Rows Removed by Filter:"). It is comparable
to the approach used in similar cases involving costs that are only
readily accessible inside an access method, not from the executor proper
(e.g., "Heap Blocks:" output for a Bitmap Heap Scan, which was recently
enhanced to show per-worker costs by commit 5a1e6df3, using essentially
the same scheme as the one used here). It is necessary for index AMs to
have direct responsibility for maintaining the new counter, since the
counter might need to be incremented multiple times per amgettuple call
(or per amgetbitmap call). But it is also necessary for the executor
proper to manage the shared memory now used to transfer each worker's
counter struct to the leader.
Author: Peter Geoghegan <pg@bowt.ie>
Reviewed-By: Robert Haas <robertmhaas@gmail.com>
Reviewed-By: Tomas Vondra <tomas@vondra.me>
Reviewed-By: Masahiro Ikeda <ikedamsh@oss.nttdata.com>
Reviewed-By: Matthias van de Meent <boekewurm+postgres@gmail.com>
Discussion: https://postgr.es/m/CAH2-WzkRqvaqR2CTNqTZP0z6FuL4-3ED6eQB0yx38XBNj1v-4Q@mail.gmail.com
Discussion: https://postgr.es/m/CAH2-Wz=PKR6rB7qbx+Vnd7eqeB5VTcrW=iJvAsTsKbdG+kW_UA@mail.gmail.com
This reverts commit 5ead85fbc8.
This commit shows test failures with debug_parallel_query=regress. The
underlying issue needs to be debugged, so revert for now.
Expose the count of index searches/index descents in EXPLAIN ANALYZE's
output for index scan nodes. This information is particularly useful
with scans that use ScalarArrayOp quals, where the number of index scans
isn't predictable in advance (at least not with optimizations like the
one added to nbtree by Postgres 17 commit 5bf748b8). It will also be
useful when EXPLAIN ANALYZE shows details of an nbtree index scan that
uses skip scan optimizations set to be introduced by an upcoming patch.
The instrumentation works by teaching index AMs to increment a new
nsearches counter whenever a new index search begins. The counter is
incremented at exactly the same point that index AMs must already
increment the index's pg_stat_*_indexes.idx_scan counter (we're counting
the same event, but at the scan level rather than the relation level).
The new counter is stored in the scan descriptor (IndexScanDescData),
which explain.c reaches by going through the scan node's PlanState.
This approach doesn't match the approach used when tracking other index
scan specific costs (e.g., "Rows Removed by Filter:"). It is similar to
the approach used in other cases where we must track costs that are only
readily accessible inside an access method, and not from the executor
(e.g., "Heap Blocks:" output for a Bitmap Heap Scan). It is inherently
necessary to maintain a counter that can be incremented multiple times
during a single amgettuple call (or amgetbitmap call), and directly
exposing PlanState.instrument to index access methods seems unappealing.
Author: Peter Geoghegan <pg@bowt.ie>
Reviewed-By: Tomas Vondra <tomas@vondra.me>
Reviewed-By: Robert Haas <robertmhaas@gmail.com>
Reviewed-By: Masahiro Ikeda <ikedamsh@oss.nttdata.com>
Reviewed-By: Matthias van de Meent <boekewurm+postgres@gmail.com>
Discussion: https://postgr.es/m/CAH2-Wz=PKR6rB7qbx+Vnd7eqeB5VTcrW=iJvAsTsKbdG+kW_UA@mail.gmail.com
Discussion: https://postgr.es/m/CAH2-WzkRqvaqR2CTNqTZP0z6FuL4-3ED6eQB0yx38XBNj1v-4Q@mail.gmail.com
Commit ddb17e387a attempted to avoid
confusing users by displaying digits after the decimal point only when
nloops > 1, since it's impossible to have a fraction row count after a
single iteration. However, this made the regression tests unstable since
parallal queries will have nloops>1 for all nodes below the Gather or
Gather Merge in normal cases, but if the workers don't start in time and
the leader finishes all the work, they will suddenly have nloops==1,
making it unpredictable whether the digits after the decimal point would
be displayed or not. Although 44cbba9a7f
seemed to fix the immediate failures, it may still be the case that there
are lower-probability failures elsewhere in the regression tests.
Various fixes are possible here. For example, it has previously been
proposed that we should try to display the digits after the decimal
point only if rows/nloops is an integer, but currently rows is storead
as a float so it's not theoretically an exact quantity -- precision
could be lost in extreme cases. It has also been proposed that we
should try to display the digits after the decimal point only if we're
under some sort of construct that could potentially cause looping
regardless of whether it actually does. While such ideas are not
without merit, this patch adopts the much simpler solution of always
display two decimal digits. If that approach stands up to scrutiny
from the buildfarm and human users, it spares us the trouble of doing
anything more complex; if not, we can reassess.
This commit incidentally reverts 44cbba9a7f,
which should no longer be needed.
Author: Robert Haas <robertmhaas@gmail.com>
Author: Ilia Evdokimov <ilya.evdokimov@tantorlabs.com>
Discussion: http://postgr.es/m/CA+TgmoazzVHn8sFOMFAEwoqBTDxKT45D7mvkyeHgqtoD2cn58Q@mail.gmail.com
Before executing a cached generic plan, AcquireExecutorLocks() in
plancache.c locks all relations in a plan's range table to ensure the
plan is safe for execution. However, this locks runtime-prunable
relations that will later be pruned during "initial" runtime pruning,
introducing unnecessary overhead.
This commit defers locking for such relations to executor startup and
ensures that if the CachedPlan is invalidated due to concurrent DDL
during this window, replanning is triggered. Deferring these locks
avoids unnecessary locking overhead for pruned partitions, resulting
in significant speedup, particularly when many partitions are pruned
during initial runtime pruning.
* Changes to locking when executing generic plans:
AcquireExecutorLocks() now locks only unprunable relations, that is,
those found in PlannedStmt.unprunableRelids (introduced in commit
cbc127917e), to avoid locking runtime-prunable partitions
unnecessarily. The remaining locks are taken by
ExecDoInitialPruning(), which acquires them only for partitions that
survive pruning.
This deferral does not affect the locks required for permission
checking in InitPlan(), which takes place before initial pruning.
ExecCheckPermissions() now includes an Assert to verify that all
relations undergoing permission checks, none of which can be in the
set of runtime-prunable relations, are properly locked.
* Plan invalidation handling:
Deferring locks introduces a window where prunable relations may be
altered by concurrent DDL, invalidating the plan. A new function,
ExecutorStartCachedPlan(), wraps ExecutorStart() to detect and handle
invalidation caused by deferred locking. If invalidation occurs,
ExecutorStartCachedPlan() updates CachedPlan using the new
UpdateCachedPlan() function and retries execution with the updated
plan. To ensure all code paths that may be affected by this handle
invalidation properly, all callers of ExecutorStart that may execute a
PlannedStmt from a CachedPlan have been updated to use
ExecutorStartCachedPlan() instead.
UpdateCachedPlan() replaces stale plans in CachedPlan.stmt_list. A new
CachedPlan.stmt_context, created as a child of CachedPlan.context,
allows freeing old PlannedStmts while preserving the CachedPlan
structure and its statement list. This ensures that loops over
statements in upstream callers of ExecutorStartCachedPlan() remain
intact.
ExecutorStart() and ExecutorStart_hook implementations now return a
boolean value indicating whether plan initialization succeeded with a
valid PlanState tree in QueryDesc.planstate, or false otherwise, in
which case QueryDesc.planstate is NULL. Hook implementations are
required to call standard_ExecutorStart() at the beginning, and if it
returns false, they should do the same without proceeding.
* Testing:
To verify these changes, the delay_execution module tests scenarios
where cached plans become invalid due to changes in prunable relations
after deferred locks.
* Note to extension authors:
ExecutorStart_hook implementations must verify plan validity after
calling standard_ExecutorStart(), as explained earlier. For example:
if (prev_ExecutorStart)
plan_valid = prev_ExecutorStart(queryDesc, eflags);
else
plan_valid = standard_ExecutorStart(queryDesc, eflags);
if (!plan_valid)
return false;
<extension-code>
return true;
Extensions accessing child relations, especially prunable partitions,
via ExecGetRangeTableRelation() must now ensure their RT indexes are
present in es_unpruned_relids (introduced in commit cbc127917e), or
they will encounter an error. This is a strict requirement after this
change, as only relations in that set are locked.
The idea of deferring some locks to executor startup, allowing locks
for prunable partitions to be skipped, was first proposed by Tom Lane.
Reviewed-by: Robert Haas <robertmhaas@gmail.com> (earlier versions)
Reviewed-by: David Rowley <dgrowleyml@gmail.com> (earlier versions)
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us> (earlier versions)
Reviewed-by: Tomas Vondra <tomas@vondra.me>
Reviewed-by: Junwang Zhao <zhjwpku@gmail.com>
Discussion: https://postgr.es/m/CA+HiwqFGkMSge6TgC9KQzde0ohpAycLQuV7ooitEEpbKB0O_mg@mail.gmail.com
The topic of turning EXPLAIN's BUFFERS option on with the ANALYZE option
has come up a few times over the past few years. In many ways, doing this
seems like a good idea as it may be more obvious to users why a given
query is running more slowly than they might expect. Also, from my own
(David's) personal experience, I've seen users posting to the mailing
lists with two identical plans, one slow and one fast asking why their
query is sometimes slow. In many cases, this is due to additional reads.
Having BUFFERS on by default may help reduce some of these questions, and
if not, make it more obvious to the user before they post, or save a
round-trip to the mailing list when additional I/O effort is the cause of
the slowness.
The general consensus is that we want BUFFERS on by default with
ANALYZE. However, there were more than zero concerns raised with doing
so. The primary reason against is the additional verbosity, making it
harder to read large plans. Another concern was that buffer information
isn't always useful so may not make sense to have it on by default.
It's currently December, so let's commit this to see if anyone comes
forward with a strong objection against making this change. We have over
half a year remaining in the v18 cycle where we could still easily consider
reverting this if someone were to come forward with a convincing enough
reason as to why doing this is a bad idea.
There were two patches independently submitted to achieve this goal, one
by me and the other by Guillaume. This commit is a mix of both of these
patches with some additional work done by me to adjust various
additional places in the documentation which include EXPLAIN ANALYZE
output.
Author: Guillaume Lelarge, David Rowley
Reviewed-by: Robert Haas, Greg Sabino Mullane, Michael Christofides
Discussion: https://postgr.es/m/CANNMO++W7MM8T0KyXN3ZheXXt-uLVM3aEtZd+WNfZ=obxffUiA@mail.gmail.com
Our parallel-mode code only works when we are executing a query
in full, so ExecutePlan must disable parallel mode when it is
asked to do partial execution. The previous logic for this
involved passing down a flag (variously named execute_once or
run_once) from callers of ExecutorRun or PortalRun. This is
overcomplicated, and unsurprisingly some of the callers didn't
get it right, since it requires keeping state that not all of
them have handy; not to mention that the requirements for it were
undocumented. That led to assertion failures in some corner
cases. The only state we really need for this is the existing
QueryDesc.already_executed flag, so let's just put all the
responsibility in ExecutePlan. (It could have been done in
ExecutorRun too, leading to a slightly shorter patch -- but if
there's ever more than one caller of ExecutePlan, it seems better
to have this logic in the subroutine than the callers.)
This makes those ExecutorRun/PortalRun parameters unnecessary.
In master it seems okay to just remove them, returning the
API for those functions to what it was before parallelism.
Such an API break is clearly not okay in stable branches,
but for them we can just leave the parameters in place after
documenting that they do nothing.
Per report from Yugo Nagata, who also reviewed and tested
this patch. Back-patch to all supported branches.
Discussion: https://postgr.es/m/20241206062549.710dc01cf91224809dd6c0e1@sraoss.co.jp
Some utility statements contain queries that can be planned and
executed: CREATE TABLE AS and DECLARE CURSOR. This commit adds query ID
computation for the inner queries executed by these two utility
commands, with and without EXPLAIN. This change leads to four new
callers of JumbleQuery() and post_parse_analyze_hook() so as extensions
can decide what to do with this new data.
Previously, extensions relying on the query ID, like pg_stat_statements,
were not able to track these nested queries as the query_id was 0.
For pg_stat_statements, this commit leads to additions under !toplevel
when pg_stat_statements.track is set to "all", as shown in its
regression tests. The output of EXPLAIN for these two utilities gains a
"Query Identifier" if compute_query_id is enabled.
Author: Anthonin Bonnefoy
Reviewed-by: Michael Paquier, Jian He
Discussion: https://postgr.es/m/CAO6_XqqM6S9bQ2qd=75W+yKATwoazxSNhv5sjW06fjGAtHbTUA@mail.gmail.com
c01743aa4 added EXPLAIN output to display the plan node's disabled_node
count whenever that count is above 0. Seemingly, there weren't many
people who liked that output as each parent of a disabled node would
also have a "Disabled Nodes" output due to the way disabled_nodes is
accumulated towards the root plan node. It was often hard and sometimes
impossible to figure out which nodes were disabled from looking at
EXPLAIN. You might think it would be possible to manually add up the
numbers from the "Disabled Nodes" output of a given node's children to
figure out if that node has a higher disabled_nodes count than its
children, but that wouldn't have worked for Append and Merge Append nodes
if some disabled child nodes were run-time pruned during init plan. Those
children are not displayed in EXPLAIN.
Here we attempt to improve this output by only showing "Disabled: true"
against only the nodes which are explicitly disabled themselves. That
seems to be the output that's desired by the most people who voiced
their opinion. This is done by summing up the disabled_nodes of the
given node's children and checking if that number is less than the
disabled_nodes of the current node.
This commit also fixes a bug in make_sort() which was neglecting to set
the Sort's disabled_nodes field. This should have copied what was done
in cost_sort(), but it hadn't been updated. With the new output, the
choice to not maintain that field properly was clearly wrong as the
disabled-ness of the node was attributed to the Sort's parent instead.
Reviewed-by: Laurenz Albe, Alena Rybakina
Discussion: https://postgr.es/m/9e4ad616bebb103ec2084bf6f724cfc739e7fabb.camel@cybertec.at
This commit is similar to 95d6e9af07, expanding the idea to CTE scan,
table function scan and recursive union scan nodes so that the maximum
tuplestore memory or disk usage is shown with EXPLAIN ANALYZE command.
Also adjust show_storage_info() so that it accepts storage type and
storage size arguments instead of Tuplestorestate. This allows the
node types to share the formatting code using show_storage_info(). Due
to this show_material_info() and show_windowagg_info() are also
modified.
Reviewed-by: David Rowley
Discussion: https://postgr.es/m/20240918.211246.1127161704188186085.ishii%40postgresql.org
This commit is similar to 1eff8279d and expands the idea to Window
aggregate nodes so that users can know how much memory or disk the
tuplestore used.
This commit uses newly introduced tuplestore_get_stats() to inquire this
information and add some additional output in EXPLAIN ANALYZE to
display the information for the Window aggregate node.
Reviewed-by: David Rowley, Ashutosh Bapat, Maxim Orlov, Jian He
Discussion: https://postgr.es/m/20240706.202254.89740021795421286.ishii%40postgresql.org
1eff8279d added an API to tuplestore.c to allow callers to obtain
storage telemetry data. That API wasn't quite good enough for callers
that perform tuplestore_clear() as the telemetry functions only
accounted for the current state of the tuplestore, not the maximums
before tuplestore_clear() was called.
There's a pending patch that would like to add tuplestore telemetry
output to EXPLAIN ANALYZE for WindowAgg. That node type uses
tuplestore_clear() before moving to the next window partition and we
want to show the maximum space used, not the space used for the final
partition.
Reviewed-by: Tatsuo Ishii, Ashutosh Bapat
Discussion: https://postgres/m/CAApHDvoY8cibGcicLV0fNh=9JVx9PANcWvhkdjBnDCc9Quqytg@mail.gmail.com
If there are subqueries in the grouping expressions, each of these
subqueries in the targetlist and HAVING clause is expanded into
distinct SubPlan nodes. As a result, only one of these SubPlan nodes
would be converted to reference to the grouping key column output by
the Agg node; others would have to get evaluated afresh. This is not
efficient, and with grouping sets this can cause wrong results issues
in cases where they should go to NULL because they are from the wrong
grouping set. Furthermore, during re-evaluation, these SubPlan nodes
might use nulled column values from grouping sets, which is not
correct.
This issue is not limited to subqueries. For other types of
expressions that are part of grouping items, if they are transformed
into another form during preprocessing, they may fail to match lower
target items. This can also lead to wrong results with grouping sets.
To fix this issue, we introduce a new kind of RTE representing the
output of the grouping step, with columns that are the Vars or
expressions being grouped on. In the parser, we replace the grouping
expressions in the targetlist and HAVING clause with Vars referencing
this new RTE, so that the output of the parser directly expresses the
semantic requirement that the grouping expressions be gotten from the
grouping output rather than computed some other way. In the planner,
we first preprocess all the columns of this new RTE and then replace
any Vars in the targetlist and HAVING clause that reference this new
RTE with the underlying grouping expressions, so that we will have
only one instance of a SubPlan node for each subquery contained in the
grouping expressions.
Bump catversion because this changes the querytree produced by the
parser.
Thanks to Tom Lane for the idea to invent a new kind of RTE.
Per reports from Geoff Winkless, Tobias Wendorff, Richard Guo from
various threads.
Author: Richard Guo
Reviewed-by: Ashutosh Bapat, Sutou Kouhei
Discussion: https://postgr.es/m/CAMbWs4_dp7e7oTwaiZeBX8+P1rXw4ThkZxh1QG81rhu9Z47VsQ@mail.gmail.com
Now that disable_cost is not included in the cost estimate, there's
no visible sign in EXPLAIN output of which plan nodes are disabled.
Fix that by propagating the number of disabled nodes from Path to
Plan, and then showing it in the EXPLAIN output.
There is some question about whether this is a desirable change.
While I personally believe that it is, it seems best to make it a
separate commit, in case we decide to back out just this part, or
rework it.
Reviewed by Andres Freund, Heikki Linnakangas, and David Rowley.
Discussion: http://postgr.es/m/CA+TgmoZ_+MS+o6NeGK2xyBv-xM+w1AfFVuHE4f_aq6ekHv7YSQ@mail.gmail.com
Commit f4b54e1ed9, which introduced macros for protocol characters,
missed updating a few places. It also did not introduce macros for
messages sent from parallel workers to their leader processes.
This commit adds a new section in protocol.h for those.
Author: Aleksander Alekseev
Discussion: https://postgr.es/m/CAJ7c6TNTd09AZq8tGaHS3LDyH_CCnpv0oOz2wN1dGe8zekxrdQ%40mail.gmail.com
Backpatch-through: 17
Both of these counters were using the "long" data type. On MSVC that's
a 32-bit type. On modern hardware, I was able to demonstrate that we can
wrap those counters with a query that only takes 15 minutes to run.
This issue may manifest itself either by not showing the values of the
counters because they've wrapped and are less than zero, resulting in
them being filtered by the > 0 checks in show_tidbitmap_info(), or bogus
numbers being displayed which are modulus 2^32 of the actual number.
Widen these counters to uint64.
Discussion: https://postgr.es/m/CAApHDvpS_97TU+jWPc=T83WPp7vJa1dTw3mojEtAVEZOWh9bjQ@mail.gmail.com
The code added in 1eff8279d was lacking a check to see if the tuplestore
had been created. In nodeMaterial.c this is done by ExecMaterial() rather
than by ExecInitMaterial(), so the tuplestore won't be created unless
the node has been executed at least once, as demonstrated by Alexander
in his report.
Here we skip showing any of the new EXPLAIN ANALYZE information when the
Materialize node has not been executed.
Reported-by: Alexander Lakhin
Discussion: https://postgr.es/m/fe7fc8fb-86e5-ecb0-3cb2-dd2c9a6c482f@gmail.com
Up until now, there was no ability to easily determine if a Material
node caused the underlying tuplestore to spill to disk or even see how
much memory the tuplestore used if it didn't.
Here we add some new functions to tuplestore.c to query this information
and add some additional output in EXPLAIN ANALYZE to display this
information for the Material node.
There are a few other executor node types that use tuplestores, so we
could also consider adding these details to the EXPLAIN ANALYZE for
those nodes too. Let's consider those independently from this. Having
the tuplestore.c infrastructure in to allow that is step 1.
Author: David Rowley
Reviewed-by: Matthias van de Meent, Dmitry Dolgov
Discussion: https://postgr.es/m/CAApHDvp5Py9g4Rjq7_inL3-MCK1Co2CRt_YWFwTU2zfQix0p4A@mail.gmail.com
Hash joins can support semijoin with the LHS input on the right, using
the existing logic for inner join, combined with the assurance that only
the first match for each inner tuple is considered, which can be
achieved by leveraging the HEAP_TUPLE_HAS_MATCH flag. This can be very
useful in some cases since we may now have the option to hash the
smaller table instead of the larger.
Merge join could likely support "Right Semi Join" too. However, the
benefit of swapping inputs tends to be small here, so we do not address
that in this patch.
Note that this patch also modifies a test query in join.sql to ensure it
continues testing as intended. With this patch the original query would
result in a right-semi-join rather than semi-join, compromising its
original purpose of testing the fix for neqjoinsel's behavior for
semi-joins.
Author: Richard Guo
Reviewed-by: wenhui qiu, Alena Rybakina, Japin Li
Discussion: https://postgr.es/m/CAMbWs4_X1mN=ic+SxcyymUqFx9bB8pqSLTGJ-F=MHy4PW3eRXw@mail.gmail.com
06286709e added a SERIALIZE option to EXPLAIN which included showing the
amount of kilobytes serialized. The calculation to convert bytes into
kilobytes wasn't consistent with how that's done in the rest of EXPLAIN.
Traditionally we round up to the nearest kB, but the new code rounded to
the nearest kB.
To fix this, invent a macro that does the conversion and use that macro
everywhere that requires this conversion.
Additionally, 5de890e36 added EXPLAIN (MEMORY) but included the memory
sizes in bytes. Convert these values to kilobytes to align with the
other memory related outputs.
In passing, swap out a "long" type in show_hash_info() and use a uint64
instead. We do support platforms where sizeof(Size) == 8 and
sizeof(long) == 4, so using a long there is questionable.
Reported-by: jian he
Reviewed-by: jian he
Discussion: https://www.postgresql.org/message-id/CACJufxE4Sp7xvgOwhqtFx5hS85AxMKobPWDo-xZHZVTpK3EBjA@mail.gmail.com
JSON_TABLE() allows JSON data to be converted into a relational view
and thus used, for example, in a FROM clause, like other tabular
data. Data to show in the view is selected from a source JSON object
using a JSON path expression to get a sequence of JSON objects that's
called a "row pattern", which becomes the source to compute the
SQL/JSON values that populate the view's output columns. Column
values themselves are computed using JSON path expressions applied to
each of the JSON objects comprising the "row pattern", for which the
SQL/JSON query functions added in 6185c9737c are used.
To implement JSON_TABLE() as a table function, this augments the
TableFunc and TableFuncScanState nodes that are currently used to
support XMLTABLE() with some JSON_TABLE()-specific fields.
Note that the JSON_TABLE() spec includes NESTED COLUMNS and PLAN
clauses, which are required to provide more flexibility to extract
data out of nested JSON objects, but they are not implemented here
to keep this commit of manageable size.
Author: Nikita Glukhov <n.gluhov@postgrespro.ru>
Author: Teodor Sigaev <teodor@sigaev.ru>
Author: Oleg Bartunov <obartunov@gmail.com>
Author: Alexander Korotkov <aekorotkov@gmail.com>
Author: Andrew Dunstan <andrew@dunslane.net>
Author: Amit Langote <amitlangote09@gmail.com>
Author: Jian He <jian.universality@gmail.com>
Reviewers have included (in no particular order):
Andres Freund, Alexander Korotkov, Pavel Stehule, Andrew Alsup,
Erik Rijkers, Zihong Yu, Himanshu Upadhyaya, Daniel Gustafsson,
Justin Pryzby, Álvaro Herrera, Jian He
Discussion: https://postgr.es/m/cd0bb935-0158-78a7-08b5-904886deac4b@postgrespro.ru
Discussion: https://postgr.es/m/20220616233130.rparivafipt6doj3@alap3.anarazel.de
Discussion: https://postgr.es/m/abd9b83b-aa66-f230-3d6d-734817f0995d%40postgresql.org
Discussion: https://postgr.es/m/CA+HiwqE4XTdfb1nW=Ojoy_tQSRhYt-q_kb6i5d4xcKyrLC1Nbg@mail.gmail.com
EXPLAIN (ANALYZE, SERIALIZE) allows collection of statistics about
the volume of data emitted by a query, as well as the time taken
to convert the data to the on-the-wire format. Previously there
was no way to investigate this without actually sending the data
to the client, in which case network transmission costs might
swamp what you wanted to see. In particular this feature allows
investigating the costs of de-TOASTing compressed or out-of-line
data during formatting.
Stepan Rutz and Matthias van de Meent,
reviewed by Tomas Vondra and myself
Discussion: https://postgr.es/m/ca0adb0e-fa4e-c37e-1cd7-91170b18cae1@gmx.de
Historically we've printed SubPlan expression nodes as "(SubPlan N)",
which is pretty uninformative. Trying to reproduce the original SQL
for the subquery is still as impractical as before, and would be
mighty verbose as well. However, we can still do better than that.
Displaying the "testexpr" when present, and adding a keyword to
indicate the SubLinkType, goes a long way toward showing what's
really going on.
In addition, this patch gets rid of EXPLAIN's use of "$n" to represent
subplan and initplan output Params. Instead we now print "(SubPlan
N).colX" or "(InitPlan N).colX" to represent the X'th output column
of that subplan. This eliminates confusion with the use of "$n" to
represent PARAM_EXTERN Params, and it's useful for the first part of
this change because it eliminates needing some other indication of
which subplan is referenced by a SubPlan that has a testexpr.
In passing, this adds simple regression test coverage of the
ROWCOMPARE_SUBLINK code paths, which were entirely unburdened
by testing before.
Tom Lane and Dean Rasheed, reviewed by Aleksander Alekseev.
Thanks to Chantal Keller for raising the question of whether
this area couldn't be improved.
Discussion: https://postgr.es/m/2838538.1705692747@sss.pgh.pa.us
There is a hook called ExplainOneQuery_hook that gives modules the
possibility to plug into this code path, but, like utility.c for utility
statement execution, there is no corresponding "standard" routine in
the case of EXPLAIN executed for one Query.
This commit adds a new standard_ExplainOneQuery() in explain.c, which is
able to run explain on a non-utility Query without calling its hook.
Per the feedback received from a couple of hackers, this change gives
the possibility to cut a few hundred lines of code in some of the
popular out-of-core modules as these maintained a copy of
ExplainOneQuery(), adding custom extra information at the beginning or
the end of the EXPLAIN output.
Author: Mats Kindahl
Reviewed-by: Aleksander Alekseev, Jelte Fennema-Nio, Andrei Lepikhov
Discussion: https://postgr.es/m/CA+14427V_B4EAoC_o-iYYucRdMSOTfpuH9k-QbexffY1HYJBiA@mail.gmail.com
as determined by include-what-you-use (IWYU)
While IWYU also suggests to *add* a bunch of #include's (which is its
main purpose), this patch does not do that. In some cases, a more
specific #include replaces another less specific one.
Some manual adjustments of the automatic result:
- IWYU currently doesn't know about includes that provide global
variable declarations (like -Wmissing-variable-declarations), so
those includes are being kept manually.
- All includes for port(ability) headers are being kept for now, to
play it safe.
- No changes of catalog/pg_foo.h to catalog/pg_foo_d.h, to keep the
patch from exploding in size.
Note that this patch touches just *.c files, so nothing declared in
header files changes in hidden ways.
As a small example, in src/backend/access/transam/rmgr.c, some IWYU
pragma annotations are added to handle a special case there.
Discussion: https://www.postgresql.org/message-id/flat/af837490-6b2f-46df-ba05-37ea6a6653fc%40eisentraut.org
This adds a new "Memory:" line under the "Planning:" group (which
currently only has "Buffers:") when the MEMORY option is specified.
In order to make the reporting reasonably accurate, we create a separate
memory context for planner activities, to be used only when this option
is given. The total amount of memory allocated by that context is
reported as "allocated"; we subtract memory in the context's freelists
from that and report that result as "used". We use
MemoryContextStatsInternal() to obtain the quantities.
The code structure to show buffer usage during planning was not in
amazing shape, so I (Álvaro) modified the patch a bit to clean that up
in passing.
Author: Ashutosh Bapat
Reviewed-by: David Rowley, Andrey Lepikhov, Jian He, Andy Fan
Discussion: https://www.postgresql.org/message-id/CAExHW5sZA=5LJ_ZPpRO-w09ck8z9p7eaYAqq3Ks9GDfhrxeWBw@mail.gmail.com
There was no I/O timing statistics for counting read and write timings
on local blocks, contrary to the counterparts for temp and shared
blocks. This information is available when track_io_timing is enabled.
The output of EXPLAIN is updated to show this information. An update of
pg_stat_statements is planned next.
Author: Nazir Bilal Yavuz
Reviewed-by: Robert Haas, Melanie Plageman
Discussion: https://postgr.es/m/CAN55FZ19Ss279mZuqGbuUNxka0iPbLgYuOQXqAKewrjNrp27VA@mail.gmail.com
These two counters, defined in BufferUsage to track respectively the
time spent while reading and writing blocks have historically only
tracked data related to shared buffers, when track_io_timing is enabled.
An upcoming patch to add specific counters for local buffers will take
advantage of this rename as it has come up that no data is currently
tracked for local buffers, and tracking local and shared buffers using
the same fields would be inconsistent with the treatment done for temp
buffers. Renaming the existing fields clarifies what the block type of
each stats field is.
pg_stat_statement is updated to reflect the rename. No extension
version bump is required as 5a3423ad8e has done one, affecting v17~.
Author: Nazir Bilal Yavuz
Reviewed-by: Robert Haas, Melanie Plageman
Discussion: https://postgr.es/m/CAN55FZ19Ss279mZuqGbuUNxka0iPbLgYuOQXqAKewrjNrp27VA@mail.gmail.com
generation_counter includes time spent on both JIT:ing expressions
and tuple deforming which are configured independently via options
jit_expressions and jit_tuple_deforming. As they are combined in
the same counter it's not apparent what fraction of time the tuple
deforming takes.
This adds deform_counter dedicated to tuple deforming, which allows
seeing more directly the influence jit_tuple_deforming is having on
the query. The counter is exposed in EXPLAIN and pg_stat_statements
bumpin pg_stat_statements to 1.11.
Author: Dmitry Dolgov <9erthalion6@gmail.com>
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
Reviewed-by: Daniel Gustafsson <daniel@yesql.se>
Discussion: https://postgr.es/m/20220612091253.eegstkufdsu4kfls@erthalion.local
Since 3db72eb, the query ID of utilities is generated using the Query
structure, making the use of the query string in JumbleQuery()
unnecessary. This commit removes the argument "querytext" from
JumbleQuery().
Reported-by: Joe Conway
Reviewed-by: Nathan Bossart
Discussion: https://postgr.es/m/ZJlQAWE4COFqHuAV@paquier.xyz
Run pgindent, pgperltidy, and reformat-dat-files.
This set of diffs is a bit larger than typical. We've updated to
pg_bsd_indent 2.1.2, which properly indents variable declarations that
have multi-line initialization expressions (the continuation lines are
now indented one tab stop). We've also updated to perltidy version
20230309 and changed some of its settings, which reduces its desire to
add whitespace to lines to make assignments etc. line up. Going
forward, that should make for fewer random-seeming changes to existing
code.
Discussion: https://postgr.es/m/20230428092545.qfb3y5wcu4cm75ur@alvherre.pgsql
Merge and hash joins can support antijoin with the non-nullable input
on the right, using very simple combinations of their existing logic
for right join and anti join. This gives the planner more freedom
about how to order the join. It's particularly useful for hash join,
since we may now have the option to hash the smaller table instead
of the larger.
Richard Guo, reviewed by Ronan Dunklau and myself
Discussion: https://postgr.es/m/CAMbWs48xh9hMzXzSy3VaPzGAz+fkxXXTUbCLohX1_L8THFRm2Q@mail.gmail.com
In ancient times, these belonged to arguments or fields that were
actually of type long, but now they are not anymore, so this "L"
decoration is just confusing. (Some other 0L and other "L" constants
remain, where they are actually associated with a long type.)
This provides a very simple way to see the generic plan for a
parameterized query. Without this, it's necessary to define
a prepared statement and temporarily change plan_cache_mode,
which is a bit tedious.
One thing that's a bit of a hack perhaps is that we disable
execution-time partition pruning when the GENERIC_PLAN option
is given. That's because the pruning code may attempt to
fetch the value of one of the parameters, which would fail.
Laurenz Albe, reviewed by Julien Rouhaud, Christoph Berg,
Michel Pelletier, Jim Jones, and myself
Discussion: https://postgr.es/m/0a29b954b10b57f0d135fe12aa0909bd41883eb0.camel@cybertec.at
force_parallel_mode is meant to be used to allow us to exercise the
parallel query infrastructure to ensure that it's working as we expect.
It seems some users think this GUC is for forcing the query planner into
picking a parallel plan regardless of the costs. A quick look at the
documentation would have made them realize that they were wrong, but the
GUC is likely too conveniently named which, evidently, seems to often
result in users expecting that it forces the planner into usefully
parallelizing queries.
Here we rename the GUC to something which casual users are less likely to
mistakenly think is what they need to make their query run more quickly.
For now, the old name can still be used. We'll revisit if the old name
mapping can be removed once the buildfarm configs are all updated.
Reviewed-by: John Naylor
Discussion: https://postgr.es/m/CAApHDvrsOi92_uA7PEaHZMH-S4Xv+MGhQWA+GrP8b1kjpS1HjQ@mail.gmail.com
