MERGE performs actions that modify rows in the target table
using a source table or query. MERGE provides a single SQL
statement that can conditionally INSERT/UPDATE/DELETE rows
a task that would other require multiple PL statements.
e.g.
MERGE INTO target AS t
USING source AS s
ON t.tid = s.sid
WHEN MATCHED AND t.balance > s.delta THEN
UPDATE SET balance = t.balance - s.delta
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED AND s.delta > 0 THEN
INSERT VALUES (s.sid, s.delta)
WHEN NOT MATCHED THEN
DO NOTHING;
MERGE works with regular and partitioned tables, including
column and row security enforcement, as well as support for
row, statement and transition triggers.
MERGE is optimized for OLTP and is parameterizable, though
also useful for large scale ETL/ELT. MERGE is not intended
to be used in preference to existing single SQL commands
for INSERT, UPDATE or DELETE since there is some overhead.
MERGE can be used statically from PL/pgSQL.
MERGE does not yet support inheritance, write rules,
RETURNING clauses, updatable views or foreign tables.
MERGE follows SQL Standard per the most recent SQL:2016.
Includes full tests and documentation, including full
isolation tests to demonstrate the concurrent behavior.
This version written from scratch in 2017 by Simon Riggs,
using docs and tests originally written in 2009. Later work
from Pavan Deolasee has been both complex and deep, leaving
the lead author credit now in his hands.
Extensive discussion of concurrency from Peter Geoghegan,
with thanks for the time and effort contributed.
Various issues reported via sqlsmith by Andreas Seltenreich
Authors: Pavan Deolasee, Simon Riggs
Reviewer: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs
Discussion:
https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.comhttps://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com
This adds simple cost based plan time decision about whether JIT
should be performed. jit_above_cost, jit_optimize_above_cost are
compared with the total cost of a plan, and if the cost is above them
JIT is performed / optimization is performed respectively.
For that PlannedStmt and EState have a jitFlags (es_jit_flags) field
that stores information about what JIT operations should be performed.
EState now also has a new es_jit field, which can store a
JitContext. When there are no errors the context is released in
standard_ExecutorEnd().
It is likely that the default values for jit_[optimize_]above_cost
will need to be adapted further, but in my test these values seem to
work reasonably.
Author: Andres Freund, with feedback by Peter Eisentraut
Discussion: https://postgr.es/m/20170901064131.tazjxwus3k2w3ybh@alap3.anarazel.de
Instead of embedding the savepoint name in a list and then requiring
complex code to unpack it, just add another struct field to store it
directly.
Reviewed-by: Alvaro Herrera <alvherre@alvh.no-ip.org>
The LIKE INCLUDING ALL clause to CREATE TABLE intuitively indicates
cloning of extended statistics on the source table, but it failed to do
so. Patch it up so that it does. Also include an INCLUDING STATISTICS
option to the LIKE clause, so that the behavior can be requested
individually, or excluded individually.
While at it, reorder the INCLUDING options, both in code and in docs, in
alphabetical order which makes more sense than feature-implementation
order that was previously used.
Backpatch this to Postgres 10, where extended statistics were
introduced, because this is seen as an oversight in a fresh feature
which is better to get consistent from the get-go instead of changing
only in pg11.
In pg11, comments on statistics objects are cloned too. In pg10 they
are not, because I (Álvaro) was too coward to change the parse node as
required to support it. Also, in pg10 I chose not to renumber the
parser symbols for the various INCLUDING options in LIKE, for the same
reason. Any corresponding user-visible changes (docs) are backpatched,
though.
Reported-by: Stephen Froehlich
Author: David Rowley
Reviewed-by: Álvaro Herrera, Tomas Vondra
Discussion: https://postgr.es/m/CY1PR0601MB1927315B45667A1B679D0FD5E5EF0@CY1PR0601MB1927.namprd06.prod.outlook.com
To support parameters in CALL, move the parse analysis of the procedure
and arguments into the global transformation phase, so that the parser
hooks can be applied. And then at execution time pass the parameters
from ProcessUtility on to ExecuteCallStmt.
This patch adds the ability to use "RANGE offset PRECEDING/FOLLOWING"
frame boundaries in window functions. We'd punted on that back in the
original patch to add window functions, because it was not clear how to
do it in a reasonably data-type-extensible fashion. That problem is
resolved here by adding the ability for btree operator classes to provide
an "in_range" support function that defines how to add or subtract the
RANGE offset value. Factoring it this way also allows the operator class
to avoid overflow problems near the ends of the datatype's range, if it
wishes to expend effort on that. (In the committed patch, the integer
opclasses handle that issue, but it did not seem worth the trouble to
avoid overflow failures for datetime types.)
The patch includes in_range support for the integer_ops opfamily
(int2/int4/int8) as well as the standard datetime types. Support for
other numeric types has been requested, but that seems like suitable
material for a follow-on patch.
In addition, the patch adds GROUPS mode which counts the offset in
ORDER-BY peer groups rather than rows, and it adds the frame_exclusion
options specified by SQL:2011. As far as I can see, we are now fully
up to spec on window framing options.
Existing behaviors remain unchanged, except that I changed the errcode
for a couple of existing error reports to meet the SQL spec's expectation
that negative "offset" values should be reported as SQLSTATE 22013.
Internally and in relevant parts of the documentation, we now consistently
use the terminology "offset PRECEDING/FOLLOWING" rather than "value
PRECEDING/FOLLOWING", since the term "value" is confusingly vague.
Oliver Ford, reviewed and whacked around some by me
Discussion: https://postgr.es/m/CAGMVOdu9sivPAxbNN0X+q19Sfv9edEPv=HibOJhB14TJv_RCQg@mail.gmail.com
Investigation of 2d2d06b7e2 revealed that
identity values were not applied in some further cases, including
logical replication subscribers, VALUES RTEs, and ALTER TABLE ... ADD
COLUMN. To fix all that, apply the identity column expression in
build_column_default() instead of repeating the same logic at each call
site.
For ALTER TABLE ... ADD COLUMN ... IDENTITY, the previous coding
completely ignored that existing rows for the new column should have
values filled in from the identity sequence. The coding using
build_column_default() fails for this because the sequence ownership
isn't registered until after ALTER TABLE, and we can't do it before
because we don't have the column in the catalog yet. So we specially
remember in ColumnDef the sequence name that we decided on and build a
custom NextValueExpr using that.
Reviewed-by: Michael Paquier <michael.paquier@gmail.com>
This clause was superseded by SQL-standard syntax back in 7.3.
We've kept it around for backwards-compatibility purposes ever since;
but 15 years seems like long enough for that, especially seeing that
there are undocumented weirdnesses in how it interacts with the
SQL-standard syntax for specifying the same options.
Michael Paquier, per an observation by Daniel Gustafsson;
some small cosmetic adjustments to nearby code by me.
Discussion: https://postgr.es/m/20180115022748.GB1724@paquier.xyz
When an UPDATE causes a row to no longer match the partition
constraint, try to move it to a different partition where it does
match the partition constraint. In essence, the UPDATE is split into
a DELETE from the old partition and an INSERT into the new one. This
can lead to surprising behavior in concurrency scenarios because
EvalPlanQual rechecks won't work as they normally did; the known
problems are documented. (There is a pending patch to improve the
situation further, but it needs more review.)
Amit Khandekar, reviewed and tested by Amit Langote, David Rowley,
Rajkumar Raghuwanshi, Dilip Kumar, Amul Sul, Thomas Munro, Álvaro
Herrera, Amit Kapila, and me. A few final revisions by me.
Discussion: http://postgr.es/m/CAJ3gD9do9o2ccQ7j7+tSgiE1REY65XRiMb=yJO3u3QhyP8EEPQ@mail.gmail.com
When CREATE INDEX is run on a partitioned table, create catalog entries
for an index on the partitioned table (which is just a placeholder since
the table proper has no data of its own), and recurse to create actual
indexes on the existing partitions; create them in future partitions
also.
As a convenience gadget, if the new index definition matches some
existing index in partitions, these are picked up and used instead of
creating new ones. Whichever way these indexes come about, they become
attached to the index on the parent table and are dropped alongside it,
and cannot be dropped on isolation unless they are detached first.
To support pg_dump'ing these indexes, add commands
CREATE INDEX ON ONLY <table>
(which creates the index on the parent partitioned table, without
recursing) and
ALTER INDEX ATTACH PARTITION
(which is used after the indexes have been created individually on each
partition, to attach them to the parent index). These reconstruct prior
database state exactly.
Reviewed-by: (in alphabetical order) Peter Eisentraut, Robert Haas, Amit
Langote, Jesper Pedersen, Simon Riggs, David Rowley
Discussion: https://postgr.es/m/20171113170646.gzweigyrgg6pwsg4@alvherre.pgsql
Introduce parallel-aware hash joins that appear in EXPLAIN plans as Parallel
Hash Join with Parallel Hash. While hash joins could already appear in
parallel queries, they were previously always parallel-oblivious and had a
partial subplan only on the outer side, meaning that the work of the inner
subplan was duplicated in every worker.
After this commit, the planner will consider using a partial subplan on the
inner side too, using the Parallel Hash node to divide the work over the
available CPU cores and combine its results in shared memory. If the join
needs to be split into multiple batches in order to respect work_mem, then
workers process different batches as much as possible and then work together
on the remaining batches.
The advantages of a parallel-aware hash join over a parallel-oblivious hash
join used in a parallel query are that it:
* avoids wasting memory on duplicated hash tables
* avoids wasting disk space on duplicated batch files
* divides the work of building the hash table over the CPUs
One disadvantage is that there is some communication between the participating
CPUs which might outweigh the benefits of parallelism in the case of small
hash tables. This is avoided by the planner's existing reluctance to supply
partial plans for small scans, but it may be necessary to estimate
synchronization costs in future if that situation changes. Another is that
outer batch 0 must be written to disk if multiple batches are required.
A potential future advantage of parallel-aware hash joins is that right and
full outer joins could be supported, since there is a single set of matched
bits for each hashtable, but that is not yet implemented.
A new GUC enable_parallel_hash is defined to control the feature, defaulting
to on.
Author: Thomas Munro
Reviewed-By: Andres Freund, Robert Haas
Tested-By: Rafia Sabih, Prabhat Sahu
Discussion:
https://postgr.es/m/CAEepm=2W=cOkiZxcg6qiFQP-dHUe09aqTrEMM7yJDrHMhDv_RA@mail.gmail.comhttps://postgr.es/m/CAEepm=37HKyJ4U6XOLi=JgfSHM3o6B-GaeO-6hkOmneTDkH+Uw@mail.gmail.com
When we create an Append node, we can spread out the workers over the
subplans instead of piling on to each subplan one at a time, which
should typically be a bit more efficient, both because the startup
cost of any plan executed entirely by one worker is paid only once and
also because of reduced contention. We can also construct Append
plans using a mix of partial and non-partial subplans, which may allow
for parallelism in places that otherwise couldn't support it.
Unfortunately, this patch doesn't handle the important case of
parallelizing UNION ALL by running each branch in a separate worker;
the executor infrastructure is added here, but more planner work is
needed.
Amit Khandekar, Robert Haas, Amul Sul, reviewed and tested by
Ashutosh Bapat, Amit Langote, Rafia Sabih, Amit Kapila, and
Rajkumar Raghuwanshi.
Discussion: http://postgr.es/m/CAJ3gD9dy0K_E8r727heqXoBmWZ83HwLFwdcaSSmBQ1+S+vRuUQ@mail.gmail.com
This adds a new object type "procedure" that is similar to a function
but does not have a return type and is invoked by the new CALL statement
instead of SELECT or similar. This implementation is aligned with the
SQL standard and compatible with or similar to other SQL implementations.
This commit adds new commands CALL, CREATE/ALTER/DROP PROCEDURE, as well
as ALTER/DROP ROUTINE that can refer to either a function or a
procedure (or an aggregate function, as an extension to SQL). There is
also support for procedures in various utility commands such as COMMENT
and GRANT, as well as support in pg_dump and psql. Support for defining
procedures is available in all the languages supplied by the core
distribution.
While this commit is mainly syntax sugar around existing functionality,
future features will rely on having procedures as a separate object
type.
Reviewed-by: Andrew Dunstan <andrew.dunstan@2ndquadrant.com>
If a PARAM_EXEC parameter is used below a Gather (Merge) but the InitPlan
that computes it is attached to or above the Gather (Merge), force the
value to be computed before starting parallelism and pass it down to all
workers. This allows us to use parallelism in cases where it previously
would have had to be rejected as unsafe. We do - in this case - lose the
optimization that the value is only computed if it's actually used. An
alternative strategy would be to have the first worker that needs the value
compute it, but one downside of that approach is that we'd then need to
select a parallel-safe path to compute the parameter value; it couldn't for
example contain a Gather (Merge) node. At some point in the future, we
might want to consider both approaches.
Independent of that consideration, there is a great deal more work that
could be done to make more kinds of PARAM_EXEC parameters parallel-safe.
This infrastructure could be used to allow a Gather (Merge) on the inner
side of a nested loop (although that's not a very appealing plan) and
cases where the InitPlan is attached below the Gather (Merge) could be
addressed as well using various techniques. But this is a good start.
Amit Kapila, reviewed and revised by me. Reviewing and testing from
Kuntal Ghosh, Haribabu Kommi, and Tushar Ahuja.
Discussion: http://postgr.es/m/CAA4eK1LV0Y1AUV4cUCdC+sYOx0Z0-8NAJ2Pd9=UKsbQ5Sr7+JQ@mail.gmail.com
Up until now, we only tracked the number of parameters, which was
sufficient to allocate an array of Datums of the appropriate size,
but not sufficient to, for example, know how to serialize a Datum
stored in one of those slots. An upcoming patch wants to do that,
so add this tracking to make it possible.
Patch by me, reviewed by Tom Lane and Amit Kapila.
Discussion: http://postgr.es/m/CA+TgmoYqpxDKn8koHdW8BEKk8FMUL0=e8m2Qe=M+r0UBjr3tuQ@mail.gmail.com
Hash partitioning is useful when you want to partition a growing data
set evenly. This can be useful to keep table sizes reasonable, which
makes maintenance operations such as VACUUM faster, or to enable
partition-wise join.
At present, we still depend on constraint exclusion for partitioning
pruning, and the shape of the partition constraints for hash
partitioning is such that that doesn't work. Work is underway to fix
that, which should both improve performance and make partitioning
pruning work with hash partitioning.
Amul Sul, reviewed and tested by Dilip Kumar, Ashutosh Bapat, Yugo
Nagata, Rajkumar Raghuwanshi, Jesper Pedersen, and by me. A few
final tweaks also by me.
Discussion: http://postgr.es/m/CAAJ_b96fhpJAP=ALbETmeLk1Uni_GFZD938zgenhF49qgDTjaQ@mail.gmail.com
Not much to say about this; does what it says on the tin.
However, formerly, if there was a column list then the ANALYZE action was
implied; now it must be specified, or you get an error. This is because
it would otherwise be a bit unclear what the user meant if some tables
have column lists and some don't.
Nathan Bossart, reviewed by Michael Paquier and Masahiko Sawada, with some
editorialization by me
Discussion: https://postgr.es/m/E061A8E3-5E3D-494D-94F0-E8A9B312BBFC@amazon.com
Allowing arrays with a domain type as their element type was left un-done
in the original domain patch, but not for any very good reason. This
omission leads to such surprising results as array_agg() not working on
a domain column, because the parser can't identify a suitable output type
for the polymorphic aggregate.
In order to fix this, first clean up the APIs of coerce_to_domain() and
some internal functions in parse_coerce.c so that we consistently pass
around a CoercionContext along with CoercionForm. Previously, we sometimes
passed an "isExplicit" boolean flag instead, which is strictly less
information; and coerce_to_domain() didn't even get that, but instead had
to reverse-engineer isExplicit from CoercionForm. That's contrary to the
documentation in primnodes.h that says that CoercionForm only affects
display and not semantics. I don't think this change fixes any live bugs,
but it makes things more consistent. The main reason for doing it though
is that now build_coercion_expression() receives ccontext, which it needs
in order to be able to recursively invoke coerce_to_target_type().
Next, reimplement ArrayCoerceExpr so that the node does not directly know
any details of what has to be done to the individual array elements while
performing the array coercion. Instead, the per-element processing is
represented by a sub-expression whose input is a source array element and
whose output is a target array element. This simplifies life in
parse_coerce.c, because it can build that sub-expression by a recursive
invocation of coerce_to_target_type(). The executor now handles the
per-element processing as a compiled expression instead of hard-wired code.
The main advantage of this is that we can use a single ArrayCoerceExpr to
handle as many as three successive steps per element: base type conversion,
typmod coercion, and domain constraint checking. The old code used two
stacked ArrayCoerceExprs to handle type + typmod coercion, which was pretty
inefficient, and adding yet another array deconstruction to do domain
constraint checking seemed very unappetizing.
In the case where we just need a single, very simple coercion function,
doing this straightforwardly leads to a noticeable increase in the
per-array-element runtime cost. Hence, add an additional shortcut evalfunc
in execExprInterp.c that skips unnecessary overhead for that specific form
of expression. The runtime speed of simple cases is within 1% or so of
where it was before, while cases that previously required two levels of
array processing are significantly faster.
Finally, create an implicit array type for every domain type, as we do for
base types, enums, etc. Everything except the array-coercion case seems
to just work without further effort.
Tom Lane, reviewed by Andrew Dunstan
Discussion: https://postgr.es/m/9852.1499791473@sss.pgh.pa.us
Index columns are referenced by ordinal number rather than name, e.g.
CREATE INDEX coord_idx ON measured (x, y, (z + t));
ALTER INDEX coord_idx ALTER COLUMN 3 SET STATISTICS 1000;
Incompatibility note for release notes:
\d+ for indexes now also displays Stats Target
Authors: Alexander Korotkov, with contribution by Adrien NAYRAT
Review: Adrien NAYRAT, Simon Riggs
Wordsmith: Simon Riggs
The ExecReScan machinery contains various optimizations for postponing
or skipping rescans of plan subtrees; for example a HashAgg node may
conclude that it can re-use the table it built before, instead of
re-reading its input subtree. But that is wrong if the input contains
a parallel-aware table scan node, since the portion of the table scanned
by the leader process is likely to vary from one rescan to the next.
This explains the timing-dependent buildfarm failures we saw after
commit a2b70c89c.
The established mechanism for showing that a plan node's output is
potentially variable is to mark it as depending on some runtime Param.
Hence, to fix this, invent a dummy Param (one that has a PARAM_EXEC
parameter number, but carries no actual value) associated with each Gather
or GatherMerge node, mark parallel-aware nodes below that node as dependent
on that Param, and arrange for ExecReScanGather[Merge] to flag that Param
as changed whenever the Gather[Merge] node is rescanned.
This solution breaks an undocumented assumption made by the parallel
executor logic, namely that all rescans of nodes below a Gather[Merge]
will happen synchronously during the ReScan of the top node itself.
But that's fundamentally contrary to the design of the ExecReScan code,
and so was doomed to fail someday anyway (even if you want to argue
that the bug being fixed here wasn't a failure of that assumption).
A follow-on patch will address that issue. In the meantime, the worst
that's expected to happen is that given very bad timing luck, the leader
might have to do all the work during a rescan, because workers think
they have nothing to do, if they are able to start up before the eventual
ReScan of the leader's parallel-aware table scan node has reset the
shared scan state.
Although this problem exists in 9.6, there does not seem to be any way
for it to manifest there. Without GatherMerge, it seems that a plan tree
that has a rescan-short-circuiting node below Gather will always also
have one above it that will short-circuit in the same cases, preventing
the Gather from being rescanned. Hence we won't take the risk of
back-patching this change into 9.6. But v10 needs it.
Discussion: https://postgr.es/m/CAA4eK1JkByysFJNh9M349u_nNjqETuEnY_y1VUc_kJiU0bxtaQ@mail.gmail.com
The executor is capable of splitting buckets during a hash join if
too much memory is being used by a small number of buckets. However,
this only helps if a bucket's population is actually divisible; if
all the hash keys are alike, the tuples still end up in the same
new bucket. This can result in an OOM failure if there are enough
inner keys with identical hash values. The planner's cost estimates
will bias it against choosing a hash join in such situations, but not
by so much that it will never do so. To mitigate the OOM hazard,
explicitly estimate the hash bucket space needed by just the inner
side's most common value, and if that would exceed work_mem then
add disable_cost to the hash cost estimate.
This approach doesn't account for the possibility that two or more
common values would share the same hash value. On the other hand,
work_mem is normally a fairly conservative bound, so that eating
two or more times that much space is probably not going to kill us.
If we have no stats about the inner side, ignore this consideration.
There was some discussion of making a conservative assumption, but that
would effectively result in disabling hash join whenever we lack stats,
which seems like an overreaction given how seldom the problem manifests
in the field.
Per a complaint from David Hinkle. Although this could be viewed
as a bug fix, the lack of similar complaints weighs against back-
patching; indeed we waited for v11 because it seemed already rather
late in the v10 cycle to be making plan choice changes like this one.
Discussion: https://postgr.es/m/32013.1487271761@sss.pgh.pa.us
Previously, UNBOUNDED meant no lower bound when used in the FROM list,
and no upper bound when used in the TO list, which was OK for
single-column range partitioning, but problematic with multiple
columns. For example, an upper bound of (10.0, UNBOUNDED) would not be
collocated with a lower bound of (10.0, UNBOUNDED), thus making it
difficult or impossible to define contiguous multi-column range
partitions in some cases.
Fix this by using MINVALUE and MAXVALUE instead of UNBOUNDED to
represent a partition column that is unbounded below or above
respectively. This syntax removes any ambiguity, and ensures that if
one partition's lower bound equals another partition's upper bound,
then the partitions are contiguous.
Also drop the constraint prohibiting finite values after an unbounded
column, and just document the fact that any values after MINVALUE or
MAXVALUE are ignored. Previously it was necessary to repeat UNBOUNDED
multiple times, which was needlessly verbose.
Note: Forces a post-PG 10 beta2 initdb.
Report by Amul Sul, original patch by Amit Langote with some
additional hacking by me.
Discussion: https://postgr.es/m/CAAJ_b947mowpLdxL3jo3YLKngRjrq9+Ej4ymduQTfYR+8=YAYQ@mail.gmail.com
The _equalTableFunc() omission of coltypmods has semantic significance,
but I did not track down resulting user-visible bugs, if any. The other
changes are cosmetic only, affecting order. catversion bump due to
readfuncs.c field order change.
Fix failure to check that we got a plain Const from const-simplification of
a coercion request. This is the cause of bug #14666 from Tian Bing: there
is an int4 to money cast, but it's only stable not immutable (because of
dependence on lc_monetary), resulting in a FuncExpr that the code was
miserably unequipped to deal with, or indeed even to notice that it was
failing to deal with. Add test cases around this coercion behavior.
In view of the above, sprinkle the code liberally with castNode() macros,
in hope of catching the next such bug a bit sooner. Also, change some
functions that were randomly declared to take Node* to take more specific
pointer types. And change some struct fields that were declared Node*
but could be given more specific types, allowing removal of assorted
explicit casts.
Place PARTITION_MAX_KEYS check a bit closer to the code it's protecting.
Likewise check only-one-key-for-list-partitioning restriction in a less
random place.
Avoid not-per-project-style usages like !strcmp(...).
Fix assorted failures to avoid scribbling on the input of parse
transformation. I'm not sure how necessary this is, but it's entirely
silly for these functions to be expending cycles to avoid that and not
getting it right.
Add guards against partitioning on system columns.
Put backend/nodes/ support code into an order that matches handling
of these node types elsewhere.
Annotate the fact that somebody added location fields to PartitionBoundSpec
and PartitionRangeDatum but forgot to handle them in
outfuncs.c/readfuncs.c. This is fairly harmless for production purposes
(since readfuncs.c would just substitute -1 anyway) but it's still bogus.
It's not worth forcing a post-beta1 initdb just to fix this, but if we
have another reason to force initdb before 10.0, we should go back and
clean this up.
Contrariwise, somebody added location fields to PartitionElem and
PartitionSpec but forgot to teach exprLocation() about them.
Consolidate duplicative code in transformPartitionBound().
Improve a couple of error messages.
Improve assorted commentary.
Re-pgindent the files touched by this patch; this affects a few comment
blocks that must have been added quite recently.
Report: https://postgr.es/m/20170524024550.29935.14396@wrigleys.postgresql.org
Previously, we had the WITH clause in the middle of the command, where
you'd specify both generic options as well as statistic types. Few
people liked this, so this commit changes it to remove the WITH keyword
from that clause and makes it accept statistic types only. (We
currently don't have any generic options, but if we invent in the
future, we will gain a new WITH clause, probably at the end of the
command).
Also, the column list is now specified without parens, which makes the
whole command look more similar to a SELECT command. This change will
let us expand the command to supporting expressions (not just columns
names) as well as multiple tables and their join conditions.
Tom added lots of code comments and fixed some parts of the CREATE
STATISTICS reference page, too; more changes in this area are
forthcoming. He also fixed a potential problem in the alter_generic
regression test, reducing verbosity on a cascaded drop to avoid
dependency on message ordering, as we do in other tests.
Tom also closed a security bug: we documented that table ownership was
required in order to create a statistics object on it, but didn't
actually implement it.
Implement tab-completion for statistics objects. This can stand some
more improvement.
Authors: Alvaro Herrera, with lots of cleanup by Tom Lane
Discussion: https://postgr.es/m/20170420212426.ltvgyhnefvhixm6i@alvherre.pgsql
It turned out this approach had problems, because a DROP command should
not have any options other than CASCADE and RESTRICT. Instead, always
attempt to drop the slot if there is one configured, but also add an
ALTER SUBSCRIPTION action to set the slot to NONE.
Author: Petr Jelinek <petr.jelinek@2ndquadrant.com>
Reported-by: Tom Lane <tgl@sss.pgh.pa.us>
Discussion: https://www.postgresql.org/message-id/29431.1493730652@sss.pgh.pa.us
Even though no actual tuples are ever inserted into a partitioned
table (the actual tuples are in the partitions, not the partitioned
table itself), we still need to have a ResultRelInfo for the
partitioned table, or per-statement triggers won't get fired.
Amit Langote, per a report from Rajkumar Raghuwanshi. Reviewed by me.
Discussion: http://postgr.es/m/CAKcux6%3DwYospCRY2J4XEFuVy0L41S%3Dfic7rmkbsU-GXhhSbmBg%40mail.gmail.com
We'd managed to avoid doing this so far, but it seems pretty obvious
that it would be forced on us some day, and this is much the cleanest
way of approaching the open problem that parallel-unsafe subplans are
being transmitted to parallel workers. Anyway there's no space cost
due to alignment considerations, and the time cost is pretty minimal
since we're just copying the flag from the corresponding Path node.
(At least in most cases ... some of the klugier spots in createplan.c
have to work a bit harder.)
In principle we could perhaps get rid of SubPlan.parallel_safe,
but I thought it better to keep that in case there are reasons to
consider a SubPlan unsafe even when its child plan is parallel-safe.
This patch doesn't actually do anything with the new flags, but
I thought I'd commit it separately anyway.
Note: although this touches outfuncs/readfuncs, there's no need for
a catversion bump because Plan trees aren't stored on disk.
Discussion: https://postgr.es/m/87tw5x4vcu.fsf@credativ.de
If there can certainly be no more than one matching inner row for a given
outer row, then the executor can move on to the next outer row as soon as
it's found one match; there's no need to continue scanning the inner
relation for this outer row. This saves useless scanning in nestloop
and hash joins. In merge joins, it offers the opportunity to skip
mark/restore processing, because we know we have not advanced past the
first possible match for the next outer row.
Of course, the devil is in the details: the proof of uniqueness must
depend only on joinquals (not otherquals), and if we want to skip
mergejoin mark/restore then it must depend only on merge clauses.
To avoid adding more planning overhead than absolutely necessary,
the present patch errs in the conservative direction: there are cases
where inner_unique or skip_mark_restore processing could be used, but
it will not do so because it's not sure that the uniqueness proof
depended only on "safe" clauses. This could be improved later.
David Rowley, reviewed and rather heavily editorialized on by me
Discussion: https://postgr.es/m/CAApHDvqF6Sw-TK98bW48TdtFJ+3a7D2mFyZ7++=D-RyPsL76gw@mail.gmail.com
This is the SQL standard-conforming variant of PostgreSQL's serial
columns. It fixes a few usability issues that serial columns have:
- CREATE TABLE / LIKE copies default but refers to same sequence
- cannot add/drop serialness with ALTER TABLE
- dropping default does not drop sequence
- need to grant separate privileges to sequence
- other slight weirdnesses because serial is some kind of special macro
Reviewed-by: Vitaly Burovoy <vitaly.burovoy@gmail.com>
A QueryEnvironment concept is added, which allows new types of
objects to be passed into queries from parsing on through
execution. At this point, the only thing implemented is a
collection of EphemeralNamedRelation objects -- relations which
can be referenced by name in queries, but do not exist in the
catalogs. The only type of ENR implemented is NamedTuplestore, but
provision is made to add more types fairly easily.
An ENR can carry its own TupleDesc or reference a relation in the
catalogs by relid.
Although these features can be used without SPI, convenience
functions are added to SPI so that ENRs can easily be used by code
run through SPI.
The initial use of all this is going to be transition tables in
AFTER triggers, but that will be added to each PL as a separate
commit.
An incidental effect of this patch is to produce a more informative
error message if an attempt is made to modify the contents of a CTE
from a referencing DML statement. No tests previously covered that
possibility, so one is added.
Kevin Grittner and Thomas Munro
Reviewed by Heikki Linnakangas, David Fetter, and Thomas Munro
with valuable comments and suggestions from many others
copyObject() is declared to return void *, which allows easily assigning
the result independent of the input, but it loses all type checking.
If the compiler supports typeof or something similar, cast the result to
the input type. This creates a greater amount of type safety. In some
cases, where the result is assigned to a generic type such as Node * or
Expr *, new casts are now necessary, but in general casts are now
unnecessary in the normal case and indicate that something unusual is
happening.
Reviewed-by: Mark Dilger <hornschnorter@gmail.com>
Add support for explicitly declared statistic objects (CREATE
STATISTICS), allowing collection of statistics on more complex
combinations that individual table columns. Companion commands DROP
STATISTICS and ALTER STATISTICS ... OWNER TO / SET SCHEMA / RENAME are
added too. All this DDL has been designed so that more statistic types
can be added later on, such as multivariate most-common-values and
multivariate histograms between columns of a single table, leaving room
for permitting columns on multiple tables, too, as well as expressions.
This commit only adds support for collection of n-distinct coefficient
on user-specified sets of columns in a single table. This is useful to
estimate number of distinct groups in GROUP BY and DISTINCT clauses;
estimation errors there can cause over-allocation of memory in hashed
aggregates, for instance, so it's a worthwhile problem to solve. A new
special pseudo-type pg_ndistinct is used.
(num-distinct estimation was deemed sufficiently useful by itself that
this is worthwhile even if no further statistic types are added
immediately; so much so that another version of essentially the same
functionality was submitted by Kyotaro Horiguchi:
https://postgr.es/m/20150828.173334.114731693.horiguchi.kyotaro@lab.ntt.co.jp
though this commit does not use that code.)
Author: Tomas Vondra. Some code rework by Álvaro.
Reviewed-by: Dean Rasheed, David Rowley, Kyotaro Horiguchi, Jeff Janes,
Ideriha Takeshi
Discussion: https://postgr.es/m/543AFA15.4080608@fuzzy.czhttps://postgr.es/m/20170320190220.ixlaueanxegqd5gr@alvherre.pgsql
Add a column collprovider to pg_collation that determines which library
provides the collation data. The existing choices are default and libc,
and this adds an icu choice, which uses the ICU4C library.
The pg_locale_t type is changed to a union that contains the
provider-specific locale handles. Users of locale information are
changed to look into that struct for the appropriate handle to use.
Also add a collversion column that records the version of the collation
when it is created, and check at run time whether it is still the same.
This detects potentially incompatible library upgrades that can corrupt
indexes and other structures. This is currently only supported by
ICU-provided collations.
initdb initializes the default collation set as before from the `locale
-a` output but also adds all available ICU locales with a "-x-icu"
appended.
Currently, ICU-provided collations can only be explicitly named
collations. The global database locales are still always libc-provided.
ICU support is enabled by configure --with-icu.
Reviewed-by: Thomas Munro <thomas.munro@enterprisedb.com>
Reviewed-by: Andreas Karlsson <andreas@proxel.se>
Partitioned tables do not contain any data; only their unpartitioned
descendents need to be scanned. However, the partitioned tables still
need to be locked, even though they're not scanned. To make that
work, Append and MergeAppend relations now need to carry a list of
(unscanned) partitioned relations that must be locked, and InitPlan
must lock all partitioned result relations.
Aside from the obvious advantage of avoiding some work at execution
time, this has two other advantages. First, it may improve the
planner's decision-making in some cases since the empty relation
might throw things off. Second, it paves the way to getting rid of
the storage for partitioned tables altogether.
Amit Langote, reviewed by me.
Discussion: http://postgr.es/m/6837c359-45c4-8044-34d1-736756335a15@lab.ntt.co.jp
Commit b6fb534f added two new node fields but neglected to add copy and
comparison support for them, Mea culpa, should have checked for that.
per buildfarm animals with -DCOPY_PARSE_PLAN_TREES
In DDL commands referring to an existing function, allow omitting the
argument list if the function name is unique in its schema, per SQL
standard.
This uses the same logic that the regproc type uses for finding
functions by name only.
Reviewed-by: Michael Paquier <michael.paquier@gmail.com>
Like Gather, we spawn multiple workers and run the same plan in each
one; however, Gather Merge is used when each worker produces the same
output ordering and we want to preserve that output ordering while
merging together the streams of tuples from various workers. (In a
way, Gather Merge is like a hybrid of Gather and MergeAppend.)
This works out to a win if it saves us from having to perform an
expensive Sort. In cases where only a small amount of data would need
to be sorted, it may actually be faster to use a regular Gather node
and then sort the results afterward, because Gather Merge sometimes
needs to wait synchronously for tuples whereas a pure Gather generally
doesn't. But if this avoids an expensive sort then it's a win.
Rushabh Lathia, reviewed and tested by Amit Kapila, Thomas Munro,
and Neha Sharma, and reviewed and revised by me.
Discussion: http://postgr.es/m/CAGPqQf09oPX-cQRpBKS0Gq49Z+m6KBxgxd_p9gX8CKk_d75HoQ@mail.gmail.com
The index is scanned by a single process, but then all cooperating
processes can iterate jointly over the resulting set of heap blocks.
In the future, we might also want to support using a parallel bitmap
index scan to set up for a parallel bitmap heap scan, but that's a
job for another day.
Dilip Kumar, with some corrections and cosmetic changes by me. The
larger patch set of which this is a part has been reviewed and tested
by (at least) Andres Freund, Amit Khandekar, Tushar Ahuja, Rafia
Sabih, Haribabu Kommi, Thomas Munro, and me.
Discussion: http://postgr.es/m/CAFiTN-uc4=0WxRGfCzs-xfkMYcSEWUC-Fon6thkJGjkh9i=13A@mail.gmail.com
XMLTABLE is defined by the SQL/XML standard as a feature that allows
turning XML-formatted data into relational form, so that it can be used
as a <table primary> in the FROM clause of a query.
This new construct provides significant simplicity and performance
benefit for XML data processing; what in a client-side custom
implementation was reported to take 20 minutes can be executed in 400ms
using XMLTABLE. (The same functionality was said to take 10 seconds
using nested PostgreSQL XPath function calls, and 5 seconds using
XMLReader under PL/Python).
The implemented syntax deviates slightly from what the standard
requires. First, the standard indicates that the PASSING clause is
optional and that multiple XML input documents may be given to it; we
make it mandatory and accept a single document only. Second, we don't
currently support a default namespace to be specified.
This implementation relies on a new executor node based on a hardcoded
method table. (Because the grammar is fixed, there is no extensibility
in the current approach; further constructs can be implemented on top of
this such as JSON_TABLE, but they require changes to core code.)
Author: Pavel Stehule, Álvaro Herrera
Extensively reviewed by: Craig Ringer
Discussion: https://postgr.es/m/CAFj8pRAgfzMD-LoSmnMGybD0WsEznLHWap8DO79+-GTRAPR4qA@mail.gmail.com
