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
Previously, the output of EXPLAIN (BUFFERS) option showed only the I/O
timing spent reading and writing shared and local buffers. This commit
adds on top of that the I/O timing for temporary buffers in the output
of EXPLAIN (for spilled external sorts, hashes, materialization. etc).
This can be helpful for users in cases where the I/O related to
temporary buffers is the bottleneck.
Like its cousin, this information is available only when track_io_timing
is enabled. Playing the patch, this is showing an extra overhead of up
to 1% even when using gettimeofday() as implementation for interval
timings, which is slightly within the usual range noise still that's
measurable.
Author: Masahiko Sawada
Reviewed-by: Georgios Kokolatos, Melanie Plageman, Julien Rouhaud,
Ranier Vilela
Discussion: https://postgr.es/m/CAD21AoAJgotTeP83p6HiAGDhs_9Fw9pZ2J=_tYTsiO5Ob-V5GQ@mail.gmail.com
EXPLAIN ANALYZE for an async-capable ForeignScan node associated with
postgres_fdw is done just by using instrumentation for ExecProcNode()
called from the node's callbacks, causing the following problems:
1) If the remote table to scan is empty, the node is incorrectly
considered as "never executed" by the command even if the node is
executed, as ExecProcNode() isn't called from the node's callbacks at
all in that case.
2) The command fails to collect timings for things other than
ExecProcNode() done in the node, such as creating a cursor for the
node's remote query.
To fix these problems, add instrumentation for async-capable nodes, and
modify postgres_fdw accordingly.
My oversight in commit 27e1f1456.
While at it, update a comment for the AsyncRequest struct in execnodes.h
and the documentation for the ForeignAsyncRequest API in fdwhandler.sgml
to match the code in ExecAsyncAppendResponse() in nodeAppend.c, and fix
typos in comments in nodeAppend.c.
Per report from Andrey Lepikhov, though I didn't use his patch.
Reviewed-by: Andrey Lepikhov
Discussion: https://postgr.es/m/2eb662bb-105d-fc20-7412-2f027cc3ca72%40postgrespro.ru
In commit 33e05f89c5, we have added the option to display WAL usage
statistics in Explain and auto_explain. The display format used two spaces
between each field which is inconsistent with Buffer usage statistics which
is using one space between each field. Change the format to make WAL usage
statistics consistent with Buffer usage statistics.
This commit also changed the usage of "full page writes" to
"full page images" for WAL usage statistics to make it consistent with
other parts of code and docs.
Author: Julien Rouhaud, Amit Kapila
Reviewed-by: Justin Pryzby, Kyotaro Horiguchi and Amit Kapila
Discussion: https://postgr.es/m/CAB-hujrP8ZfUkvL5OYETipQwA=e3n7oqHFU=4ZLxWS_Cza3kQQ@mail.gmail.com
Currently, we don't account for buffer usage incurred by parallel workers
for parallel create index. This commit allows each worker to record the
buffer usage stats and leader backend to accumulate that stats at the
end of the operation. This will allow pg_stat_statements to display
correct buffer usage stats for (parallel) create index command.
Reported-by: Julien Rouhaud
Author: Sawada Masahiko
Reviewed-by: Dilip Kumar, Julien Rouhaud and Amit Kapila
Backpatch-through: 11, where this was introduced
Discussion: https://postgr.es/m/20200328151721.GB12854@nol
This allows gathering the WAL generation statistics for each statement
execution. The three statistics that we collect are the number of WAL
records, the number of full page writes and the amount of WAL bytes
generated.
This helps the users who have write-intensive workload to see the impact
of I/O due to WAL. This further enables us to see approximately what
percentage of overall WAL is due to full page writes.
In the future, we can extend this functionality to allow us to compute the
the exact amount of WAL data due to full page writes.
This patch in itself is just an infrastructure to compute WAL usage data.
The upcoming patches will expose this data via explain, auto_explain,
pg_stat_statements and verbose (auto)vacuum output.
Author: Kirill Bychik, Julien Rouhaud
Reviewed-by: Dilip Kumar, Fujii Masao and Amit Kapila
Discussion: https://postgr.es/m/CAB-hujrP8ZfUkvL5OYETipQwA=e3n7oqHFU=4ZLxWS_Cza3kQQ@mail.gmail.com
Previously pg_stat_statements calculated the difference of buffer counters
by its own code even while BufferUsageAccumDiff() had the same code.
This commit expose BufferUsageAccumDiff() and makes pg_stat_statements
use it for the calculation, in order to simply the code.
This change also would be useful for the upcoming patch for the planning
counters in pg_stat_statements because the patch will add one more code
for the calculation of difference of buffer counters and that can easily be
done by using BufferUsageAccumDiff().
Author: Julien Rouhaud
Reviewed-by: Fujii Masao
Discussion: https://postgr.es/m/bdfee4e0-a304-2498-8da5-3cb52c0a193e@oss.nttdata.com
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
This code provides infrastructure for a parallel leader to start up
parallel workers to execute subtrees of the plan tree being executed
in the master. User-supplied parameters from ParamListInfo are passed
down, but PARAM_EXEC parameters are not. Various other constructs,
such as initplans, subplans, and CTEs, are also not currently shared.
Nevertheless, there's enough here to support a basic implementation of
parallel query, and we can lift some of the current restrictions as
needed.
Amit Kapila and Robert Haas
Commit af7914c662, which added the TIMING
option to EXPLAIN, had an oversight: if the TIMING option is disabled
then control in InstrStartNode() goes through an elog(DEBUG2) call, which
typically does nothing but takes a noticeable amount of time to do it.
Tweak the logic to avoid that.
In HEAD, also change the elog(DEBUG2)'s in instrument.c to elog(ERROR).
It's not very clear why they weren't like that to begin with, but this
episode shows that not complaining more vociferously about misuse is
likely to do little except allow bugs to remain hidden.
While at it, adjust some code that was making possibly-dangerous
assumptions about flag bits being in the rightmost byte of the
instrument_options word.
Problem reported by Pavel Stehule (via Tomas Vondra).
Currently, the only way to see the numbers this gathers is via
EXPLAIN (ANALYZE, BUFFERS), but the plan is to add visibility through
the stats collector and pg_stat_statements in subsequent patches.
Ants Aasma, reviewed by Greg Smith, with some further changes by me.
Sometimes it may be useful to get actual row counts out of EXPLAIN
(ANALYZE) without paying the cost of timing every node entry/exit.
With this patch, you can say EXPLAIN (ANALYZE, TIMING OFF) to get that.
Tomas Vondra, reviewed by Eric Theise, with minor doc changes by me.
This provides information about the numbers of tuples that were visited
but not returned by table scans, as well as the numbers of join tuples
that were considered and discarded within a join plan node.
There is still some discussion going on about the best way to report counts
for outer-join situations, but I think most of what's in the patch would
not change if we revise that, so I'm going to go ahead and commit it as-is.
Documentation changes to follow (they weren't in the submitted patch
either).
Marko Tiikkaja, reviewed by Marc Cousin, somewhat revised by Tom
This patch also removes buffer-usage statistics from the track_counts
output, since this (or the global server statistics) is deemed to be a better
interface to this information.
Itagaki Takahiro, reviewed by Euler Taveira de Oliveira.
file portability/instr_time.h, and add a couple more macros to eliminate
some abstraction leakage we formerly had. Also update psql to use this
header instead of its own copy of nearly the same code.
This commit in itself is just code cleanup and shouldn't change anything.
It lays some groundwork for the upcoming function-stats patch, though.
it is just the total time to do INSTR_TIME_SET_CURRENT(), and not any of
the other code involved in InstrStartNode/InstrStopNode. Even though I
fear we may end up reverting this patch altogether, we may as well have
the most correct version in our CVS archive.
return just a single tuple at a time. Currently the only such node
type is Hash, but I expect we will soon have indexscans that can return
tuple bitmaps. A side benefit is that EXPLAIN ANALYZE now shows the
correct tuple count for a Hash node.
Bruce Momjian
Michael Paquier
Etsuro Fujita
Amit Kapila
Fujii Masao
Tom Lane
Alvaro Herrera
Robert Haas
Magnus Hagander