Simply applies
```SQL
SELECT textlike(command, citus.grep_remote_commands)
```
And, if returns true, the command is logged. Else, the log is ignored.
When citus.grep_remote_commands is empty string, all commands are
logged.
This can save a lot of data to be sent in some cases, thus improving
performance for which inter query bandwidth is the bottleneck.
There's some issues with enabling this as default, so that's currently not done.
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.
This is a preperation for the new executor, where creating shards
would go through the executor. So, explicitly generate the commands
for further processing.
VLAs aren't supported by Visual Studio.
- Remove all existing instances of VLAs.
- Add a flag, -Werror=vla, which makes gcc refuse to compile if we add
VLAs in the future.
We sent multiple commands to worker when starting a transaction.
Previously we only checked the result of the first command that
is transaction 'BEGIN' which always succeeds. Any failure on
following commands were not checked.
With this commit, we make sure all command results are checked.
If there is any error we report the first error found.
When a NULL connection is provided to PQerrorMessage(), the
returned error message is a static text. Modifying that static
text, which doesn't necessarly be in a writeable memory, is
dangreous and might cause a segfault.
With this commit, we started to send explain queries within a savepoint. After
running explain query, we rollback to savepoint. This saves us from side effects
of EXPLAIN ANALYZE on DML queries.
A small refactor which pulls some code out of `RecoverWorkerTransactions`
and into `remote_commands.c`. This code block currently only occurs in
`RecoverWorkerTransactions` but will be useful to other functions
shortly.
Unfortunately we couldn't call it `ExecuteRemoteCommand`, that name was
already taken.
This includes basic infrastructure for logging of commands sent to
remote/worker nodes. Note that this has no effect as of yet, since no
callers are converted to the new infrastructure.
Marco Slot
Onder Kalaci
Onur Tirtir
Jelte Fennema
SaitTalhaNisanci
Philip Dubé
Nils Dijk
Onder Kalaci
Hadi Moshayedi
Brian Cloutier
Murat Tuncer
Andres Freund
Metin Doslu