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
In preparation of sorting and grouping all includes we wanted to move
this file to the toplevel includes for good grouping/sorting.
(cherry picked from commit 0dac63afc0)
We need to rewind the tuplestorestate's tuple index to get correct
results on fetching scrollable with hold cursors.
`PersistHoldablePortal` is responsible for persisting out
tuplestorestate inside a with hold cursor before commiting a
transaction.
It rewinds the cursor like below (`ExecutorRewindcalls` calls `rescan`):
```c
if (portal->cursorOptions & CURSOR_OPT_SCROLL)
{
ExecutorRewind(queryDesc);
}
```
At the end, it adjusts tuple index for holdStore in the portal properly.
```c
if (portal->cursorOptions & CURSOR_OPT_SCROLL)
{
if (!tuplestore_skiptuples(portal->holdStore,
portal->portalPos,
true))
elog(ERROR, "unexpected end of tuple stream");
}
```
DESCRIPTION: Fixes incorrect results on fetching scrollable with hold
cursors.
Fixes https://github.com/citusdata/citus/issues/7010
1) For distributed tables that are not colocated.
2) When joining on a non-distribution column for colocated tables.
3) When merging into a distributed table using reference or citus-local tables as the data source.
This is accomplished primarily through the implementation of the following two strategies.
Repartition: Plan the source query independently,
execute the results into intermediate files, and repartition the files to
co-locate them with the merge-target table. Subsequently, compile a final
merge query on the target table using the intermediate results as the data
source.
Pull-to-coordinator: Execute the plan that requires evaluation at the coordinator,
run the query on the coordinator, and redistribute the resulting rows to ensure
colocation with the target shards. Direct the MERGE SQL operation to the worker
nodes' target shards, using the intermediate files colocated with the data as the
data source.
DESCRIPTION: Enabling citus_stat_tenants to support schema-based
tenants.
This pull request modifies the existing logic to enable tenant
monitoring with schema-based tenants. The changes made are as follows:
- If a query has a partitionKeyValue (which serves as a tenant
key/identifier for distributed tables), Citus annotates the query with
both the partitionKeyValue and colocationId. This allows for accurate
tracking of the query.
- If a query does not have a partitionKeyValue, but its colocationId
belongs to a distributed schema, Citus annotates the query with only the
colocationId. The tenant monitor can then easily look up the schema to
determine if it's a distributed schema and make a decision on whether to
track the query.
---------
Co-authored-by: Jelte Fennema <jelte.fennema@microsoft.com>
DESCRIPTION: Adds views that monitor statistics on tenant usages
This PR adds `citus_stats_tenants` view that monitors the tenants on the
cluster.
`citus_stats_tenants` shows the node id, colocation id, tenant
attribute, read count in this period and last period, and query count in
this period and last period of the tenant.
Tenant attribute currently is the tenant's distribution column value,
later when schema based sharding is introduced, this meaning might
change.
A period is a time bucket the queries are counted by. Read and query
counts for this period can increase until the current period ends. After
that those counts are moved to last period's counts, which cannot
change. The period length can be set using 'citus.stats_tenants_period'.
`SELECT` queries are counted as _read_ queries, `INSERT`, `UPDATE` and
`DELETE` queries are counted as _write_ queries. So in the view read
counts are `SELECT` counts and query counts are `SELECT`, `INSERT`,
`UPDATE` and `DELETE` count.
The data is stored in shared memory, in a struct named
`MultiTenantMonitor`.
`citus_stats_tenants` shows the data from local tenants.
`citus_stats_tenants` show up to `citus.stats_tenant_limit` number of
tenants.
The tenants are scored based on the number of queries they run and the
recency of those queries. Every query ran increases the score of tenant
by `ONE_QUERY_SCORE`, and after every period ends the scores are halved.
Halving is done lazily.
To retain information a longer the monitor keeps up to 3 times
`citus.stats_tenant_limit` tenants. When the tenant count hits `3 *
citus.stats_tenant_limit`, last `citus.stats_tenant_limit` tenants are
removed. To see all stored tenants you can use
`citus_stats_tenants(return_all_tenants := true)`
- [x] Create collector view that gets data from all nodes. #6761
- [x] Add monitoring log #6762
- [x] Create enable/disable GUC #6769
- [x] Parse the annotation string correctly #6796
- [x] Add local queries and prepared statements #6797
- [x] Rename to citus_stat_statements #6821
- [x] Run pgbench
- [x] Fix role permissions #6812
---------
Co-authored-by: Gokhan Gulbiz <ggulbiz@gmail.com>
Co-authored-by: Jelte Fennema <github-tech@jeltef.nl>
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`
CitusInitiatedBackend was a pre-mature implemenation of the whole
GlobalPID infrastructure. We used it to track whether any individual
query is triggered by Citus or not.
As of now, after GlobalPID is already in place, we don't need
CitusInitiatedBackend, in fact it could even be wrong.
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
With local query caching, we try to avoid deparse/parse stages as the
operation is too costly.
However, we can do deparse/parse operations once per cached queries, right
before we put the plan into the cache. With that, we avoid edge
cases like (4239) or (5038).
In a sense, we are making the local plan caching behave similar for non-cached
local/remote queries, by forcing to deparse the query once.
Baseinfo also has pushed down filters etc, so it makes more sense to use
BaseRestrictInfo to determine what columns have constant equality
filters.
Also RteIdentity is used for removing conversion candidates instead of
rteIndex.
It seems that most of the updates were broken, we weren't aware of it
because there wasn't any data in the tables. They are broken mostly
because local tables do not have a shard id and some code paths should
be updated with that information, currently when there is an invalid
shard id, it is assumed to be pruned.
Consider local tables in router planner
In case there is a local table, the shard id will not be valid and there
are some checks that rely on shard id, we should skip these in case of
local tables, which is handled with a dummy placement.
Add citus local table dist table join tests
add local-dist table mixed joins tests
Before this commit, we let AdaptiveExecutorPreExecutorRun()
to be effective multiple times on every FETCH on cursors.
That does not affect the correctness of the query results,
but adds significant overhead.
* 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
We still recursively plan some cases, eg:
- INSERTs
- SELECT FOR UPDATE when reference tables in query
- Everything must be same single shard & replication model
We can use local copy in INSERT..SELECT, so the check that disables
local execution is removed.
Also a test for local copy where the data size >
LOCAL_COPY_FLUSH_THRESHOLD is added.
use local execution with insert..select
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.
The root of the problem is that, standard_planner() converts the following qual
```
{OPEXPR
:opno 98
:opfuncid 67
:opresulttype 16
:opretset false
:opcollid 0
:inputcollid 100
:args (
{VAR
:varno 1
:varattno 1
:vartype 25
:vartypmod -1
:varcollid 100
:varlevelsup 0
:varnoold 1
:varoattno 1
:location 45
}
{CONST
:consttype 25
:consttypmod -1
:constcollid 100
:constlen -1
:constbyval false
:constisnull true
:location 51
:constvalue <>
}
)
:location 49
}
```
To
```
(
{CONST
:consttype 16
:consttypmod -1
:constcollid 0
:constlen 1
:constbyval true
:constisnull true
:location -1
:constvalue <>
}
)
```
So, Citus doesn't deal with NULL values in real-time or non-fast path router queries.
And, in the FastPathRouter planner, we check constisnull in DistKeyInSimpleOpExpression().
However, in deferred pruning case, we do not check for isnull for const.
Thus, the fix consists of two parts:
- Let PruneShards() not crash when NULL parameter is passed
- For deferred shard pruning in fast-path queries, explicitly check that we have CONST which is not NULL
Previously, the logic for evaluting the functions and the parameters
were the same. That ended-up evaluting the functions inaccurately
on the coordinator. Instead, split the function evaluation logic
from parameter evalution logic.
This is purely to enable better performance with prepared statements.
Before this commit, the fast path queries with prepared statements
where the distribution key includes a parameter always went through
distributed planning. After this change, we only go through distributed
planning on the first 5 executions.
Different versions of reindent tool reformatted citus_custom_scan.c
and citus_copyfuncs.c differently. So some developers spent some
extra attention not to commit these two files after reindent.
This PR tries to address this.
Naisila Puka
Jelte Fennema-Nio
Nils Dijk
aykut-bozkurt
Teja Mupparti
Gokhan Gulbiz
Halil Ozan Akgül
Marco Slot
Onder Kalaci
SaitTalhaNisanci
Hadi Moshayedi
Philip Dubé
Onur Tirtir
Philip Dubé
Önder Kalacı