Today we allow planning the queries that reference non-colocated tables
if the shards that query targets are placed on the same node. However,
this may not be the case, e.g., after rebalancing shards because it's
not guaranteed to have those shards on the same node anymore.
This commit adds citus.enable_non_colocated_router_query_pushdown GUC
that can be used to disallow planning such queries via router planner,
when it's set to false. Note that the default value for this GUC will be
"true" for 11.3, but we will alter it to "false" on 12.0 to not
introduce
a breaking change in a minor release.
Closes#692.
Even more, allowing such queries to go through router planner also
causes
generating an incorrect plan for the DML queries that reference
distributed
tables that are sharded based on different replication factor settings.
For
this reason, #6779 can be closed after altering the default value for
this
GUC to "false", hence not now.
DESCRIPTION: Adds `citus.enable_non_colocated_router_query_pushdown` GUC
to ensure generating a consistent distributed plan for the queries that
reference non-colocated distributed tables (when set to "false", the
default is "true").
Because they're only interested in distributed tables. Even more,
this replaces HasDistributionKey() check with
IsCitusTableType(DISTRIBUTED_TABLE) because this doesn't make a
difference on main and sounds slightly more intuitive. Plus, this
would also allow safely using this function in
https://github.com/citusdata/citus/pull/6773.
Fixes#6672
2) Move all MERGE related routines to a new file merge_planner.c
3) Make ConjunctionContainsColumnFilter() static again, and rearrange the code in MergeQuerySupported()
4) Restore the original format in the comments section.
5) Add big serial test. Implement latest set of comments
This implements the phase - II of MERGE sql support
Support routable query where all the tables in the merge-sql are distributed, co-located, and both the source and
target relations are joined on the distribution column with a constant qual. This should be a Citus single-task
query. Below is an example.
SELECT create_distributed_table('t1', 'id');
SELECT create_distributed_table('s1', 'id', colocate_with => ‘t1’);
MERGE INTO t1
USING s1 ON t1.id = s1.id AND t1.id = 100
WHEN MATCHED THEN
UPDATE SET val = s1.val + 10
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED THEN
INSERT (id, val, src) VALUES (s1.id, s1.val, s1.src)
Basically, MERGE checks to see if
There are a minimum of two distributed tables (source and a target).
All the distributed tables are indeed colocated.
MERGE relations are joined on the distribution column
MERGE .. USING .. ON target.dist_key = source.dist_key
The query should touch only a single shard i.e. JOIN AND with a constant qual
MERGE .. USING .. ON target.dist_key = source.dist_key AND target.dist_key = <>
If any of the conditions are not met, it raises an exception.
(cherry picked from commit 44c387b978)
This implements MERGE phase3
Support pushdown query where all the tables in the merge-sql are Citus-distributed, co-located, and both
the source and target relations are joined on the distribution column. This will generate multiple tasks
which execute independently after pushdown.
SELECT create_distributed_table('t1', 'id');
SELECT create_distributed_table('s1', 'id', colocate_with => ‘t1’);
MERGE INTO t1
USING s1
ON t1.id = s1.id
WHEN MATCHED THEN
UPDATE SET val = s1.val + 10
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED THEN
INSERT (id, val, src) VALUES (s1.id, s1.val, s1.src)
*The only exception for both the phases II and III is, UPDATEs and INSERTs must be done on the same shard-group
as the joined key; for example, below scenarios are NOT supported as the key-value to be inserted/updated is not
guaranteed to be on the same node as the id distribution-column.
MERGE INTO target t
USING source s ON (t.customer_id = s.customer_id)
WHEN NOT MATCHED THEN - -
INSERT(customer_id, …) VALUES (<non-local-constant-key-value>, ……);
OR this scenario where we update the distribution column itself
MERGE INTO target t
USING source s On (t.customer_id = s.customer_id)
WHEN MATCHED THEN
UPDATE SET customer_id = 100;
(cherry picked from commit fa7b8949a8)
Now that we will soon add another table type having DISTRIBUTE_BY_NONE
as distribution method and that we want the code to interpret such
tables mostly as distributed tables, let's make the definition of those
other two table types more strict by removing
CITUS_TABLE_WITH_NO_DIST_KEY
macro.
And instead, use HasDistributionKey() check in the places where the
logic applies to all table types that have / don't have a distribution
key. In future PRs, we might want to convert some of those
HasDistributionKey() checks if logic only applies to Citus local /
reference tables, not the others.
And adding HasDistributionKey() also allows us to consider having
DISTRIBUTE_BY_NONE as the distribution method as a "table attribute"
that can apply to distributed tables too, rather something that
determines the table type.
When auto_explain module is loaded and configured, EXPLAIN will be
implicitly run for all the supported commands. Postgres does not support
`EXPLAIN` for `ALTER` command. However, auto_explain will try to
`EXPLAIN` other supported commands internally triggered by `ALTER`.
For instance,
`ALTER TABLE target_table ADD CONSTRAINT fkey_167 FOREIGN KEY (col_1)
REFERENCES ref_table(key) ... `
command may trigger a SELECT command in the following form for foreign
key validation purpose:
`SELECT fk.col_1 FROM ONLY target_table fk LEFT OUTER JOIN ONLY
ref_table pk ON ( pk.key OPERATOR(pg_catalog.=) fk.col_1) WHERE pk.key
IS NULL AND (fk.col_1 IS NOT NULL) `
For Citus tables, the Citus utility hook should ensure that constraint
validation is skipped for shell tables but they are done for shard
tables. The reason behind this design choice can be summed up as:
- An ALTER TABLE command via coordinator node is run in a distributed
transaction.
- Citus does not support nested distributed transactions.
- A SELECT query on a distributed table (aka shell table) is also run in
a distributed transaction.
- Therefore, Citus does not support running a SELECT query on a shell
table while an ALTER TABLE command is running.
With
eadc88a800
a bug is introduced breaking the skip constraint validation behaviour of
Citus. With this change, we see that validation queries on distributed
tables are triggered within `ALTER` command adding constraints with
validation check. This regression did not cause an issue for regular use
cases since the citus executor hook blocks those queries heuristically
when there is an ALTER TABLE command in progress.
The issue is surfaced as a crash (#6424 Workers, when configured to use
auto_explain, crash during distributed transactions.) when auto_explain
is enabled. This is due to auto_explain trying to execute the SELECT
queries in a nested distributed transaction.
Now since the regression with constraint validation is fixed in
https://github.com/citusdata/citus/issues/6543, we should be able to
remove the workaround.
Recursive planner should handle all the tree from bottom to top at
single pass. i.e. It should have already recursively planned all
required parts in its first pass. Otherwise, this means we have bug at
recursive planner, which needs to be handled. We add a check here and
return error.
DESCRIPTION: Fixes wrong results by throwing error in case recursive
planner multipass the query.
We found 3 different cases which causes recursive planner passes the
query multiple times.
1. Sublink in WHERE clause is planned at second pass after we
recursively planned a distributed table at the first pass. Fixed by PR
#6657.
2. Local-distributed joins are recursively planned at both the first and
the second pass. Issue #6659.
3. Some parts of the query is considered to be noncolocated at the
second pass as we do not generate attribute equivalances between
nondistributed and distributed tables. Issue #6653
We should do the sublink conversations at the end of the recursive
planning because earlier steps might have transformed the query into a
shape that needs recursively planning the sublinks.
DESCRIPTION: Fixes early sublink check at recursive planner.
Related to PR https://github.com/citusdata/citus/pull/6650
If an update query on a reference table has a returns clause with a
subquery that accesses some other local table, we end-up with an crash.
This commit prevents the crash, but does not prevent other error
messages from happening due to Citus not being able to pushdown the
results of that subquery in a valid SQL command.
Related: #6634
This implements the phase - II of MERGE sql support
Support routable query where all the tables in the merge-sql are distributed, co-located, and both the source and
target relations are joined on the distribution column with a constant qual. This should be a Citus single-task
query. Below is an example.
SELECT create_distributed_table('t1', 'id');
SELECT create_distributed_table('s1', 'id', colocate_with => ‘t1’);
MERGE INTO t1
USING s1 ON t1.id = s1.id AND t1.id = 100
WHEN MATCHED THEN
UPDATE SET val = s1.val + 10
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED THEN
INSERT (id, val, src) VALUES (s1.id, s1.val, s1.src)
Basically, MERGE checks to see if
There are a minimum of two distributed tables (source and a target).
All the distributed tables are indeed colocated.
MERGE relations are joined on the distribution column
MERGE .. USING .. ON target.dist_key = source.dist_key
The query should touch only a single shard i.e. JOIN AND with a constant qual
MERGE .. USING .. ON target.dist_key = source.dist_key AND target.dist_key = <>
If any of the conditions are not met, it raises an exception.
All the tables (target, source or any CTE present) in the SQL statement are local i.e. a merge-sql with a combination of Citus local and
Non-Citus tables (regular Postgres tables) should work and give the same result as Postgres MERGE on regular tables. Catch and throw an
exception (not-yet-supported) for all other scenarios during Citus-planning phase.
Removes unused job boundary tag `SUBQUERY_MAP_MERGE_JOB`.
Only usage is at `BuildMapMergeJob`, which is only called when the
boundary = `JOIN_MAP_MERGE_JOB`. Hence, it should be safe to remove.
**Problem**: Currently, we error out if we detect recurring tuples in
one side without checking the other side of the join.
**Solution**: When one side of the full join consists recurring tuples
and the other side consists nonrecurring tuples, we should not pushdown
to prevent duplicate results. Otherwise, safe to pushdown.
Fixes a bug that causes crash when using auto_explain extension with
ALTER TABLE...ADD FOREIGN KEY... queries.
Those queries trigger a SELECT query on the citus tables as part of the
foreign key constraint validation check. At the explain hook, workers
try to explain this SELECT query as a distributed query causing memory
corruption in the connection data structures. Hence, we will not explain
ALTER TABLE...ADD FOREIGN KEY... and the triggered queries on the
workers.
Fixes#6424.
This crash happens with recursively planned queries. For such queries,
subplans are explained via the ExplainOnePlan function of postgresql.
This function reconstructs the query description from the plan therefore
it expects the ActiveSnaphot for the query be available. This fix makes
sure that the snapshot is in the stack before calling ExplainOnePlan.
Fixes#2920.
Comment from the code is clear on this:
/*
* The statistics objects of the distributed table are not relevant
* for the distributed planning, so we can override it.
*
* Normally, we should not need this. However, the combination of
* Postgres commit 269b532aef55a579ae02a3e8e8df14101570dfd9 and
* Citus function AdjustPartitioningForDistributedPlanning()
* forces us to do this. The commit expects statistics objects
* of partitions to have "inh" flag set properly. Whereas, the
* function overrides "inh" flag. To avoid Postgres to throw error,
* we override statlist such that Postgres does not try to process
* any statistics objects during the standard_planner() on the
* coordinator. In the end, we do not need the standard_planner()
* on the coordinator to generate an optimized plan. We call
* into standard_planner() for other purposes, such as generating the
* relationRestrictionContext here.
*
* AdjustPartitioningForDistributedPlanning() is a hack that we use
* to prevent Postgres' standard_planner() to expand all the partitions
* for the distributed planning when a distributed partitioned table
* is queried. It is required for both correctness and performance
* reasons. Although we can eliminate the use of the function for
* the correctness (e.g., make sure that rest of the planner can handle
* partitions), it's performance implication is hard to avoid. Certain
* planning logic of Citus (such as router or query pushdown) relies
* heavily on the relationRestrictionList. If
* AdjustPartitioningForDistributedPlanning() is removed, all the
* partitions show up in the, causing high planning times for
* such queries.
*/
* Fix issue : 6109 Segfault or (assertion failure) is possible when using a SQL function
* DESCRIPTION: Ensures disallowing the usage of SQL functions referencing to a distributed table and prevents a segfault.
Using a SQL function may result in segmentation fault in some cases.
This change fixes the issue by throwing an error message when a SQL function cannot be handled.
Fixes#6109.
* DESCRIPTION: Ensures disallowing the usage of SQL functions referencing to a distributed table and prevents a segfault.
Using a SQL function may result in segmentation fault in some cases. This change fixes the issue by throwing an error message when a SQL function cannot be handled.
Fixes#6109.
Co-authored-by: Emel Simsek <emel.simsek@microsoft.com>
Before, this was the default mode for CustomScan providers.
Now, the default is to assume that they can't project.
This causes performance penalties due to adding unnecessary
Result nodes.
Hence we use the newly added flag, CUSTOMPATH_SUPPORT_PROJECTION
to get it back to how it was.
In PG15 support branch we created explain functions to ignore
the new Result nodes, so we undo that in this commit.
Relevant PG commit:
955b3e0f9269639fb916cee3dea37aee50b82df0
Postgres supports JSON_TABLE feature on PG 15.
We treat JSON_TABLE the same as correlated functions (e.g., recurring tuples).
In the end, for multi-shard JSON_TABLE commands, we apply the same
restrictions as reference tables (e.g., cannot be in the outer part of
an outer join etc.)
Co-authored-by: Onder Kalaci <onderkalaci@gmail.com>
use RecurseObjectDependencies api to find if an object is citus depended
make vanilla tests runnable to see if citus_depended function is working correctly
* Remove if conditions with PG_VERSION_NUM < 13
* Remove server_above_twelve(&eleven) checks from tests
* Fix tests
* Remove pg12 and pg11 alternative test output files
* Remove pg12 specific normalization rules
* Some more if conditions in the code
* Change RemoteCollationIdExpression and some pg12/pg13 comments
* Remove some more normalization rules
This PR makes all of the features open source that were previously only
available in Citus Enterprise.
Features that this adds:
1. Non blocking shard moves/shard rebalancer
(`citus.logical_replication_timeout`)
2. Propagation of CREATE/DROP/ALTER ROLE statements
3. Propagation of GRANT statements
4. Propagation of CLUSTER statements
5. Propagation of ALTER DATABASE ... OWNER TO ...
6. Optimization for COPY when loading JSON to avoid double parsing of
the JSON object (`citus.skip_jsonb_validation_in_copy`)
7. Support for row level security
8. Support for `pg_dist_authinfo`, which allows storing different
authentication options for different users, e.g. you can store
passwords or certificates here.
9. Support for `pg_dist_poolinfo`, which allows using connection poolers
in between coordinator and workers
10. Tracking distributed query execution times using
citus_stat_statements (`citus.stat_statements_max`,
`citus.stat_statements_purge_interval`,
`citus.stat_statements_track`). This is disabled by default.
11. Blocking tenant_isolation
12. Support for `sslkey` and `sslcert` in `citus.node_conninfo`
The error comes due to the datum jsonb in pg_dist_metadata_node.metadata being 0 in some scenarios. This is likely due to not copying the data when receiving a datum from a tuple and pg deciding to deallocate that memory when the table that the tuple was from is closed.
Also fix another place in the code that might have been susceptible to this issue.
I tested on both multi-vg and multi-1-vg and the test were successful.
Teja Mupparti
Onur Tirtir
Emel Şimşek
Marco Slot
aykut-bozkurt
Hanefi Onaldi
Önder Kalacı
Philip Dubé
naisila
Naisila Puka
Marco Slot
Jelte Fennema
Gledis Zeneli
Burak Velioglu
Jeff Davis