* Use CalculateUniformHashRangeIndex in HashPartitionId
INT32_MIN definition can change among different platforms hence it is
possible to get overflow, we would see crashes because of this in debian
distros. We have already solved a similar problem with introducing
CalculateUniformHashRangeIndex method, hence to solve it we can use the
same method, this also removes some duplication and has a single place
to decide that.
* Use PG_INT32_XX instead of INT32_XX to be safer
1) Rename CONNECTION_PER_PLACEMENT to REQUIRE_CLEAN_CONNECTION. This is
mostly to make things clear as the new name reveals more.
2) We also make sure that mark all the copy connections critical,
even if they are accessed earlier in the transction
Some GUCs support a list of values which is indicated by GUC_LIST_INPUT flag.
When an ALTER ROLE .. SET statement is executed, the new configuration
default for affected users and databases are stored in the
setconfig(text[]) column in a pg_db_role_setting record.
If a GUC that supports a list of values is used in an ALTER ROLE .. SET
statement, we need to split the text into items delimited by commas.
* use adaptive executor even if task-tracker is set
* Update check-multi-mx tests for adaptive executor
Basically repartition joins are enabled where necessary. For parallel
tests max adaptive executor pool size is decresed to 2, otherwise we
would get too many clients error.
* Update limit_intermediate_size test
It seems that when we use adaptive executor instead of task tracker, we
exceed the intermediate result size less in the test. Therefore updated
the tests accordingly.
* Update multi_router_planner
It seems that there is one problem with multi_router_planner when we use
adaptive executor, we should fix the following error:
+ERROR: relation "authors_range_840010" does not exist
+CONTEXT: while executing command on localhost:57637
* update repartition join tests for check-multi
* update isolation tests for repartitioning
* Error out if shard_replication_factor > 1 with repartitioning
As we are removing the task tracker, we cannot switch to it if
shard_replication_factor > 1. In that case, we simply error out.
* Remove MULTI_EXECUTOR_TASK_TRACKER
* Remove multi_task_tracker_executor
Some utility methods are moved to task_execution_utils.c.
* Remove task tracker protocol methods
* Remove task_tracker.c methods
* remove unused methods from multi_server_executor
* fix style
* remove task tracker specific tests from worker_schedule
* comment out task tracker udf calls in tests
We were using task tracker udfs to test permissions in
multi_multiuser.sql. We should find some other way to test them, then we
should remove the commented out task tracker calls.
* remove task tracker test from follower schedule
* remove task tracker tests from multi mx schedule
* Remove task-tracker specific functions from worker functions
* remove multi task tracker extra schedule
* Remove unused methods from multi physical planner
* remove task_executor_type related things in tests
* remove LoadTuplesIntoTupleStore
* Do initial cleanup for repartition leftovers
During startup, task tracker would call TrackerCleanupJobDirectories and
TrackerCleanupJobSchemas to clean up leftover directories and job
schemas. With adaptive executor, while doing repartitions it is possible
to leak these things as well. We don't retry cleanups, so it is possible
to have leftover in case of errors.
TrackerCleanupJobDirectories is renamed as
RepartitionCleanupJobDirectories since it is repartition specific now,
however TrackerCleanupJobSchemas cannot be used currently because it is
task tracker specific. The thing is that this function is a no-op
currently.
We should add cleaning up intermediate schemas to DoInitialCleanup
method when that problem is solved(We might want to solve it in this PR
as well)
* Revert "remove task tracker tests from multi mx schedule"
This reverts commit 03ecc0a681.
* update multi mx repartition parallel tests
* not error with task_tracker_conninfo_cache_invalidate
* not run 4 repartition queries in parallel
It seems that when we run 4 repartition queries in parallel we get too
many clients error on CI even though we don't get it locally. Our guess
is that, it is because we open/close many connections without doing some
work and postgres has some delay to close the connections. Hence even
though connections are removed from the pg_stat_activity, they might
still not be closed. If the above assumption is correct, it is unlikely
for it to happen in practice because:
- There is some network latency in clusters, so this leaves some times
for connections to be able to close
- Repartition joins return some data and that also leaves some time for
connections to be fully closed.
As we don't get this error in our local, we currently assume that it is
not a bug. Ideally this wouldn't happen when we get rid of the
task-tracker repartition methods because they don't do any pruning and
might be opening more connections than necessary.
If this still gives us "too many clients" error, we can try to increase
the max_connections in our test suite(which is 100 by default).
Also there are different places where this error is given in postgres,
but adding some backtrace it seems that we get this from
ProcessStartupPacket. The backtraces can be found in this link:
https://circleci.com/gh/citusdata/citus/138702
* Set distributePlan->relationIdList when it is needed
It seems that we were setting the distributedPlan->relationIdList after
JobExecutorType is called, which would choose task-tracker if
replication factor > 1 and there is a repartition query. However, it
uses relationIdList to decide if the query has a repartition query, and
since it was not set yet, it would always think it is not a repartition
query and would choose adaptive executor when it should choose
task-tracker.
* use adaptive executor even with shard_replication_factor > 1
It seems that we were already using adaptive executor when
replication_factor > 1. So this commit removes the check.
* remove multi_resowner.c and deprecate some settings
* remove TaskExecution related leftovers
* change deprecated API error message
* not recursively plan single relatition repartition subquery
* recursively plan single relation repartition subquery
* test depreceated task tracker functions
* fix overlapping shard intervals in range-distributed test
* fix error message for citus_metadata_container
* drop task-tracker deprecated functions
* put the implemantation back to worker_cleanup_job_schema_cachesince citus cloud uses it
* drop some functions, add downgrade script
Some deprecated functions are dropped.
Downgrade script is added.
Some gucs are deprecated.
A new guc for repartition joins bucket size is added.
* order by a test to fix flappiness
Rename TargetWorkerSet enums to make them more explicit about what they
mean. Ideally it would be good to treat everything as a node without the
'worker' concept because it makes things complicated. Another
improvement could be to rename TargetWorkerSet as TargetNodeSet but it
goes to renaming many occurrences of Worker, which is probably too big
for this PR.
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 should check the remove type in IsDropCitusStmt because if the remove
type is not OBJECT_EXTENSION then the stored objects in
dropStmt->objects may not be of type Value. This was crashing PG-13.
Also rename the method as IsDropCitusExtensionStmt.
To reduce code duplication, implement function that pushes search_path
to be NIL and sets addCatalog to true so that all objects outside of
pg_catalog will be schema-prefixed.
SELECT_TASK is renamed to READ_TASK as a SELECT with modifying CTEs will be a MODIFYING_TASK
RouterInsertJob: Assert originalQuery->commandType == CMD_INSERT
CreateModifyPlan: Assert originalQuery->commandType != CMD_SELECT
Remove unused function IsModifyDistributedPlan
DistributedExecution, ExecutionParams, DistributedPlan: Rename hasReturning to expectResults
SELECTs set expectResults to true
Rename CreateSingleTaskRouterPlan to CreateSingleTaskRouterSelectPlan
Do not release AccessShareLock when closing pg_constraint to prevent
modifications to be done on pg_constraint to make sure that caller
will process valid foreign key constraints through the transaction.
This PR removes ExecuteUtilityTaskListWithoutResults and uses the same
path for local execution via ExecuteTaskListExtended.
ExecuteUtilityTaskList is added. ExecuteLocalTaskListExtended now has a
parameter for utility commands so that it can call the right method. In
order not to change the existing calls,
ExecuteTaskListExtendedInternal is added, which is the main method that
runs the execution, via local and remote execution.
DESCRIPTION: Alter role only works for citus managed roles
Alter role was implemented before we implemented good role management that hooks into the object propagation framework. This is a refactor of all alter role commands that have been implemented to
- be on by default
- only work for supported roles
- make the citus extension owner a supported role
Instead of distributing the alter role commands for roles at the beginning of the node activation role it now _only_ executes the alter role commands for all users in all databases and in the current database.
In preparation of full role support small refactors have been done in the deparser.
Earlier tests targeting other roles than the citus extension owner have been either slightly changed or removed to be put back where we have full role support.
Fixes#2549
We had 9+ parameters in some of the functions related to execution.
Execution params is created to simplify this a bit so that we can set
only the fields that we are interested in and it is easier to read.
With this commit, we're introducing a new infrastructure to throttle
connections to the worker nodes. This infrastructure is useful for
multi-shard queries, router queries are have not been affected by this.
The goal is to prevent establishing more than citus.max_shared_pool_size
number of connections per worker node in total, across sessions.
To do that, we've introduced a new connection flag OPTIONAL_CONNECTION.
The idea is that some connections are optional such as the second
(and further connections) for the adaptive executor. A single connection
is enough to finish the distributed execution, the others are useful to
execute the query faster. Thus, they can be consider as optional connections.
When an optional connection is not allowed to the adaptive executor, it
simply skips it and continues the execution with the already established
connections. However, it'll keep retrying to establish optional
connections, in case some slots are open again.
This PR:
- Declares variables when they are needed.
- Creates DoCopyFromLocalTableIntoShards for better readability.
- Doesn't use a hardcoded value, instead use a variable for better
readability.
We have two variables that are related to local execution status.
TransactionAccessedLocalPlacement and
TransactionConnectedToLocalGroup. Only one of these fields should be
set, however we didn't have any check for this contraint and it was
error prone.
What those two variables are used is that we are trying to understand if
we should use local execution, the current session, or if we should be
using a connection to execute the current query, therefore the tasks. In
the enum, now it is more clear what these variables mean.
Also, now we have a method to change the local execution status. The
method will error if we are trying to transition from a state to a wrong
state. This will help us avoid problems.
* explicitly return false if transaction connected to local node
* not set TransactionConnectedToLocalGroup if we are writing to a file
We use TransactionConnectedToLocalGroup to prevent local execution from
happening as that might cause visibility problems. As files are visible
to all transactions, we shouldn't set this variable if we are writing to
a file.
For shardplacements, we were setting nodeid, nodename, nodeport and
nodegroup manually. This makes it very error prone, and it seems that we
already forgot to set some of them. This would mean that they would have
their default values, e.g group id would be 0 when its group id is not
0.
So the implication is that we would have inconsistent worker metadata.
A new method is introduced, and we call the method to set those fields
now, so that as long as we call this method, we won't be setting
inconsistent metadata.
It probably makes sense to have a struct for these fields. We already
have NodeMetadata but it doesn't have nodename or nodeport. So that
could be done over another refactor to make things simpler.
ExecuteTaskListExtended is the common method for different codepaths,
and instead of writing separate local execution logics in different
codepaths, it makes more sense to have the logic here. We still need to
do some refactoring, this is an initial step.
After this commit, we can run create shard commands locally. There is a
special case with shard creation commands. A create shard command might
have a concatenated query string, however local execution did not know
how to execute a task with multiple query strings. This is also
implemented in this commit. We go over each query in the concatenated
query string and plan/execute them one by one.
A more clean solution to this would be to make sure that each task has a
single query. We currently cannot do that because we need to ensure the
task dependencies. However, it would make sense to do that at some point
and it would simplify the code a lot.
In PostgreSQL, user defaults for config parameters can be changed by
ALTER ROLE .. SET statements. We wish to propagate those defaults
accross the Citus cluster so that the behaviour will be similar in
different workers.
The defaults can either be set in a specific database, or the whole
cluster, similarly they can be set for a single role or all roles.
We propagate the ALTER ROLE .. SET if all the conditions below are met:
- The query affects the current database, or all databases
- The user is already created in worker nodes
Sometimes we have concatenated query strings for a task. However,
when we want to find each query string, it is not a trivial task.
Therefore, it makes sense to store this in task so that when we need
each query string we can easily get it.
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