With this commit, we add the range table list of the original query to our
custom plan. Therefore, PostgreSQL can check relations in the original query
for access permissions and error out if the proper access is not granted.
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.
All router, real-time, task-tracker plannable queries should now have
full prepared statement support (and even use router when possible),
unless they don't go through the custom plan interface (which
basically just affects LANGUAGE SQL (not plpgsql) functions).
This is achieved by forcing postgres' planner to always choose a
custom plan, by assigning very low costs to plans with bound
parameters (i.e. ones were the postgres planner replanned the query
upon EXECUTE with all parameter values provided), instead of the
generic one.
This requires some trickery, because for custom plans to work the
costs for a non-custom plan have to be known, which means we can't
error out when planning the generic plan. Instead we have to return a
"faux" plan, that'd trigger an error message if executed. But due to
the custom plan logic that plan will likely (unless called by an SQL
function, or because we can't support that query for some reason) not
be executed; instead the custom plan will be chosen.
So far router planner had encapsulated different functionality in
MultiRouterPlanCreate. Modifications always go through router, selects
sometimes. Modifications always error out if the query is unsupported,
selects return NULL. Especially the error handling is a problem for
the upcoming extension of prepared statement support.
Split MultiRouterPlanCreate into CreateRouterPlan and
CreateModifyPlan, and change them to not throw errors.
Instead errors are now reported by setting the new
MultiPlan->plannigError.
Callers of router planner functionality now have to throw errors
themselves if desired, but also can skip doing so.
This is a pre-requisite for expanding prepared statement support.
While touching all those lines, improve a number of error messages by
getting them closer to the postgres error message guidelines.
The name CreatePhysicalPlan() hasn't been accurate for a while, and
the split of work between multi_planner() and CreatePhysicalPlan()
doesn't seem perfect. So rename to CreateDistributedPlan() and move a
bit more logic in there.
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.
We used to disable router planner and executor
when task executor is set to task-tracker.
This change enables router planning and execution
at all times regardless of task execution mode.
We are introducing a hidden flag enable_router_execution
to enable/disable router execution. Its default value is
true. User may disable router planning by setting it to false.
This commit adds INSERT INTO ... SELECT feature for distributed tables.
We implement INSERT INTO ... SELECT by pushing down the SELECT to
each shard. To compute that we use the router planner, by adding
an "uninstantiated" constraint that the partition column be equal to a
certain value. standard_planner() distributes that constraint to all
the tables where it knows how to push the restriction safely. An example
is that the tables that are connected via equi joins.
The router planner then iterates over the target table's shards,
for each we replace the "uninstantiated" restriction, with one that
PruneShardList() handles. Do so by replacing the partitioning qual
parameter added in multi_planner() with the current shard's
actual boundary values. Also, add the current shard's boundary values to the
top level subquery to ensure that even if the partitioning qual is
not distributed to all the tables, we never run the queries on the shards
that don't match with the current shard boundaries. Finally, perform the
normal shard pruning to decide on whether to push the query to the
current shard or not.
We do not support certain SQLs on the subquery, which are described/commented
on ErrorIfInsertSelectQueryNotSupported().
We also added some locking on the router executor. When an INSERT/SELECT command
runs on a distributed table with replication factor >1, we need to ensure that
it sees the same result on each placement of a shard. So we added the ability
such that router executor takes exclusive locks on shards from which the SELECT
in an INSERT/SELECT reads in order to prevent concurrent changes. This is not a
very optimal solution, but it's simple and correct. The
citus.all_modifications_commutative can be used to avoid aggressive locking.
An INSERT/SELECT whose filters are known to exclude any ongoing writes can be
marked as commutative. See RequiresConsistentSnapshot() for the details.
We also moved the decison of whether the multiPlan should be executed on
the router executor or not to the planning phase. This allowed us to
integrate multi task router executor tasks to the router executor smoothly.
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
The old targetlist wasn't used so far, but the upcoming RETURNING
support relies on it.
This also allows to get rid of some crufty code in
multi_executor.c:multi_ExecutorStart(), which used the worker query's
targetlist instead of the main statement's (which didn't have one up to
now).
The targetlist contains TargetEntrys containing expressions, not
expressions directly. That didn't matter so far, but with the upcoming
RETURNING support, the targetlist is inspected to build a TupleDesc.
ExecCleanTypeFromTL hits an assert when looking at something that's not
a TargetEntry.
Mark the entry as resjunk, so it's not actually used.
- non-router plannable queries can be executed
by router executor if they satisfy the criteria
- router executor is removed from configuration,
now task executor can not be set to router
- removed some tests that error out for router executor
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.
Previously we used, for historical reasons, MessageContext.
That is problematic if a single message from the client
causes a lot of statements to be planned. E.g. for the
copy_to_distributed_table script one insert statement
is planned for each row inserted via COPY, and only freed
when COPY has finished.
Metin Doslu
Andres Freund
Onder Kalaci
Murat Tuncer
Marco Slot
Jason Petersen