and the expression originating from the source. If the types are different, Citus uses
different hash functions for the two column types, which might lead to incorrect repartitioning
of the result data
Previously, we only checked whether the relations are colocated, but we
ignore the shard indexes. That causes certain queries still to be
accidentally router. We should enforce colocation checks for both shard
index and table colocation id to make the check restrictive enough.
For example, the following query should not be router, and after this
patch, it won't:
```SQL
SELECT
user_id
FROM
((SELECT user_id FROM raw_events_first WHERE user_id = 15) EXCEPT
(SELECT user_id FROM raw_events_second where user_id = 17)) as foo;
```
DESCRIPTION: Enforce shard level colocation with
citus.enable_non_colocated_router_query_pushdown
This PR provides successful compilation against PG16Beta2. It does some
necessary refactoring to prepare for full support of version 16, in
https://github.com/citusdata/citus/pull/6952 .
Change RelFileNode to RelFileNumber or RelFileLocator
Relevant PG commit
b0a55e43299c4ea2a9a8c757f9c26352407d0ccc
new header for varatt.h
Relevant PG commit:
d952373a987bad331c0e499463159dd142ced1ef
drop support for Abs, use fabs
Relevant PG commit
357cfefb09115292cfb98d504199e6df8201c957
tuplesort PGcommit: d37aa3d35832afde94e100c4d2a9618b3eb76472
Relevant PG commit:
d37aa3d35832afde94e100c4d2a9618b3eb76472
Fix vacuum in columnar
Relevant PG commit:
4ce3afb82ecfbf64d4f6247e725004e1da30f47c
older one:
b6074846cebc33d752f1d9a66e5a9932f21ad177
Add alloc_flags to pg_clean_ascii
Relevant PG commit:
45b1a67a0fcb3f1588df596431871de4c93cb76f
Merge GetNumConfigOptions() into get_guc_variables()
Relevant PG commit:
3057465acfbea2f3dd7a914a1478064022c6eecd
Minor PG refactor PG_FUNCNAME_MACRO __func__
Relevant PG commit
320f92b744b44f961e5d56f5f21de003e8027a7f
Pass NULL context to stringToQualifiedNameList, typeStringToTypeName
The pre-PG16 error behaviour for the following
stringToQualifiedNameList & typeStringToTypeName
was ereport(ERROR, ...)
Now with PG16 we have this context input. We preserve the same behaviour
by passing a NULL context, because of the following:
(copy paste comment from PG16)
If "context" isn't an ErrorSaveContext node, this behaves as
errstart(ERROR, domain), and the errsave() macro ends up acting
exactly like ereport(ERROR, ...).
Relevant PG commit
858e776c84f48841e7e16fba7b690b76e54f3675
Use RangeVarCallbackMaintainsTable instead of RangeVarCallbackOwnsTable
Relevant PG commit:
60684dd834a222fefedd49b19d1f0a6189c1632e
FIX THIS: Not implemented grant-level control of role inheritance
see PG commit
e3ce2de09d814f8770b2e3b3c152b7671bcdb83f
Make Scan node abstract
PG commit:
8c73c11a0d39049de2c1f400d8765a0eb21f5228
Change in Var representations, get_relids_in_jointree
PG commit
2489d76c4906f4461a364ca8ad7e0751ead8aa0d
Deadlock detection changes because SHM_QUEUE is removed
Relevant PG Commit:
d137cb52cb7fd44a3f24f3c750fbf7924a4e9532
TU_UpdateIndexes
Relevant PG commit
19d8e2308bc51ec4ab993ce90077342c915dd116
Use object_ownercheck and object_aclcheck functions
Relevant PG commits:
afbfc02983f86c4d71825efa6befd547fe81a926
c727f511bd7bf3c58063737bcf7a8f331346f253
Rework Permission Info for successful compilation
Relevant PG commits:
postgres/postgres@a61b1f7postgres/postgres@b803b7d
---------
Co-authored-by: onderkalaci <onderkalaci@gmail.com>
This commit is the second and last phase of dropping PG13 support.
It consists of the following:
- Removes all PG_VERSION_13 & PG_VERSION_14 from codepaths
- Removes pg_version_compat entries and columnar_version_compat entries
specific for PG13
- Removes alternative pg13 test outputs
- Removes PG13 normalize lines and fix the test outputs based on that
It is a continuation of 5bf163a27d
1) For distributed tables that are not colocated.
2) When joining on a non-distribution column for colocated tables.
3) When merging into a distributed table using reference or citus-local tables as the data source.
This is accomplished primarily through the implementation of the following two strategies.
Repartition: Plan the source query independently,
execute the results into intermediate files, and repartition the files to
co-locate them with the merge-target table. Subsequently, compile a final
merge query on the target table using the intermediate results as the data
source.
Pull-to-coordinator: Execute the plan that requires evaluation at the coordinator,
run the query on the coordinator, and redistribute the resulting rows to ensure
colocation with the target shards. Direct the MERGE SQL operation to the worker
nodes' target shards, using the intermediate files colocated with the data as the
data source.
While going over this piece of code (a long time ago) it was bothering
to me we keep a bool array with the size of shardcount to iterate only
over shards present in the list of non-pruned shards. Especially since
we keep min/max of the set shards to optimize iteration.
Postgres has the bitmapset datastructure which a) takes significantly
less space, b) has iterator functions to only iterate over set bits, c)
can efficiently skip long sequences of unset bits and d) stops quickly
once the last set bit has been reached.
I have been contemplating if it is worth to keep the minShardOffset
because of readability and the efficient skipping of unset bits,
however, I have decided to keep it -although less readable-, as there
are known usecases where 100k+ shards are pruned to single digit shards.
If these would end up at the end of `shardcount` a hotloop of zero
checks on the first iteration _could_ cause a theoretical performance
regression.
All in all, this code is using less memory in all cases where it
matters, and less cpu in most cases, while using more idiomatic
datastructures for the task at hand.
PG16beta1 added some sanity checks for GUCS, find the Relevant PG
commits below:
1- Add check on initial and boot values when loading GUCs
a73952b795
2- Extend check_GUC_init() with checks on flag combinations when loading
GUCs
009f8d1714
I fixed our currently problematic GUCS, we can merge this directly into
main as these make sense for any PG version.
There was a particular NodeConninfo issue:
Previously we would rely on the fact that NodeConninfo initial value
is an empty string. However, with PG16 enforcing same initial and boot
values, we can't use an empty initial value for NodeConninfo anymore.
Therefore we add a new flag to indicate whether we are at boot check.
PG16 removed them. They were already identical to Assert. We can merge
this directly to main branch
Relevant PG commit:
b1099eca8f
b1099eca8f38ff5cfaf0901bb91cb6a22f909bc6
Co-authored-by: onderkalaci <onderkalaci@gmail.com>
Verify Citus UDFs work well with single shard tables
SUPPORTED
* citus_table_size
* citus_total_relation_size
* citus_relation_size
* citus_shard_sizes
* truncate_local_data_after_distributing_table
* create_distributed_function // test function colocated with a single
shard table
* undistribute_table
* alter_table_set_access_method
UNSUPPORTED - error out for single shard tables
* master_create_empty_shard
* create_distributed_table_concurrently
* create_distributed_table
* create_reference_table
* citus_add_local_table_to_metadata
* citus_split_shard_by_split_points
* alter_distributed_table
Previously INSERT .. SELECT planner were pushing down some queries that should not be pushed down due to wrong colocation checks. It was checking whether one of the table in SELECT part and target table are colocated. But now, we check colocation for all tables in SELECT part and the target table.
Another problem with INSERT .. SELECT planner was that some queries, which is valid to be pushed down, were not pushed down due to unnecessary checks which are currently supported. e.g. UNION check. As solution, we reused the pushdown planner checks for INSERT .. SELECT planner.
DESCRIPTION: Fixes a bug that causes incorrectly pushing down some
INSERT .. SELECT queries that we shouldn't
DESCRIPTION: Prevents unnecessarily pulling the data into coordinator
for some INSERT .. SELECT queries
DESCRIPTION: Drops support for pushing down INSERT .. SELECT with append
table as target
Fixes#6749.
Fixes#1428.
Fixes#6920.
---------
Co-authored-by: aykutbozkurt <aykut.bozkurt1995@gmail.com>
We mark objects as distributed objects in Citus metadata only if we need
to propagate given the command that creates it to worker nodes. For this
reason, we were not doing this for the objects that are created while
pg_dist_node is empty.
One implication of doing so is that we defer the schema propagation to
the time when user creates the first distributed table in the schema.
However, this doesn't help for schema-based sharding (#6866) because we
want to sync pg_dist_tenant_schema to the worker nodes even for empty
schemas too.
* Support test dependencies for isolation tests without a schedule
* Comment out a test due to a known issue (#6901)
* Also, reduce the verbosity for some log messages and make some
tests compatible with run_test.py.
* Add support for dist insert select by selecting from a reference
table.
This was the only pushable insert .. select case that
#6773 didn't cover.
* For the cases where we insert into a Citus table but the INSERT ..
SELECT
query cannot be pushed down, allow pull-to-coordinator when possible.
Remove the checks that we had at the very beginning of
CreateInsertSelectPlanInternal so that we can try insert .. select via
pull-to-coordinator for the cases where we cannot push-down the insert
.. select query. What we support via pull-to-coordinator is still
limited due to lacking of logical planner support for SELECT queries,
but this commit at least allows using pull-to-coordinator for the cases
where the select query can be planned via router planner, without
limiting ourselves to restrictive top-level checks.
Also introduce some additional restrictions into
CreateDistributedInsertSelectPlan for the cases it was missing to check
for null-shard-key tables. Indeed, it would make more sense to have
those checks for distributed tables in general, via separate PRs against
main branch. See https://github.com/citusdata/citus/pull/6817.
* Add support for inserting into a Postgres table.
Enable router planner and a limited version of INSERT .. SELECT planner
for the queries that reference colocated null shard key tables.
* SELECT / UPDATE / DELETE / MERGE is supported as long as it's a router
query.
* INSERT .. SELECT is supported as long as it only references colocated
null shard key tables.
Note that this is not only limited to distributed INSERT .. SELECT but
also
covers a limited set of query types that require pull-to-coordinator,
e.g.,
due to LIMIT clause, generate_series() etc. ...
(Ideally distributed INSERT .. SELECT could handle such queries too,
e.g.,
when we're only referencing tables that don't have a shard key, but
today
this is not the case. See
https://github.com/citusdata/citus/pull/6773#discussion_r1140130562.
Add tests for ddl coverage:
* indexes
* partitioned tables + indexes with long names
* triggers
* foreign keys
* statistics
* grant & revoke statements
* truncate & vacuum
* create/test/drop view that depends on a dist table with no shard key
* policy & rls test
* alter table add/drop/alter_type column (using sequences/different data
types/identity columns)
* alter table add constraint (not null, check, exclusion constraint)
* alter table add column with a default value / set default / drop
default
* alter table set option (autovacuum)
* indexes / constraints without names
* multiple subcommands
Adds support for
* Creating new partitions after distributing (with null key) the parent
table
* Attaching partitions to a distributed table with null distribution key
(and automatically distribute the new partition with null key as well)
* Detaching partitions from it
With this PR, we allow creating distributed tables with without
specifying a shard key via create_distributed_table(). Here are the
the important details about those tables:
* Specifying `shard_count` is not allowed because it is assumed to be 1.
* We mostly call such tables as "null shard-key" table in code /
comments.
* To avoid doing a breaking layout change in create_distributed_table();
instead of throwing an error, it will inform the user that
`distribution_type`
param is ignored unless it's explicitly set to NULL or 'h'.
* `colocate_with` param allows colocating such null shard-key tables to
each other.
* We define this table type, i.e., NULL_SHARD_KEY_TABLE, as a subclass
of
DISTRIBUTED_TABLE because we mostly want to treat them as distributed
tables in terms of SQL / DDL / operation support.
* Metadata for such tables look like:
- distribution method => DISTRIBUTE_BY_NONE
- replication model => REPLICATION_MODEL_STREAMING
- colocation id => **!=** INVALID_COLOCATION_ID (distinguishes from
Citus local tables)
* We assign colocation groups for such tables to different nodes in a
round-robin fashion based on the modulo of "colocation id".
Note that this PR doesn't care about DDL (except CREATE TABLE) / SQL /
operation (i.e., Citus UDFs) support for such tables but adds a
preliminary
API.
`PlaceHolderVar` is not relevant to be processed inside a restriction
clause. Otherwise, `pull_var_clause_default` would throw error. PG would
create the restriction to physical `Var` that `PlaceHolderVar` points to
anyway, so it is safe to skip this restriction.
DESCRIPTION: Fixes a bug related to WHERE clause list which contains
placeholder.
Fixes https://github.com/citusdata/citus/issues/6758
DESCRIPTION: Adds views that monitor statistics on tenant usages
This PR adds `citus_stats_tenants` view that monitors the tenants on the
cluster.
`citus_stats_tenants` shows the node id, colocation id, tenant
attribute, read count in this period and last period, and query count in
this period and last period of the tenant.
Tenant attribute currently is the tenant's distribution column value,
later when schema based sharding is introduced, this meaning might
change.
A period is a time bucket the queries are counted by. Read and query
counts for this period can increase until the current period ends. After
that those counts are moved to last period's counts, which cannot
change. The period length can be set using 'citus.stats_tenants_period'.
`SELECT` queries are counted as _read_ queries, `INSERT`, `UPDATE` and
`DELETE` queries are counted as _write_ queries. So in the view read
counts are `SELECT` counts and query counts are `SELECT`, `INSERT`,
`UPDATE` and `DELETE` count.
The data is stored in shared memory, in a struct named
`MultiTenantMonitor`.
`citus_stats_tenants` shows the data from local tenants.
`citus_stats_tenants` show up to `citus.stats_tenant_limit` number of
tenants.
The tenants are scored based on the number of queries they run and the
recency of those queries. Every query ran increases the score of tenant
by `ONE_QUERY_SCORE`, and after every period ends the scores are halved.
Halving is done lazily.
To retain information a longer the monitor keeps up to 3 times
`citus.stats_tenant_limit` tenants. When the tenant count hits `3 *
citus.stats_tenant_limit`, last `citus.stats_tenant_limit` tenants are
removed. To see all stored tenants you can use
`citus_stats_tenants(return_all_tenants := true)`
- [x] Create collector view that gets data from all nodes. #6761
- [x] Add monitoring log #6762
- [x] Create enable/disable GUC #6769
- [x] Parse the annotation string correctly #6796
- [x] Add local queries and prepared statements #6797
- [x] Rename to citus_stat_statements #6821
- [x] Run pgbench
- [x] Fix role permissions #6812
---------
Co-authored-by: Gokhan Gulbiz <ggulbiz@gmail.com>
Co-authored-by: Jelte Fennema <github-tech@jeltef.nl>
DESCRIPTION: Fix an issue that caused some queries with custom
aggregates to fail
While playing around with https://github.com/pgvector/pgvector I noticed
that the AVG query was broken. That's because we treat it as any other
AVG by breaking it down in SUM and COUNT, but there are no SUM/COUNT
functions in this case, but there is a perfectly usable combinefunc.
This PR changes our aggregate logic to prefer custom aggregates with a
combinefunc even if they have a common name.
Co-authored-by: Marco Slot <marco.slot@gmail.com>
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.
We've had custom versions of Postgres its `foreach` macro which with a
hidden ListCell for quite some time now. People like these custom
macros, because they are easier to use and require less boilerplate.
This adds similar custom versions of Postgres its `forboth` macro. Now
you don't need ListCells anymore when looping over two lists at the same
time.
With the introduction of #4385 we inadvertently started allowing and
pushing down certain lateral subqueries that were unsafe to push down.
To be precise the type of LATERAL subqueries that is unsafe to push down
has all of the following properties:
1. The lateral subquery contains some non recurring tuples
2. The lateral subquery references a recurring tuple from
outside of the subquery (recurringRelids)
3. The lateral subquery requires a merge step (e.g. a LIMIT)
4. The reference to the recurring tuple should be something else than an
equality check on the distribution column, e.g. equality on a non
distribution column.
Property number four is considered both hard to detect and probably not
used very often. Thus this PR ignores property number four and causes
query planning to error out if the first three properties hold.
Fixes#5327
If a worker node is being added, a command is sent to get the server_id of the worker from the pg_dist_node_metadata table. If the worker's id is the same as the node executing the code, we will know the node is trying to add itself. If the node tries to add itself without specifying `groupid:=0` the operation will result in an error.
If the expression is simple, such as, SELECT function() or PEFORM function()
in PL/PgSQL code, PL engine does a simple expression evaluation which can't
interpret the Citus CustomScan Node. Code checks for simple expressions when
executing an UDF but missed the DO-Block scenario, this commit fixes it.
Previously, we were wrapping targetlist nodes with Vars that reference
to the result of the worker query, if the node itself is not `Const` or
not a `Param`. Indeed, we should not do that unless the node itself is
a `Var` node or contains a `Var` within it (e.g.: `OpExpr(Var(column_a) > 2)`).
Otherwise, when worker query returns empty result set, then combine
query exec would crash since the `Var` would be pointing to an empty
tuple slot, which is not desirable for the node-executor methods.
Teja Mupparti
Önder Kalacı
Naisila Puka
Nils Dijk
Onur Tirtir
Ahmet Gedemenli
aykut-bozkurt
Halil Ozan Akgül
Marco Slot
Emel Şimşek
Hanefi Onaldi
Philip Dubé
naisila
Marco Slot
Jelte Fennema
Gledis Zeneli
Burak Velioglu
Jeff Davis