On top of our foreign key graph, implement the infrastructure to get
list of relations that are connected to input relation via a foreign key
graph.
We need this to support cascading create_citus_local_table &
undistribute_table operations.
Also add regression tests to see what our foreign key graph is able to
capture currently.
Attribute number in a subquery RTE and relation RTE means different
things. In a relation attribute number will point to the column number
in the table definition including the dropped columns as well however in
subquery, it means the index in the target list. When we convert a
relation RTE to subquery RTE we should either correct all the relevant
attribute numbers or we can just add a dummy column for the dropped
columns. We choose the latter in this commit because it is practically
too vulnerable to update all the vars in a query.
Another thing this commit fixes is that in case a join restriction
clause list contains a false clause, we should just returns a false
clause instead of the whole list, because the whole list will contain
restrictions from other RTEs as well and this breaks the query, which
can be seen from the output changes, now it is much simpler.
Also instead of adding single tests for dropped columns, we choose to
run the whole mixed queries with tables with dropped columns, this
revealed some bugs already, which are fixed in this commit.
It seems that there are only very few cases where that is useful, and
for now we prefer not having that check. This means that we might
perform some unnecessary checks, but that should be rare and not
performance critical.
Instead of sending NULL's over a network, we now convert the subqueries
in the form of:
SELECT t.a, NULL, NULL FROM (SELECT a FROM table)t;
And we recursively plan the inner part so that we don't send the NULL's
over network. We still need the NULLs in the outer subquery because we
currently don't have an easy way of updating all the necessary places in
the query.
Add some documentation for how the conversion is done
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
AllDataLocallyAccessible and ContainsLocalTableSubqueryJoin are removed.
We can possibly remove ModifiesLocalTableWithRemoteCitusLocalTable as
well. Though this removal has a side effect that now when all the data
is locally available, we could still wrap a relation into a subquery, I
guess that should be resolved in the router planner itself.
Add more tests
When we wrap an RTE to subquery we are updating the variables varno's as
1, however we should also update the varno's of vars in quals.
Also some other small code quality improvements are done.
The previous algorithm was not consistent and it could convert different
RTEs based on the table orders in the query. Now we convert local tables
if there is a distributed table which doesn't have a unique index. So if
there are 4 tables, local1, local2, dist1, dist2_with_pkey then we will
convert local1 and local2 in `auto` mode. Converting a distributed table
is not that logical because as there is a distributed table without a
unique index, we will need to convert the local tables anyway. So
converting the distributed table with pkey is redundant.
Remove FillLocalAndDistributedRTECandidates and use
ShouldConvertLocalTableJoinsToSubqueries, which simplifies things as we
rely on a single function to decide whether we should continue
converting RTE to subquery.
We should not recursively plan an already routable plannable query. An
example of this is (SELECT * FROM local JOIN (SELECT * FROM dist) d1
USING(a));
So we let the recursive planner do all of its work and at the end we
convert the final query to to handle unsupported joins. While doing each
conversion, we check if it is router plannable, if so we stop.
Only consider range table entries that are in jointree
If a range table is not in jointree then there is no point in
considering that because we are trying to convert range table entries to
subqueries for join use case.
Check equality in quals
We want to recursively plan distributed tables only if they have an
equality filter on a unique column. So '>' and '<' operators will not
trigger recursive planning of distributed tables in local-distributed
table joins.
Recursively plan distributed table only if the filter is constant
If the filter is not a constant then the join might return multiple rows
and there is a chance that the distributed table will return huge data.
Hence if the filter is not constant we choose to recursively plan the
local table.
When doing local-distributed table joins we convert one of them to
subquery. The current policy is that we convert distributed tables to
subquery if it has a unique index on a column that has unique
index(primary key also has a unique index).
UPDATEs on partitioned tables that affect only row partitions should
succeed, the rest should fail.
Also rename CStoreScan to ColumnarScan to make the error message more
relevant.
When Citus needs to parallelize queries on the local node (e.g., the node
executing the distributed query and the shards are the same), we need to
be mindful about the connection management. The reason is that the client
backends that are running distributed queries are competing with the client
backends that Citus initiates to parallelize the queries in order to get
a slot on the max_connections.
In that regard, we implemented a "failover" mechanism where if the distributed
queries cannot get a connection, the execution failovers the tasks to the local
execution.
The failover logic is follows:
- As the connection manager if it is OK to get a connection
- If yes, we are good.
- If no, we fail the workerPool and the failure triggers
the failover of the tasks to local execution queue
The decision of getting a connection is follows:
/*
* For local nodes, solely relying on citus.max_shared_pool_size or
* max_connections might not be sufficient. The former gives us
* a preview of the future (e.g., we let the new connections to establish,
* but they are not established yet). The latter gives us the close to
* precise view of the past (e.g., the active number of client backends).
*
* Overall, we want to limit both of the metrics. The former limit typically
* kics in under regular loads, where the load of the database increases in
* a reasonable pace. The latter limit typically kicks in when the database
* is issued lots of concurrent sessions at the same time, such as benchmarks.
*/
When distributing a columnar table, as well as changing options on a distributed columnar table, this patch will forward the settings from the coordinator to the workers.
For propagating options changes on an already distributed table this change is pretty straight forward. Before applying the change in options locally we will create a `DDLJob` that contains a call to `alter_columnar_table_set(...)` for every shard placement with all settings of the current table. This goes both for setting an option as well as resetting. This will reset the values to the defaults configured on the coordinator. Having the effect that the coordinator is authoritative on the settings and makes sure the shards have the same settings set as the table on the coordinator.
When a columnar table is distributed it is using the `TableDDLCommand` infra structure to create a new kind of `TableDDLCommand`. This new type, called a `TableDDLCommandFunction` contains a context and 2 function pointers to execute. One function returns the command as applied on the table, the second function will return the sql command to apply to a shard with a given shard id. The schema name is ignored as it will use the fully qualified name of the shard in the same schema as the base table.
Multi-row execution already uses sequential execution. When shards
are local, using local execution is profitable as it avoids
an extra connection establishment to the local node.
Join test gets too many clients error too frequently hence we should
not run anything concurrently with that. Hopefully this will fix the
flakiness of test.
This is to avoid flaky changes like the following in test outputs:
-CPU: user: 0.00 s, system: 0.00 s, elapsed: 0.00 s.
+CPU: user: 0.00 s, system: 0.00 s, elapsed: 0.02 s.
Columnar options were by accident linked to the relfilenode instead of the regclass/relation oid. This PR moves everything related to columnar options to their own catalog table.
Considering the adaptive connection management
improvements that we plan to roll soon, it makes it
very helpful to know the number of active client
backends.
We are doing this addition to simplify yhe adaptive connection
management for single node Citus. In single node Citus, both the
client backends and Citus parallel queries would compete to get
slots on Postgres' `max_connections` on the same Citus database.
With adaptive connection management, we have the counters for
Citus parallel queries. That helps us to adaptively decide
on the remote executions pool size (e.g., throttle connections
if necessary).
However, we do not have any counters for the total number of
client backends on the database. For single node Citus, we
should consider all the client backends, not only the remote
connections that Citus does.
Of course Postgres internally knows how many client
backends are active. However, to get that number Postgres
iterates over all the backends. For examaple, see [pg_stat_get_db_numbackends](8e90ec5580/src/backend/utils/adt/pgstatfuncs.c (L1240))
where Postgres iterates over all the backends.
For our purpuses, we need this information on every connection
establishment. That's why we cannot affort to do this kind of
iterattion.
CitusTableTypeIdList() function iterates on all the entries of pg_dist_partition
and loads all the metadata in to the cache. This can be quite memory intensive
especially when there are lots of distributed tables.
When partitioned tables are used, it is common to have many distributed tables
given that each partition also becomes a distributed table.
CitusTableTypeIdList() is used on every CREATE TABLE .. PARTITION OF.. command
as well. It means that, anytime a partition is created, Citus loads all the
metadata to the cache. Note that Citus typically only loads the accessed table's
metadata to the cache.
* Move local execution after the remote execution
Before this commit, when both local and remote tasks
exist, the executor was starting the execution with
local execution. There is no strict requirements on
this.
Especially considering the adaptive connection management
improvements that we plan to roll soon, moving the local
execution after to the remote execution makes more sense.
The adaptive connection management for single node Citus
would look roughly as follows:
- Try to connect back to the coordinator for running
parallel queries.
- If succeeds, go on and execute tasks in parallel
- If fails, fallback to the local execution
So, we'll use local execution as a fallback mechanism. And,
moving it after to the remote execution allows us to implement
such further scenarios.
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.
TableAM API doesn't allow us to pass around a state variable along all of the tuple inserts belonging to the same command. We require this in columnar store, since we batch them, and when we have enough rows we flush them as stripes.
To do that, we keep a (relfilenode) -> stack of (subxact id, TableWriteState) global mapping.
**Inserts**
Whenever we want to insert a tuple, we look up for the relation's relfilenode in this mapping. If top of the stack matches current subtransaction, we us the existing TableWriteState. Otherwise, we allocate a new TableWriteState and push it on top of stack.
**(Sub)Transaction Commit/Aborts**
When the subtransaction or transaction is committed, we flush and pop all entries matching current SubTransactionId.
When the subtransaction or transaction is committed, we pop all entries matching current SubTransactionId and discard them without flushing.
**Reads**
Since we might have unwritten rows which needs to be read by a table scan, we flush write states on SELECTs. Since flushing the write state of upper transactions in a subtransaction will cause metadata being written in wrong subtransaction, we ERROR out if any of the upper subtransactions have unflushed rows.
**Table Drops**
We record in which subtransaction the table was dropped. When committing a subtransaction in which table was dropped, we propagate the drop to upper transaction. When aborting a subtransaction in which table was dropped, we mark table as not deleted.
* Update failure test dependencies
There was a security alert for cryptography. The vulnerability was fixed
in 3.2.0. The vulnebarility:
"RSA decryption was vulnerable to Bleichenbacher timing vulnerabilities,
which would impact people using RSA decryption in online scenarios."
The fix:
58494b41d6
It wasn't enough to only update crpytography because mitm was
incompatible with the new version, so mitm is also upgraded.
The steps to do in local:
python -m pip install -U cryptography
python -m pip install -U mitmproxy
When a relation is used on an OUTER JOIN with FALSE filters,
set_rel_pathlist_hook may not be called for the table.
There might be other cases as well, so do not rely on the hook
for classification of the tables.
Aliases that postgres choose for partitioned tables in explain output
might change in different pg versions, so normalize them and remove
the alternative test output
* Fix incorrect join related fields
Ruleutils expect to give the original index of join columns hence we
should consider the dropped columns while setting the fields in
SetJoinRelatedFieldsCompat.
* add some more tests for joins
* Move tests to join.sql and create a utility function
Disallow `ON TRUE` outer joins with reference & distributed tables
when reference table is outer relation by fixing the logic bug made
when calling `LeftListIsSubset` function.
Also, be more defensive when removing duplicate join restrictions
when join clause is empty for non-inner joins as they might still
contain useful information for non-inner joins.
It seems like Postgres could call set_rel_pathlist() for
the same relation multiple times. This breaks the logic
where we assume relationCount eqauls to the number of
entries in relationRestrictionList.
In summary, relationRestrictionList may contain duplicate
entries.
With this commit, we make sure that local execution adds the
intermediate result size as the distributed execution adds. Plus,
it enforces the citus.max_intermediate_result_size value.
Before this commit, the logic was:
- As long as the outer side of the JOIN is not a JOIN (e.g., relation
or subquery etc.), we check for the existence of any recurring
tuples. There were two implications of this decision.
First, even if a subquery which is on the outer side contains
distributed table JOIN reference table, Citus would unnecessarily throw
an error. Note that, the JOIN inside the subquery would already
be going to be tested recursively. But, as long as that check
passes, there is no reason for the upper JOIN to fail. An example, which
used to fail and now works:
SELECT * FROM (SELECT * FROM dist JOIN ref) as foo LEFT JOIN dist;
Second, certain JOINs, especially with ON (true) conditions were not
represented as Citus expects the JOINs to be in the format
DeferredErrorIfUnsupportedRecurringTuplesJoin().
Use short lived per-tuple context in citus_evaluate_expr like
(pg) evaluate_expr does.
We should not use planState->ExprContext when evaluating expressions
as it might lead to freeing the same executor twice (first one happens
in citus_evaluate_expr itself and the other one happens when postgres
doing clean-up for the top level executor state), which in turn might
cause seg.faults.
However, now as we don't have necessary planState info to evaluate
prepared statements, we also add planState->es_param_list_info to
per-tuple ExprContext.
With postgres 13, there is a global lock that prevents multiple VACUUMs
happening in the current database. This global lock is taken for a short
time but this creates a problem because of the following:
- We execute the VACUUM for the shell table through the standard process
utility. In this step the global lock is taken for the current database.
- If the current node has shard placements then it tries to execute
VACUUM over a connection to localhost with ExecuteUtilityTaskList.
- the VACUUM on shard placements cannot proceed because it is waiting
for the global lock for the current database to be released.
- The acquired lock from the VACUUM for shell table will not be released
until the transaction is committed.
- So there is a deadlock.
As a solution, we commit the current transaction in case of VACUUM after
the VACUUM is executed for the shell table. Executing the VACUUM on a
shell table is not important because the data there will probably be
truncated. PostprocessVacuumStmt takes the necessary locks on the shell
table so we don't need to take any extra locks after we commit the
current transaction.
In our test structure, we have been passing postgres configurations from
the terminal, which causes problems after it hits to a certain length
hence it cannot start the server and understanding why it failed is not
easy because there isn't a nice error message.
This commit changes this to write the settings directly to the postgres
configuration file. This way we can add as many postgres settings as we
want to without needing to worry about the length problem.
Multi-row & router INSERT's were crashing with local execution if at
least one of the DEFAULT columns were not specified in VALUES list.
This was because, the changes we make on query->values_lists and
query->targetList was sufficient for deparsing given INSERT for remote
execution but not sufficient for local execution.
With this commit, DEFAULT value normalization for multi-row & router
INSERT's is fixed by adding dummy column references for unspecified
DEFAULT columns.
Citus has the logic to truncate the long shard names to prevent
various issues, including self-deadlocks. However, for partitioned
tables, when index is created on the parent table, the index names
on the partitions are auto-generated by Postgres. We use the same
Postgres function to generate the index names on the shards of the
partitions. If the length exceeds the limit, we switch to sequential
execution mode.
We currently do not support volatile functions in update/delete statements
because the function evaluation logic does not know how to distinguish
volatile functions (that need to be evaluated per row) from stable functions
(that need to be evaluated per query), and it is also not safe to push the
volatile functions down on replicated tables.
Add sort method parameter for regression tests
Fix check-style
Change sorting method parameters to enum
Polish
Add task fields to OutTask
Add test into multi_explain
Fix isolation test
As the previous versions of Citus don't know how to handle citus local
tables, we should prevent downgrading from 9.5 to older versions if any
citus local tables exists.
Pushing down the CALLs to the node that the CALL is executed is
dangerous and could lead to infinite recursion.
When the coordinator added as worker, Citus was by chance preventing
this. The coordinator was marked as "not metadatasynced" node
in pg_dist_node, which prevented CALL/function delegation to happen.
With this commit, we do the following:
- Fix metadatasynced column for the coordinator on pg_dist_node
- Prevent pushdown of function/procedure to the same node that
the function/procedure is being executed. Today, we do not sync
pg_dist_object (e.g., distributed functions metadata) to the
worker nodes. But, even if we do it now, the function call delegation
would prevent the infinite recursion.
* Not allow removing a single node with ref tables
We should not allow removing a node if it is the only node in the
cluster and there is a data on it. We have this check for distributed
tables but we didn't have it for reference tables.
* Update src/test/regress/expected/single_node.out
Co-authored-by: Onur Tirtir <onurcantirtir@gmail.com>
* Update src/test/regress/sql/single_node.sql
Co-authored-by: Onur Tirtir <onurcantirtir@gmail.com>
This commit brings following features:
Foreign key support from citus local tables to reference tables
* Foreign key support from reference tables to citus local tables
(only with RESTRICT & NO ACTION behavior)
* ALTER TABLE ENABLE/DISABLE trigger command support
* CREATE/DROP/ALTER trigger command support
and disallows:
* ALTER TABLE ATTACH/DETACH PARTITION commands
* CREATE TABLE <postgres table> ATTACH PARTITION <citus local table>
commands
* Foreign keys from postgres tables to citus local tables
(the other way was already disallowed)
for citus local tables.
create_distributed_function(function_name,
distribution_arg_name,
colocate_with text)
This UDF did not allow colocate_with parameters when there were no
disttribution_arg_name supplied. This commit changes the behaviour to
allow missing distribution_arg_name parameters when the function should
be colocated with a reference table.
* Hide citus.subquery_pushdown flag
This flag is dangerous and could likely to let queries
return wrong results.
The flag has a very specific purpose for a very specific
data distribution and query structure. In those cases, when
the flag is set, the user can skip recursive planning altogether
*at their own risk*.
The meaning of the flag is that "I know what I'm doing such that
the query structure/data distribution is on my control, so Citus
can skip many correctness checks".
For regular users, enabling this flag is discouraged. We have to
keep the support only for backward compatibility for some users.
In addition to that, give a NOTICE to discourage new users to
use it.
* Update and separate test images
The build image was a single one and it would contain pg11, pg12 and
pg13. Now it is separated so that we can build each pg major
independently.
Tags are used as full postgres versions so that we can know which
version we use by looking at the tag. For example exttester:11.9 would
mean we are using pg11.9.
pg11 is updated from 11.5 to 11.9.
pg12 is updated from 12rc to 12.4.
* Ignore memory usage in pg13 explain
* Use citus instead of personal repo
AllTargetExpressionsAreColumnReferences would return false if a query
had an entry that is referencing the outer query. It seems safe to not
have this for non-distributed tables, such as reference tables. We
already have separate checks for other cases such as having limits.
The error message when index has opclassopts is improved and the commit
from postgres side is also included for future reference.
Also some minor style related changes are applied.
Error out if index has opclassopts.
Changelog entry on PG13:
Allow CREATE INDEX to specify the GiST signature length and maximum number of integer ranges (Nikita Glukhov)
It seems that we don't support propagating commands related to base
types. Therefore Alter TYPE options doesn't seem to apply to us. I have
added a test to verify that we don't propagate them.
Changelog entry on pg13:
Add ALTER TYPE options useful for extensions, like TOAST and I/O functions control (Tomas Vondra, Tom Lane)
Unicode escapes work as expected, related tests are added.
Changelog entry on PG13:
Allow Unicode escapes, e.g., E'\u####', U&'\####', to specify any character available in the database encoding, even when the database encoding is not UTF-8 (Tom Lane)
Tests for is_normalized and normalized ar eadded. One thing that seems
to be because of existent bug is that when we don't give the second
argument to normalize or is_normalized, which is optional, it crashes.
Because in the executor part, in the expression we don't have the
default argument.
Changelog entry in PG-13:
Add SQL functions NORMALIZE() to normalize Unicode strings, and IS NORMALIZED to check for normalization (Peter Eisentraut)
Commit on Postgres:
2991ac5fc9b3904ca4582be6d323497d7c3d17c9
It seems that row suffix notation is working fine with our code, a test
is added.
Changelog entry in PG13:
Allow ROW values values to have their members extracted with suffix notation (Tom Lane)
PG13 now supports dropping expression from a column such as generated
columns. We error out with this currently.
Changelog entry in postgres:
Add ALTER TABLE clause DROP EXPRESSION to remove generated properties from columns (Peter Eisentraut)
Postgres 13 added a new VACUUM option, PARALLEL. It is now supported
in our code as well.
Relevant changelog message on postgres:
Allow VACUUM to process indexes in parallel (Masahiko Sawada, Amit Kapila)
With pg13, constants functions from "FROM" clause are replaced. This
means that in citus side, we will see the constraints in restriction
info, instead of the function call. For example:
SELECT * FROM table1 JOIN add(3,5) sum ON (id = sum) ORDER BY id ASC;
Assuming that the function `add` returns constant, it will be evaluated
on postgres side. This means that this query will be routable because
there will be only one shard after pruning with the restrictions.
However before pg13, this would be multi shard query. And it would go
into recursive planning, the function would be evaluated on the
coordinator because it can be.
This means that with pg13, users will need to distribute the function
because when it is routable executable, it will currently also send the
function call to the worker in the query. So the function should exist
in the worker.
It could be better to replace the constant in the query tree as well so
that the query string sent to the worker has the constant value and
therefore it doesn't need the function. However I feel like users would
already have the function in workers if they have any multi shard query.
Commit on Postgres side:
7266d0997dd2a0632da38a594c78e25ff21df67e
CREATE EXTENSION <name> FROM <old_version> is not supported anymore with
postgres 13. An alternative output is added for pg13 where we basically
error for that statement.
The not-null constraint message changed with pg13 slightly hence a
normalization rule is added for that, which converts it to pg < 13
output.
Commit on postgres:
05f18c6b6b6e4b44302ee20a042cedc664532aa2
An extra debug message is added related to indexes on postgres, these
are safe to be ignored, so we can delete them from tests.
Commit on Postgres side:
612a1ab76724aa1514b6509269342649f8cab375
varnoold is renamed as varnosyn and varoattno is renamed as varattnosyn
so in the output we normalize the values as the old ones to simply pass
the tests.
With this patch, we introduce `locally_reserved_shared_connections.c/h` files
which are responsible for reserving some space in shared memory counters
upfront.
We sometimes need to reserve connections, but not necessarily
establish them. For example:
- COPY command should reserve connections as it cannot know which
connections it needs in which order. COPY establishes connections
as any input data hits the workers. For example, for router COPY
command, it only establishes 1 connection.
As discussed here (https://github.com/citusdata/citus/pull/3849#pullrequestreview-431792473),
COPY needs to reserve connections up-front, otherwise we can end
up with resource starvation/un-detected deadlocks.
* ensure propagation of CHECK statements to workers with parantheses & adjust regression test outputs
* add tests for distributing tables with simple CHECK constraints
* added test for CHECK on bool variable
Enable custom aggregates with multiple parameters to be executed on workers.
#2921 introduces distributed execution of custom aggregates. One of the limitations of this feature is that only aggregate functions with a single aggregation parameter can be pushed to worker nodes. Aim of this change is to remove that limitation and support handling of multi-parameter aggregates.
Resolves: #3997
See also: #2921
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.
As noted by Talha https://github.com/citusdata/citus/pull/4029#issuecomment-660466972 there was still some sort order flappiness in the test.
The root cause is that sorting on `1::text` sorts on the literal `'1'` which causes sorting to be indeterministic.
This behaviour is consistent with Postgres' behaviour, so no bug on Citus' side.
* 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
As reported on #4011https://github.com/citusdata/citus/pull/4011/files#r453804702 some of the tests were flapping due to an indeterministic order for test outputs.
This PR makes the test output ordered for all tests returning non-zero rows.
Needs to be backported to 9.2, 9.3, 9.4
The reason we should use ActiveReadableNodeList instead of ActiveReadableNonCoordinatorNodeList is that if coordinator is added to cluster as a worker, it should be counted as well. Otherwise if there is only coordinator in the cluster, the count will be 0, hence we get a warning.
In MultiTaskTrackerExecute, we should connect to coordinator if it is
added to the cluster because it will also be assigned tasks.
ActiveReadableWorkerNodeList doesn't include coordinator, however if
coordinator is added as a worker, we should also include that while
planning. The current methods are very easily misusable and this
requires a refactoring to make the distinction between methods that
include coordinator and that don't very explicit as they can introduce
subtle/major bugs pretty easily.
We were using ALL_WORKERS TargetWorkerSet while sending temporary schema
creation and cleanup. We(well mostly I) thought that ALL_WORKERS would also include coordinator when it is added as a worker. It turns out that it was FILTERING OUT the coordinator even if it is added as a worker to the cluster.
So to have some context here, in repartitions, for each jobId we create
(at least we were supposed to) a schema in each worker node in the cluster. Then we partition each shard table into some intermediate files, which is called the PARTITION step. So after this partition step each node has some intermediate files having tuples in those nodes. Then we fetch the partition files to necessary worker nodes, which is called the FETCH step. Then from the files we create intermediate tables in the temporarily created schemas, which is called a MERGE step. Then after evaluating the result, we remove the temporary schemas(one for each job ID in each node) and files.
If node 1 has file1, and node 2 has file2 after PARTITION step, it is
enough to either move file1 from node1 to node2 or vice versa. So we
prune one of them.
In the MERGE step, if the schema for a given jobID doesn't exist, the
node tries to use the `public` schema if it is a superuser, which is
actually added for testing in the past.
So when we were not sending schema creation comands for each job ID to
the coordinator(because we were using ALL_WORKERS flag, and it doesn't
include the coordinator), we would basically not have any schemas for
repartitions in the coordinator. The PARTITION step would be executed on
the coordinator (because the tasks are generated in the planner part)
and it wouldn't give us any error because it doesn't have anything to do
with the temporary schemas(that we didn't create). But later two things
would happen:
- If by chance the fetch is pruned on the coordinator side, we the other
nodes would fetch the partitioned files from the coordinator and execute
the query as expected, because it has all the information.
- If the fetch tasks are not pruned in the coordinator, in the MERGE
step, the coordinator would either error out saying that the necessary
schema doesn't exist, or it would try to create the temporary tables
under public schema ( if it is a superuser). But then if we had the same
task ID with different jobID it would fail saying that the table already
exists, which is an error we were getting.
In the first case, the query would work okay, but it would still not do
the cleanup, hence we would leave the partitioned files from the
PARTITION step there. Hence ensure_no_intermediate_data_leak would fail.
To make things more explicit and prevent such bugs in the future,
ALL_WORKERS is named as ALL_NON_COORD_WORKERS. And a new flag to return
all the active nodes is added as ALL_DATA_NODES. For repartition case,
we don't use the only-reference table nodes but this version makes the
code simpler and there shouldn't be any significant performance issue
with that.
DESCRIPTION: Force aliases in deparsing for queries with anonymous column references
Fixes: #3985
The root cause has todo with discrepancies in the query tree we create. I think in the future we should spend some time on categorising all changes we made to ruleutils and see if we can change the data structure `query` we pass to the deparser to have an actual valid postgres query for the deparser to render.
For now the fix is to keep track, besides changing the names of the entries in the target list, also if we have a reference to an anonymous columns. If there are anonymous columns we set the `printaliases` flag to true which forces the deparser to add the aliases.
Static analysis found an issue where we could dereference `NULL`, because
`CreateDummyPlacement` could return `NULL` when there were no workers. This
PR changes it so that it never returns `NULL`, which was intended by
@marcocitus when doing this change: https://github.com/citusdata/citus/pull/3887/files#r438136433
While adding tests for citus on a single node I also added some more basic
tests and it turns out we error out on repartition joins. This has been
present since `shouldhaveshards` was introduced and is not trivial to fix.
So I created a separate issue for this: https://github.com/citusdata/citus/issues/3996
I recently forgot to add tests to a schedule in two of my PRs. One of
these was caught by review, but the other one was not. This adds a
script to causes CI to ensure that each test in the repo is included in
at least one schedule.
Three tests were found that were currently not part of a schedule. This PR
adds those three tests to a schedule as well and it also fixes some small
issues with these tests.
We keep accumulating more and more scripts to flag issues in CI. This is
good, but we are currently missing consistent documentation for them.
This commit moves all these scripts to the `ci` directory and adds some
documentation for all of them in the README. It also makes sure that the
last line of output of a failed script points to this documentation.
It was possible to get an assertion error, if a DML command was
cancelled that opened a connection and then "ROLLBACK TO SAVEPOINT" was
used to continue the transaction. The reason for this was that canceling
the transaction might leave the `claimedExclusively` flag on for (some
of) it's connections.
This caused an assertion failure because `CanUseExistingConnection`
would return false and a new connection would be opened, and then there
would be two connections doing DML for the same placement. Which is
disallowed. That this situation caused an assertion failure instead of
an error, means that without asserts this could possibly result in some
visibility bugs, similar to the ones described
https://github.com/citusdata/citus/issues/3867
This is so we don't need to calculate it twice in
insert_select_executor.c and multi_explain.c, which can
cause discrepancy if an update in one of them is not
reflected in the other site.
Ahmet Gedemenli
naisila
Onur Tirtir
Marco Slot
jeff-davis
Hadi Moshayedi
Marco Slot
SaitTalhaNisanci
Nils Dijk
Onder Kalaci
Hadi Moshayedi
Jeff Davis
Halil Ozan Akgül
Önder Kalacı
Hanefi Önaldı
Jelte Fennema
Philip Dubé
nukoyluoglu
Benjamin Satzger