This adds support for writing CREATE FUNCTION and CREATE PROCEDURE
statements for language SQL with a function body that conforms to the
SQL standard and is portable to other implementations.
Instead of the PostgreSQL-specific AS $$ string literal $$ syntax,
this allows writing out the SQL statements making up the body
unquoted, either as a single statement:
CREATE FUNCTION add(a integer, b integer) RETURNS integer
LANGUAGE SQL
RETURN a + b;
or as a block
CREATE PROCEDURE insert_data(a integer, b integer)
LANGUAGE SQL
BEGIN ATOMIC
INSERT INTO tbl VALUES (a);
INSERT INTO tbl VALUES (b);
END;
The function body is parsed at function definition time and stored as
expression nodes in a new pg_proc column prosqlbody. So at run time,
no further parsing is required.
However, this form does not support polymorphic arguments, because
there is no more parse analysis done at call time.
Dependencies between the function and the objects it uses are fully
tracked.
A new RETURN statement is introduced. This can only be used inside
function bodies. Internally, it is treated much like a SELECT
statement.
psql needs some new intelligence to keep track of function body
boundaries so that it doesn't send off statements when it sees
semicolons that are inside a function body.
Tested-by: Jaime Casanova <jcasanov@systemguards.com.ec>
Reviewed-by: Julien Rouhaud <rjuju123@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/1c11f1eb-f00c-43b7-799d-2d44132c02d7@2ndquadrant.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 allows something like
SELECT ... FROM t1 JOIN t2 USING (a, b, c) AS x
where x has the columns a, b, c and unlike a regular alias it does not
hide the range variables of the tables being joined t1 and t2.
Per SQL:2016 feature F404 "Range variable for common column names".
Reviewed-by: Vik Fearing <vik.fearing@2ndquadrant.com>
Reviewed-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://www.postgresql.org/message-id/flat/454638cf-d563-ab76-a585-2564428062af@2ndquadrant.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
Here we aim to reduce duplicate work done by contain_volatile_functions()
by caching whether PathTargets and RestrictInfos contain any volatile
functions the first time contain_volatile_functions() is called for them.
Any future calls for these nodes just use the cached value rather than
going to the trouble of recursively checking the sub-node all over again.
Thanks to Tom Lane for the idea.
Any locations in the code which make changes to a PathTarget or
RestrictInfo which could change the outcome of the volatility check must
change the cached value back to VOLATILITY_UNKNOWN again.
contain_volatile_functions() is the only code in charge of setting the
cache value to either VOLATILITY_VOLATILE or VOLATILITY_NOVOLATILE.
Some existing code does benefit from this additional caching, however,
this change is mainly aimed at an upcoming patch that must check for
volatility during the join search. Repeated volatility checks in that
case can become very expensive when the join search contains more than a
few relations.
Author: David Rowley
Discussion: https://postgr.es/m/3795226.1614059027@sss.pgh.pa.us
Allow defining extended statistics on expressions, not just just on
simple column references. With this commit, expressions are supported
by all existing extended statistics kinds, improving the same types of
estimates. A simple example may look like this:
CREATE TABLE t (a int);
CREATE STATISTICS s ON mod(a,10), mod(a,20) FROM t;
ANALYZE t;
The collected statistics are useful e.g. to estimate queries with those
expressions in WHERE or GROUP BY clauses:
SELECT * FROM t WHERE mod(a,10) = 0 AND mod(a,20) = 0;
SELECT 1 FROM t GROUP BY mod(a,10), mod(a,20);
This introduces new internal statistics kind 'e' (expressions) which is
built automatically when the statistics object definition includes any
expressions. This represents single-expression statistics, as if there
was an expression index (but without the index maintenance overhead).
The statistics is stored in pg_statistics_ext_data as an array of
composite types, which is possible thanks to 79f6a942bd.
CREATE STATISTICS allows building statistics on a single expression, in
which case in which case it's not possible to specify statistics kinds.
A new system view pg_stats_ext_exprs can be used to display expression
statistics, similarly to pg_stats and pg_stats_ext views.
ALTER TABLE ... ALTER COLUMN ... TYPE now treats indexes the same way it
treats indexes, i.e. it drops and recreates the statistics. This means
all statistics are reset, and we no longer try to preserve at least the
functional dependencies. This should not be a major issue in practice,
as the functional dependencies actually rely on per-column statistics,
which were always reset anyway.
Author: Tomas Vondra
Reviewed-by: Justin Pryzby, Dean Rasheed, Zhihong Yu
Discussion: https://postgr.es/m/ad7891d2-e90c-b446-9fe2-7419143847d7%40enterprisedb.com
To allow inserts in parallel-mode this feature has to ensure that all the
constraints, triggers, etc. are parallel-safe for the partition hierarchy
which is costly and we need to find a better way to do that. Additionally,
we could have used existing cached information in some cases like indexes,
domains, etc. to determine the parallel-safety.
List of commits reverted, in reverse chronological order:
ed62d3737c Doc: Update description for parallel insert reloption.
c8f78b6161 Add a new GUC and a reloption to enable inserts in parallel-mode.
c5be48f092 Improve FK trigger parallel-safety check added by 05c8482f7f.
e2cda3c20a Fix use of relcache TriggerDesc field introduced by commit 05c8482f7f.
e4e87a32cc Fix valgrind issue in commit 05c8482f7f.
05c8482f7f Enable parallel SELECT for "INSERT INTO ... SELECT ...".
Discussion: https://postgr.es/m/E1lMiB9-0001c3-SY@gemulon.postgresql.org
There is now a per-column COMPRESSION option which can be set to pglz
(the default, and the only option in up until now) or lz4. Or, if you
like, you can set the new default_toast_compression GUC to lz4, and
then that will be the default for new table columns for which no value
is specified. We don't have lz4 support in the PostgreSQL code, so
to use lz4 compression, PostgreSQL must be built --with-lz4.
In general, TOAST compression means compression of individual column
values, not the whole tuple, and those values can either be compressed
inline within the tuple or compressed and then stored externally in
the TOAST table, so those properties also apply to this feature.
Prior to this commit, a TOAST pointer has two unused bits as part of
the va_extsize field, and a compessed datum has two unused bits as
part of the va_rawsize field. These bits are unused because the length
of a varlena is limited to 1GB; we now use them to indicate the
compression type that was used. This means we only have bit space for
2 more built-in compresison types, but we could work around that
problem, if necessary, by introducing a new vartag_external value for
any further types we end up wanting to add. Hopefully, it won't be
too important to offer a wide selection of algorithms here, since
each one we add not only takes more coding but also adds a build
dependency for every packager. Nevertheless, it seems worth doing
at least this much, because LZ4 gets better compression than PGLZ
with less CPU usage.
It's possible for LZ4-compressed datums to leak into composite type
values stored on disk, just as it is for PGLZ. It's also possible for
LZ4-compressed attributes to be copied into a different table via SQL
commands such as CREATE TABLE AS or INSERT .. SELECT. It would be
expensive to force such values to be decompressed, so PostgreSQL has
never done so. For the same reasons, we also don't force recompression
of already-compressed values even if the target table prefers a
different compression method than was used for the source data. These
architectural decisions are perhaps arguable but revisiting them is
well beyond the scope of what seemed possible to do as part of this
project. However, it's relatively cheap to recompress as part of
VACUUM FULL or CLUSTER, so this commit adjusts those commands to do
so, if the configured compression method of the table happens not to
match what was used for some column value stored therein.
Dilip Kumar. The original patches on which this work was based were
written by Ildus Kurbangaliev, and those were patches were based on
even earlier work by Nikita Glukhov, but the design has since changed
very substantially, since allow a potentially large number of
compression methods that could be added and dropped on a running
system proved too problematic given some of the architectural issues
mentioned above; the choice of which specific compression method to
add first is now different; and a lot of the code has been heavily
refactored. More recently, Justin Przyby helped quite a bit with
testing and reviewing and this version also includes some code
contributions from him. Other design input and review from Tomas
Vondra, Álvaro Herrera, Andres Freund, Oleg Bartunov, Alexander
Korotkov, and me.
Discussion: http://postgr.es/m/20170907194236.4cefce96%40wp.localdomain
Discussion: http://postgr.es/m/CAFiTN-uUpX3ck%3DK0mLEk-G_kUQY%3DSNOTeqdaNRR9FMdQrHKebw%40mail.gmail.com
With grouping sets, it's possible that some of the grouping sets are
duplicate. This is especially common with CUBE and ROLLUP clauses. For
example GROUP BY CUBE (a,b), CUBE (b,c) is equivalent to
GROUP BY GROUPING SETS (
(a, b, c),
(a, b, c),
(a, b, c),
(a, b),
(a, b),
(a, b),
(a),
(a),
(a),
(c, a),
(c, a),
(c, a),
(c),
(b, c),
(b),
()
)
Some of the grouping sets are calculated multiple times, which is mostly
unnecessary. This commit implements a new GROUP BY DISTINCT feature, as
defined in the SQL standard, which eliminates the duplicate sets.
Author: Vik Fearing
Reviewed-by: Erik Rijkers, Georgios Kokolatos, Tomas Vondra
Discussion: https://postgr.es/m/bf3805a8-d7d1-ae61-fece-761b7ff41ecc@postgresfriends.org
Parallel SELECT can't be utilized for INSERT in the following cases:
- INSERT statement uses the ON CONFLICT DO UPDATE clause
- Target table has a parallel-unsafe: trigger, index expression or
predicate, column default expression or check constraint
- Target table has a parallel-unsafe domain constraint on any column
- Target table is a partitioned table with a parallel-unsafe partition key
expression or support function
The planner is updated to perform additional parallel-safety checks for
the cases listed above, for determining whether it is safe to run INSERT
in parallel-mode with an underlying parallel SELECT. The planner will
consider using parallel SELECT for "INSERT INTO ... SELECT ...", provided
nothing unsafe is found from the additional parallel-safety checks, or
from the existing parallel-safety checks for SELECT.
While checking parallel-safety, we need to check it for all the partitions
on the table which can be costly especially when we decide not to use a
parallel plan. So, in a separate patch, we will introduce a GUC and or a
reloption to enable/disable parallelism for Insert statements.
Prior to entering parallel-mode for the execution of INSERT with parallel
SELECT, a TransactionId is acquired and assigned to the current
transaction state. This is necessary to prevent the INSERT from attempting
to assign the TransactionId whilst in parallel-mode, which is not allowed.
This approach has a disadvantage in that if the underlying SELECT does not
return any rows, then the TransactionId is not used, however that
shouldn't happen in practice in many cases.
Author: Greg Nancarrow, Amit Langote, Amit Kapila
Reviewed-by: Amit Langote, Hou Zhijie, Takayuki Tsunakawa, Antonin Houska, Bharath Rupireddy, Dilip Kumar, Vignesh C, Zhihong Yu, Amit Kapila
Tested-by: Tang, Haiying
Discussion: https://postgr.es/m/CAJcOf-cXnB5cnMKqWEp2E2z7Mvcd04iLVmV=qpFJrR3AcrTS3g@mail.gmail.com
Discussion: https://postgr.es/m/CAJcOf-fAdj=nDKMsRhQzndm-O13NY4dL6xGcEvdX5Xvbbi0V7g@mail.gmail.com
This adds a new executor node named TID Range Scan. The query planner
will generate paths for TID Range scans when quals are discovered on base
relations which search for ranges on the table's ctid column. These
ranges may be open at either end. For example, WHERE ctid >= '(10,0)';
will return all tuples on page 10 and over.
To support this, two new optional callback functions have been added to
table AM. scan_set_tidrange is used to set the scan range to just the
given range of TIDs. scan_getnextslot_tidrange fetches the next tuple
in the given range.
For AMs were scanning ranges of TIDs would not make sense, these functions
can be set to NULL in the TableAmRoutine. The query planner won't
generate TID Range Scan Paths in that case.
Author: Edmund Horner, David Rowley
Reviewed-by: David Rowley, Tomas Vondra, Tom Lane, Andres Freund, Zhihong Yu
Discussion: https://postgr.es/m/CAMyN-kB-nFTkF=VA_JPwFNo08S0d-Yk0F741S2B7LDmYAi8eyA@mail.gmail.com
It turns out that the calculation of [Merge]AppendPath.partitioned_rels
in allpaths.c is faulty and sometimes omits relevant non-leaf partitions,
allowing an assertion added by commit a929e17e5a to trigger. Rather
than fix that, it seems better to get rid of those fields altogether.
We don't really need the info until create_plan time, and calculating
it once for the selected plan should be cheaper than calculating it
for each append path we consider.
The preceding two commits did away with all use of the partitioned_rels
values; this commit just mechanically removes the fields and the code
that calculated them.
Discussion: https://postgr.es/m/87sg8tqhsl.fsf@aurora.ydns.eu
Discussion: https://postgr.es/m/CAJKUy5gCXDSmFs2c=R+VGgn7FiYcLCsEFEuDNNLGfoha=pBE_g@mail.gmail.com
This adds the SQL standard feature that adds the SEARCH and CYCLE
clauses to recursive queries to be able to do produce breadth- or
depth-first search orders and detect cycles. These clauses can be
rewritten into queries using existing syntax, and that is what this
patch does in the rewriter.
Reviewed-by: Vik Fearing <vik@postgresfriends.org>
Reviewed-by: Pavel Stehule <pavel.stehule@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/db80ceee-6f97-9b4a-8ee8-3ba0c58e5be2@2ndquadrant.com
Invent new RawParseModes that allow the core grammar to handle
pl/pgsql expressions and assignments directly, and thereby get rid
of a lot of hackery in pl/pgsql's parser. This moves a good deal
of knowledge about pl/pgsql into the core code: notably, we have to
invent a CoercionContext that matches pl/pgsql's (rather dubious)
historical behavior for assignment coercions. That's getting away
from the original idea of pl/pgsql as an arm's-length extension of
the core, but really we crossed that bridge a long time ago.
The main advantage of doing this is that we can now use the core
parser to generate FieldStore and/or SubscriptingRef nodes to handle
assignments to pl/pgsql variables that are records or arrays. That
fixes a number of cases that had never been implemented in pl/pgsql
assignment, such as nested records and array slicing, and it allows
pl/pgsql assignment to support the datatype-specific subscripting
behaviors introduced in commit c7aba7c14.
There are cosmetic benefits too: when a syntax error occurs in a
pl/pgsql expression, the error report no longer includes the confusing
"SELECT" keyword that used to get prefixed to the expression text.
Also, there seem to be some small speed gains.
Discussion: https://postgr.es/m/4165684.1607707277@sss.pgh.pa.us
This patch generalizes the subscripting infrastructure so that any
data type can be subscripted, if it provides a handler function to
define what that means. Traditional variable-length (varlena) arrays
all use array_subscript_handler(), while the existing fixed-length
types that support subscripting use raw_array_subscript_handler().
It's expected that other types that want to use subscripting notation
will define their own handlers. (This patch provides no such new
features, though; it only lays the foundation for them.)
To do this, move the parser's semantic processing of subscripts
(including coercion to whatever data type is required) into a
method callback supplied by the handler. On the execution side,
replace the ExecEvalSubscriptingRef* layer of functions with direct
calls to callback-supplied execution routines. (Thus, essentially
no new run-time overhead should be caused by this patch. Indeed,
there is room to remove some overhead by supplying specialized
execution routines. This patch does a little bit in that line,
but more could be done.)
Additional work is required here and there to remove formerly
hard-wired assumptions about the result type, collation, etc
of a SubscriptingRef expression node; and to remove assumptions
that the subscript values must be integers.
One useful side-effect of this is that we now have a less squishy
mechanism for identifying whether a data type is a "true" array:
instead of wiring in weird rules about typlen, we can look to see
if pg_type.typsubscript == F_ARRAY_SUBSCRIPT_HANDLER. For this
to be bulletproof, we have to forbid user-defined types from using
that handler directly; but there seems no good reason for them to
do so.
This patch also removes assumptions that the number of subscripts
is limited to MAXDIM (6), or indeed has any hard-wired limit.
That limit still applies to types handled by array_subscript_handler
or raw_array_subscript_handler, but to discourage other dependencies
on this constant, I've moved it from c.h to utils/array.h.
Dmitry Dolgov, reviewed at various times by Tom Lane, Arthur Zakirov,
Peter Eisentraut, Pavel Stehule
Discussion: https://postgr.es/m/CA+q6zcVDuGBv=M0FqBYX8DPebS3F_0KQ6OVFobGJPM507_SZ_w@mail.gmail.com
Discussion: https://postgr.es/m/CA+q6zcVovR+XY4mfk-7oNk-rF91gH0PebnNfuUjuuDsyHjOcVA@mail.gmail.com
This GUC was always intended as a temporary solution to help with
finding 9.4-to-9.5 migration issues. Now that all pre-9.5 branches
are out of support, and 9.5 will be too before v14 is released,
it seems like it's okay to drop it. Doing so allows removal of
several hundred lines of poorly-tested code in parse_expr.c,
which have been a fertile source of bugs when people did use this.
Discussion: https://postgr.es/m/2234320.1607117945@sss.pgh.pa.us
As it stood, expandTableLikeClause() re-did the same relation_openrv
call that transformTableLikeClause() had done. However there are
scenarios where this would not find the same table as expected.
We hold lock on the LIKE source table, so it can't be renamed or
dropped, but another table could appear before it in the search path.
This explains the odd behavior reported in bug #16758 when cloning a
table as a temp table of the same name. This case worked as expected
before commit 502898192 introduced the need to open the source table
twice, so we should fix it.
To make really sure we get the same table, let's re-open it by OID not
name. That requires adding an OID field to struct TableLikeClause,
which is a little nervous-making from an ABI standpoint, but as long
as it's at the end I don't think there's any serious risk.
Per bug #16758 from Marc Boeren. Like the previous patch,
back-patch to all supported branches.
Discussion: https://postgr.es/m/16758-840e84a6cfab276d@postgresql.org
For debugging purposes, Path nodes are supposed to have outfuncs
support, but this was overlooked in the original incremental sort patch.
While at it, clean up a couple other minor oversights, as well as
bizarre choice of return type for create_incremental_sort_path().
(All the existing callers just cast it to "Path *" immediately, so
they don't care, but some future caller might care.)
outfuncs.c fix by Zhijie Hou, the rest by me
Discussion: https://postgr.es/m/324c4d81d8134117972a5b1f6cdf9560@G08CNEXMBPEKD05.g08.fujitsu.local
This feature was added a long time ago, in 7c1e67bd5 and eb121ba2c,
but never documented in any user-facing way. (Documentation added
in 6126d3e70 was commented out almost immediately, in 8272fc3f7.)
That's because, while this syntax is defined by SQL:99, our
implementation is only vaguely related to the standard's semantics.
The standard appears to intend a run-time not parse-time test, and
it definitely intends that the test should understand subtype
relationships.
No one has stepped up to fix that in the intervening years, but
people keep coming across the code and asking why it's not documented.
Let's just get rid of it: if anyone ever wants to make it work per
spec, they can easily recover whatever parts of this code are still
of value from our git history.
If there's anyone out there who's actually using this despite its
undocumented status, they can switch to using pg_typeof() instead,
eg. "pg_typeof(something) = 'mytype'::regtype". That gives
essentially the same semantics as what our IS OF code did.
(We didn't have that function last time this was discussed, or
we would have ripped out IS OF then.)
Discussion: https://postgr.es/m/CAKFQuwZ2pTc-DSkOiTfjauqLYkNREeNZvWmeg12Q-_69D+sYZA@mail.gmail.com
Discussion: https://postgr.es/m/BAY20-F23E9F2B4DAB3E4E88D3623F99B0@phx.gbl
Discussion: https://postgr.es/m/3E7CF81D.1000203@joeconway.com
The SQL spec calls out nonstandard syntax for certain function calls,
for example substring() with numeric position info is supposed to be
spelled "SUBSTRING(string FROM start FOR count)". We accept many
of these things, but up to now would not print them in the same format,
instead simplifying down to "substring"(string, start, count).
That's long annoyed me because it creates an interoperability
problem: we're gratuitously injecting Postgres-specific syntax into
what might otherwise be a perfectly spec-compliant view definition.
However, the real reason for addressing it right now is to support
a planned change in the semantics of EXTRACT() a/k/a date_part().
When we switch that to returning numeric, we'll have the parser
translate EXTRACT() to some new function name (might as well be
"extract" if you ask me) and then teach ruleutils.c to reverse-list
that per SQL spec. In this way existing calls to date_part() will
continue to have the old semantics.
To implement this, invent a new CoercionForm value COERCE_SQL_SYNTAX,
and make the parser insert that rather than COERCE_EXPLICIT_CALL when
the input has SQL-spec decoration. (But if the input has the form of
a plain function call, continue to mark it COERCE_EXPLICIT_CALL, even
if it's calling one of these functions.) Then ruleutils.c recognizes
COERCE_SQL_SYNTAX as a cue to emit SQL call syntax. It can know
which decoration to emit using hard-wired knowledge about the
functions that could be called this way. (While this solution isn't
extensible without manual additions, neither is the grammar, so this
doesn't seem unmaintainable.) Notice that this solution will
reverse-list a function call with SQL decoration only if it was
entered that way; so dump-and-reload will not by itself produce any
changes in the appearance of views.
This requires adding a CoercionForm field to struct FuncCall.
(I couldn't resist the temptation to rearrange that struct's
field order a tad while I was at it.) FuncCall doesn't appear
in stored rules, so that change isn't a reason for a catversion
bump, but I did one anyway because the new enum value for
CoercionForm fields could confuse old backend code.
Possible future work:
* Perhaps CoercionForm should now be renamed to DisplayForm,
or something like that, to reflect its more general meaning.
This'd require touching a couple hundred places, so it's not
clear it's worth the code churn.
* The SQLValueFunction node type, which was invented partly for
the same goal of improving SQL-compatibility of view output,
could perhaps be replaced with regular function calls marked
with COERCE_SQL_SYNTAX. It's unclear if this would be a net
code savings, however.
Discussion: https://postgr.es/m/42b73d2d-da12-ba9f-570a-420e0cce19d9@phystech.edu
Previously we only tagged on the required information to allow the
executor to perform run-time partition pruning for Append/MergeAppend
nodes belonging to base relations. It was thought that nested
Append/MergeAppend nodes were just about always pulled up into the
top-level Append/MergeAppend and that making the run-time pruning info for
any sub Append/MergeAppend nodes was a waste of time. However, that was
likely badly thought through.
Some examples of cases we're unable to pullup nested Append/MergeAppends
are: 1) Parallel Append nodes with a mix of parallel and non-parallel
paths into a Parallel Append. 2) When planning an ordered Append scan a
sub-partition which is unordered may require a nested MergeAppend path to
ensure sub-partitions don't mix up the order of tuples being fed into the
top-level Append.
Unfortunately, it was not just as simple as removing the lines in
createplan.c which were purposefully not building the run-time pruning
info for anything but RELOPT_BASEREL relations. The code in
add_paths_to_append_rel() was far too sloppy about which partitioned_rels
it included for the Append/MergeAppend paths. The original code there
would always assume accumulate_append_subpath() would pull each sub-Append
and sub-MergeAppend path into the top-level path. While it does not
appear that there were any actual bugs caused by having the additional
partitioned table RT indexes recorded, what it did mean is that later in
planning, when we built the run-time pruning info that we wasted effort
and built PartitionedRelPruneInfos for partitioned tables that we had no
subpaths for the executor to run-time prune.
Here we tighten that up so that partitioned_rels only ever contains the RT
index for partitioned tables which actually have subpaths in the given
Append/MergeAppend. We can now Assert that every PartitionedRelPruneInfo
has a non-empty present_parts. That should allow us to catch any weird
corner cases that have been missed.
In passing, it seems there is no longer a good reason to have the
AppendPath and MergeAppendPath's partitioned_rel fields a List of IntList.
We can simply have a List of Relids instead. This is more compact in
memory and faster to add new members to. We still know which is the root
level partition as these always have a lower relid than their children.
Previously this field was used for more things, but run-time partition
pruning now remains the only user of it and it has no need for a List of
IntLists.
Here we also get rid of the RelOptInfo partitioned_child_rels field. This
is what was previously used to (sometimes incorrectly) set the
Append/MergeAppend path's partitioned_rels field. That was the only usage
of that field, so we can happily just remove it.
I also couldn't resist changing some nearby code to make use of the newly
added for_each_from macro so we can skip the first element in the list
without checking if the current item was the first one on each
iteration.
A bug report from Andreas Kretschmer prompted all this work, however,
after some consideration, I'm not personally classing this as a bug fix.
So no backpatch. In Andreas' test case, it just wasn't that clear that
there was a nested Append since the top-level Append just had a single
sub-path which was pulled up a level, per 8edd0e794.
Author: David Rowley
Reviewed-by: Amit Langote
Discussion: https://postgr.es/m/flat/CAApHDvqSchs%2BubdybcfFaSPB%2B%2BEA7kqMaoqajtP0GtZvzOOR3g%40mail.gmail.com
get_foreign_key_join_selectivity() looks for join clauses that equate
the two sides of the FK constraint. However, if we have a query like
"WHERE fktab.a = pktab.a and fktab.a = 1", it won't find any such join
clause, because equivclass.c replaces the given clauses with "fktab.a
= 1 and pktab.a = 1", which can be enforced at the scan level, leaving
nothing to be done for column "a" at the join level.
We can fix that expectation without much trouble, but then a new problem
arises: applying the foreign-key-based selectivity rule produces a
rowcount underestimate, because we're effectively double-counting the
selectivity of the "fktab.a = 1" clause. So we have to cancel that
selectivity out of the estimate.
To fix, refactor process_implied_equality() so that it can pass back the
new RestrictInfo to its callers in equivclass.c, allowing the generated
"fktab.a = 1" clause to be saved in the EquivalenceClass's ec_derives
list. Then it's not much trouble to dig out the relevant RestrictInfo
when we need to adjust an FK selectivity estimate. (While at it, we
can also remove the expensive use of initialize_mergeclause_eclasses()
to set up the new RestrictInfo's left_ec and right_ec pointers.
The equivclass.c code can set those basically for free.)
This seems like clearly a bug fix, but I'm hesitant to back-patch it,
first because there's some API/ABI risk for extensions and second because
we're usually loath to destabilize plan choices in stable branches.
Per report from Sigrid Ehrenreich.
Discussion: https://postgr.es/m/1019549.1603770457@sss.pgh.pa.us
Discussion: https://postgr.es/m/AM6PR02MB5287A0ADD936C1FA80973E72AB190@AM6PR02MB5287.eurprd02.prod.outlook.com
FDWs that can perform an UPDATE/DELETE remotely using the "direct modify"
set of APIs need to access the ResultRelInfo of the target table. That's
currently available in EState.es_result_relation_info, but the next
commit will remove that field.
This commit adds a new resultRelation field in ForeignScan, to store the
target relation's RT index, and the corresponding ResultRelInfo in
ForeignScanState. The FDW's PlanDirectModify callback is expected to set
'resultRelation' along with 'operation'. The core code doesn't need them
for anything, they are for the convenience of FDW's Begin- and
IterateDirectModify callbacks.
Authors: Amit Langote, Etsuro Fujita
Discussion: https://www.postgresql.org/message-id/CA%2BHiwqGEmiib8FLiHMhKB%2BCH5dRgHSLc5N5wnvc4kym%2BZYpQEQ%40mail.gmail.com
Instead of allocating all the ResultRelInfos upfront in one big array,
allocate them in ExecInitModifyTable(). es_result_relations is now an
array of ResultRelInfo pointers, rather than an array of structs, and it
is indexed by the RT index.
This simplifies things: we get rid of the separate concept of a "result
rel index", and don't need to set it in setrefs.c anymore. This also
allows follow-up optimizations (not included in this commit yet) to skip
initializing ResultRelInfos for target relations that were not needed at
runtime, and removal of the es_result_relation_info pointer.
The EState arrays of regular result rels and root result rels are merged
into one array. Similarly, the resultRelations and rootResultRelations
lists in PlannedStmt are merged into one. It's not actually clear to me
why they were kept separate in the first place, but now that the
es_result_relations array is indexed by RT index, it certainly seems
pointless.
The PlannedStmt->resultRelations list is now only needed for
ExecRelationIsTargetRelation(). One visible effect of this change is that
ExecRelationIsTargetRelation() will now return 'true' also for the
partition root, if a partitioned table is updated. That seems like a good
thing, although the function isn't used in core code, and I don't see any
reason for an FDW to call it on a partition root.
Author: Amit Langote
Discussion: https://www.postgresql.org/message-id/CA%2BHiwqGEmiib8FLiHMhKB%2BCH5dRgHSLc5N5wnvc4kym%2BZYpQEQ%40mail.gmail.com
When commit bd3daddaf introduced AlternativeSubPlans, I had some
ambitions towards allowing the choice of subplan to change during
execution. That has not happened, or even been thought about, in the
ensuing twelve years; so it seems like a failed experiment. So let's
rip that out and resolve the choice of subplan at the end of planning
(in setrefs.c) rather than during executor startup. This has a number
of positive benefits:
* Removal of a few hundred lines of executor code, since
AlternativeSubPlans need no longer be supported there.
* Removal of executor-startup overhead (particularly, initialization
of subplans that won't be used).
* Removal of incidental costs of having a larger plan tree, such as
tree-scanning and copying costs in the plancache; not to mention
setrefs.c's own costs of processing the discarded subplans.
* EXPLAIN no longer has to print a weird (and undocumented)
representation of an AlternativeSubPlan choice; it sees only the
subplan actually used. This should mean less confusion for users.
* Since setrefs.c knows which subexpression of a plan node it's
working on at any instant, it's possible to adjust the estimated
number of executions of the subplan based on that. For example,
we should usually estimate more executions of a qual expression
than a targetlist expression. The implementation used here is
pretty simplistic, because we don't want to expend a lot of cycles
on the issue; but it's better than ignoring the point entirely,
as the executor had to.
That last point might possibly result in shifting the choice
between hashed and non-hashed EXISTS subplans in a few cases,
but in general this patch isn't meant to change planner choices.
Since we're doing the resolution so late, it's really impossible
to change any plan choices outside the AlternativeSubPlan itself.
Patch by me; thanks to David Rowley for review.
Discussion: https://postgr.es/m/1992952.1592785225@sss.pgh.pa.us
Thomas Munro fixed a longstanding annoyance in pg_bsd_indent, that
it would misformat lines containing IsA() macros on the assumption
that the IsA() call should be treated like a cast. This improves
some other cases involving field/variable names that match typedefs,
too. The only places that get worse are a couple of uses of the
OpenSSL macro STACK_OF(); we'll gladly take that trade-off.
Discussion: https://postgr.es/m/20200114221814.GA19630@alvherre.pgsql
0f5ca02f53 introduces 3 new keywords. It appears to be too much for relatively
small feature. Given now we past feature freeze, it's already late for
discussion of the new syntax. So, revert.
Discussion: https://postgr.es/m/28209.1586294824%40sss.pgh.pa.us
Previously, the partitionwise join technique only allowed partitionwise
join when input partitioned tables had exactly the same partition
bounds. This commit extends the technique to some cases when the tables
have different partition bounds, by using an advanced partition-matching
algorithm introduced by this commit. For both the input partitioned
tables, the algorithm checks whether every partition of one input
partitioned table only matches one partition of the other input
partitioned table at most, and vice versa. In such a case the join
between the tables can be broken down into joins between the matching
partitions, so the algorithm produces the pairs of the matching
partitions, plus the partition bounds for the join relation, to allow
partitionwise join for computing the join. Currently, the algorithm
works for list-partitioned and range-partitioned tables, but not
hash-partitioned tables. See comments in partition_bounds_merge().
Ashutosh Bapat and Etsuro Fujita, most of regression tests by Rajkumar
Raghuwanshi, some of the tests by Mark Dilger and Amul Sul, reviewed by
Dmitry Dolgov and Amul Sul, with additional review at various points by
Ashutosh Bapat, Mark Dilger, Robert Haas, Antonin Houska, Amit Langote,
Justin Pryzby, and Tomas Vondra
Discussion: https://postgr.es/m/CAFjFpRdjQvaUEV5DJX3TW6pU5eq54NCkadtxHX2JiJG_GvbrCA@mail.gmail.com
This commit adds following optional clause to BEGIN and START TRANSACTION
commands.
WAIT FOR LSN lsn [ TIMEOUT timeout ]
New clause pospones transaction start till given lsn is applied on standby.
This clause allows user be sure, that changes previously made on primary would
be visible on standby.
New shared memory struct is used to track awaited lsn per backend. Recovery
process wakes up backend once required lsn is applied.
Author: Ivan Kartyshov, Anna Akenteva
Reviewed-by: Craig Ringer, Thomas Munro, Robert Haas, Kyotaro Horiguchi
Reviewed-by: Masahiko Sawada, Ants Aasma, Dmitry Ivanov, Simon Riggs
Reviewed-by: Amit Kapila, Alexander Korotkov
Discussion: https://postgr.es/m/0240c26c-9f84-30ea-fca9-93ab2df5f305%40postgrespro.ru
WITH TIES is an option to the FETCH FIRST N ROWS clause (the SQL
standard's spelling of LIMIT), where you additionally get rows that
compare equal to the last of those N rows by the columns in the
mandatory ORDER BY clause.
There was a proposal by Andrew Gierth to implement this functionality in
a more powerful way that would yield more features, but the other patch
had not been finished at this time, so we decided to use this one for
now in the spirit of incremental development.
Author: Surafel Temesgen <surafel3000@gmail.com>
Reviewed-by: Álvaro Herrera <alvherre@alvh.no-ip.org>
Reviewed-by: Tomas Vondra <tomas.vondra@2ndquadrant.com>
Discussion: https://postgr.es/m/CALAY4q9ky7rD_A4vf=FVQvCGngm3LOes-ky0J6euMrg=_Se+ag@mail.gmail.com
Discussion: https://postgr.es/m/87o8wvz253.fsf@news-spur.riddles.org.uk
Incremental Sort is an optimized variant of multikey sort for cases when
the input is already sorted by a prefix of the requested sort keys. For
example when the relation is already sorted by (key1, key2) and we need
to sort it by (key1, key2, key3) we can simply split the input rows into
groups having equal values in (key1, key2), and only sort/compare the
remaining column key3.
This has a number of benefits:
- Reduced memory consumption, because only a single group (determined by
values in the sorted prefix) needs to be kept in memory. This may also
eliminate the need to spill to disk.
- Lower startup cost, because Incremental Sort produce results after each
prefix group, which is beneficial for plans where startup cost matters
(like for example queries with LIMIT clause).
We consider both Sort and Incremental Sort, and decide based on costing.
The implemented algorithm operates in two different modes:
- Fetching a minimum number of tuples without check of equality on the
prefix keys, and sorting on all columns when safe.
- Fetching all tuples for a single prefix group and then sorting by
comparing only the remaining (non-prefix) keys.
We always start in the first mode, and employ a heuristic to switch into
the second mode if we believe it's beneficial - the goal is to minimize
the number of unnecessary comparions while keeping memory consumption
below work_mem.
This is a very old patch series. The idea was originally proposed by
Alexander Korotkov back in 2013, and then revived in 2017. In 2018 the
patch was taken over by James Coleman, who wrote and rewrote most of the
current code.
There were many reviewers/contributors since 2013 - I've done my best to
pick the most active ones, and listed them in this commit message.
Author: James Coleman, Alexander Korotkov
Reviewed-by: Tomas Vondra, Andreas Karlsson, Marti Raudsepp, Peter Geoghegan, Robert Haas, Thomas Munro, Antonin Houska, Andres Freund, Alexander Kuzmenkov
Discussion: https://postgr.es/m/CAPpHfdscOX5an71nHd8WSUH6GNOCf=V7wgDaTXdDd9=goN-gfA@mail.gmail.com
Discussion: https://postgr.es/m/CAPpHfds1waRZ=NOmueYq0sx1ZSCnt+5QJvizT8ndT2=etZEeAQ@mail.gmail.com
Until now, only selected bulk operations (e.g. COPY) did this. If a
given relfilenode received both a WAL-skipping COPY and a WAL-logged
operation (e.g. INSERT), recovery could lose tuples from the COPY. See
src/backend/access/transam/README section "Skipping WAL for New
RelFileNode" for the new coding rules. Maintainers of table access
methods should examine that section.
To maintain data durability, just before commit, we choose between an
fsync of the relfilenode and copying its contents to WAL. A new GUC,
wal_skip_threshold, guides that choice. If this change slows a workload
that creates small, permanent relfilenodes under wal_level=minimal, try
adjusting wal_skip_threshold. Users setting a timeout on COMMIT may
need to adjust that timeout, and log_min_duration_statement analysis
will reflect time consumption moving to COMMIT from commands like COPY.
Internally, this requires a reliable determination of whether
RollbackAndReleaseCurrentSubTransaction() would unlink a relation's
current relfilenode. Introduce rd_firstRelfilenodeSubid. Amend the
specification of rd_createSubid such that the field is zero when a new
rel has an old rd_node. Make relcache.c retain entries for certain
dropped relations until end of transaction.
Bump XLOG_PAGE_MAGIC, since this introduces XLOG_GIST_ASSIGN_LSN.
Future servers accept older WAL, so this bump is discretionary.
Kyotaro Horiguchi, reviewed (in earlier, similar versions) by Robert
Haas. Heikki Linnakangas and Michael Paquier implemented earlier
designs that materially clarified the problem. Reviewed, in earlier
designs, by Andrew Dunstan, Andres Freund, Alvaro Herrera, Tom Lane,
Fujii Masao, and Simon Riggs. Reported by Martijn van Oosterhout.
Discussion: https://postgr.es/m/20150702220524.GA9392@svana.org
PostgreSQL provides set of template index access methods, where opclasses have
much freedom in the semantics of indexing. These index AMs are GiST, GIN,
SP-GiST and BRIN. There opclasses define representation of keys, operations on
them and supported search strategies. So, it's natural that opclasses may be
faced some tradeoffs, which require user-side decision. This commit implements
opclass parameters allowing users to set some values, which tell opclass how to
index the particular dataset.
This commit doesn't introduce new storage in system catalog. Instead it uses
pg_attribute.attoptions, which is used for table column storage options but
unused for index attributes.
In order to evade changing signature of each opclass support function, we
implement unified way to pass options to opclass support functions. Options
are set to fn_expr as the constant bytea expression. It's possible due to the
fact that opclass support functions are executed outside of expressions, so
fn_expr is unused for them.
This commit comes with some examples of opclass options usage. We parametrize
signature length in GiST. That applies to multiple opclasses: tsvector_ops,
gist__intbig_ops, gist_ltree_ops, gist__ltree_ops, gist_trgm_ops and
gist_hstore_ops. Also we parametrize maximum number of integer ranges for
gist__int_ops. However, the main future usage of this feature is expected
to be json, where users would be able to specify which way to index particular
json parts.
Catversion is bumped.
Discussion: https://postgr.es/m/d22c3a18-31c7-1879-fc11-4c1ce2f5e5af%40postgrespro.ru
Author: Nikita Glukhov, revised by me
Reviwed-by: Nikolay Shaplov, Robert Haas, Tom Lane, Tomas Vondra, Alvaro Herrera
Until now, only selected bulk operations (e.g. COPY) did this. If a
given relfilenode received both a WAL-skipping COPY and a WAL-logged
operation (e.g. INSERT), recovery could lose tuples from the COPY. See
src/backend/access/transam/README section "Skipping WAL for New
RelFileNode" for the new coding rules. Maintainers of table access
methods should examine that section.
To maintain data durability, just before commit, we choose between an
fsync of the relfilenode and copying its contents to WAL. A new GUC,
wal_skip_threshold, guides that choice. If this change slows a workload
that creates small, permanent relfilenodes under wal_level=minimal, try
adjusting wal_skip_threshold. Users setting a timeout on COMMIT may
need to adjust that timeout, and log_min_duration_statement analysis
will reflect time consumption moving to COMMIT from commands like COPY.
Internally, this requires a reliable determination of whether
RollbackAndReleaseCurrentSubTransaction() would unlink a relation's
current relfilenode. Introduce rd_firstRelfilenodeSubid. Amend the
specification of rd_createSubid such that the field is zero when a new
rel has an old rd_node. Make relcache.c retain entries for certain
dropped relations until end of transaction.
Back-patch to 9.5 (all supported versions). This introduces a new WAL
record type, XLOG_GIST_ASSIGN_LSN, without bumping XLOG_PAGE_MAGIC. As
always, update standby systems before master systems. This changes
sizeof(RelationData) and sizeof(IndexStmt), breaking binary
compatibility for affected extensions. (The most recent commit to
affect the same class of extensions was
089e4d405d0f3b94c74a2c6a54357a84a681754b.)
Kyotaro Horiguchi, reviewed (in earlier, similar versions) by Robert
Haas. Heikki Linnakangas and Michael Paquier implemented earlier
designs that materially clarified the problem. Reviewed, in earlier
designs, by Andrew Dunstan, Andres Freund, Alvaro Herrera, Tom Lane,
Fujii Masao, and Simon Riggs. Reported by Martijn van Oosterhout.
Discussion: https://postgr.es/m/20150702220524.GA9392@svana.org
The core idea of this patch is to make the parser generate join alias
Vars (that is, ones with varno pointing to a JOIN RTE) only when the
alias Var is actually different from any raw join input, that is a type
coercion and/or COALESCE is necessary to generate the join output value.
Otherwise just generate varno/varattno pointing to the relevant join
input column.
In effect, this means that the planner's flatten_join_alias_vars()
transformation is already done in the parser, for all cases except
(a) columns that are merged by JOIN USING and are transformed in the
process, and (b) whole-row join Vars. In principle that would allow
us to skip doing flatten_join_alias_vars() in many more queries than
we do now, but we don't have quite enough infrastructure to know that
we can do so --- in particular there's no cheap way to know whether
there are any whole-row join Vars. I'm not sure if it's worth the
trouble to add a Query-level flag for that, and in any case it seems
like fit material for a separate patch. But even without skipping the
work entirely, this should make flatten_join_alias_vars() faster,
particularly where there are nested joins that it previously had to
flatten recursively.
An essential part of this change is to replace Var nodes'
varnoold/varoattno fields with varnosyn/varattnosyn, which have
considerably more tightly-defined meanings than the old fields: when
they differ from varno/varattno, they identify the Var's position in
an aliased JOIN RTE, and the join alias is what ruleutils.c should
print for the Var. This is necessary because the varno change
destroyed ruleutils.c's ability to find the JOIN RTE from the Var's
varno.
Another way in which this change broke ruleutils.c is that it's no
longer feasible to determine, from a JOIN RTE's joinaliasvars list,
which join columns correspond to which columns of the join's immediate
input relations. (If those are sub-joins, the joinaliasvars entries
may point to columns of their base relations, not the sub-joins.)
But that was a horrid mess requiring a lot of fragile assumptions
already, so let's just bite the bullet and add some more JOIN RTE
fields to make it more straightforward to figure that out. I added
two integer-List fields containing the relevant column numbers from
the left and right input rels, plus a count of how many merged columns
there are.
This patch depends on the ParseNamespaceColumn infrastructure that
I added in commit 5815696bc. The biggest bit of code change is
restructuring transformFromClauseItem's handling of JOINs so that
the ParseNamespaceColumn data is propagated upward correctly.
Other than that and the ruleutils fixes, everything pretty much
just works, though some processing is now inessential. I grabbed
two pieces of low-hanging fruit in that line:
1. In find_expr_references, we don't need to recurse into join alias
Vars anymore. There aren't any except for references to merged USING
columns, which are more properly handled when we scan the join's RTE.
This change actually fixes an edge-case issue: we will now record a
dependency on any type-coercion function present in a USING column's
joinaliasvar, even if that join column has no references in the query
text. The odds of the missing dependency causing a problem seem quite
small: you'd have to posit somebody dropping an implicit cast between
two data types, without removing the types themselves, and then having
a stored rule containing a whole-row Var for a join whose USING merge
depends on that cast. So I don't feel a great need to change this in
the back branches. But in theory this way is more correct.
2. markRTEForSelectPriv and markTargetListOrigin don't need to recurse
into join alias Vars either, because the cases they care about don't
apply to alias Vars for USING columns that are semantically distinct
from the underlying columns. This removes the only case in which
markVarForSelectPriv could be called with NULL for the RTE, so adjust
the comments to describe that hack as being strictly internal to
markRTEForSelectPriv.
catversion bump required due to changes in stored rules.
Discussion: https://postgr.es/m/7115.1577986646@sss.pgh.pa.us
This patch causes EXPLAIN to always assign a separate table alias to the
parent RTE of an append relation (inheritance set); before, such RTEs
were ignored if not actually scanned by the plan. Since the child RTEs
now always have that same alias to start with (cf. commit 55a1954da),
the net effect is that the parent RTE usually gets the alias used or
implied by the query text, and the children all get that alias with "_N"
appended. (The exception to "usually" is if there are duplicate aliases
in different subtrees of the original query; then some of those original
RTEs will also have "_N" appended.)
This results in more uniform output for partitioned-table plans than
we had before: the partitioned table itself gets the original alias,
and all child tables have aliases with "_N", rather than the previous
behavior where one of the children would get an alias without "_N".
The reason for giving the parent RTE an alias, even if it isn't scanned
by the plan, is that we now use the parent's alias to qualify Vars that
refer to an appendrel output column and appear above the Append or
MergeAppend that computes the appendrel. But below the append, Vars
refer to some one of the child relations, and are displayed that way.
This seems clearer than the old behavior where a Var that could carry
values from any child relation was displayed as if it referred to only
one of them.
While at it, change ruleutils.c so that the code paths used by EXPLAIN
deal in Plan trees not PlanState trees. This effectively reverts a
decision made in commit 1cc29fe7c, which seemed like a good idea at
the time to make ruleutils.c consistent with explain.c. However,
it's problematic because we'd really like to allow executor startup
pruning to remove all the children of an append node when possible,
leaving no child PlanState to resolve Vars against. (That's not done
here, but will be in the next patch.) This requires different handling
of subplans and initplans than before, but is otherwise a pretty
straightforward change.
Discussion: https://postgr.es/m/001001d4f44b$2a2cca50$7e865ef0$@lab.ntt.co.jp
This provides for cheaper mapping of child columns back to parent
columns. The one existing use-case in examine_simple_variable()
would hardly justify this by itself; but an upcoming bug fix will
make use of this array in a mainstream code path, and it seems
likely that we'll find other uses for it as we continue to build
out the partitioning infrastructure.
Discussion: https://postgr.es/m/12424.1575168015@sss.pgh.pa.us
When building statistics, we need to decide how many rows to sample and
how accurate the resulting statistics should be. Until now, it was not
possible to explicitly define statistics target for extended statistics
objects, the value was always computed from the per-attribute targets
with a fallback to the system-wide default statistics target.
That's a bit inconvenient, as it ties together the statistics target set
for per-column and extended statistics. In some cases it may be useful
to require larger sample / higher accuracy for extended statics (or the
other way around), but with this approach that's not possible.
So this commit introduces a new command, allowing to specify statistics
target for individual extended statistics objects, overriding the value
derived from per-attribute targets (and the system default).
ALTER STATISTICS stat_name SET STATISTICS target_value;
When determining statistics target for an extended statistics object we
first look at this explicitly set value. When this value is -1, we fall
back to the old formula, looking at the per-attribute targets first and
then the system default. This means the behavior is backwards compatible
with older PostgreSQL releases.
Author: Tomas Vondra
Discussion: https://postgr.es/m/20190618213357.vli3i23vpkset2xd@development
Reviewed-by: Kirk Jamison, Dean Rasheed
In 5f32b29c18 I changed the creation of HashState.hashkeys to
actually use HashState as the parent (instead of HashJoinState, which
was incorrect, as they were executed below HashState), to fix the
problem of hashkeys expressions otherwise relying on slot types
appropriate for HashJoinState, rather than HashState as would be
correct. That reliance was only introduced in 12, which is why it
previously worked to use HashJoinState as the parent (although I'd be
unsurprised if there were problematic cases).
Unfortunately that's not a sufficient solution, because before this
commit, the to-be-hashed expressions referenced inner/outer as
appropriate for the HashJoin, not Hash. That didn't have obvious bad
consequences, because the slots containing the tuples were put into
ecxt_innertuple when hashing a tuple for HashState (even though Hash
doesn't have an inner plan).
There are less common cases where this can cause visible problems
however (rather than just confusion when inspecting such executor
trees). E.g. "ERROR: bogus varno: 65000", when explaining queries
containing a HashJoin where the subsidiary Hash node's hash keys
reference a subplan. While normally hashkeys aren't displayed by
EXPLAIN, if one of those expressions references a subplan, that
subplan may be printed as part of the Hash node - which then failed
because an inner plan was referenced, and Hash doesn't have that.
It seems quite possible that there's other broken cases, too.
Fix the problem by properly splitting the expression for the HashJoin
and Hash nodes at plan time, and have them reference the proper
subsidiary node. While other workarounds are possible, fixing this
correctly seems easy enough. It was a pretty ugly hack to have
ExecInitHashJoin put the expression into the already initialized
HashState, in the first place.
I decided to not just split inner/outer hashkeys inside
make_hashjoin(), but also to separate out hashoperators and
hashcollations at plan time. Otherwise we would have ended up having
two very similar loops, one at plan time and the other during executor
startup. The work seems to more appropriately belong to plan time,
anyway.
Reported-By: Nikita Glukhov, Alexander Korotkov
Author: Andres Freund
Reviewed-By: Tom Lane, in an earlier version
Discussion: https://postgr.es/m/CAPpHfdvGVegF_TKKRiBrSmatJL2dR9uwFCuR+teQ_8tEXU8mxg@mail.gmail.com
Backpatch: 12-
Previously in order to determine which ECs a relation had members in, we
had to loop over all ECs stored in PlannerInfo's eq_classes and check if
ec_relids mentioned the relation. For the most part, this was fine, as
generally, unless queries were fairly complex, the overhead of performing
the lookup would have not been that significant. However, when queries
contained large numbers of joins and ECs, the overhead to find the set of
classes matching a given set of relations could become a significant
portion of the overall planning effort.
Here we allow a much more efficient method to access the ECs which match a
given relation or set of relations. A new Bitmapset field in RelOptInfo
now exists to store the indexes into PlannerInfo's eq_classes list which
each relation is mentioned in. This allows very fast lookups to find all
ECs belonging to a single relation. When we need to lookup ECs belonging
to a given pair of relations, we can simply bitwise-AND the Bitmapsets from
each relation and use the result to perform the lookup.
We also take the opportunity to write a new implementation of
generate_join_implied_equalities which makes use of the new indexes.
generate_join_implied_equalities_for_ecs must remain as is as it can be
given a custom list of ECs, which we can't easily determine the indexes of.
This was originally intended to fix the performance penalty of looking up
foreign keys matching a join condition which was introduced by 100340e2d.
However, we're speeding up much more than just that here.
Author: David Rowley, Tom Lane
Reviewed-by: Tom Lane, Tomas Vondra
Discussion: https://postgr.es/m/6970.1545327857@sss.pgh.pa.us
Originally, Postgres Lists were a more or less exact reimplementation of
Lisp lists, which consist of chains of separately-allocated cons cells,
each having a value and a next-cell link. We'd hacked that once before
(commit d0b4399d8) to add a separate List header, but the data was still
in cons cells. That makes some operations -- notably list_nth() -- O(N),
and it's bulky because of the next-cell pointers and per-cell palloc
overhead, and it's very cache-unfriendly if the cons cells end up
scattered around rather than being adjacent.
In this rewrite, we still have List headers, but the data is in a
resizable array of values, with no next-cell links. Now we need at
most two palloc's per List, and often only one, since we can allocate
some values in the same palloc call as the List header. (Of course,
extending an existing List may require repalloc's to enlarge the array.
But this involves just O(log N) allocations not O(N).)
Of course this is not without downsides. The key difficulty is that
addition or deletion of a list entry may now cause other entries to
move, which it did not before.
For example, that breaks foreach() and sister macros, which historically
used a pointer to the current cons-cell as loop state. We can repair
those macros transparently by making their actual loop state be an
integer list index; the exposed "ListCell *" pointer is no longer state
carried across loop iterations, but is just a derived value. (In
practice, modern compilers can optimize things back to having just one
loop state value, at least for simple cases with inline loop bodies.)
In principle, this is a semantics change for cases where the loop body
inserts or deletes list entries ahead of the current loop index; but
I found no such cases in the Postgres code.
The change is not at all transparent for code that doesn't use foreach()
but chases lists "by hand" using lnext(). The largest share of such
code in the backend is in loops that were maintaining "prev" and "next"
variables in addition to the current-cell pointer, in order to delete
list cells efficiently using list_delete_cell(). However, we no longer
need a previous-cell pointer to delete a list cell efficiently. Keeping
a next-cell pointer doesn't work, as explained above, but we can improve
matters by changing such code to use a regular foreach() loop and then
using the new macro foreach_delete_current() to delete the current cell.
(This macro knows how to update the associated foreach loop's state so
that no cells will be missed in the traversal.)
There remains a nontrivial risk of code assuming that a ListCell *
pointer will remain good over an operation that could now move the list
contents. To help catch such errors, list.c can be compiled with a new
define symbol DEBUG_LIST_MEMORY_USAGE that forcibly moves list contents
whenever that could possibly happen. This makes list operations
significantly more expensive so it's not normally turned on (though it
is on by default if USE_VALGRIND is on).
There are two notable API differences from the previous code:
* lnext() now requires the List's header pointer in addition to the
current cell's address.
* list_delete_cell() no longer requires a previous-cell argument.
These changes are somewhat unfortunate, but on the other hand code using
either function needs inspection to see if it is assuming anything
it shouldn't, so it's not all bad.
Programmers should be aware of these significant performance changes:
* list_nth() and related functions are now O(1); so there's no
major access-speed difference between a list and an array.
* Inserting or deleting a list element now takes time proportional to
the distance to the end of the list, due to moving the array elements.
(However, it typically *doesn't* require palloc or pfree, so except in
long lists it's probably still faster than before.) Notably, lcons()
used to be about the same cost as lappend(), but that's no longer true
if the list is long. Code that uses lcons() and list_delete_first()
to maintain a stack might usefully be rewritten to push and pop at the
end of the list rather than the beginning.
* There are now list_insert_nth...() and list_delete_nth...() functions
that add or remove a list cell identified by index. These have the
data-movement penalty explained above, but there's no search penalty.
* list_concat() and variants now copy the second list's data into
storage belonging to the first list, so there is no longer any
sharing of cells between the input lists. The second argument is
now declared "const List *" to reflect that it isn't changed.
This patch just does the minimum needed to get the new implementation
in place and fix bugs exposed by the regression tests. As suggested
by the foregoing, there's a fair amount of followup work remaining to
do.
Also, the ENABLE_LIST_COMPAT macros are finally removed in this
commit. Code using those should have been gone a dozen years ago.
Patch by me; thanks to David Rowley, Jesper Pedersen, and others
for review.
Discussion: https://postgr.es/m/11587.1550975080@sss.pgh.pa.us
Peter Eisentraut
David Rowley
Tom Lane
Etsuro Fujita
Tomas Vondra
Amit Kapila
Robert Haas
Bruce Momjian
Heikki Linnakangas
Noah Misch
Alexander Korotkov
Alvaro Herrera
Jeff Davis
Andres Freund