Commit Graph

19 Commits (1c2ee39f15d34b78ea8b64a2eac6dcdb8371f969)

Author SHA1 Message Date
Sait Talha Nisanci 1c2ee39f15 update repartition join tests for check-multi 2020-05-19 13:51:40 +03:00
Nils Dijk a77ed9cd23
Refactor master query to be planned by postgres' planner (#3326)
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.
2020-02-25 14:39:56 +01:00
Nils Dijk d5433400f9
Fix: Unnecessary repartition on joins with more than 4 tables (#3473)
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
2020-02-06 15:07:07 +01:00
velioglu 121ff39b26 Removes large_table_shard_count GUC 2018-04-29 10:34:50 +02:00
Murat Tuncer a6fe5ca183 PG11 compatibility update
- changes in ruleutils_11.c is reflected
- vacuum statement api change is handled. We now allow
  multi-table vacuum commands.
- some other function header changes are reflected
- api conflicts between PG11 and earlier versions
  are handled by adding shims in version_compat.h
- various regression tests are fixed due output and
  functionality in PG1
- no change is made to support new features in PG11
  they need to be handled by new commit
2018-04-26 11:29:43 +03:00
velioglu 82b2d21b0c Convert broadcast join to reference join
After this commit large_table_shard_count wont be used to
check whether broadcast join, which is renamed as reference
join, can be applied. Reference join can only be applied over
reference tables.
2018-04-13 12:58:14 +03:00
velioglu 72dfe4a289 Adds colocation check to local join 2018-04-04 22:49:27 +03:00
Marco Slot 89eb833375 Use citus.next_shard_id where practical in regression tests 2017-11-15 10:12:05 +01:00
Andres Freund 2dfd55070c Remove 9.5 regression test output files. 2017-06-26 12:17:46 -07:00
Jason Petersen 2204da19f0 Support PostgreSQL 10 (#1379)
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.
2017-06-26 02:35:46 -06:00
Marco Slot f838c83809 Remove redundant pg_dist_jobid_seq restarts in tests 2017-04-18 11:42:32 +02:00
Metin Doslu 1f838199f8 Use CustomScan API for query execution
Custom Scan is a node in the planned statement which helps external providers
to abstract data scan not just for foreign data wrappers but also for regular
relations so you can benefit your version of caching or hardware optimizations.
This sounds like only an abstraction on the data scan layer, but we can use it
as an abstraction for our distributed queries. The only thing we need to do is
to find distributable parts of the query, plan for them and replace them with
a Citus Custom Scan. Then, whenever PostgreSQL hits this custom scan node in
its Vulcano style execution, it will call our callback functions which run
distributed plan and provides tuples to the upper node as it scans a regular
relation. This means fewer code changes, fewer bugs and more supported features
for us!

First, in the distributed query planner phase, we create a Custom Scan which
wraps the distributed plan. For real-time and task-tracker executors, we add
this custom plan under the master query plan. For router executor, we directly
pass the custom plan because there is not any master query. Then, we simply let
the PostgreSQL executor run this plan. When it hits the custom scan node, we
call the related executor parts for distributed plan, fill the tuple store in
the custom scan and return results to PostgreSQL executor in Vulcano style,
a tuple per XXX_ExecScan() call.

* Modify planner to utilize Custom Scan node.
* Create different scan methods for different executors.
* Use native PostgreSQL Explain for master part of queries.
2017-03-14 12:17:51 +02:00
Andres Freund 52358fe891 Initial temp table removal implementation 2017-03-14 12:09:49 +02:00
Murat Tuncer cc33a450c4 Expand router planner coverage
We can now support richer set of queries in router planner.
This allow us to support CTEs, joins, window function, subqueries
if they are known to be executed at a single worker with a single
task (all tables are filtered down to a single shard and a single
worker contains all table shards referenced in the query).

Fixes : #501
2016-07-27 23:35:38 +03:00
Eren 5512bb359a Set Explicit ShardId/JobId In Regression Tests
Fixes #271

This change sets ShardIds and JobIds for each test case. Before this change,
when a new test that somehow increments Job or Shard IDs is added, then
the tests after the new test should be updated.

ShardID and JobID sequences are set at the beginning of each file with the
following commands:

```
ALTER SEQUENCE pg_catalog.pg_dist_shardid_seq RESTART 290000;
ALTER SEQUENCE pg_catalog.pg_dist_jobid_seq RESTART 290000;
```

ShardIds and JobIds are multiples of 10000. Exceptions are:
- multi_large_shardid: shardid and jobid sequences are set to much larger values
- multi_fdw_large_shardid: same as above
- multi_join_pruning: Causes a race condition with multi_hash_pruning since
they are run in parallel.
2016-06-07 14:32:44 +03:00
Burak Yücesoy 2f096cad74 Update regression tests where metadata edited manually
Fixes #302

Since our previous syntax did not allow creating hash partitioned tables,
some of the previous tests manually changed partition method to hash to
be able to test it. With this change we remove unnecessary workaround and
create hash distributed tables instead. Also in some tests metadata was
created manually. With this change we also fixed this issue.
2016-06-04 13:50:42 +00:00
Marco Slot fc4f23065a Add EXPLAIN for simple distributed queries 2016-04-30 00:11:02 +02:00
Murat Tuncer 55c44b48dd Changed product name to citus
All citusdb references in
- extension, binary names
- file headers
- all configuration name prefixes
- error/warning messages
- some functions names
- regression tests

are changed to be citus.
2016-02-15 16:04:31 +02:00
Onder Kalaci 136306a1fe Initial commit of Citus 5.0 2016-02-11 04:05:32 +02:00