When a relation is used on an OUTER JOIN with FALSE filters,
set_rel_pathlist_hook may not be called for the table.
There might be other cases as well, so do not rely on the hook
for classification of the tables.
RemoveDuplicateJoinRestrictions() function was introduced with the aim of decrasing the overall planning times by eliminating the duplicate JOIN restriction entries (#1989). However, it turns out that the function itself is so CPU intensive with a very high algorithmic complexity, it hurts a lot more than it helps. The function is a clear example of premature optimization.
The table below shows the difference clearly:
"distributed query planning
time master" RemoveDuplicateJoinRestrictions() execution time on master "Remove the function RemoveDuplicateJoinRestrictions()
this PR"
5 table INNER JOIN 9 msec 2msec 7 msec
10 table INNER JOIN 227 msec 194 msec 29 msec
20 table INNER JOIN 1 sec 235 msec 1 sec 139 msec 90 msecs
50 table INNER JOIN 24 seconds 21 seconds 1.5 seconds
100 table INNER JOIN 2 minutes 16 secods 1 minute 53 seconds 23 seconds
250 table INNER JOIN Bottleneck on JoinClauseList 18 minutes 52 seconds Bottleneck on JoinClauseList
5 table INNER JOIN in subquery 9 msec 0 msec 6 msec
10 table INNER JOIN subquery 33 msec 10 msec 32 msec
20 table INNER JOIN subquery 132 msec 67 msec 123 msec
50 table INNER JOIN subquery 1.2 seconds 900 msec 500 msec
100 table INNER JOIN subquery 6 seconds 5 seconds 2 seconds
250 table INNER JOIN subquery 54 seconds 37 seconds 20 seconds
5 table LEFT JOIN 5 msec 0 msec 5 msec
10 table LEFT JOIN 11 msec 0 msec 13 msec
20 table LEFT JOIN 26 msec 2 msec 30 msec
50 table LEFT JOIN 150 msec 15 msec 193 msec
100 table LEFT JOIN 757 msec 71 msec 722 msec
250 table LEFT JOIN 8 seconds 600 msec 8 seconds
5 JOINs among 2 table JOINs 37 msec 11 msec 25 msec
10 JOINs among 2 table JOINs 536 msec 306 msec 352 msec
20 JOINs among 2 table JOINs 794 msec 181 msec 640 msec
50 JOINs among 2 table JOINs 25 seconds 2 seconds 22 seconds
100 JOINs among 2 table JOINs Bottleneck on JoinClauseList 9 seconds Bottleneck on JoinClauseList
150 JOINs among 2 table JOINs Bottleneck on JoinClauseList 46 seconds Bottleneck on JoinClauseList
On top of the performance penalty, the function had a critical bug #4255, and with #4254 we hit one more important bug. It should be fixed by adding the followig check to the ContextCoversJoinRestriction():
```
static bool
JoinRelIdsSame(JoinRestriction *leftRestriction, JoinRestriction *rightRestriction)
{
Relids leftInnerRelIds = leftRestriction->innerrel->relids;
Relids rightInnerRelIds = rightRestriction->innerrel->relids;
if (!bms_equal(leftInnerRelIds, rightInnerRelIds))
{
return false;
}
Relids leftOuterRelIds = leftRestriction->outerrel->relids;
Relids rightOuterRelIds = rightRestriction->outerrel->relids;
if (!bms_equal(leftOuterRelIds, rightOuterRelIds))
{
return false;
}
return true;
}
```
However, adding this eliminates all the benefits tha RemoveDuplicateJoinRestrictions() brings.
I've used the commands here to generate the JOINs mentioned in the PR: https://gist.github.com/onderkalaci/fe8654f9df5916c7af4c7c5eb892561e#file-gistfile1-txt
Inner and outer JOINs behave roughly the same, to simplify the table only added INNER joins.
Disallow `ON TRUE` outer joins with reference & distributed tables
when reference table is outer relation by fixing the logic bug made
when calling `LeftListIsSubset` function.
Also, be more defensive when removing duplicate join restrictions
when join clause is empty for non-inner joins as they might still
contain useful information for non-inner joins.
It seems like Postgres could call set_rel_pathlist() for
the same relation multiple times. This breaks the logic
where we assume relationCount eqauls to the number of
entries in relationRestrictionList.
In summary, relationRestrictionList may contain duplicate
entries.
Introduce table entry utility functions
Citus table cache entry utilities are introduced so that we can easily
extend existing functionality with minimum changes, specifically changes
to these functions. For example IsNonDistributedTableCacheEntry can be
extended for citus local tables without the need to scan the whole
codebase and update each relevant part.
* Introduce utility functions to find the type of tables
A table type can be a reference table, a hash/range/append distributed
table. Utility methods are created so that we don't have to worry about
how a table is considered as a reference table etc. This also makes it
easy to extend the table types.
* Add IsCitusTableType utilities
* Rename IsCacheEntryCitusTableType -> IsCitusTableTypeCacheEntry
* Change citus table types in some checks
This commit mostly adds pg_get_triggerdef_command to our ruleutils_13.
This doesn't add anything extra for ruleutils 13 so it is basically a copy
of the change on ruleutils_12
Rte index is increased by range table index offset in pg >= 13. The
offset is removed with the pg >= 13.
Currently pushdown for union all is disabled because translatedVars is
set to nil on postgres side, and we were using translatedVars to
figure out if partition key has the same index in both sides of union
all. This should be fixed.
Commit on postgres side:
6ef77cf46e81f45716ec981cb08781d426181378
fix union all pushdown logic for pg13
Before pg 13, there was a field, translatedVars, and we were using that
to understand if the partition key has the same index on both sides of
the union all. With pg13 there is a parent_colnos field in appendRelInfo
and we can use that to get the attribute numbers(varattnos) in union all
vars. We make use of parent_colnos instead of translatedVars in pg >=13.
Some refactoring:
Consolidate expression which decides whether GROUP BY/HAVING are pushed down
Rename early pullUpIntermediateRows to hasNonDistributableAggregates
Create WorkerColumnName to handle formatting WORKER_COLUMN_FORMAT
Ignore NULL StringInfo pointers to SafeToPushdownWindowFunction
Fix bug where SubqueryPushdownMultiNodeTree mutates supplied Query,
SafeToPushdownWindowFunction requires the original query as it relies on rtable
Semmle reported quite some places where we use a value that could be NULL. Most of these are not actually a real issue, but better to be on the safe side with these things and make the static analysis happy.
We've changed the logic for pulling RTE_RELATIONs in #3109 and
non-colocated subquery joins and partitioned tables.
@onurctirtir found this steps where I traced back and found the issues.
While looking into it in more detail, we decided to expand the list in a
way that the callers get all the relevant RTE_RELATIONs RELKIND_RELATION,
RELKIND_PARTITIONED_TABLE, RELKIND_FOREIGN_TABLE and RELKIND_MATVIEW.
These are all relation kinds that Citus planner is aware of.
PostgreSQL might remove some of the subqueries when they do not
contribute to the query result at all. Citus should not try to
access such subqueries during planning.
With #1804 (and related PRs), Citus gained the ability to
plan subqueries that are not safe to pushdown.
There are two high-level requirements for pushing down subqueries:
* Individual subqueries that require a merge step (i.e., GROUP BY
on non-distribution key, or LIMIT in the subquery etc). We've
handled such subqueries via #1876.
* Combination of subqueries that are not joined on distribution keys.
This commit aims to recursively plan some of such subqueries to make
the whole query safe to pushdown.
The main logic behind non colocated subquery joins is that we pick
an anchor range table entry and check for distribution key equality
of any other subqueries in the given query. If for a given subquery,
we cannot find distribution key equality with the anchor rte, we
recursively plan that subquery.
We also used a hacky solution for picking relations as the anchor range
table entries. The hack is that we wrap them into a subquery. This is only
necessary since some of the attribute equivalance checks are based on
queries rather than range table entries.
We used to only support pushdownable set operations inside a
subquery, however, we could easily expand the restriction
checks to cover top level set operations as well.
We use PostgreSQL hooks to accumulate the join restrictions
and PostgreSQL gives us all the join paths it tries while
deciding on the join order. Thus, for queries that have many
joins, this function is likely to remove lots of duplicate join
restrictions. This becomes relevant for Citus on query pushdown
check peformance.
We added the ability to filter out the planner restriction information
for specific parts of the query. This might lead to situations where
the common restriction includes some other relations that we're searching
for. The reason is that while filtering for join restrictions, we add the
restriction as soon as we find the relation.
With this commit we make sure that the common attribute
equivalance class always includes the input relations.
In subquery pushdown, we first ensure that each relation is joined with at least
on another relation on the partition keys. That's fine given that the decision
is binary: pushdown the query at all or not.
With recursive planning, we'd want to check whether any specific part
of the query can be pushded down or not. Thus, we need the ability to
understand which part(s) of the subquery is safe to pushdown. This commit
adds the infrastructure for doing that.
With this commit, we relax the restrictions put on the reference
tables with subquery pushdown.
We did three notable improvements:
1) Relax equi-join restrictions
Previously, we always expected that the non-reference tables are
equi joined with reference tables on the partition key of the
non-reference table.
With this commit, we allow any column of non-reference tables
joined using non-equi joins as well.
2) Relax OUTER JOIN restrictions
Previously Citus errored out if any reference table exists at
any point of the outer part of an outer join. For instance,
See the below sketch where (h) denotes a hash distributed relation,
(r) denotes a reference table, (L) denotes LEFT JOIN and
(I) denotes INNER JOIN.
(L)
/ \
(I) h
/ \
r h
Before this commit Citus would error out since a reference table
appears on the left most part of an left join. However, that was
too restrictive so that we only error out if the reference table
is directly below and in the outer part of an outer join.
3) Bug fixes
We've done some minor bugfixes in the existing implementation.
Adds support for PostgreSQL 10 by copying in the requisite ruleutils
and updating all API usages to conform with changes in PostgreSQL 10.
Most changes are fairly minor but they are numerous. One particular
obstacle was the change in \d behavior in PostgreSQL 10's psql; I had
to add SQL implementations (views, mostly) to mimic the pre-10 output.
* Enabling physical planner for subquery pushdown changes
This commit applies the logic that exists in INSERT .. SELECT
planning to the subquery pushdown changes.
The main algorithm is followed as :
- pick an anchor relation (i.e., target relation)
- per each target shard interval
- add the target shard interval's shard range
as a restriction to the relations (if all relations
joined on the partition keys)
- Check whether the query is router plannable per
target shard interval.
- If router plannable, create a task
* Add union support within the JOINS
This commit adds support for UNION/UNION ALL subqueries that are
in the following form:
.... (Q1 UNION Q2 UNION ...) as union_query JOIN (QN) ...
In other words, we currently do NOT support the queries that are
in the following form where union query is not JOINed with
other relations/subqueries :
.... (Q1 UNION Q2 UNION ...) as union_query ....
* Subquery pushdown planner uses original query
With this commit, we change the input to the logical planner for
subquery pushdown. Before this commit, the planner was relying
on the query tree that is transformed by the postgresql planner.
After this commit, the planner uses the original query. The main
motivation behind this change is the simplify deparsing of
subqueries.
* Enable top level subquery join queries
This work enables
- Top level subquery joins
- Joins between subqueries and relations
- Joins involving more than 2 range table entries
A new regression test file is added to reflect enabled test cases
* Add top level union support
This commit adds support for UNION/UNION ALL subqueries that are
in the following form:
.... (Q1 UNION Q2 UNION ...) as union_query ....
In other words, Citus supports allow top level
unions being wrapped into aggregations queries
and/or simple projection queries that only selects
some fields from the lower level queries.
* Disallow subqueries without a relation in the range table list for subquery pushdown
This commit disallows subqueries without relation in the range table
list. This commit is only applied for subquery pushdown. In other words,
we do not add this limitation for single table re-partition subqueries.
The reasoning behind this limitation is that if we allow pushing down
such queries, the result would include (shardCount * expectedResults)
where in a non distributed world the result would be (expectedResult)
only.
* Disallow subqueries without a relation in the range table list for INSERT .. SELECT
This commit disallows subqueries without relation in the range table
list. This commit is only applied for INSERT.. SELECT queries.
The reasoning behind this limitation is that if we allow pushing down
such queries, the result would include (shardCount * expectedResults)
where in a non distributed world the result would be (expectedResult)
only.
* Change behaviour of subquery pushdown flag (#1315)
This commit changes the behaviour of the citus.subquery_pushdown flag.
Before this commit, the flag is used to enable subquery pushdown logic. But,
with this commit, that behaviour is enabled by default. In other words, the
flag is now useless. We prefer to keep the flag since we don't want to break
the backward compatibility. Also, we may consider using that flag for other
purposes in the next commits.
* Require subquery_pushdown when limit is used in subquery
Using limit in subqueries may cause returning incorrect
results. Therefore we allow limits in subqueries only
if user explicitly set subquery_pushdown flag.
* Evaluate expressions on the LIMIT clause (#1333)
Subquery pushdown uses orignal query, the LIMIT and OFFSET clauses
are not evaluated. However, logical optimizer expects these expressions
are already evaluated by the standard planner. This commit manually
evaluates the functions on the logical planner for subquery pushdown.
* Better format subquery regression tests (#1340)
* Style fix for subquery pushdown regression tests
With this commit we intented a more consistent style for the
regression tests we've added in the
- multi_subquery_union.sql
- multi_subquery_complex_queries.sql
- multi_subquery_behavioral_analytics.sql
* Enable the tests that are temporarily commented
This commit enables some of the regression tests that were commented
out until all the development is done.
* Fix merge conflicts (#1347)
- Update regression tests to meet the changes in the regression
test output.
- Replace Ifs with Asserts given that the check is already done
- Update shard pruning outputs
* Add view regression tests for increased subquery coverage (#1348)
- joins between views and tables
- joins between views
- union/union all queries involving views
- views with limit
- explain queries with view
* Improve btree operators for the subquery tests
This commit adds the missing comprasion for subquery composite key
btree comparator.
In this PR, we aim to deduce whether each of the RTE_RELATION
is joined with at least on another RTE_RELATION on their partition keys. If each
RTE_RELATION follows the above rule, we can conclude that all RTE_RELATIONs are
joined on their partition keys.
In order to do that, we invented a new equivalence class namely:
AttributeEquivalenceClass. In very simple words, a AttributeEquivalenceClass is
identified by an unique id and consists of a list of AttributeEquivalenceMembers.
Each AttributeEquivalenceMember is designed to identify attributes uniquely within the
whole query. The necessity of this arise since varno attributes are defined within
a single level of a query. Instead, here we want to identify each RTE_RELATION uniquely
and try to find equality among each RTE_RELATION's partition key.
Whenever we find an equality clause A = B, where both A and B originates from
relation attributes (i.e., not random expressions), we create an
AttributeEquivalenceClass to record this knowledge. If we later find another
equivalence B = C, we create another AttributeEquivalenceClass. Finally, we can
apply transitity rules and generate a new AttributeEquivalenceClass which includes
A, B and C.
Note that equality among the members are identified by the varattno and rteIdentity.
Each equality among RTE_RELATION is saved using an AttributeEquivalenceClass where
each member attribute is identified by a AttributeEquivalenceMember. In the final
step, we try generate a common attribute equivalence class that holds as much as
AttributeEquivalenceMembers whose attributes are a partition keys.
Onder Kalaci
Onur Tirtir
SaitTalhaNisanci
Jelte Fennema
Philip Dubé
Marco Slot
Önder Kalacı
Hadi Moshayedi
velioglu
Jason Petersen