DESCRIPTION: Adds JSON_TABLE() support
PG17 has added basic `JSON_TABLE()` functionality
`JSON_TABLE()` allows `JSON` data to be converted into a relational view
and thus used, for example, in a `FROM` clause, like other tabular data.
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 perform a lateral
outer join when a distributed subquery references a (reference
table)/(json table) etc.)
Relevant PG17 commits:
[basic JSON
table](https://github.com/postgres/postgres/commit/de3600452), [nested
paths in json
table](https://github.com/postgres/postgres/commit/bb766cde6)
Onder had previously added json table support for PG15BETA1, but we
reverted that commit because json table was reverted in PG15.
ce7f1a530f
Previous relevant PG15Beta1 commit:
https://github.com/postgres/postgres/commit/4e34747c8
Therefore, I referred to Onder's commit for this commit as well, with a
few changes due to some differences between PG15/PG17:
1) In PG15Beta1, we had also `PLAN` clauses for `JSON_TABLE`
https://github.com/postgres/postgres/commit/fadb48b00, and Onder's
commit includes tests for those as well. However, `PLAN` nodes are _not_
added in PG17. Therefore, I didn't include the `json_table_select_only`
test, which had mostly queries involving `PLAN`. I only included the
last query from that test.
2) In PG15 timeline (Citus 11.1), we didn't support outer joins where
the outer rel is a recurring one and the inner one is a non-recurring
one. However, [Onur added support for that one in Citus
11.2](https://github.com/citusdata/citus/pull/6512), therefore I updated
the tests from Onder's commit accordingly.
3) PG17 json table has nested paths and columns, therefore I added a
test
with a distributed table, which is exactly the same as the one in
sqljson_jsontable in PG17.
https://github.com/postgres/postgres/commit/bb766cde6
This pull request also adds some basic tests on validation of SQL/JSON
constructor functions JSON(), JSON_SCALAR(), and JSON_SERIALIZE(),
and also SQL/JSON query functions JSON_EXISTS(), JSON_QUERY(), and
JSON_VALUE(). The relevant PG commits are the following:
[JSON(), JSON_SCALAR(),
JSON_SERIALIZE()](https://github.com/postgres/postgres/commit/03734a7fe)
[JSON_EXISTS(), JSON_VALUE(),
JSON_QUERY()](https://github.com/postgres/postgres/commit/6185c9737)
This is prep work for successful compilation with PG17
PG17added foreach_ptr, foreach_int and foreach_oid macros
Relevant PG commit
14dd0f27d7cd56ffae9ecdbe324965073d01a9ff
14dd0f27d7
We already have these macros, but they are different with the
PG17 ones because our macros take a DECLARED variable, whereas
the PG16 macros declare a locally-scoped loop variable themselves.
Hence I am renaming our macros to foreach_declared_
I am separating this into its own PR since it touches many files. The
main compilation PR is https://github.com/citusdata/citus/pull/7699
This change adds a script to programatically group all includes in a
specific order. The script was used as a one time invocation to group
and sort all includes throught our formatted code. The grouping is as
follows:
- System includes (eg. `#include<...>`)
- Postgres.h (eg. `#include "postgres.h"`)
- Toplevel imports from postgres, not contained in a directory (eg.
`#include "miscadmin.h"`)
- General postgres includes (eg . `#include "nodes/..."`)
- Toplevel citus includes, not contained in a directory (eg. `#include
"citus_verion.h"`)
- Columnar includes (eg. `#include "columnar/..."`)
- Distributed includes (eg. `#include "distributed/..."`)
Because it is quite hard to understand the difference between toplevel
citus includes and toplevel postgres includes it hardcodes the list of
toplevel citus includes. In the same manner it assumes anything not
prefixed with `columnar/` or `distributed/` as a postgres include.
The sorting/grouping is enforced by CI. Since we do so with our own
script there are not changes required in our uncrustify configuration.
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
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.
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.
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>
* 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
* Fix UNION not being pushdown
Postgres optimizes column fields that are not needed in the output. We
were relying on these fields to understand if it is safe to push down a
union query.
This fix looks at the parse query, which has the original column fields
to detect if it is safe to push down a union query.
* Add more tests
* Simplify code and make it more robust
* Process varlevelsup > 0 in FindReferencedTableColumn
* Only look for outers vars in union path
* Add more comments
* Remove UNION ALL specific logic for pulling up childvars
As long as the VALUES clause contains constant values, we should not
recursively plan the queries/CTEs.
This is a follow-up work of #1805. So, we can easily apply OUTER join
checks as if VALUES clause is a reference table/immutable function.
Baseinfo also has pushed down filters etc, so it makes more sense to use
BaseRestrictInfo to determine what columns have constant equality
filters.
Also RteIdentity is used for removing conversion candidates instead of
rteIndex.
AllDataLocallyAccessible and ContainsLocalTableSubqueryJoin are removed.
We can possibly remove ModifiesLocalTableWithRemoteCitusLocalTable as
well. Though this removal has a side effect that now when all the data
is locally available, we could still wrap a relation into a subquery, I
guess that should be resolved in the router planner itself.
Add more tests
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
AllTargetExpressionsAreColumnReferences would return false if a query
had an entry that is referencing the outer query. It seems safe to not
have this for non-distributed tables, such as reference tables. We
already have separate checks for other cases such as having limits.
FindNodeCheck is not clear about what the function is doing. They are
renamed to FindNodeMatchingCheckFunctionXXX. Also for choosing elements in these
functions, CheckNodeFunc type is introduced.
* use adaptive executor even if task-tracker is set
* Update check-multi-mx tests for adaptive executor
Basically repartition joins are enabled where necessary. For parallel
tests max adaptive executor pool size is decresed to 2, otherwise we
would get too many clients error.
* Update limit_intermediate_size test
It seems that when we use adaptive executor instead of task tracker, we
exceed the intermediate result size less in the test. Therefore updated
the tests accordingly.
* Update multi_router_planner
It seems that there is one problem with multi_router_planner when we use
adaptive executor, we should fix the following error:
+ERROR: relation "authors_range_840010" does not exist
+CONTEXT: while executing command on localhost:57637
* update repartition join tests for check-multi
* update isolation tests for repartitioning
* Error out if shard_replication_factor > 1 with repartitioning
As we are removing the task tracker, we cannot switch to it if
shard_replication_factor > 1. In that case, we simply error out.
* Remove MULTI_EXECUTOR_TASK_TRACKER
* Remove multi_task_tracker_executor
Some utility methods are moved to task_execution_utils.c.
* Remove task tracker protocol methods
* Remove task_tracker.c methods
* remove unused methods from multi_server_executor
* fix style
* remove task tracker specific tests from worker_schedule
* comment out task tracker udf calls in tests
We were using task tracker udfs to test permissions in
multi_multiuser.sql. We should find some other way to test them, then we
should remove the commented out task tracker calls.
* remove task tracker test from follower schedule
* remove task tracker tests from multi mx schedule
* Remove task-tracker specific functions from worker functions
* remove multi task tracker extra schedule
* Remove unused methods from multi physical planner
* remove task_executor_type related things in tests
* remove LoadTuplesIntoTupleStore
* Do initial cleanup for repartition leftovers
During startup, task tracker would call TrackerCleanupJobDirectories and
TrackerCleanupJobSchemas to clean up leftover directories and job
schemas. With adaptive executor, while doing repartitions it is possible
to leak these things as well. We don't retry cleanups, so it is possible
to have leftover in case of errors.
TrackerCleanupJobDirectories is renamed as
RepartitionCleanupJobDirectories since it is repartition specific now,
however TrackerCleanupJobSchemas cannot be used currently because it is
task tracker specific. The thing is that this function is a no-op
currently.
We should add cleaning up intermediate schemas to DoInitialCleanup
method when that problem is solved(We might want to solve it in this PR
as well)
* Revert "remove task tracker tests from multi mx schedule"
This reverts commit 03ecc0a681.
* update multi mx repartition parallel tests
* not error with task_tracker_conninfo_cache_invalidate
* not run 4 repartition queries in parallel
It seems that when we run 4 repartition queries in parallel we get too
many clients error on CI even though we don't get it locally. Our guess
is that, it is because we open/close many connections without doing some
work and postgres has some delay to close the connections. Hence even
though connections are removed from the pg_stat_activity, they might
still not be closed. If the above assumption is correct, it is unlikely
for it to happen in practice because:
- There is some network latency in clusters, so this leaves some times
for connections to be able to close
- Repartition joins return some data and that also leaves some time for
connections to be fully closed.
As we don't get this error in our local, we currently assume that it is
not a bug. Ideally this wouldn't happen when we get rid of the
task-tracker repartition methods because they don't do any pruning and
might be opening more connections than necessary.
If this still gives us "too many clients" error, we can try to increase
the max_connections in our test suite(which is 100 by default).
Also there are different places where this error is given in postgres,
but adding some backtrace it seems that we get this from
ProcessStartupPacket. The backtraces can be found in this link:
https://circleci.com/gh/citusdata/citus/138702
* Set distributePlan->relationIdList when it is needed
It seems that we were setting the distributedPlan->relationIdList after
JobExecutorType is called, which would choose task-tracker if
replication factor > 1 and there is a repartition query. However, it
uses relationIdList to decide if the query has a repartition query, and
since it was not set yet, it would always think it is not a repartition
query and would choose adaptive executor when it should choose
task-tracker.
* use adaptive executor even with shard_replication_factor > 1
It seems that we were already using adaptive executor when
replication_factor > 1. So this commit removes the check.
* remove multi_resowner.c and deprecate some settings
* remove TaskExecution related leftovers
* change deprecated API error message
* not recursively plan single relatition repartition subquery
* recursively plan single relation repartition subquery
* test depreceated task tracker functions
* fix overlapping shard intervals in range-distributed test
* fix error message for citus_metadata_container
* drop task-tracker deprecated functions
* put the implemantation back to worker_cleanup_job_schema_cachesince citus cloud uses it
* drop some functions, add downgrade script
Some deprecated functions are dropped.
Downgrade script is added.
Some gucs are deprecated.
A new guc for repartition joins bucket size is added.
* order by a test to fix flappiness
We still recursively plan some cases, eg:
- INSERTs
- SELECT FOR UPDATE when reference tables in query
- Everything must be same single shard & replication model
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
Add failing tests, make changes to avoid crashes at least
Fix HAVING subquery pushdown ignoring reference table only subqueries,
also include HAVING in recursive planning
Given that we have a function IsDistributedTable which includes reference tables,
it seems best to have IsDistributedTableRTE & QueryContainsDistributedTableRTE
reflect that they do not include reference tables in their check
Similarly SublinkList's name should reflect that it only scans WHERE
contain_agg_clause asserts that we don't have SubLinks,
use contain_aggs_of_level as suggested by pg sourcecode
DESCRIPTION: Replace the query planner for the coordinator part with the postgres planner
Closes#2761
Citus had a simple rule based planner for the query executed on the query coordinator. This planner grew over time with the addigion of SQL support till it was getting close to the functionality of the postgres planner. Except the code was brittle and its complexity rose which made it hard to add new SQL support.
Given its resemblance with the postgres planner it was a long outstanding wish to replace our hand crafted planner with the well supported postgres planner. This patch replaces our planner with a call to postgres' planner.
Due to the functionality of the postgres planner we needed to support both projections and filters/quals on the citus custom scan node. When a sort operation is planned above the custom scan it might require fields to be reordered in the custom scan before returning the tuple (projection). The postgres planner assumes every custom scan node implements projections. Because we controlled the plan that was created we prevented reordering in the custom scan and never had implemented it before.
A same optimisation applies to having clauses that could have been where clauses. Instead of applying the filter as a having on the aggregate it will push it down into the plan which could reach a custom scan node.
For both filters and projections we have implemented them when tuples are read from the tuple store. If no projections or filters are required it will directly return the tuple from the tuple store. Otherwise it will loop tuples from the tuple store through the filter and projection until a tuple is found and returned.
Besides filters being pushed down a side effect of having quals that could have been a where clause is that a call to read intermediate result could be called before the first tuple is fetched from the custom scan. This failed because the intermediate result would only be pulled to the coordinator on the first tuple fetch. To overcome this problem we do run the distributed subplans now before we run the postgres executor. This ensures the intermediate result is present on the coordinator in time. We do account for total time instrumentation by removing the instrumentation before handing control to the psotgres executor and update the timings our self.
For future SQL support it is enough to create a valid query structure for the part of the query to be executed on the query coordinating node. As a utility we do serialise and print the query at debug level4 for engineers to inspect what kind of query is being planned on the query coordinator.
DESCRIPTION: Fix unnecessary repartition on joins with more than 4 tables
In 9.1 we have introduced support for all CH-benCHmark queries by widening our definitions of joins to include joins with expressions in them. This had the undesired side effect of Q5 regressing on its plan by implementing a repartition join.
It turned out this regression was not directly related to widening of the join clause, nor the schema employed by CH-benCHmark. Instead it had to do with 4 or more tables being joined in a chain. A chain meaning:
```sql
SELECT * FROM a,b,c,d WHERE a.part = b.part AND b.part = c.part AND ....
```
Due to how our join order planner was implemented it would only keep track of 1 of the partition columns when comparing if the join could be executed locally. This manifested in a join chain of 4 tables to _always_ be executed as a repartition join. 3 tables joined in a chain would have the middle table shared by the two outer tables causing the local join possibility to be found.
With this patch we keep a unique list (or set) of all partition columns participating in the join. When a candidate table is checked for a possibility to execute a local join it will check if there is any partition column in that set that matches an equality join clause on the partition column of the candidate table.
By taking into account all partition columns in the left relation it will now find the local join path on >= 4 tables joined in a chain.
fixes: #3276
Mehmet Yilmaz
Naisila Puka
zhjwpku
Nils Dijk
Teja Mupparti
Onur Tirtir
naisila
Onder Kalaci
Marco Slot
SaitTalhaNisanci
Halil Ozan Akgul
Philip Dubé
Jelte Fennema
Hadi Moshayedi