Waiting for PostgreSQL 11 – Improve run-time partition pruning to handle any stable expression.

On 10th of June 2018, Tom Lane committed patch:

Improve run-time partition pruning to handle any stable expression.
 
 
The initial coding of the run-time-pruning feature only coped with cases
where the partition key(s) are compared to Params.  That is a bit silly;
we can allow it to work with any non-Var-containing stable expression, as
long as we take special care with expressions containing PARAM_EXEC Params.
The code is hardly any longer this way, and it's considerably clearer
(IMO at least).  Per gripe from Pavel Stehule.
 
David Rowley, whacked around a bit by me
 
Discussion: https://postgr.es/m/CAFj8pRBjrufA3ocDm8o4LPGNye9Y+pm1b9kCwode4X04CULG3g@mail.gmail.com

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Waiting for PostgreSQL 11 – Support partition pruning at execution time

On 7th of April 2018, Alvaro Herrera committed patch:

Support partition pruning at execution time
Existing partition pruning is only able to work at plan time, for query
quals that appear in the parsed query. This is good but limiting, as
there can be parameters that appear later that can be usefully used to
further prune partitions.
This commit adds support for pruning subnodes of Append which cannot
possibly contain any matching tuples, during execution, by evaluating
Params to determine the minimum set of subnodes that can possibly match.
We support more than just simple Params in WHERE clauses. Support
additionally includes:
1. Parameterized Nested Loop Joins: The parameter from the outer side of the
join can be used to determine the minimum set of inner side partitions to
scan.
2. Initplans: Once an initplan has been executed we can then determine which
partitions match the value from the initplan.
Partition pruning is performed in two ways. When Params external to the plan
are found to match the partition key we attempt to prune away unneeded Append
subplans during the initialization of the executor. This allows us to bypass
the initialization of non-matching subplans meaning they won't appear in the
EXPLAIN or EXPLAIN ANALYZE output.
For parameters whose value is only known during the actual execution
then the pruning of these subplans must wait. Subplans which are
eliminated during this stage of pruning are still visible in the EXPLAIN
output. In order to determine if pruning has actually taken place, the
EXPLAIN ANALYZE must be viewed. If a certain Append subplan was never
executed due to the elimination of the partition then the execution
timing area will state "(never executed)". Whereas, if, for example in
the case of parameterized nested loops, the number of loops stated in
the EXPLAIN ANALYZE output for certain subplans may appear lower than
others due to the subplan having been scanned fewer times. This is due
to the list of matching subnodes having to be evaluated whenever a
parameter which was found to match the partition key changes.
This commit required some additional infrastructure that permits the
building of a data structure which is able to perform the translation of
the matching partition IDs, as returned by get_matching_partitions, into
the list index of a subpaths list, as exist in node types such as
Append, MergeAppend and ModifyTable. This allows us to translate a list
of clauses into a Bitmapset of all the subpath indexes which must be
included to satisfy the clause list.
Author: David Rowley, based on an earlier effort by Beena Emerson
Reviewers: Amit Langote, Robert Haas, Amul Sul, Rajkumar Raghuwanshi,
Jesper Pedersen
Discussion: https://postgr.es/m/CAOG9ApE16ac-_VVZVvv0gePSgkg_BwYEV1NBqZFqDR2bBE0X0A@mail.gmail.com

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Waiting for PostgreSQL 11 – Indexes with INCLUDE columns and their support in B-tree

On 7th of April 2018, Teodor Sigaev committed patch:

Indexes with INCLUDE columns and their support in B-tree
 
This patch introduces INCLUDE clause to index definition.  This clause
specifies a list of columns which will be included as a non-key part in
the index.  The INCLUDE columns exist solely to allow more queries to
benefit from index-only scans.  Also, such columns don't need to have
appropriate operator classes.  Expressions are not supported as INCLUDE
columns since they cannot be used in index-only scans.
 
Index access methods supporting INCLUDE are indicated by amcaninclude flag
in IndexAmRoutine.  For now, only B-tree indexes support INCLUDE clause.
 
In B-tree indexes INCLUDE columns are truncated from pivot index tuples
(tuples located in non-leaf pages and high keys).  Therefore, B-tree indexes
now might have variable number of attributes.  This patch also provides
generic facility to support that: pivot tuples contain number of their
attributes in t_tid.ip_posid.  Free 13th bit of t_info is used for indicating
that.  This facility will simplify further support of index suffix truncation.
The changes of above are backward-compatible, pg_upgrade doesn't need special
handling of B-tree indexes for that.
 
Bump catalog version
 
Author: Anastasia Lubennikova with contribition by Alexander Korotkov and me
Reviewed by: Peter Geoghegan, Tomas Vondra, Antonin Houska, Jeff Janes,
             David Rowley, Alexander Korotkov
Discussion: https://www.postgresql.org/message-id/flat/.4010101@postgrespro.ru

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Waiting for PostgreSQL 11 – Add json(b)_to_tsvector function

On 7th of April 2018, Teodor Sigaev committed patch:

Add json(b)_to_tsvector function
 
Jsonb has a complex nature so there isn't best-for-everything way to convert it
to tsvector for full text search. Current to_tsvector(json(b)) suggests to
convert only string values, but it's possible to index keys, numerics and even
booleans value. To solve that json(b)_to_tsvector has a second required
argument contained a list of desired types of json fields. Second argument is
a jsonb scalar or array right now with possibility to add new options in a
future.
 
Bump catalog version
 
Author: Dmitry Dolgov with some editorization by me
Reviewed by: Teodor Sigaev
Discussion: https://www.postgresql.org/message-id/CA+q6zcXJQbS1b4kJ_HeAOoOc=unfnOrUEL=KGgE32QKDww7d8g@mail.gmail.com

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Waiting for PostgreSQL 11 – Transforms for jsonb to PL/Python and to PL/Perl

On 28th of March 2018, Peter Eisentraut committed patch:

Transforms for jsonb to PL/Python
 
Add a new contrib module jsonb_plpython that provide a transform between
jsonb and PL/Python.  jsonb values are converted to appropriate Python
types such as dicts and lists, and vice versa.
 
Author: Anthony Bykov <a.bykov@postgrespro.ru>

and then, on 3rd of April 2018, he also committed patch:

Transforms for jsonb to PL/Perl
 
Add a new contrib module jsonb_plperl that provides a transform between
jsonb and PL/Perl.  jsonb values are converted to appropriate Perl types
such as arrays and hashes, and vice versa.
 
Author: Anthony Bykov <a.bykov@postgrespro.ru>

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Waiting for PostgreSQL 11 – MERGE SQL Command following SQL:2016

update!

It looks that this has been reverted

On 2nd of April 2018, Simon Riggs committed patch:

MERGE SQL Command following SQL:2016
 
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
Reviewers: Peter Geoghegan, Amit Langote, Tomas Vondra, Simon Riggs
 
Discussion:
https://postgr.es/m/CANP8+jKitBSrB7oTgT9CY2i1ObfOt36z0XMraQc+Xrz8QB0nXA@mail.gmail.com
https://postgr.es/m/CAH2-WzkJdBuxj9PO=2QaO9-3h3xGbQPZ34kJH=HukRekwM-GZg@mail.gmail.com

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Waiting for PostgreSQL 11 – Fast ALTER TABLE ADD COLUMN with a non-NULL default

On 28th of March 2018, Andrew Dunstan committed patch:

Fast ALTER TABLE ADD COLUMN with a non-NULL default
 
 
Currently adding a column to a table with a non-NULL default results in
a rewrite of the table. For large tables this can be both expensive and
disruptive. This patch removes the need for the rewrite as long as the
default value is not volatile. The default expression is evaluated at
the time of the ALTER TABLE and the result stored in a new column
(attmissingval) in pg_attribute, and a new column (atthasmissing) is set
to true. Any existing row when fetched will be supplied with the
attmissingval. New rows will have the supplied value or the default and
so will never need the attmissingval.
 
Any time the table is rewritten all the atthasmissing and attmissingval
settings for the attributes are cleared, as they are no longer needed.
 
The most visible code change from this is in heap_attisnull, which
acquires a third TupleDesc argument, allowing it to detect a missing
value if there is one. In many cases where it is known that there will
not be any (e.g.  catalog relations) NULL can be passed for this
argument.
 
Andrew Dunstan, heavily modified from an original patch from Serge
Rielau.
Reviewed by Tom Lane, Andres Freund, Tomas Vondra and David Rowley.
 
Discussion: https://postgr.es/m/-7002-4c27-59f5-@2ndQuadrant.com

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Waiting for PostgreSQL 11 – Support all SQL:2011 options for window frame clauses.

On 7th of February 2018, Tom Lane committed patch:

Support all SQL:2011 options for window frame clauses.
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

Continue reading Waiting for PostgreSQL 11 – Support all SQL:2011 options for window frame clauses.

Waiting for PostgreSQL 11 – Support parallel btree index builds.

Support parallel btree index builds.
 
 
To make this work, tuplesort.c and logtape.c must also support
parallelism, so this patch adds that infrastructure and then applies
it to the particular case of parallel btree index builds.  Testing
to date shows that this can often be 2-3x faster than a serial
index build.
 
The model for deciding how many workers to use is fairly primitive
at present, but it's better than not having the feature.  We can
refine it as we get more experience.
 
Peter Geoghegan with some help from Rushabh Lathia.  While Heikki
Linnakangas is not an author of this patch, he wrote other patches
without which this feature would not have been possible, and
therefore the release notes should possibly credit him as an author
of this feature.  Reviewed by Claudio Freire, Heikki Linnakangas,
Thomas Munro, Tels, Amit Kapila, me.
 
Discussion: http://postgr.es/m/CAM3SWZQKM=Pzc=CAHzRixKjp2eO5Q0Jg1SoFQqeXFQ647JiwqQ@mail.gmail.com
Discussion: http://postgr.es/m/CAH2-Wz=AxWqDoVvGU7dq856S4r6sJAj6DBn7VMtigkB33N5eyg@mail.gmail.com

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Waiting for PostgreSQL 11 – Allow UPDATE to move rows between partitions.

On 19th of January 2018, Robert Haas committed patch:

Allow UPDATE to move rows between partitions.
 
 
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

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Tag: pg11