Commit 27e1f1456 failed to process a pending asynchronous request made
for a given ForeignScan node in postgresReScanForeignScan() (if any) in
cases where we would only reset the next_tuple counter in that function,
contradicting the assumption that there should be no pending
asynchronous requests that have been made for async-capable subplans for
the parent Append node after ReScan. This led to an assert failure in
an assert-enabled build. I think this would also lead to mis-rewinding
the cursor in that function in the case where we have already fetched
one batch for the ForeignScan node and the asynchronous request has been
made for the second batch, because even in that case we would just reset
the counter when called from that function, so we would fail to execute
MOVE BACKWARD ALL.
To fix, modify that function to process the asynchronous request before
restarting the scan.
While at it, add a comment to a function to match other places.
Per bug #17344 from Alexander Lakhin. Back-patch to v14 where the
aforesaid commit came in.
Patch by me. Test case by Alexander Lakhin, adjusted by me. Reviewed
and tested by Alexander Lakhin and Dmitry Dolgov.
Discussion: https://postgr.es/m/17344-226b78b00de73a7e@postgresql.org
One code path related to this flavor of ALTER TABLE was checking that
the relation to detach has to be a normal table or a partitioned table,
which would fail if using the command with a different relation kind.
Views, sequences and materialized views cannot be part of a partition
tree, so these would cause the command to fail anyway, but the assertion
was triggered. Foreign tables can be part of a partition tree, and
again the assertion would have failed. The simplest solution is just to
remove this assertion, so as we get the same failure as the
non-concurrent code path.
While on it, add a regression test in postgres_fdw for the concurrent
partition detach of a foreign table, as per a suggestion from Alexander
Lakhin.
Issue introduced in 71f4c8c.
Reported-by: Alexander Lakhin
Author: Michael Paquier, Alexander Lakhin
Reviewed-by: Peter Eisentraut, Kyotaro Horiguchi
Discussion: https://postgr.es/m/17339-a9e09aaf38a3457a@postgresql.org
Backpatch-through: 14
Memoize would always use the hash equality operator for the cache key
types to determine if the current set of parameters were the same as some
previously cached set. Certain types such as floating points where -0.0
and +0.0 differ in their binary representation but are classed as equal by
the hash equality operator may cause problems as unless the join uses the
same operator it's possible that whichever join operator is being used
would be able to distinguish the two values. In which case we may
accidentally return in the incorrect rows out of the cache.
To fix this here we add a binary mode to Memoize to allow it to the
current set of parameters to previously cached values by comparing
bit-by-bit rather than logically using the hash equality operator. This
binary mode is always used for LATERAL joins and it's used for normal
joins when any of the join operators are not hashable.
Reported-by: Tom Lane
Author: David Rowley
Discussion: https://postgr.es/m/3004308.1632952496@sss.pgh.pa.us
Backpatch-through: 14, where Memoize was added
Commit c7b7311f6 adjusted conversion_error_callback to always use
information from the query's rangetable, to avoid doing catalog lookups
in an already-failed transaction. However, as a result of the utterly
inadequate documentation for make_tuple_from_result_row, I failed to
realize that fsstate could be NULL in some contexts. That led to a
crash if we got a conversion error in such a context. Fix by falling
back to the previous coding when fsstate is NULL. Improve the
commentary, too.
Per report from Andrey Borodin. Back-patch to 9.6, like the previous
patch.
Discussion: https://postgr.es/m/08916396-55E4-4D68-AB3A-BD6066F9E5C0@yandex-team.ru
postgres_fdw imported generated columns from the remote tables as plain
columns, and caused failures like "ERROR: cannot insert a non-DEFAULT
value into column "foo"" when inserting into the foreign tables, as it
tried to insert values into the generated columns. To fix, we do the
following under the assumption that generated columns in a postgres_fdw
foreign table are defined so that they represent generated columns in
the underlying remote table:
* Send DEFAULT for the generated columns to the foreign server on insert
or update, not generated column values computed on the local server.
* Add to postgresImportForeignSchema() an option "import_generated" to
include column generated expressions in the definitions of foreign
tables imported from a foreign server. The option is true by default.
The assumption seems reasonable, because that would make a query of the
postgres_fdw foreign table return values for the generated columns that
are consistent with the generated expression.
While here, fix another issue in postgresImportForeignSchema(): it tried
to include column generated expressions as column default expressions in
the foreign table definitions when the import_default option was enabled.
Per bug #16631 from Daniel Cherniy. Back-patch to v12 where generated
columns were added.
Discussion: https://postgr.es/m/16631-e929fe9db0ffc7cf%40postgresql.org
A pending asynchronous request is handled by process_pending_request(),
which previously not only processed an in-progress remote query but
performed ExecForeignScan() to produce a tuple to return to the local
server asynchronously from the result of the remote query. But that led
to a server crash when executing a query or led to an "InstrStartNode
called twice in a row" or "InstrEndLoop called on running node" failure
when doing EXPLAIN ANALYZE of it, in cases where the plan tree for it
contained multiple async-capable nodes accessing the same
initplan/subplan that contained multiple async-capable nodes scanning
the same foreign tables as for the parent async-capable nodes, as
reported by Andrey Lepikhov. The reason is that the second step in
process_pending_request() invoked when executing the initplan/subplan
for one of the parent async-capable nodes caused recursive execution of
the initplan/subplan for another of the parent async-capable nodes.
To fix, split process_pending_request() into the two steps and postpone
the second step until ForeignAsyncConfigureWait() is called for each of
the pending asynchronous requests. Also, in ExecAppendAsyncEventWait()
we assumed that FDWs would register at least one wait event in a
WaitEventSet created there when they were called from
ForeignAsyncConfigureWait() in that function, but allow FDWs to register
zero wait events in the WaitEventSet; modify ExecAppendAsyncEventWait()
to just return in that case.
Oversight in commit 27e1f1456. Back-patch to v14 where that commit went
in.
Andrey Lepikhov and Etsuro Fujita
Discussion: https://postgr.es/m/fe5eaa19-1704-e4a4-76ee-3b9d37ade399@postgrespro.ru
"Result Cache" was never a great name for this node, but nobody managed
to come up with another name that anyone liked enough. That was until
David Johnston mentioned "Node Memoization", which Tom Lane revised to
just "Memoize". People seem to like "Memoize", so let's do the rename.
Reviewed-by: Justin Pryzby
Discussion: https://postgr.es/m/20210708165145.GG1176@momjian.us
Backpatch-through: 14, where Result Cache was introduced
In 86dc90056, I'd written find_modifytable_subplan with the assumption
that if the immediate child of a ModifyTable is a Result, it must be
a projecting Result with a subplan. However, if the UPDATE or DELETE
has a provably-constant-false WHERE clause, that's not so: we'll
generate a dummy subplan with a childless Result. Add the missing
null-check so we don't crash on such cases.
Per report from Alexander Pyhalov.
Discussion: https://postgr.es/m/b9a6f53549456b2f3e2fd150dcd79d72@postgrespro.ru
Previously the values such as '100$%$#$#', '9,223,372,' were accepted and
treated as valid integers for postgres_fdw options batch_size and fetch_size.
Whereas this is not the case with fdw_startup_cost and fdw_tuple_cost options
for which an error is thrown. This was because endptr was not used
while converting strings to integers using strtol.
This commit changes the logic so that it uses parse_int function
instead of strtol as it serves the purpose by returning false in case
if it is unable to convert the string to integer. Note that
this function also rounds off the values such as '100.456' to 100 and
'100.567' or '100.678' to 101.
While on this, use parse_real for fdw_startup_cost and fdw_tuple_cost options.
Since parse_int and parse_real are being used for reloptions and GUCs,
it is more appropriate to use in postgres_fdw rather than using strtol
and strtod directly.
Back-patch to v14.
Author: Bharath Rupireddy
Reviewed-by: Ashutosh Bapat, Tom Lane, Kyotaro Horiguchi, Fujii Masao
Discussion: https://postgr.es/m/CALj2ACVMO6wY5Pc4oe1OCgUOAtdjHuFsBDw8R5uoYR86eWFQDA@mail.gmail.com
As in 50371df26, this is a bad idea since the callback can't really
know what error is being thrown and thus whether or not it is safe
to attempt catalog accesses. Rather than pushing said accesses into
the mainline code where they'd usually be a waste of cycles, we can
look at the query's rangetable instead.
This change does mean that we'll be printing query aliases (if any
were used) rather than the table or column's true name. But that
doesn't seem like a bad thing: it's certainly a more useful definition
in self-join cases, for instance. In any case, it seems unlikely that
any applications would be depending on this detail, so it seems safe
to change.
Patch by me. Original complaint by Andres Freund; Bharath Rupireddy
noted the connection to conversion_error_callback.
Discussion: https://postgr.es/m/20210106020229.ne5xnuu6wlondjpe@alap3.anarazel.de
The queries involving ft1_nopw don't stably return the same row
anymore. I surmise that an autovacuum hitting "S 1"."T 1"
right after the updates introduced by f61db909d/5843659d0 freed
some space, changing where subsequent insertions get stored.
It's only by good luck that these results were stable before,
though, since a LIMIT without ORDER BY isn't well defined,
and it's not like we've ever treated that table as append-only
in this test script.
Since we only really care whether these commands succeed or not,
just replace "SELECT *" with "SELECT 1".
Report: https://buildfarm.postgresql.org/cgi-bin/show_log.pl?nm=crake&dt=2021-06-23%2019%3A52%3A08
Buildfarm members ayu and tern have sometimes shown a different
plan than expected for this query. I'd been unable to reproduce
that before today, but I finally realized what is happening.
If there is a concurrent open transaction (probably an autovacuum
run in the buildfarm, but this can also be arranged manually),
then the index entries for the rows removed by the DELETE a few
lines up are not killed promptly, causing a change in the planner's
estimate of the extremal value of ft2.c1, which moves the rowcount
estimate for "c1 > 1100" by enough to change the join plan from
nestloop to hash.
To fix, change the query condition to "c1 > 1000", causing the
hash plan to be preferred whether or not a concurrent open
transaction exists. Since this UPDATE is tailored to be a no-op,
nothing else changes.
Report: https://buildfarm.postgresql.org/cgi-bin/show_log.pl?nm=ayu&dt=2021-06-09%2022%3A45%3A48
Report: https://buildfarm.postgresql.org/cgi-bin/show_log.pl?nm=ayu&dt=2021-06-13%2022%3A38%3A18
Report: https://buildfarm.postgresql.org/cgi-bin/show_log.pl?nm=tern&dt=2021-06-20%2004%3A55%3A36
Commit b676ac443b optimized handling of tuple slots with bulk inserts
into foreign tables, so that the slots are initialized only once and
reused for all batches. The data was however copied into the slots only
after the initialization, inserting duplicate values when the slot gets
reused. Fixed by moving the ExecCopySlot outside the init branch.
The existing postgres_fdw tests failed to catch this due to inserting
data into foreign tables without unique indexes, and then checking only
the number of inserted rows. This adds a new test with both a unique
index and a check of inserted values.
Reported-by: Alexander Pyhalov
Discussion: https://postgr.es/m/7a8cf8d56b3d18e5c0bccd6cd42d04ac%40postgrespro.ru
The FE/BE protocol identifies parameters with an Int16 index, which
limits the maximum number of parameters per query to 65535. With
batching added to postges_fdw this limit is much easier to hit, as
the whole batch is essentially a single query, making this error much
easier to hit.
The failures are a bit unpredictable, because it also depends on the
number of columns in the query. So instead of just failing, this patch
tweaks the batch_size to not exceed the maximum number of parameters.
Reported-by: Hou Zhijie <houzj.fnst@cn.fujitsu.com>
Reviewed-by: Bharath Rupireddy <bharath.rupireddyforpostgres@gmail.com>
Discussion: https://postgr.es/m/OS0PR01MB571603973C0AC2874AD6BF2594299%40OS0PR01MB5716.jpnprd01.prod.outlook.com
In cases where run-time pruning isn't required, the synchronous and
asynchronous subplans for an async-aware Append node determined using
classify_matching_subplans() should be re-used when rescanning the node,
but the previous code re-determined them using that function repeatedly
each time when rescanning the node, leading to incorrect results in a
normal build and an Assert failure in an Assert-enabled build as that
function doesn't assume that it's called repeatedly in such cases. Fix
the code as mentioned above.
My oversight in commit 27e1f1456.
While at it, initialize async-related pointers/variables to NULL/zero
explicitly in ExecInitAppend() and ExecReScanAppend(), just to be sure.
(The variables would have been set to zero before we get to the latter
function, but let's do so.)
Reviewed-by: Kyotaro Horiguchi
Discussion: https://postgr.es/m/CAPmGK16Q4B2_KY%2BJH7rb7wQbw54AUprp7TMekGTd2T1B62yysQ%40mail.gmail.com
Commit 86dc90056 expects that FDWs can cope with whole-row Vars for
their tables, even if the Vars are marked with vartype RECORDOID.
Previously, whole-row Vars generated by the planner had vartype equal
to the relevant table's rowtype OID. (The point behind this change is
to enable sharing of resjunk columns across inheritance child tables.)
It turns out that postgres_fdw fails to cope with this, though through
bad fortune none of its test cases exposed that. Things mostly work,
but when we try to read back a value of such a Var, the expected
rowtype is not available to record_in(). Fortunately, it's not
difficult to hack up the tupdesc that controls this process to
substitute the foreign table's rowtype for RECORDOID. Thus we can
solve the runtime problem while still sharing the resjunk column
with other tables.
Per report from Alexander Pyhalov.
Discussion: https://postgr.es/m/7817fb9ebd6661cdf9b67dec6e129a78@postgrespro.ru
Commit 428b260f8 broke planning of cases where row marks are needed
(SELECT FOR UPDATE, etc) and one of the query's tables is a foreign
table that has regular table(s) as inheritance children. We got the
reverse case right, but apparently were thinking that foreign tables
couldn't be inheritance parents. Not so; so we need to be able to
add a CTID junk column while adding a new child, not only a wholerow
junk column.
Back-patch to v12 where the faulty code came in.
Amit Langote
Discussion: https://postgr.es/m/CA+HiwqEmo3FV1LAQ4TVyS2h1WM=kMkZUmbNuZSCnfHvMcUcPeA@mail.gmail.com
Commits 27e1f1456 and 86dc90056, which were independently discussed,
cause a crash when executing an inherited foreign UPDATE/DELETE query
with asynchronous execution enabled, where children of an Append node
that is the direct/indirect child of the ModifyTable node are rewritten
so as to modify foreign tables directly by postgresPlanDirectModify();
as in that case the direct modifications are executed asynchronously,
which is not currently supported by asynchronous execution. Fix by
disabling asynchronous execution of the direct modifications in that
function.
Author: Etsuro Fujita
Reviewed-by: Amit Langote
Discussion: https://postgr.es/m/CAPmGK158e9sJOfuWxfn%2B0ynrspXQU3JhNjSCbaoeSzMvnga%2Bbw%40mail.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
Commit 93f414614 improved a pre-existing test case so that it would
show whether or not termination of the "remote" worker process happened.
This soon exposed that, when debug_invalidate_system_caches_always
(nee CLOBBER_CACHE_ALWAYS) is enabled, no such termination occurs.
That's because cache invalidation forces postgres_fdw connections
to be dropped at end of transaction, so that there's no worker to
terminate. There's a race condition as to whether the worker will
manage to get out of the BackendStatusArray before we look, but at
least on buildfarm member hyrax, it's failed twice in two attempts.
Rather than re-lobotomizing the test, let's fix this by transiently
disabling debug_invalidate_system_caches_always. (Hooray for that
being just a GUC nowadays, rather than a compile-time option.)
If this proves not to be enough to make the test stable, we can
do the other thing instead.
Discussion: https://postgr.es/m/3854538.1620081771@sss.pgh.pa.us
Commit 8ff1c94649 allowed TRUNCATE command to truncate foreign tables.
Previously the information about "ONLY" options specified in TRUNCATE
command were passed to the foreign data wrapper. Then postgres_fdw
constructed the TRUNCATE command to issue the remote server and
included "ONLY" options in it based on the passed information.
On the other hand, "ONLY" options specified in SELECT, UPDATE or DELETE
have no effect when accessing or modifying the remote table, i.e.,
are not passed to the foreign data wrapper. So it's inconsistent to
make only TRUNCATE command pass the "ONLY" options to the foreign data
wrapper. Therefore this commit changes the TRUNCATE command so that
it doesn't pass the "ONLY" options to the foreign data wrapper,
for the consistency with other statements. Also this commit changes
postgres_fdw so that it always doesn't include "ONLY" options in
the TRUNCATE command that it constructs.
Author: Fujii Masao
Reviewed-by: Bharath Rupireddy, Kyotaro Horiguchi, Justin Pryzby, Zhihong Yu
Discussion: https://postgr.es/m/551ed8c1-f531-818b-664a-2cecdab99cd8@oss.nttdata.com
The tests introduced in 32a9c0b for connections broken and
re-established rely on pg_terminate_backend() for their logic. When
these were introduced, this function simply sent a signal to a backend
without waiting for the operation to complete, and the tests repeatedly
looked at pg_stat_activity to check if the operation was completed or
not. Since aaf0432, it is possible to define a timeout to make
pg_terminate_backend() wait for a certain duration, so make use of it,
with a timeout reasonably large enough (3min) to give enough room for
the tests to pass even on slow machines.
Some measurements show that the tests of postgres_fdw are much faster
with this change. For example, on my laptop, they now take 4s instead
of 6s.
Author: Bharath Rupireddy
Discussion: https://postgr.es/m/CALj2ACXGY_EfGrMTjKjHy2zi-u1u9rdeioU_fro0T6Jo8t56KQ@mail.gmail.com
This commit introduces new foreign data wrapper API for TRUNCATE.
It extends TRUNCATE command so that it accepts foreign tables as
the targets to truncate and invokes that API. Also it extends postgres_fdw
so that it can issue TRUNCATE command to foreign servers, by adding
new routine for that TRUNCATE API.
The information about options specified in TRUNCATE command, e.g.,
ONLY, CACADE, etc is passed to FDW via API. The list of foreign tables to
truncate is also passed to FDW. FDW truncates the foreign data sources
that the passed foreign tables specify, based on those information.
For example, postgres_fdw constructs TRUNCATE command using them
and issues it to the foreign server.
For performance, TRUNCATE command invokes the FDW routine for
TRUNCATE once per foreign server that foreign tables to truncate belong to.
Author: Kazutaka Onishi, Kohei KaiGai, slightly modified by Fujii Masao
Reviewed-by: Bharath Rupireddy, Michael Paquier, Zhihong Yu, Alvaro Herrera, Stephen Frost, Ashutosh Bapat, Amit Langote, Daniel Gustafsson, Ibrar Ahmed, Fujii Masao
Discussion: https://postgr.es/m/CAOP8fzb_gkReLput7OvOK+8NHgw-RKqNv59vem7=524krQTcWA@mail.gmail.com
Discussion: https://postgr.es/m/CAJuF6cMWDDqU-vn_knZgma+2GMaout68YUgn1uyDnexRhqqM5Q@mail.gmail.com
By default, have libpq set the TLS extension "Server Name Indication" (SNI).
This allows an SNI-aware SSL proxy to route connections. (This
requires a proxy that is aware of the PostgreSQL protocol, not just
any SSL proxy.)
In the future, this could also allow the server to use different SSL
certificates for different host specifications. (That would require
new server functionality. This would be the client-side functionality
for that.)
Since SNI makes the host name appear in cleartext in the network
traffic, this might be undesirable in some cases. Therefore, also add
a libpq connection option "sslsni" to turn it off.
Discussion: https://www.postgresql.org/message-id/flat/7289d5eb-62a5-a732-c3b9-438cee2cb709%40enterprisedb.com
Commit f49bcd4ef3 disallowed postgres_fdw to import table partitions.
Because all data can be accessed through the partitioned table which
is the root of the partitioning hierarchy, importing only partitioned
table should allow access to all the data without creating extra objects.
This is a reasonable default when importing a whole schema. But there
may be the case where users want to explicitly import one of
a partitioned tables' partitions.
For that use case, this commit allows postgres_fdw to import tables or
foreign tables which are partitions of some other table only when they
are explicitly specified in LIMIT TO clause. It doesn't change
the behavior that any partitions not specified in LIMIT TO are
automatically excluded in IMPORT FOREIGN SCHEMA command.
Author: Matthias van de Meent
Reviewed-by: Bernd Helmle, Amit Langote, Michael Paquier, Fujii Masao
Discussion: https://postgr.es/m/CAEze2Whwg4i=mzApMe+PXxCEfgoZmHGqdqQFW7J4bmj_5p6t1A@mail.gmail.com
This commit adds a new option keep_connections that controls
whether postgres_fdw keeps the connections to the foreign server open
so that the subsequent queries can re-use them. This option can only be
specified for a foreign server. The default is on. If set to off,
all connections to the foreign server will be discarded
at the end of transaction. Closed connections will be re-established
when they are necessary by future queries using a foreign table.
This option is useful, for example, when users want to prevent
the connections from eating up the foreign servers connections
capacity.
Author: Bharath Rupireddy
Reviewed-by: Alexey Kondratov, Vignesh C, Fujii Masao
Discussion: https://postgr.es/m/CALj2ACVvrp5=AVp2PupEm+nAC8S4buqR3fJMmaCoc7ftT0aD2A@mail.gmail.com
Here we add a new executor node type named "Result Cache". The planner
can include this node type in the plan to have the executor cache the
results from the inner side of parameterized nested loop joins. This
allows caching of tuples for sets of parameters so that in the event that
the node sees the same parameter values again, it can just return the
cached tuples instead of rescanning the inner side of the join all over
again. Internally, result cache uses a hash table in order to quickly
find tuples that have been previously cached.
For certain data sets, this can significantly improve the performance of
joins. The best cases for using this new node type are for join problems
where a large portion of the tuples from the inner side of the join have
no join partner on the outer side of the join. In such cases, hash join
would have to hash values that are never looked up, thus bloating the hash
table and possibly causing it to multi-batch. Merge joins would have to
skip over all of the unmatched rows. If we use a nested loop join with a
result cache, then we only cache tuples that have at least one join
partner on the outer side of the join. The benefits of using a
parameterized nested loop with a result cache increase when there are
fewer distinct values being looked up and the number of lookups of each
value is large. Also, hash probes to lookup the cache can be much faster
than the hash probe in a hash join as it's common that the result cache's
hash table is much smaller than the hash join's due to result cache only
caching useful tuples rather than all tuples from the inner side of the
join. This variation in hash probe performance is more significant when
the hash join's hash table no longer fits into the CPU's L3 cache, but the
result cache's hash table does. The apparent "random" access of hash
buckets with each hash probe can cause a poor L3 cache hit ratio for large
hash tables. Smaller hash tables generally perform better.
The hash table used for the cache limits itself to not exceeding work_mem
* hash_mem_multiplier in size. We maintain a dlist of keys for this cache
and when we're adding new tuples and realize we've exceeded the memory
budget, we evict cache entries starting with the least recently used ones
until we have enough memory to add the new tuples to the cache.
For parameterized nested loop joins, we now consider using one of these
result cache nodes in between the nested loop node and its inner node. We
determine when this might be useful based on cost, which is primarily
driven off of what the expected cache hit ratio will be. Estimating the
cache hit ratio relies on having good distinct estimates on the nested
loop's parameters.
For now, the planner will only consider using a result cache for
parameterized nested loop joins. This works for both normal joins and
also for LATERAL type joins to subqueries. It is possible to use this new
node for other uses in the future. For example, to cache results from
correlated subqueries. However, that's not done here due to some
difficulties obtaining a distinct estimation on the outer plan to
calculate the estimated cache hit ratio. Currently we plan the inner plan
before planning the outer plan so there is no good way to know if a result
cache would be useful or not since we can't estimate the number of times
the subplan will be called until the outer plan is generated.
The functionality being added here is newly introducing a dependency on
the return value of estimate_num_groups() during the join search.
Previously, during the join search, we only ever needed to perform
selectivity estimations. With this commit, we need to use
estimate_num_groups() in order to estimate what the hit ratio on the
result cache will be. In simple terms, if we expect 10 distinct values
and we expect 1000 outer rows, then we'll estimate the hit ratio to be
99%. Since cache hits are very cheap compared to scanning the underlying
nodes on the inner side of the nested loop join, then this will
significantly reduce the planner's cost for the join. However, it's
fairly easy to see here that things will go bad when estimate_num_groups()
incorrectly returns a value that's significantly lower than the actual
number of distinct values. If this happens then that may cause us to make
use of a nested loop join with a result cache instead of some other join
type, such as a merge or hash join. Our distinct estimations have been
known to be a source of trouble in the past, so the extra reliance on them
here could cause the planner to choose slower plans than it did previous
to having this feature. Distinct estimations are also fairly hard to
estimate accurately when several tables have been joined already or when a
WHERE clause filters out a set of values that are correlated to the
expressions we're estimating the number of distinct value for.
For now, the costing we perform during query planning for result caches
does put quite a bit of faith in the distinct estimations being accurate.
When these are accurate then we should generally see faster execution
times for plans containing a result cache. However, in the real world, we
may find that we need to either change the costings to put less trust in
the distinct estimations being accurate or perhaps even disable this
feature by default. There's always an element of risk when we teach the
query planner to do new tricks that it decides to use that new trick at
the wrong time and causes a regression. Users may opt to get the old
behavior by turning the feature off using the enable_resultcache GUC.
Currently, this is enabled by default. It remains to be seen if we'll
maintain that setting for the release.
Additionally, the name "Result Cache" is the best name I could think of
for this new node at the time I started writing the patch. Nobody seems
to strongly dislike the name. A few people did suggest other names but no
other name seemed to dominate in the brief discussion that there was about
names. Let's allow the beta period to see if the current name pleases
enough people. If there's some consensus on a better name, then we can
change it before the release. Please see the 2nd discussion link below
for the discussion on the "Result Cache" name.
Author: David Rowley
Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu, Hou Zhijie
Tested-By: Konstantin Knizhnik
Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com
This removes "Add Result Cache executor node". It seems that something
weird is going on with the tracking of cache hits and misses as
highlighted by many buildfarm animals. It's not yet clear what the
problem is as other parts of the plan indicate that the cache did work
correctly, it's just the hits and misses that were being reported as 0.
This is especially a bad time to have the buildfarm so broken, so
reverting before too many more animals go red.
Discussion: https://postgr.es/m/CAApHDvq_hydhfovm4=izgWs+C5HqEeRScjMbOgbpC-jRAeK3Yw@mail.gmail.com
Here we add a new executor node type named "Result Cache". The planner
can include this node type in the plan to have the executor cache the
results from the inner side of parameterized nested loop joins. This
allows caching of tuples for sets of parameters so that in the event that
the node sees the same parameter values again, it can just return the
cached tuples instead of rescanning the inner side of the join all over
again. Internally, result cache uses a hash table in order to quickly
find tuples that have been previously cached.
For certain data sets, this can significantly improve the performance of
joins. The best cases for using this new node type are for join problems
where a large portion of the tuples from the inner side of the join have
no join partner on the outer side of the join. In such cases, hash join
would have to hash values that are never looked up, thus bloating the hash
table and possibly causing it to multi-batch. Merge joins would have to
skip over all of the unmatched rows. If we use a nested loop join with a
result cache, then we only cache tuples that have at least one join
partner on the outer side of the join. The benefits of using a
parameterized nested loop with a result cache increase when there are
fewer distinct values being looked up and the number of lookups of each
value is large. Also, hash probes to lookup the cache can be much faster
than the hash probe in a hash join as it's common that the result cache's
hash table is much smaller than the hash join's due to result cache only
caching useful tuples rather than all tuples from the inner side of the
join. This variation in hash probe performance is more significant when
the hash join's hash table no longer fits into the CPU's L3 cache, but the
result cache's hash table does. The apparent "random" access of hash
buckets with each hash probe can cause a poor L3 cache hit ratio for large
hash tables. Smaller hash tables generally perform better.
The hash table used for the cache limits itself to not exceeding work_mem
* hash_mem_multiplier in size. We maintain a dlist of keys for this cache
and when we're adding new tuples and realize we've exceeded the memory
budget, we evict cache entries starting with the least recently used ones
until we have enough memory to add the new tuples to the cache.
For parameterized nested loop joins, we now consider using one of these
result cache nodes in between the nested loop node and its inner node. We
determine when this might be useful based on cost, which is primarily
driven off of what the expected cache hit ratio will be. Estimating the
cache hit ratio relies on having good distinct estimates on the nested
loop's parameters.
For now, the planner will only consider using a result cache for
parameterized nested loop joins. This works for both normal joins and
also for LATERAL type joins to subqueries. It is possible to use this new
node for other uses in the future. For example, to cache results from
correlated subqueries. However, that's not done here due to some
difficulties obtaining a distinct estimation on the outer plan to
calculate the estimated cache hit ratio. Currently we plan the inner plan
before planning the outer plan so there is no good way to know if a result
cache would be useful or not since we can't estimate the number of times
the subplan will be called until the outer plan is generated.
The functionality being added here is newly introducing a dependency on
the return value of estimate_num_groups() during the join search.
Previously, during the join search, we only ever needed to perform
selectivity estimations. With this commit, we need to use
estimate_num_groups() in order to estimate what the hit ratio on the
result cache will be. In simple terms, if we expect 10 distinct values
and we expect 1000 outer rows, then we'll estimate the hit ratio to be
99%. Since cache hits are very cheap compared to scanning the underlying
nodes on the inner side of the nested loop join, then this will
significantly reduce the planner's cost for the join. However, it's
fairly easy to see here that things will go bad when estimate_num_groups()
incorrectly returns a value that's significantly lower than the actual
number of distinct values. If this happens then that may cause us to make
use of a nested loop join with a result cache instead of some other join
type, such as a merge or hash join. Our distinct estimations have been
known to be a source of trouble in the past, so the extra reliance on them
here could cause the planner to choose slower plans than it did previous
to having this feature. Distinct estimations are also fairly hard to
estimate accurately when several tables have been joined already or when a
WHERE clause filters out a set of values that are correlated to the
expressions we're estimating the number of distinct value for.
For now, the costing we perform during query planning for result caches
does put quite a bit of faith in the distinct estimations being accurate.
When these are accurate then we should generally see faster execution
times for plans containing a result cache. However, in the real world, we
may find that we need to either change the costings to put less trust in
the distinct estimations being accurate or perhaps even disable this
feature by default. There's always an element of risk when we teach the
query planner to do new tricks that it decides to use that new trick at
the wrong time and causes a regression. Users may opt to get the old
behavior by turning the feature off using the enable_resultcache GUC.
Currently, this is enabled by default. It remains to be seen if we'll
maintain that setting for the release.
Additionally, the name "Result Cache" is the best name I could think of
for this new node at the time I started writing the patch. Nobody seems
to strongly dislike the name. A few people did suggest other names but no
other name seemed to dominate in the brief discussion that there was about
names. Let's allow the beta period to see if the current name pleases
enough people. If there's some consensus on a better name, then we can
change it before the release. Please see the 2nd discussion link below
for the discussion on the "Result Cache" name.
Author: David Rowley
Reviewed-by: Andy Fan, Justin Pryzby, Zhihong Yu
Tested-By: Konstantin Knizhnik
Discussion: https://postgr.es/m/CAApHDvrPcQyQdWERGYWx8J%2B2DLUNgXu%2BfOSbQ1UscxrunyXyrQ%40mail.gmail.com
Discussion: https://postgr.es/m/CAApHDvq=yQXr5kqhRviT2RhNKwToaWr9JAN5t+5_PzhuRJ3wvg@mail.gmail.com
This patch makes two closely related sets of changes:
1. For UPDATE, the subplan of the ModifyTable node now only delivers
the new values of the changed columns (i.e., the expressions computed
in the query's SET clause) plus row identity information such as CTID.
ModifyTable must re-fetch the original tuple to merge in the old
values of any unchanged columns. The core advantage of this is that
the changed columns are uniform across all tables of an inherited or
partitioned target relation, whereas the other columns might not be.
A secondary advantage, when the UPDATE involves joins, is that less
data needs to pass through the plan tree. The disadvantage of course
is an extra fetch of each tuple to be updated. However, that seems to
be very nearly free in context; even worst-case tests don't show it to
add more than a couple percent to the total query cost. At some point
it might be interesting to combine the re-fetch with the tuple access
that ModifyTable must do anyway to mark the old tuple dead; but that
would require a good deal of refactoring and it seems it wouldn't buy
all that much, so this patch doesn't attempt it.
2. For inherited UPDATE/DELETE, instead of generating a separate
subplan for each target relation, we now generate a single subplan
that is just exactly like a SELECT's plan, then stick ModifyTable
on top of that. To let ModifyTable know which target relation a
given incoming row refers to, a tableoid junk column is added to
the row identity information. This gets rid of the horrid hack
that was inheritance_planner(), eliminating O(N^2) planning cost
and memory consumption in cases where there were many unprunable
target relations.
Point 2 of course requires point 1, so that there is a uniform
definition of the non-junk columns to be returned by the subplan.
We can't insist on uniform definition of the row identity junk
columns however, if we want to keep the ability to have both
plain and foreign tables in a partitioning hierarchy. Since
it wouldn't scale very far to have every child table have its
own row identity column, this patch includes provisions to merge
similar row identity columns into one column of the subplan result.
In particular, we can merge the whole-row Vars typically used as
row identity by FDWs into one column by pretending they are type
RECORD. (It's still okay for the actual composite Datums to be
labeled with the table's rowtype OID, though.)
There is more that can be done to file down residual inefficiencies
in this patch, but it seems to be committable now.
FDW authors should note several API changes:
* The argument list for AddForeignUpdateTargets() has changed, and so
has the method it must use for adding junk columns to the query. Call
add_row_identity_var() instead of manipulating the parse tree directly.
You might want to reconsider exactly what you're adding, too.
* PlanDirectModify() must now work a little harder to find the
ForeignScan plan node; if the foreign table is part of a partitioning
hierarchy then the ForeignScan might not be the direct child of
ModifyTable. See postgres_fdw for sample code.
* To check whether a relation is a target relation, it's no
longer sufficient to compare its relid to root->parse->resultRelation.
Instead, check it against all_result_relids or leaf_result_relids,
as appropriate.
Amit Langote and Tom Lane
Discussion: https://postgr.es/m/CA+HiwqHpHdqdDn48yCEhynnniahH78rwcrv1rEX65-fsZGBOLQ@mail.gmail.com
This implements asynchronous execution, which runs multiple parts of a
non-parallel-aware Append concurrently rather than serially to improve
performance when possible. Currently, the only node type that can be
run concurrently is a ForeignScan that is an immediate child of such an
Append. In the case where such ForeignScans access data on different
remote servers, this would run those ForeignScans concurrently, and
overlap the remote operations to be performed simultaneously, so it'll
improve the performance especially when the operations involve
time-consuming ones such as remote join and remote aggregation.
We may extend this to other node types such as joins or aggregates over
ForeignScans in the future.
This also adds the support for postgres_fdw, which is enabled by the
table-level/server-level option "async_capable". The default is false.
Robert Haas, Kyotaro Horiguchi, Thomas Munro, and myself. This commit
is mostly based on the patch proposed by Robert Haas, but also uses
stuff from the patch proposed by Kyotaro Horiguchi and from the patch
proposed by Thomas Munro. Reviewed by Kyotaro Horiguchi, Konstantin
Knizhnik, Andrey Lepikhov, Movead Li, Thomas Munro, Justin Pryzby, and
others.
Discussion: https://postgr.es/m/CA%2BTgmoaXQEt4tZ03FtQhnzeDEMzBck%2BLrni0UWHVVgOTnA6C1w%40mail.gmail.com
Discussion: https://postgr.es/m/CA%2BhUKGLBRyu0rHrDCMC4%3DRn3252gogyp1SjOgG8SEKKZv%3DFwfQ%40mail.gmail.com
Discussion: https://postgr.es/m/20200228.170650.667613673625155850.horikyota.ntt%40gmail.com
This partially reverts 096bbf7 and 9d2d457, undoing the libpq changes as
it could cause breakages in distributions that share one single libpq
version across multiple major versions of Postgres for extensions and
applications linking to that.
Note that the backend is unchanged here, and it still disables SSL
compression while simplifying the underlying catalogs that tracked if
compression was enabled or not for a SSL connection.
Per discussion with Tom Lane and Daniel Gustafsson.
Discussion: https://postgr.es/m/YEbq15JKJwIX+S6m@paquier.xyz
Per buildfarm member crake, any servers including a postgres_fdw server
with this option set would fail to do a pg_upgrade properly as the
option got hidden in f9264d1 by becoming a debug option, making the
restore of the FDW server fail.
This changes back the option in libpq to be visible, but still inactive
to fix this upgrade issue.
Discussion: https://postgr.es/m/YEbq15JKJwIX+S6m@paquier.xyz
PostgreSQL disabled compression as of e3bdb2d and the documentation
recommends against using it since. Additionally, SSL compression has
been disabled in OpenSSL since version 1.1.0, and was disabled in many
distributions long before that. The most recent TLS version, TLSv1.3,
disallows compression at the protocol level.
This commit removes the feature itself, removing support for the libpq
parameter sslcompression (parameter still listed for compatibility
reasons with existing connection strings, just ignored), and removes
the equivalent field in pg_stat_ssl and de facto PgBackendSSLStatus.
Note that, on top of removing the ability to activate compression by
configuration, compression is actively disabled in both frontend and
backend to avoid overrides from local configurations.
A TAP test is added for deprecated SSL parameters to check after
backwards compatibility.
Bump catalog version.
Author: Daniel Gustafsson
Reviewed-by: Peter Eisentraut, Magnus Hagander, Michael Paquier
Discussion: https://postgr.es/m/7E384D48-11C5-441B-9EC3-F7DB1F8518F6@yesql.se
Add another method to specify CRLs, hashed directory method, for both
server and client side. This offers a means for server or libpq to
load only CRLs that are required to verify a certificate. The CRL
directory is specifed by separate GUC variables or connection options
ssl_crl_dir and sslcrldir, alongside the existing ssl_crl_file and
sslcrl, so both methods can be used at the same time.
Author: Kyotaro Horiguchi <horikyota.ntt@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/20200731.173911.904649928639357911.horikyota.ntt@gmail.com
A cross-partition update on a partitioned table is implemented as a
delete followed by an insert. With foreign partitions, this was however
causing issues, because the FDW and core may disagree on when to enable
batching. postgres_fdw was only allowing batching for plain inserts
(CMD_INSERT) while core was trying to batch the insert component of the
cross-partition update. Fix by restricting core to apply batching only
to plain CMD_INSERT queries.
It's possible to allow batching for cross-partition updates, but that
will require more extensive changes, so better to leave that for a
separate patch.
Author: Amit Langote
Reviewed-by: Tomas Vondra, Takayuki Tsunakawa
Discussion: https://postgr.es/m/20200628151002.7x5laxwpgvkyiu3q@development
Commit 08d2d58a2 added an assertion assuming that the retrieved_rows
estimate for a foreign relation, which is re-used to cost pre-sorted
foreign paths with local stats, is set to at least one row in
estimate_path_cost_size(), which isn't correct because if the relation
is a foreign table with tuples=0, the estimate would be set to 0 there
when not using remote estimates.
Per bug #16807 from Alexander Lakhin. Back-patch to v13 where the
aforementioned commit went in.
Author: Etsuro Fujita
Reviewed-by: Kyotaro Horiguchi
Discussion: https://postgr.es/m/16807-9fe4e08fbaa5c7ce%40postgresql.org
The regression tests added in commits 708d165ddb and 411ae64997 caused
buildfarm failures when CLOBBER_CACHE_ALWAYS was enabled.
This commit stabilizes those tests.
The foreign server connections established by postgres_fdw behaves
differently depending on whether CLOBBER_CACHE_ALWAYS is enabled or not.
If it's not enabled, those connections are cached. On the other hand,
if it's enabled, when the connections are established outside transaction
block, they are not cached (i.e., they are immediately closed at the end of
query that established them). So the subsequent postgres_fdw_get_connections()
cannot list those connections and postgres_fdw_disconnect() cannot close them
(because they are already closed).
When the connections are established inside transaction block, they are
cached whether CLOBBER_CACHE_ALWAYS was enabled or not. But if it's enabled,
they are immediately marked as invalid, otherwise not. This causes the
subsequent postgres_fdw_get_connections() to return different result in
"valid" column depending on whether CLOBBER_CACHE_ALWAYS was enabled or not.
This commit prevents the above differences of behavior from
affecting the regression tests.
Per buildfarm failure on trilobite.
Original patch by Bharath Rupireddy. I (Fujii Masao) extracted
the regression test fix from that and revised it a bit.
Reported-by: Tom Lane
Author: Bharath Rupireddy
Reviewed-by: Fujii Masao
Discussion: https://postgr.es/m/2688508.1611865371@sss.pgh.pa.us
The regression test added in commit 411ae64997 caused buildfarm failures.
The cause of them was that the order of warning messages output in the test
was not stable. To fix this, this commit sets client_min_messages to ERROR
temporarily when performing the test generating those warnings.
Per buildfarm failures.
Discussion: https://postgr.es/m/2147113.1611644754@sss.pgh.pa.us
This commit introduces two new functions postgres_fdw_disconnect()
and postgres_fdw_disconnect_all(). The former function discards
the cached connections to the specified foreign server. The latter discards
all the cached connections. If the connection is used in the current
transaction, it's not closed and a warning message is emitted.
For example, these functions are useful when users want to explicitly
close the foreign server connections that are no longer necessary and
then to prevent them from eating up the foreign servers connections
capacity.
Author: Bharath Rupireddy, tweaked a bit by Fujii Masao
Reviewed-by: Alexey Kondratov, Zhijie Hou, Zhihong Yu, Fujii Masao
Discussion: https://postgr.es/m/CALj2ACVvrp5=AVp2PupEm+nAC8S4buqR3fJMmaCoc7ftT0aD2A@mail.gmail.com
Extends the FDW API to allow batching inserts into foreign tables. That
is usually much more efficient than inserting individual rows, due to
high latency for each round-trip to the foreign server.
It was possible to implement something similar in the regular FDW API,
but it was inconvenient and there were issues with reporting the number
of actually inserted rows etc. This extends the FDW API with two new
functions:
* GetForeignModifyBatchSize - allows the FDW picking optimal batch size
* ExecForeignBatchInsert - inserts a batch of rows at once
Currently, only INSERT queries support batching. Support for DELETE and
UPDATE may be added in the future.
This also implements batching for postgres_fdw. The batch size may be
specified using "batch_size" option both at the server and table level.
The initial patch version was written by me, but it was rewritten and
improved in many ways by Takayuki Tsunakawa.
Author: Takayuki Tsunakawa
Reviewed-by: Tomas Vondra, Amit Langote
Discussion: https://postgr.es/m/20200628151002.7x5laxwpgvkyiu3q@development
This commit adds function postgres_fdw_get_connections() to return
the foreign server names of all the open connections that postgres_fdw
established from the local session to the foreign servers. This function
also returns whether each connection is valid or not.
This function is useful when checking all the open foreign server connections.
If we found some connection to drop, from the result of function, probably
we can explicitly close them by the function that upcoming commit will add.
This commit bumps the version of postgres_fdw to 1.1 since it adds
new function.
Author: Bharath Rupireddy, tweaked by Fujii Masao
Reviewed-by: Zhijie Hou, Alexey Kondratov, Zhihong Yu, Fujii Masao
Discussion: https://postgr.es/m/2d5cb0b3-a6e8-9bbb-953f-879f47128faa@oss.nttdata.com
In postgres_fdw, the cached connections to foreign servers will not be
closed until the local session exits if the user mappings or foreign servers
that those connections depend on are dropped. Those connections can be
leaked.
To fix that connection leak issue, after a change to a pg_foreign_server
or pg_user_mapping catalog entry, this commit makes postgres_fdw close
the connections depending on that entry immediately if current
transaction has not used those connections yet. Otherwise, mark those
connections as invalid and then close them at the end of current transaction,
since they cannot be closed in the midst of the transaction using them.
Closed connections will be remade at the next opportunity if necessary.
Back-patch to all supported branches.
Author: Bharath Rupireddy
Reviewed-by: Zhihong Yu, Zhijie Hou, Fujii Masao
Discussion: https://postgr.es/m/CALj2ACVNcGH_6qLY-4_tXz8JLvA+4yeBThRfxMz7Oxbk1aHcpQ@mail.gmail.com
Buildfarm member lorikeet is still failing the test from commit
32a9c0bdf, but now it's down to the should-have-foreseen-it problem
that the error message isn't what the expected-output file expects.
Let's see if we can get stable results by printing just the SQLSTATE.
I believe we'll reliably see ERRCODE_CONNECTION_FAILURE, since
pgfdw_report_error() will report that for any libpq-originated error.
There may be a better way to do this, but I'd like to get the
buildfarm back to green before we discuss further improvements.
Discussion: https://postgr.es/m/E1kPc9v-0005L4-2l@gemulon.postgresql.org
Discussion: https://postgr.es/m/2621622.1602184554@sss.pgh.pa.us
In postgres_fdw, once remote connections are established, they are cached
and re-used for subsequent queries and transactions. There can be some
cases where those cached connections are unavaiable, for example,
by the restart of remote server. In these cases, previously an error was
reported and the query accessing to remote server failed if new remote
transaction failed to start because the cached connection was broken.
This commit improves postgres_fdw so that new connection is remade
if broken connection is detected when starting new remote transaction.
This is useful to avoid unnecessary failure of queries when connection is
broken but can be reestablished.
Author: Bharath Rupireddy, tweaked a bit by Fujii Masao
Reviewed-by: Ashutosh Bapat, Tatsuhito Kasahara, Fujii Masao
Discussion: https://postgr.es/m/CALj2ACUAi23vf1WiHNar_LksM9EDOWXcbHCo-fD4Mbr1d=78YQ@mail.gmail.com
The "!" operator is our only built-in postfix operator. Remove it,
on the way to removal of grammar support for postfix operators.
There is also a "!!" prefix operator, but since it's been marked
deprecated for most of its existence, we might as well remove it too.
Also zap the SQL alias function numeric_fac(), which seems to have
equally little reason to live.
Mark Dilger, based on work by myself and Robert Haas;
review by John Naylor
Discussion: https://postgr.es/m/38ca86db-42ab-9b48-2902-337a0d6b8311@2ndquadrant.com
Until now, REINDEX was not able to work with partitioned tables and
indexes, forcing users to reindex partitions one by one. This extends
REINDEX INDEX and REINDEX TABLE so as they can accept a partitioned
index and table in input, respectively, to reindex all the partitions
assigned to them with physical storage (foreign tables, partitioned
tables and indexes are then discarded).
This shares some logic with schema and database REINDEX as each
partition gets processed in its own transaction after building a list of
relations to work on. This choice has the advantage to minimize the
number of invalid indexes to one partition with REINDEX CONCURRENTLY in
the event a cancellation or failure in-flight, as the only indexes
handled at once in a single REINDEX CONCURRENTLY loop are the ones from
the partition being working on.
Isolation tests are added to emulate some cases I bumped into while
developing this feature, particularly with the concurrent drop of a
leaf partition reindexed. However, this is rather limited as LOCK would
cause REINDEX to block in the first transaction building the list of
partitions.
Per its multi-transaction nature, this new flavor cannot run in a
transaction block, similarly to REINDEX SCHEMA, SYSTEM and DATABASE.
Author: Justin Pryzby, Michael Paquier
Reviewed-by: Anastasia Lubennikova
Discussion: https://postgr.es/m/db12e897-73ff-467e-94cb-4af03705435f.adger.lj@alibaba-inc.com