TEXT SEARCH DICTIONARY objects depend on TEXT SEARCH TEMPLATE objects.
Since we do not yet support distributed TS TEMPLATE objects, we skip
dependency checks for text search templates, similar to what we do for
roles.
The user is expected to manually create the TEXT SEARCH TEMPLATE objects
before a) adding new nodes, b) creating TEXT SEARCH DICTIONARY objects.
DESCRIPTION: Add GUC to control ddl creation behaviour in transactions
Historically we would _not_ propagate objects when we are in a transaction block. Creation of distributed tables would not always work in sequential mode, hence objects created in the same transaction as distributing a table that would use the just created object wouldn't work. The benefit was that the user could still benefit from parallelism.
Now that the creation of distributed tables is supported in sequential mode it would make sense for users to force transactional consistency of ddl commands for distributed tables. A transaction could switch more aggressively to sequential mode when creating new objects in a transaction.
We don't change the default behaviour just yet.
Also, many objects would not even propagate their creation when the transaction was already set to sequential, leaving the probability of a self deadlock. The new policy checks solve this discrepancy between objects as well.
DESCRIPTION: Implement TEXT SEARCH CONFIGURATION propagation
The change adds support to Citus for propagating TEXT SEARCH CONFIGURATION objects. TSConfig objects cannot always be created in one create statement, and instead require a create statement followed by many alter statements to get turned into the object they should represent.
To support this we add functionality to the worker to create or replace objects based on a list of statements. When the lists of the local object and the remote object correspond 1:1 we skip the creation of the object and simply mark it distributed. This is especially important for TSConfig objects as initdb pre-populates databases with a dozen configurations (for many different languages).
When the user creates a new TSConfig based on the copy of an existing configuration there is no direct link to the object copied from. Since there is no link we can't simply rely on propagating the dependencies to the worker and send a qualified
With this commit, rebalancer backends are identified by application_name = citus_rebalancer
and the regular internal backends are identified by application_name = citus_internal
BEGIN/COMMIT transaction block or in a UDF calling another UDF.
(2) Prohibit/Limit the delegated function not to do a 2PC (or any work on a
remote connection).
(3) Have a safety net to ensure the (2) i.e. we should block the connections
from the delegated procedure or make sure that no 2PC happens on the node.
(4) Such delegated functions are restricted to use only the distributed argument
value.
Note: To limit the scope of the project we are considering only Functions(not
procedures) for the initial work.
DESCRIPTION: Introduce a new flag "force_delegation" in create_distributed_function(),
which will allow a function to be delegated in an explicit transaction block.
Fixes#3265
Once the function is delegated to the worker, on that node during the planning
distributed_planner()
TryToDelegateFunctionCall()
CheckDelegatedFunctionExecution()
EnableInForceDelegatedFuncExecution()
Save the distribution argument (Constant)
ExecutorStart()
CitusBeginScan()
IsShardKeyValueAllowed()
Ensure to not use non-distribution argument.
ExecutorRun()
AdaptiveExecutor()
StartDistributedExecution()
EnsureNoRemoteExecutionFromWorkers()
Ensure all the shards are local to the node in the remoteTaskList.
NonPushableInsertSelectExecScan()
InitializeCopyShardState()
EnsureNoRemoteExecutionFromWorkers()
Ensure all the shards are local to the node in the placementList.
This also fixes a minor issue: Properly handle expressions+parameters in distribution arguments
- [x] Add some more regression test coverage
- [x] Make sure returning works fine in case of
local execution + remote execution
(task->partiallyLocalOrRemote works as expected, already added tests)
- [x] Implement locking properly (and add isolation tests)
- [x] We do #shardcount round-trips on `SerializeNonCommutativeWrites`.
We made it a single round-trip.
- [x] Acquire locks for subselects on the workers & add isolation tests
- [x] Add a GUC to prevent modification from the workers, hence increase the
coordinator-only throughput
- The performance slightly drops (~%15), unless
`citus.allow_modifications_from_workers_to_replicated_tables`
is set to false
CopyState struct is divided into parts and one of them is CopyFromState
This macro uses the appropriate one for PG versions
Relevant PG commit:
c532d15dddff14b01fe9ef1d465013cb8ef186df
CMDTAG_SELECT exists in PG12 hence defining a MACRO such as
CMDTAG_SELECT -> "SELECT" is not possible. I chose CMDTAG_SELECT_COMPAT
because with the COMPAT suffix it is explicit that it maps to different
things in different versions and also has a less chance of mapping
something irrevelant. For example if we used SELECT as a macro, then it
would map every SELECT to whatever it is mapping to, which might have
unexpected/undesired behaviour.
This commit mostly adds pg_get_triggerdef_command to our ruleutils_13.
This doesn't add anything extra for ruleutils 13 so it is basically a copy
of the change on ruleutils_12
PortalDefineQuery doesn't accept char* for command tag anymore with PG
>= 13. We are currently only using it with Select, therefore a Portal
define query compat for select is created.
Commit on PG side:
2f9661311b83dc481fc19f6e3bda015392010a40
As the new planner and pg_plan_query_compat methods expect the query
string as well, macros are defined to be compatible in different
versions of postgres.
Relevant commit on Postgres:
6aba63ef3e606db71beb596210dd95fa73c44ce2
Command on Postgres:
git log --all --grep="pg_plan_query"
* 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
#3866 removed the shard ID hash in metadata_cache.c to simplify cache management,
but we observed a significant performance regression that was being masked by the
performance improvement provided by #3654 in our benchmarks, but #3654 only
applies to specific workloads.
This PR brings back the shard ID cache as it existed before #3866 with some extra
measures to handle invalidation. When we load a table entry, we overwrite
ShardIdCacheEntry->tableEntry pointers for all the shards in that table, though
it's possible that the table no longer contains the old shard ID or the table
entry is never reloaded, which would leave a dangling pointer once the table
entry is freed. To handle that case, we remove all shard ID cache entries that
point exactly to that table entry when a table is freed (at the end of the
transaction or any call to CitusTableCacheFlushInvalidatedEntries).
Co-authored-by: SaitTalhaNisanci <s.talhanisanci@gmail.com>
Co-authored-by: Marco Slot <marco.slot@gmail.com>
Co-authored-by: Jelte Fennema <github-tech@jeltef.nl>
Shard id to index mapping stored in cache entry as there may now be multiple entries alive for a given relation
insert_select_executor: revert copying cache entry, which was a hack added to avoid memory safety issues
* reimplement ExecuteUtilityTaskListWithoutResults for local utility command execution
* introduce new functions for local execution of utility commands
* change ErrorIfTransactionAccessedPlacementsLocally logic for local utility command execution
* enable local execution for TRUNCATE command on distributed & reference tables
* update existing tests for local utility command execution
* enable local execution for DDL commands on distributed & reference tables
* enable local execution for DROP command on distributed & reference tables
* add normalization rules for cascaded commands
* add new tests for local utility command execution
DESCRIPTION: Replace the query planner for the coordinator part with the postgres planner
Closes#2761
Citus had a simple rule based planner for the query executed on the query coordinator. This planner grew over time with the addigion of SQL support till it was getting close to the functionality of the postgres planner. Except the code was brittle and its complexity rose which made it hard to add new SQL support.
Given its resemblance with the postgres planner it was a long outstanding wish to replace our hand crafted planner with the well supported postgres planner. This patch replaces our planner with a call to postgres' planner.
Due to the functionality of the postgres planner we needed to support both projections and filters/quals on the citus custom scan node. When a sort operation is planned above the custom scan it might require fields to be reordered in the custom scan before returning the tuple (projection). The postgres planner assumes every custom scan node implements projections. Because we controlled the plan that was created we prevented reordering in the custom scan and never had implemented it before.
A same optimisation applies to having clauses that could have been where clauses. Instead of applying the filter as a having on the aggregate it will push it down into the plan which could reach a custom scan node.
For both filters and projections we have implemented them when tuples are read from the tuple store. If no projections or filters are required it will directly return the tuple from the tuple store. Otherwise it will loop tuples from the tuple store through the filter and projection until a tuple is found and returned.
Besides filters being pushed down a side effect of having quals that could have been a where clause is that a call to read intermediate result could be called before the first tuple is fetched from the custom scan. This failed because the intermediate result would only be pulled to the coordinator on the first tuple fetch. To overcome this problem we do run the distributed subplans now before we run the postgres executor. This ensures the intermediate result is present on the coordinator in time. We do account for total time instrumentation by removing the instrumentation before handing control to the psotgres executor and update the timings our self.
For future SQL support it is enough to create a valid query structure for the part of the query to be executed on the query coordinating node. As a utility we do serialise and print the query at debug level4 for engineers to inspect what kind of query is being planned on the query coordinator.
DESCRIPTION: Fix counter that keeps track of internal depth in executor
While reviewing #3302 I ran into the `ExecutorLevel` variable which used a variable to keep the original value to restore on successful exit. I haven't explored the full space and if it is possible to get into an inconsistent state. However using `PG_TRY`/`PG_CATCH` seems generally more correct.
Given very bad things will happen if this level is not reset, I kept the failsafe of setting the variiable back to 0 on the `XactCallback` but I did add an assert to treat it as a developer bug.
Test ALTER ROLE doesn't deadlock when coordinator added, or propagate from mx workers
Consolidate wait_until_metadata_sync & verify_metadata to multi_test_helpers
In plain words, each distributed plan pulls the necessary intermediate
results to the worker nodes that the plan hits. This is primarily useful
in three ways.
(i) If the distributed plan that uses intermediate
result(s) is a router query, then the intermediate results are only
broadcasted to a single node.
(ii) If a distributed plan consists of only intermediate results, which
is not uncommon, the intermediate results are broadcasted to a single
node only.
(iii) If a distributed query hits a sub-set of the shards in multiple
workers, the intermediate results will be broadcasted to the relevant
node(s).
The final item (iii) becomes crucial for append/range distributed
tables where typically the distributed queries hit a small subset of
shards/workers.
To do this, for each query that Citus creates a distributed plan, we keep
track of the subPlans used in the queryTree, and save it in the distributed
plan. Just before Citus executes each subPlan, Citus first keeps track of
every worker node that the distributed plan hits, and marks every subPlan
should be broadcasted to these nodes. Later, for each subPlan which is a
distributed plan, Citus does this operation recursively since these
distributed plans may access to different subPlans, and those have to be
recorded as well.
* Remove unused executor codes
All of the codes of real-time executor. Some functions
in router executor still remains there because there
are common functions. We'll move them to accurate places
in the follow-up commits.
* Move GUCs to transaction mngnt and remove unused struct
* Update test output
* Get rid of references of real-time executor from code
* Warn if real-time executor is picked
* Remove lots of unused connection codes
* Removed unused code for connection restrictions
Real-time and router executors cannot handle re-using of the existing
connections within a transaction block.
Adaptive executor and COPY can re-use the connections. So, there is no
reason to keep the code around for applying the restrictions in the
placement connection logic.
/*
* local_executor.c
*
* The scope of the local execution is locally executing the queries on the
* shards. In other words, local execution does not deal with any local tables
* that are not shards on the node that the query is being executed. In that sense,
* the local executor is only triggered if the node has both the metadata and the
* shards (e.g., only Citus MX worker nodes).
*
* The goal of the local execution is to skip the unnecessary network round-trip
* happening on the node itself. Instead, identify the locally executable tasks and
* simply call PostgreSQL's planner and executor.
*
* The local executor is an extension of the adaptive executor. So, the executor uses
* adaptive executor's custom scan nodes.
*
* One thing to note that Citus MX is only supported with replication factor = 1, so
* keep that in mind while continuing the comments below.
*
* On the high level, there are 3 slightly different ways of utilizing local execution:
*
* (1) Execution of local single shard queries of a distributed table
*
* This is the simplest case. The executor kicks at the start of the adaptive
* executor, and since the query is only a single task the execution finishes
* without going to the network at all.
*
* Even if there is a transaction block (or recursively planned CTEs), as long
* as the queries hit the shards on the same, the local execution will kick in.
*
* (2) Execution of local single queries and remote multi-shard queries
*
* The rule is simple. If a transaction block starts with a local query execution,
* all the other queries in the same transaction block that touch any local shard
* have to use the local execution. Although this sounds restrictive, we prefer to
* implement in this way, otherwise we'd end-up with as complex scenarious as we
* have in the connection managements due to foreign keys.
*
* See the following example:
* BEGIN;
* -- assume that the query is executed locally
* SELECT count(*) FROM test WHERE key = 1;
*
* -- at this point, all the shards that reside on the
* -- node is executed locally one-by-one. After those finishes
* -- the remaining tasks are handled by adaptive executor
* SELECT count(*) FROM test;
*
*
* (3) Modifications of reference tables
*
* Modifications to reference tables have to be executed on all nodes. So, after the
* local execution, the adaptive executor keeps continuing the execution on the other
* nodes.
*
* Note that for read-only queries, after the local execution, there is no need to
* kick in adaptive executor.
*
* There are also few limitations/trade-offs that is worth mentioning. First, the
* local execution on multiple shards might be slow because the execution has to
* happen one task at a time (e.g., no parallelism). Second, if a transaction
* block/CTE starts with a multi-shard command, we do not use local query execution
* since local execution is sequential. Basically, we do not want to lose parallelism
* across local tasks by switching to local execution. Third, the local execution
* currently only supports queries. In other words, any utility commands like TRUNCATE,
* fails if the command is executed after a local execution inside a transaction block.
* Forth, the local execution cannot be mixed with the executors other than adaptive,
* namely task-tracker, real-time and router executors. Finally, related with the
* previous item, COPY command cannot be mixed with local execution in a transaction.
* The implication of that any part of INSERT..SELECT via coordinator cannot happen
* via the local execution.
*/
Nils Dijk
Hanefi Onaldi
Ahmet Gedemenli
Teja Mupparti
Marco Slot
Önder Kalacı
Philip Dubé
Sait Talha Nisanci
Halil Ozan Akgul
Hadi Moshayedi
Marco Slot
Philip Dubé
Onur Tirtir
Philip Dubé
Jelte Fennema
Hanefi Onaldi