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.
This commit is intended to improve the error messages while planning
INSERT INTO .. SELECT queries. The main motivation for this change is
that we used to map multiple cases into a single message. With this change,
we added explicit error messages for many cases.
Since we will now replicate reference tables each time we add node, we need to ensure
that test space is clean in terms of reference tables before any add node operation.
For this purpose we had to change order of multi_drop_extension test which caused
change of some of the colocation ids.
With this commit, we implemented some basic features of reference tables.
To start with, a reference table is
* a distributed table whithout a distribution column defined on it
* the distributed table is single sharded
* and the shard is replicated to all nodes
Reference tables follows the same code-path with a single sharded
tables. Thus, broadcast JOINs are applicable to reference tables.
But, since the table is replicated to all nodes, table fetching is
not required any more.
Reference tables support the uniqueness constraints for any column.
Reference tables can be used in INSERT INTO .. SELECT queries with
the following rules:
* If a reference table is in the SELECT part of the query, it is
safe join with another reference table and/or hash partitioned
tables.
* If a reference table is in the INSERT part of the query, all
other participating tables should be reference tables.
Reference tables follow the regular co-location structure. Since
all reference tables are single sharded and replicated to all nodes,
they are always co-located with each other.
Queries involving only reference tables always follows router planner
and executor.
Reference tables can have composite typed columns and there is no need
to create/define the necessary support functions.
All modification queries, master_* UDFs, EXPLAIN, DDLs, TRUNCATE,
sequences, transactions, COPY, schema support works on reference
tables as expected. Plus, all the pre-requisites associated with
distribution columns are dismissed.
Metin Doslu
Marco Slot
Onder Kalaci
Burak Yucesoy