This PR provides successful compilation against PG17.0.
- Remove ExecFreeExprContext call
Relevant PG commit
d060e921ea5aa47b6265174c32e1128cebdbc3df
d060e921ea
- PG17 uses streaming IO in analyze, fix scan_analyze_next_block function
Relevant PG commit
041b96802efa33d2bc9456f2ad946976b92b5ae1
041b96802e
- Define ObjectClass for PG17+ only since it's removed
Relevant PG commit:
89e5ef7e21812916c9cf9fcf56e45f0f74034656
89e5ef7e21
- Remove ReorderBufferTupleBuf structure.
Relevant PG commit:
08e6344fd6423210b339e92c069bb979ba4e7cd6
08e6344fd6
- Define colliculocale and daticulocale since they have been renamed
Relevant PG commit:
f696c0cd5f299f1b51e214efc55a22a782cc175d
f696c0cd5f
- makeStringConst defined in PG17
Relevant PG commit:
de3600452b61d1bc3967e9e37e86db8956c8f577
de3600452b
- RangeVarCallbackOwnsTable was replaced by RangeVarCallbackMaintainsTable
Relevant PG commit:
ecb0fd33720fab91df1207e85704f382f55e1eb7
ecb0fd3372
- attstattarget is nullable, define pg compatible functions for it
Relevant PG commit:
4f622503d6de975ac87448aea5cea7de4bc140d5
4f622503d6
- stxstattarget is nullable in PG17, write compat functions for it
Relevant PG commit:
012460ee93c304fbc7220e5b55d9d0577fc766ab
012460ee93
- Use ResourceOwner to track WaitEventSet in PG17
Relevant PG commit:
50c67c2019ab9ade8aa8768bfe604cd802fe8591
50c67c2019
- getIdentitySequence now uses Relation instead of relation_id
Relevant PG commit:
509199587df73f06eda898ae13284292f4ae573a
509199587d
- Remove no-op tuplestore_donestoring function
Relevant PG commit:
75680c3d805e2323cd437ac567f0677fdfc7b680
75680c3d80
- MergeAction can have 3 merge kinds (now enum) in PG17, write compat
Relevant PG commit:
0294df2f1f842dfb0eed79007b21016f486a3c6c
0294df2f1f
- EXPLAIN (MEMORY) is added, make changes to ExplainOnePlan
Relevant PG commit:
5de890e3610d5a12cdaea36413d967cf5c544e20
5de890e361
- LIMIT_OPTION_DEFAULT has been removed as it's useless, use LIMIT_OPTION_COUNT
Relevant PG commit:
a6be0600ac3b71dda8277ab0fcbe59ee101ac1ce
a6be0600ac
- write compat for create_foreignscan_path bcs of more arguments in PG17
Relevant PG commit:
9e9931d2bf40e2fea447d779c2e133c2c1256ef3
9e9931d2bf
- pgprocno and lxid have been combined into a struct in PGPROC
Relevant PG commits:
28f3915b73f75bd1b50ba070f56b34241fe53fd1
28f3915b73
ab355e3a88de745607f6dd4c21f0119b5c68f2ad
ab355e3a88
024c521117579a6d356050ad3d78fdc95e44eefa
024c521117
- Simplify CitusNewNode (#7434)
postgres refactored newNode() in PG 17, the main point for doing this is
the original tricks is no longer neccessary for modern compilers[1].
This does the same for Citus.
This should have no backward compatibility issues since it just replaces
palloc0fast with palloc0.
This is good for forward compatibility since palloc0fast no longer
exists in PG 17.
[1]
https://www.postgresql.org/message-id/b51f1fa7-7e6a-4ecc-936d-90a8a1659e7c@iki.fi
(cherry picked from commit 4b295cc)
This is prep work for successful compilation with PG17
PG17added foreach_ptr, foreach_int and foreach_oid macros
Relevant PG commit
14dd0f27d7cd56ffae9ecdbe324965073d01a9ff
14dd0f27d7
We already have these macros, but they are different with the
PG17 ones because our macros take a DECLARED variable, whereas
the PG16 macros declare a locally-scoped loop variable themselves.
Hence I am renaming our macros to foreach_declared_
I am separating this into its own PR since it touches many files. The
main compilation PR is https://github.com/citusdata/citus/pull/7699
Variables being modified in the PG_TRY block and read in the PG_CATCH
block should be qualified with volatile.
The variable waitEventSet is modified in the PG_TRY block (line 1085)
and read in the PG_CATCH block (line 1095).
The variable relation is modified in the PG_TRY block (line 500) and
read in the PG_CATCH block (line 515).
Besides, the variable objectAddress doesn't need the volatile qualifier.
Ref: C99 7.13.2.1[^1],
> All accessible objects have values, and all other components of the
abstract machine have state, as of the time the longjmp function was
called, except that the values of objects of automatic storage duration
that are local to the function containing the invocation of the
corresponding setjmp macro that do not have volatile-qualified type and
have been changed between the setjmp invocation and longjmp call are
indeterminate.
[^1]: https://www.open-std.org/jtc1/sc22/wg14/www/docs/n1256.pdf
DESCRIPTION: Correctly mark some variables as volatile
---------
Co-authored-by: Hong Yi <zouzou0208@gmail.com>
This patch includes the username in the reported error message.
This makes debugging easier when certain commands open connections
as other users than the user that is executing the command.
```
monitora_snapshot=# SELECT citus_move_shard_placement(102030, 'monitora.db-dev-worker-a', 6005, 'monitora.db-dev-worker-a', 6017);
ERROR: connection to the remote node monitora_user@monitora.db-dev-worker-a:6017 failed with the following error: fe_sendauth: no password supplied
Time: 40,198 ms
```
This change adds a script to programatically group all includes in a
specific order. The script was used as a one time invocation to group
and sort all includes throught our formatted code. The grouping is as
follows:
- System includes (eg. `#include<...>`)
- Postgres.h (eg. `#include "postgres.h"`)
- Toplevel imports from postgres, not contained in a directory (eg.
`#include "miscadmin.h"`)
- General postgres includes (eg . `#include "nodes/..."`)
- Toplevel citus includes, not contained in a directory (eg. `#include
"citus_verion.h"`)
- Columnar includes (eg. `#include "columnar/..."`)
- Distributed includes (eg. `#include "distributed/..."`)
Because it is quite hard to understand the difference between toplevel
citus includes and toplevel postgres includes it hardcodes the list of
toplevel citus includes. In the same manner it assumes anything not
prefixed with `columnar/` or `distributed/` as a postgres include.
The sorting/grouping is enforced by CI. Since we do so with our own
script there are not changes required in our uncrustify configuration.
Description:
Implementing CDC changes using Logical Replication to avoid
re-publishing events multiple times by setting up replication origin
session, which will add "DoNotReplicateId" to every WAL entry.
- shard splits
- shard moves
- create distributed table
- undistribute table
- alter distributed tables (for some cases)
- reference table operations
The citus decoder which will be decoding WAL events for CDC clients,
ignores any WAL entry with replication origin that is not zero.
It also maps the shard names to distributed table names.
increasing logical clock. Clock guarantees to never go back in value after restarts,
and makes best attempt to keep the value close to unix epoch time in milliseconds.
Also, introduces a new GUC "citus.enable_cluster_clock", when true, every
distributed transaction is stamped with logical causal clock and persisted
in a catalog pg_dist_commit_transaction.
PostgreSQL 15 exposes WL_SOCKET_CLOSED in WaitEventSet API, which is
useful for detecting closed remote sockets. In this patch, we use this
new event and try to detect closed remote sockets in the executor.
When a closed socket is detected, the executor now has the ability to
retry the connection establishment. Note that, the executor can retry
connection establishments only for the connection that has not been
used. Basically, this patch is mostly useful for preventing the executor
to fail if a cached connection is closed because of the worker node
restart (or worker failover).
In other words, the executor cannot retry connection establishment if we
are in a distributed transaction AND any command has been sent over the
connection. That requires more sophisticated retry mechanisms. For now,
fixing the above use case is enough.
Fixes#5538
Earlier discussions: #5908, #6259 and #6283
### Summary of the current approach regards to earlier trials
As noted, we explored some alternatives before getting into this.
https://github.com/citusdata/citus/pull/6283 is simple, but lacks an
important property. We should be checking for `WL_SOCKET_CLOSED`
_before_ sending anything over the wire. Otherwise, it becomes very
tricky to understand which connection is actually safe to retry. For
example, in the current patch, we can safely check
`transaction->transactionState == REMOTE_TRANS_NOT_STARTED` before
restarting a connection.
#6259 does what we intent here (e.g., check for sending any command).
However, as @marcocitus noted, it is very tricky to handle
`WaitEventSets` in multiple places. And, the executor is designed such
that it reacts to the events. So, adding anything `pre-executor` seemed
too ugly.
In the end, I converged into this patch. This patch relies on the
simplicity of #6283 and also does a very limited handling of
`WaitEventSets`, just for our purpose. Just before we add any connection
to the execution, we check if the remote session has already closed.
With that, we do a brief interaction of multiple wait event processing,
but with different purposes. The new wait event processing we added does
not even consider cancellations. We let that handled by the main event
processing loop.
Co-authored-by: Marco Slot <marco.slot@gmail.com>
This PR makes all of the features open source that were previously only
available in Citus Enterprise.
Features that this adds:
1. Non blocking shard moves/shard rebalancer
(`citus.logical_replication_timeout`)
2. Propagation of CREATE/DROP/ALTER ROLE statements
3. Propagation of GRANT statements
4. Propagation of CLUSTER statements
5. Propagation of ALTER DATABASE ... OWNER TO ...
6. Optimization for COPY when loading JSON to avoid double parsing of
the JSON object (`citus.skip_jsonb_validation_in_copy`)
7. Support for row level security
8. Support for `pg_dist_authinfo`, which allows storing different
authentication options for different users, e.g. you can store
passwords or certificates here.
9. Support for `pg_dist_poolinfo`, which allows using connection poolers
in between coordinator and workers
10. Tracking distributed query execution times using
citus_stat_statements (`citus.stat_statements_max`,
`citus.stat_statements_purge_interval`,
`citus.stat_statements_track`). This is disabled by default.
11. Blocking tenant_isolation
12. Support for `sslkey` and `sslcert` in `citus.node_conninfo`
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.
We currently put the actual error message to the detail part. However,
many drivers don't show detail part.
As connection errors are somehow common, and hard to trace back, can't
we added the detail to the message itself.
In addition to that, we changed "connection error" message, as it
was confusing to the users who think that the error was happening
while connecting to the coordinator. In fact, this error is showing
up when the coordinator fails to connect remote nodes.
* WIP
* wip
* add basic logic to run a single job with repartioning joins with adaptive executor
* fix some warnings and return in ExecuteDependedTasks if there is none
* Add the logic to run depended jobs in adaptive executor
The execution of depended tasks logic is changed. With the current
logic:
- All tasks are created from the top level task list.
- At one iteration:
- CurTasks whose dependencies are executed are found.
- CurTasks are executed in parallel with adapter executor main
logic.
- The iteration is repeated until all tasks are completed.
* Separate adaptive executor repartioning logic
* Remove duplicate parts
* cleanup directories and schemas
* add basic repartion tests for adaptive executor
* Use the first placement to fetch data
In task tracker, when there are replicas, we try to fetch from a replica
for which a map task is succeeded. TaskExecution is used for this,
however TaskExecution is not used in adaptive executor. So we cannot use
the same thing as task tracker.
Since adaptive executor fails when a map task fails (There is no retry
logic yet). We know that if we try to execute a fetch task, all of its
map tasks already succeeded, so we can just use the first one to fetch
from.
* fix clean directories logic
* do not change the search path while creating a udf
* Enable repartition joins with adaptive executor with only enable_reparitition_joins guc
* Add comments to adaptive_executor_repartition
* dont run adaptive executor repartition test in paralle with other tests
* execute cleanup only in the top level execution
* do cleanup only in the top level ezecution
* not begin a transaction if repartition query is used
* use new connections for repartititon specific queries
New connections are opened to send repartition specific queries. The
opened connections will be closed at the FinishDistributedExecution.
While sending repartition queries no transaction is begun so that
we can see all changes.
* error if a modification was done prior to repartition execution
* not start a transaction if a repartition query and sql task, and clean temporary files and schemas at each subplan level
* fix cleanup logic
* update tests
* add missing function comments
* add test for transaction with DDL before repartition query
* do not close repartition connections in adaptive executor
* rollback instead of commit in repartition join test
* use close connection instead of shutdown connection
* remove unnecesary connection list, ensure schema owner before removing directory
* rename ExecuteTaskListRepartition
* put fetch query string in planner not executor as we currently support only replication factor = 1 with adaptive executor and repartition query and we know the query string in the planner phase in that case
* split adaptive executor repartition to DAG execution logic and repartition logic
* apply review items
* apply review items
* use an enum for remote transaction state and fix cleanup for repartition
* add outside transaction flag to find connections that are unclaimed instead of always opening a new transaction
* fix style
* wip
* rename removejobdir to partition cleanup
* do not close connections at the end of repartition queries
* do repartition cleanup in pg catch
* apply review items
* decide whether to use transaction or not at execution creation
* rename isOutsideTransaction and add missing comment
* not error in pg catch while doing cleanup
* use replication factor of the creation time, not current time to decide if task tracker should be chosen
* apply review items
* apply review items
* apply review item
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.
Without this change we crash on Windows with COPYing into a table with
62 shards, and we ERROR when COPYing into a table with >62 shards:
ERROR: WaitForMutipleObjects() failed: error code 87
This commit checks the connection status right after any IO happens
on the socket.
This is necessary since before this commit we didn't pass any information
to the higher level functions whether we're done with the connection
(e.g., no IO required anymore) or an errors happened during the IO.