This commit adds support for long partition names for distributed tables:
- ALTER TABLE dist_table ATTACH PARTITION ..
- CREATE TABLE .. PARTITION OF dist_table ..
Note: create_distributed_table UDF does not support long table and
partition names, and is not covered in this commit
For certaion purposes, we drop and recreate the foreign
keys. As we acquire exclusive locks on the tables in between
drop and re-create, we can safely skip validation phase of
the foreign keys. The reason is purely being performance as
foreign key validation could take a long value.
When enabled any foreign keys between local tables and reference
tables supported by converting the local table to a citus local
table.
When the coordinator is not in the metadata, the logic is disabled
as foreign keys are not allowed in this configuration.
Because master_add_node(or others) might acquire ExclusiveLock
and their initiated sessions may call CoordinatorAddedAsWorkerNode().
With this we prevent potential deadlocks.
This commit brings following features:
Foreign key support from citus local tables to reference tables
* Foreign key support from reference tables to citus local tables
(only with RESTRICT & NO ACTION behavior)
* ALTER TABLE ENABLE/DISABLE trigger command support
* CREATE/DROP/ALTER trigger command support
and disallows:
* ALTER TABLE ATTACH/DETACH PARTITION commands
* CREATE TABLE <postgres table> ATTACH PARTITION <citus local table>
commands
* Foreign keys from postgres tables to citus local tables
(the other way was already disallowed)
for citus local tables.
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
Calling ErrorIfUnsupportedConstraint was still giving errors on Semmle. This
makes sure that we check for NULL at runtime. This way we can safely ignore all
errors created by this function.
Semmle reported quite some places where we use a value that could be NULL. Most of these are not actually a real issue, but better to be on the safe side with these things and make the static analysis happy.
Deparsing and parsing a query can be heavy on CPU. When locally executing
the query we don't need to do this in theory most of the time.
This PR is the first step in allowing to skip deparsing and parsing
the query in these cases, by lazily creating the query string and
storing the query in the task. Future commits will make use of this and
not deparse and parse the query anymore, but use the one from the task
directly.
DESCRIPTION: Distribute Types to worker nodes
When to propagate
==============
There are two logical moments that types could be distributed to the worker nodes
- When they get used ( just in time distribution )
- When they get created ( proactive distribution )
The just in time distribution follows the model used by how schema's get created right before we are going to create a table in that schema, for types this would be when the table uses a type as its column.
The proactive distribution is suitable for situations where it is benificial to have the type on the worker nodes directly. They can later on be used in queries where an intermediate result gets created with a cast to this type.
Just in time creation is always the last resort, you cannot create a distributed table before the type gets created. A good example use case is; you have an existing postgres server that needs to scale out. By adding the citus extension, add some nodes to the cluster, and distribute the table. The type got created before citus existed. There was no moment where citus could have propagated the creation of a type.
Proactive is almost always a good option. Types are not resource intensive objects, there is no performance overhead of having 100's of types. If you want to use them in a query to represent an intermediate result (which happens in our test suite) they just work.
There is however a moment when proactive type distribution is not beneficial; in transactions where the type is used in a distributed table.
Lets assume the following transaction:
```sql
BEGIN;
CREATE TYPE tt1 AS (a int, b int);
CREATE TABLE t1 AS (a int PRIMARY KEY, b tt1);
SELECT create_distributed_table('t1', 'a');
\copy t1 FROM bigdata.csv
```
Types are node scoped objects; meaning the type exists once per worker. Shards however have best performance when they are created over their own connection. For the type to be visible on all connections it needs to be created and committed before we try to create the shards. Here the just in time situation is most beneficial and follows how we create schema's on the workers. Outside of a transaction block we will just use 1 connection to propagate the creation.
How propagation works
=================
Just in time
-----------
Just in time propagation hooks into the infrastructure introduced in #2882. It adds types as a supported object in `SupportedDependencyByCitus`. This will make sure that any object being distributed by citus that depends on types will now cascade into types. When types are depending them self on other objects they will get created first.
Creation later works by getting the ddl commands to create the object by its `ObjectAddress` in `GetDependencyCreateDDLCommands` which will dispatch types to `CreateTypeDDLCommandsIdempotent`.
For the correct walking of the graph we follow array types, when later asked for the ddl commands for array types we return `NIL` (empty list) which makes that the object will not be recorded as distributed, (its an internal type, dependant on the user type).
Proactive distribution
---------------------
When the user creates a type (composite or enum) we will have a hook running in `multi_ProcessUtility` after the command has been applied locally. Running after running locally makes that we already have an `ObjectAddress` for the type. This is required to mark the type as being distributed.
Keeping the type up to date
====================
For types that are recorded in `pg_dist_object` (eg. `IsObjectDistributed` returns true for the `ObjectAddress`) we will intercept the utility commands that alter the type.
- `AlterTableStmt` with `relkind` set to `OBJECT_TYPE` encapsulate changes to the fields of a composite type.
- `DropStmt` with removeType set to `OBJECT_TYPE` encapsulate `DROP TYPE`.
- `AlterEnumStmt` encapsulates changes to enum values.
Enum types can not be changed transactionally. When the execution on a worker fails a warning will be shown to the user the propagation was incomplete due to worker communication failure. An idempotent command is shown for the user to re-execute when the worker communication is fixed.
Keeping types up to date is done via the executor. Before the statement is executed locally we create a plan on how to apply it on the workers. This plan is executed after we have applied the statement locally.
All changes to types need to be done in the same transaction for types that have already been distributed and will fail with an error if parallel queries have already been executed in the same transaction. Much like foreign keys to reference tables.
Hanefi Onaldi
Ahmet Gedemenli
Halil Ozan Akgul
SaitTalhaNisanci
Onur Tirtir
Naisila Puka
Onder Kalaci
Jelte Fennema
Marco Slot
Hadi Moshayedi
Philip Dubé
Philip Dubé
Hadi Moshayedi
Nils Dijk
Onder Kalaci