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`
Do not obtain AccessShareLock before acquiring the distributed locks.
Acquiring an AccessShareLock ensures that the relations which we are trying to get a distributed lock on will not be dropped in the time between when the LOCK command is issued and the LOCK commands are send to the worker. However, this also leads to distributed deadlocks in such scenarios:
```sql
-- for dist lock acquiring order coor, w1, w2
-- on w2
LOCK t1 IN ACCESS EXLUSIVE MODE;
-- acquire AccessShareLock locally on t1 to ensure it is not dropped while we get ready to distribute the lock
-- concurrently on w1
LOCK t1 IN ACCESS EXLUSIVE MODE;
-- acquire AccessShareLock locally on t1 to ensure it is not dropped while we get ready to distribute the lock
-- acquire dist lock on coor, w1, gets blocked on local AccessShareLock on w2
-- on w2 continuation of the execution above
-- starts to acquire dist locks and gets blocked on the coor by the lock acquired by w1
-- distributed deadlock
```
We opt for avoiding such deadlocks with the cost of the possibility of running into errors when the relations on which we are trying to acquire locks on get dropped.
It is often useful to be able to sync the metadata in parallel
across nodes.
Also citus_finalize_upgrade_to_citus11() uses
start_metadata_sync_to_primary_nodes() after this commit.
Note that this commit does not parallelize all pieces of node
activation or metadata syncing. Instead, it tries to parallelize
potenially large parts of metadata, which is the objects and
distributed tables (in general Citus tables).
In the future, it would be nice to sync the reference tables
in parallel across nodes.
Create ~720 distributed tables / ~23450 shards
```SQL
-- declaratively partitioned table
CREATE TABLE github_events_looooooooooooooong_name (
event_id bigint,
event_type text,
event_public boolean,
repo_id bigint,
payload jsonb,
repo jsonb,
actor jsonb,
org jsonb,
created_at timestamp
) PARTITION BY RANGE (created_at);
SELECT create_time_partitions(
table_name := 'github_events_looooooooooooooong_name',
partition_interval := '1 day',
end_at := now() + '24 months'
);
CREATE INDEX ON github_events_looooooooooooooong_name USING btree (event_id, event_type, event_public, repo_id);
SELECT create_distributed_table('github_events_looooooooooooooong_name', 'repo_id');
SET client_min_messages TO ERROR;
```
across 1 node: almost same as expected
```SQL
SELECT start_metadata_sync_to_primary_nodes();
Time: 15664.418 ms (00:15.664)
select start_metadata_sync_to_node(nodename,nodeport) from pg_dist_node;
Time: 14284.069 ms (00:14.284)
```
across 7 nodes: ~3.5x improvement
```SQL
SELECT start_metadata_sync_to_primary_nodes();
┌──────────────────────────────────────┐
│ start_metadata_sync_to_primary_nodes │
├──────────────────────────────────────┤
│ t │
└──────────────────────────────────────┘
(1 row)
Time: 25711.192 ms (00:25.711)
-- across 7 nodes
select start_metadata_sync_to_node(nodename,nodeport) from pg_dist_node;
Time: 82126.075 ms (01:22.126)
```
Breaking down #5899 into smaller PR-s
This particular PR changes the way TRUNCATE acquires distributed locks on the relations it is truncating to use the LOCK command instead of lock_relation_if_exists. This has the benefit of using pg's recursive locking logic it implements for the LOCK command instead of us having to resolve relation dependencies and lock them explicitly. While this does not directly affect truncate, it will allow us to generalize this locking logic to then log different relations where the pg recursive locking will become useful (e.g. locking views).
This implementation is a bit more complex that it needs to be due to pg not supporting locking foreign tables. We can however, still lock foreign tables with lock_relation_if_exists. So for a command:
TRUNCATE dist_table_1, dist_table_2, foreign_table_1, foreign_table_2, dist_table_3;
We generate and send the following command to all the workers in metadata:
```sql
SEL citus.enable_ddl_propagation TO FALSE;
LOCK dist_table_1, dist_table_2 IN ACCESS EXCLUSIVE MODE;
SELECT lock_relation_if_exists('foreign_table_1', 'ACCESS EXCLUSIVE');
SELECT lock_relation_if_exists('foreign_table_2', 'ACCESS EXCLUSIVE');
LOCK dist_table_3 IN ACCESS EXCLUSIVE MODE;
SEL citus.enable_ddl_propagation TO TRUE;
```
Note that we need to alternate between the lock command and lock_table_if_exists in order to preserve the TRUNCATE order of relations.
When pg supports locking foreign tables, we will be able to massive simplify this logic and send a single LOCK command.
We've had custom versions of Postgres its `foreach` macro which with a
hidden ListCell for quite some time now. People like these custom
macros, because they are easier to use and require less boilerplate.
This adds similar custom versions of Postgres its `forboth` macro. Now
you don't need ListCells anymore when looping over two lists at the same
time.
If a worker node is being added, a command is sent to get the server_id of the worker from the pg_dist_node_metadata table. If the worker's id is the same as the node executing the code, we will know the node is trying to add itself. If the node tries to add itself without specifying `groupid:=0` the operation will result in an error.
With this commit we've started to propagate sequences and shell
tables within the object dependency resolution. So, ensuring any
dependencies for any object will consider shell tables and sequences
as well. Separate logics for both shell tables and sequences have
been removed.
Since both shell tables and sequences logic were implemented as a
part of the metadata handling before that logic, we were propagating
them while syncing table metadata. With this commit we've divided
metadata (which means anything except shards thereafter) syncing
logic into multiple parts and implemented it either as a part of
ActivateNode. You can check the functions called in ActivateNode
to check definition of different metadata.
Definitions of start_metadata_sync_to_node and citus_activate_node
have also been updated. citus_activate_node will basically create
an active node with all metadata and reference table shards.
start_metadata_sync_to_node will be same with citus_activate_node
except replicating reference tables. stop_metadata_sync_to_node
will remove all the metadata. All of those UDFs need to be called
by superuser.
* Require superuser while activating a node
With this change, we require ActiveNode() (hence citus_add_node(),
citus_activate_node()) explicitly require for a superuser.
Before this commit, these functions were designed to work with
non-superuser roles with the relevent GRANTs given.
However, that is not a widely used way for calling the functions
above.
Due to possibility of non-super user calling the UDFs, they were
designed in a way that some commands were using some additional
short-lived superuser connections. That is:
(a) breaking transactional behavior (e.g., ROLLBACK
wouldn't fully rollback the whole transaction)
(b) Making it very complicated to reason about which
parts of the node activation goes over which connections,
and becoming vulnerable to deadlocks / visibility issues.
We prefer the background daemon to only sync node metadata. That's
why we move placement metadata changes from disable node to
activate node. With that, we can make sure that disable node
only changes node metadata, whereas activate node syncs all
the metadata changes. In essence, we already expect all
nodes to be up when a node is activated. So, this does not change
the behavior much.
With this commit, fix_partition_shard_index_names()
works significantly faster.
For example,
32 shards, 365 partitions, 5 indexes drop from ~120 seconds to ~44 seconds
32 shards, 1095 partitions, 5 indexes drop from ~600 seconds to ~265 seconds
`queryStringList` can be really long, because it may contain #partitions * #indexes entries.
Before this change, we were actually going through the executor where each command
in the query string triggers 1 round trip per entry in queryStringList.
The aim of this commit is to avoid the round-trips by creating a single query string.
I first simply tried sending `q1;q2;..;qn` . However, the executor is designed to
handle `q1;q2;..;qn` type of query executions via the infrastructure mentioned
above (e.g., by tracking the query indexes in the list and doing 1 statement
per round trip).
One another option could have been to change the executor such that only track
the query index when `queryStringList` is provided not with queryString
including multiple `;`s . That is (a) more work (b) could cause weird edge
cases with failure handling (c) felt like coding a special case in to the executor
As of master branch, Citus does all the modifications to replicated tables
(e.g., reference tables and distributed tables with replication factor > 1),
via 2PC and avoids any shardstate=3. As a side-effect of those changes,
handling node failures for replicated tables change.
With this PR, when one (or multiple) node failures happen, the users would
see query errors on modifications. If the problem is intermitant, that's OK,
once the node failure(s) recover by themselves, the modification queries would
succeed. If the node failure(s) are permenant, the users should call
`SELECT citus_disable_node(...)` to disable the node. As soon as the node is
disabled, modification would start to succeed. However, now the old node gets
behind. It means that, when the node is up again, the placements should be
re-created on the node. First, use `SELECT citus_activate_node()`. Then, use
`SELECT replicate_table_shards(...)` to replicate the missing placements on
the re-activated node.
Before this commit, we acquire the metadata locks on the reference
tables while removing/disabling a node on all the MX nodes.
Although it has some marginal benefits, such as a concurrent
modification during remove/disable node blocks, instead of erroring
out, the drawbacks seems worse. Both citus_remove_node and citus_disable_node
are not tolerant to multiple node failures.
With this commit, we relax the locks. The implication is that while
a node is removed/disabled, users might see query errors. On the
other hand, this change becomes removing/disabling nodes more
tolerant to multiple node failures.
- [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
Before this commit, we required the user to be owner of the shard/table
in order to call lock_shard_resources.
However, that is too restrictive. We can have users with GRANTS
to the table who are not owners of the tables/shards.
With this commit, we allow such patterns.
In the past, we allowed users to manually switch to 1PC
(e.g., one phase commit). However, with this commit, we
don't. All multi-shard modifications are done via 2PC.
Add/fix tests
Fix creating partitions
Add test for mx - partition creating case
Enable cascading to partitioned tables
Fix mx partition adding test
Fix cascading through fkeys
Style
Disable converting with non-inherited fkeys
Fix detach bug
Early return in case of cascade & Add tests
Style
Fix undistribute_table bug & Fix test outputs
Remove RemovePartitionRelationIds
Test with undistribute_table
Add test for mx+convert+undistribute
Remove redundant usage of CreatePartitionedCitusLocalTable
Add some comments
Introduce bulk functions for generating attach/detach partition commands
Fix: Convert partitioned tables after adding fkey
Change the error message for partitions
Introduce function ErrorIfPartitionTableAddedToMetadata
Polish attach/detach command generation functions
Use time_partitions for testing
Move mx tests to citus_local_tables_mx
Add new partitioned table to cascade test
Add test with time series management UDFs
Fix test output
Fix: Assertion fail on relation access tracking
Style
Refactor creating partitioned citus local tables
Remove CreatePartitionedCitusLocalTable
Style
Error out if converting multi-level table
Revert some old tests
Error out adding partitioned partition
Polish
Polish/address
Fix create table partition of case
Use CascadeOperationForRelationIdList if no cascade needed
Fix create partition bug
Revert / Add new tests to mx
Style
Fix dropping fkey bug
Add test with IF NOT EXISTS
Convert to CLT when doing ATTACH PARTITION
Add comments
Add more tests with time series management
Edit the error message for converting the child
Use OR instead of AND in ErrorIfUnsupportedAlterTableStmt
Edit/improve tests
Disable ddl prop when dropping default column definitions
Disable/enable ddl prop just before/after the command
Add comment
Add sequence test
Add trigger test
Remove NeedCascadeViaForeignKeys
Add one more insert to sequence test
Add comment
Style
Fix test output shard ids
Update comments
Disable creating fkey on partitions
Move partition check to CreateCitusLocalTable
Add comment
Add check for attachingmulti-level partition
Add test for pg_constraint
Check pg_dist_partition in tests
Add test inserting on the worker
* Add udf to include shardId in broken partition shard index names
* Address reviews: rename index such that operations can be done on it
* More comprehensive index tests
* Final touches and formatting
Postgres expects to set the HASH_STRINGS explicitly in case of the
default behaivor for string hash function.
Postgres Commit
b3817f5f774663d55931dd4fab9c5a94a15ae7ab
get_partition_parent and RelationGetPartitionDesc functions now have new parameters to also include detached partitions
Thess new macros give us the ability to use these new parameter for PG14 and they don't give the parameters for previous versions
Existing parameters are set to not accept detached partitions
Relevant PG commit:
71f4c8c6f74ba021e55d35b1128d22fb8c6e1629
New macros: FuncnameGetCandidates_compat and expand_function_arguments_compat
The functions (the ones without _compat) now have a new bool include_out_arguments parameter
These new macros give us the ability to use this new parameter for PG14 and it doesn't give the parameter for previous versions
Existing include_out_arguments parameters are set to 'false' to keep current behavior
Relevant PG commit:
e56bce5d43789cce95d099554ae9593ada92b3b7
As we use the current user to sync the metadata to the nodes
with #5105 (and many other PRs), there is no reason that
prevents us to use the coordinated transaction for metadata syncing.
This commit also renames few functions to reflect their actual
implementation.
Before this commit, creating a partition after a DROP column
on the parent (position before dist. key) was leading to
partition to have the wrong distribution column.
update_distributed_table_colocation can be called by the relation
owner, and internally it updates pg_dist_partition. With this
commit, update_distributed_table_colocation uses an internal
UDF to access pg_dist_partition.
As a result, this operation can now be done by regular users
on MX.
Before this commit, we always synced the metadata with superuser.
However, that creates various edge cases such as visibility errors
or self distributed deadlocks or complicates user access checks.
Instead, with this commit, we use the current user to sync the metadata.
Note that, `start_metadata_sync_to_node` still requires super user
because accessing certain metadata (like pg_dist_node) always require
superuser (e.g., the current user should be a superuser).
However, metadata syncing operations regarding the distributed
tables can now be done with regular users, as long as the user
is the owner of the table. A table owner can still insert non-sense
metadata, however it'd only affect its own table. So, we cannot do
anything about that.
Ignore orphaned shards in more places
Only use active shard placements in RouterInsertTaskList
Use IncludingOrphanedPlacements in some more places
Fix comment
Add tests
Originally ReplicateShardToNode was meant for
`upgrade_to_reference_table`, which required handling of existing inactive
placements. These days `upgrade_to_reference_table` is deprecated and
cannot be used anymore. Now that we have SHARD_STATE_TO_DELETE too, this
left over code seemed error prone. So this removes support for
activating inactive reference table placemements, since these should not
be possible. If it finds a non active reference table placement anyway
it now errors out.
This also removes a few outdated comments related to `upgrade_to_refeference_table`.
InvalidateForeignKeyGraph sends an invalidation via shared memory to all
backends, including the current one.
However, we might not call AcceptInvalidationMessages before reading
from the cache below. It would be better to also add a call to
AcceptInvalidationMessages in IsForeignConstraintRelationshipGraphValid.
Previously this was usually done after argument parsing. This can cause
SEGFAULTs if the number or type of arguments changes in a new version.
By checking that Citus version is correct before doing any argument
parsing we protect against these types of issues. Issues like this have
occurred in pg_auto_failover, so it's not just a theoretical issue.
The main reason why these calls were not at the top of functions is
really just historical. It was because in the past we didn't allow
statements before declarations. Thus having this check before the
argument parsing would have only been possible if we first declared all
variables.
In addition to moving existing CheckCitusVersion calls it also adds
these calls to rebalancer related functions (they were missing there).
It was possible to block maintenance daemon by taking an SHARE ROW
EXCLUSIVE lock on pg_dist_placement. Until the lock is released
maintenance daemon would be blocked.
We should not block the maintenance daemon under any case hence now we
try to get the pg_dist_placement lock without waiting, if we cannot get
it then we don't try to drop the old placements.
DESCRIPTION: introduce `citus.local_hostname` GUC for connections to the current node
Citus once in a while needs to connect to itself for some systems operations. This used to be hardcoded to `localhost`. The hardcoded hostname causes some issues, for example in environments where `sslmode=verify-full` is required. It is not always desirable or even feasible to get `localhost` as an alt name on the certificate.
By introducing a GUC to use when connecting to the current instance the user has more control what network path is used and what hostname is required to be present in the server certificate.
* Fix problews with concurrent calls of DropMarkedShards
When trying to enable `citus.defer_drop_after_shard_move` by default it
turned out that DropMarkedShards was not safe to call concurrently.
This could especially cause big problems when also moving shards at the
same time. During tests it was possible to trigger a state where a shard
that was moved would not be available on any of the nodes anymore after
the move.
Currently DropMarkedShards is only called in production by the
maintenaince deamon. Since this is only a single process triggering such
a race is currently impossible in production settings. In future changes
we will want to call DropMarkedShards from other places too though.
* Add some isolation tests
Co-authored-by: Jelte Fennema <github-tech@jeltef.nl>
This commit adds support for long partition names for distributed tables:
- ALTER TABLE dist_table ATTACH PARTITION ..
- CREATE TABLE .. PARTITION OF dist_table ..
Note: create_distributed_table UDF does not support long table and
partition names, and is not covered in this commit
* Reimplement citus_update_table_statistics
* Update stats for the given table not colocation group
* Add tests for reimplemented citus_update_table_statistics
* Use coordinated transaction, merge with citus_shard_sizes functions
* Update the old master_update_table_statistics as well
When we use PROCESS_UTILITY_TOPLEVEL it causes some problems when
combined with other extensions such as pg_audit. With this commit we use
PROCESS_UTILITY_QUERY in the codebase to fix those problems.
* Fix partition column index issue
We send column names to worker_hash/range_partition_table methods, and
in these methods we check the column name index from tuple descriptor.
Then this index is used to decide the bucket that the current row will
be sent for the repartition.
This becomes a problem when there are the same column names in the
tupleDescriptor. Then we can choose the wrong index. Hence the
partitioned data will be put to wrong workers. Then the result could
miss some data because workers might contain different range of data.
An example:
TupleDescriptor contains "trip_id", "car_id", "car_id" for one table.
It contains only "car_id" for the other table. And assuming that the
tables will be partitioned by car_id, it is not certain what should be
used for deciding the bucket number for the first table. Assuming value
2 goes to bucket 2 and value 3 goes to bucket 3, it is not certain which
bucket "1 2 3" (trip_id, car_id, car_id) row will go to.
As a solution we send the index of partition column in targetList
instead of the column name.
The old API is kept so that if workers upgrade work, it still works
(though it will have the same bug)
* Use the same method so that backporting is easier
Currently we choose an arbitrary colocation id from all the matches for
a colocation id. This could mean that 2 distributed tables, which have
the same scheme could go into different colocation groups. This fix
makes sure that the same match will go to the same colocation group.
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.
With this commit, we remove visited flags from ForeignConstraintRelationshipNode
struct since keeping local state in global object is both dangerous and
meaningless.
Also to improve readability, this commit also converts needless recursion to
iterative DFS to avoid passing local hash-map as another parameter to
GetConnectedListHelper function.
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
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.
Refactor internals on how Citus creates the SQL commands it sends to recreate shards.
Before Citus collected solely ddl commands as `char *`'s to recreate a table. If they were used to create a shard they were wrapped with `worker_apply_shard_ddl_command` and send to the workers. On the workers the UDF wrapping the ddl command would rewrite the parsetree to replace tables names with their shard name equivalent.
This worked well, but poses an issue when adding columnar. Due to limitations in Postgres on creating custom options on table access methods we need to fall back on a UDF to set columnar specific options. Now, to recreate the table, we can not longer rely on having solely DDL statements to recreate a table.
A prototype was made to run this UDF wrapped in `worker_apply_shard_ddl_command`. This became pretty messy, hard to understand and subsequently hard to maintain.
This PR proposes a refactor of the internal representation of table ddl commands into a `TableDDLCommand` structure. The current implementation only supports a `char *` as its contents. Based on the use of the DDL statement (eg. creating the table -mx- or creating a shard) one of two different functions can be called to get the statement to send to the worker:
- `GetTableDDLCommand(TableDDLCommand *command)`: This function returns that ddl command to create the table. In this implementation it will just return the `char *`. This has the same functionality as getting the old list and not wrapping it.
- `GetShardedTableDDLCommand(TableDDLCommand *command, uint64 shardId, char *schemaName)`: This function returns the ddl command wrapped in `worker_apply_shard_ddl_command` with the `shardId` as an argument. Due to backwards compatibility it also accepts a. `schemaName`. The exact purpose is not directly clear. Ideally new implementations would work with fully qualified statements and ignore the `schemaName`.
A future implementation could accept 2.function pointers and a `void *` for context to let the two pointers work on. This gives greater flexibility in controlling what commands get send in which situations. Also, in a future, we could implement the intermediate step of creating the `parsetree` datastructure of statements based on the contents in the catalog with a corresponding deparser. For sharded queries a mutator could be ran over the parsetree to rewrite the tablenames to the names with the shard identifier. This will completely omit the requirement for `worker_apply_shard_ddl_command`.
RemoveDuplicateJoinRestrictions() function was introduced with the aim of decrasing the overall planning times by eliminating the duplicate JOIN restriction entries (#1989). However, it turns out that the function itself is so CPU intensive with a very high algorithmic complexity, it hurts a lot more than it helps. The function is a clear example of premature optimization.
The table below shows the difference clearly:
"distributed query planning
time master" RemoveDuplicateJoinRestrictions() execution time on master "Remove the function RemoveDuplicateJoinRestrictions()
this PR"
5 table INNER JOIN 9 msec 2msec 7 msec
10 table INNER JOIN 227 msec 194 msec 29 msec
20 table INNER JOIN 1 sec 235 msec 1 sec 139 msec 90 msecs
50 table INNER JOIN 24 seconds 21 seconds 1.5 seconds
100 table INNER JOIN 2 minutes 16 secods 1 minute 53 seconds 23 seconds
250 table INNER JOIN Bottleneck on JoinClauseList 18 minutes 52 seconds Bottleneck on JoinClauseList
5 table INNER JOIN in subquery 9 msec 0 msec 6 msec
10 table INNER JOIN subquery 33 msec 10 msec 32 msec
20 table INNER JOIN subquery 132 msec 67 msec 123 msec
50 table INNER JOIN subquery 1.2 seconds 900 msec 500 msec
100 table INNER JOIN subquery 6 seconds 5 seconds 2 seconds
250 table INNER JOIN subquery 54 seconds 37 seconds 20 seconds
5 table LEFT JOIN 5 msec 0 msec 5 msec
10 table LEFT JOIN 11 msec 0 msec 13 msec
20 table LEFT JOIN 26 msec 2 msec 30 msec
50 table LEFT JOIN 150 msec 15 msec 193 msec
100 table LEFT JOIN 757 msec 71 msec 722 msec
250 table LEFT JOIN 8 seconds 600 msec 8 seconds
5 JOINs among 2 table JOINs 37 msec 11 msec 25 msec
10 JOINs among 2 table JOINs 536 msec 306 msec 352 msec
20 JOINs among 2 table JOINs 794 msec 181 msec 640 msec
50 JOINs among 2 table JOINs 25 seconds 2 seconds 22 seconds
100 JOINs among 2 table JOINs Bottleneck on JoinClauseList 9 seconds Bottleneck on JoinClauseList
150 JOINs among 2 table JOINs Bottleneck on JoinClauseList 46 seconds Bottleneck on JoinClauseList
On top of the performance penalty, the function had a critical bug #4255, and with #4254 we hit one more important bug. It should be fixed by adding the followig check to the ContextCoversJoinRestriction():
```
static bool
JoinRelIdsSame(JoinRestriction *leftRestriction, JoinRestriction *rightRestriction)
{
Relids leftInnerRelIds = leftRestriction->innerrel->relids;
Relids rightInnerRelIds = rightRestriction->innerrel->relids;
if (!bms_equal(leftInnerRelIds, rightInnerRelIds))
{
return false;
}
Relids leftOuterRelIds = leftRestriction->outerrel->relids;
Relids rightOuterRelIds = rightRestriction->outerrel->relids;
if (!bms_equal(leftOuterRelIds, rightOuterRelIds))
{
return false;
}
return true;
}
```
However, adding this eliminates all the benefits tha RemoveDuplicateJoinRestrictions() brings.
I've used the commands here to generate the JOINs mentioned in the PR: https://gist.github.com/onderkalaci/fe8654f9df5916c7af4c7c5eb892561e#file-gistfile1-txt
Inner and outer JOINs behave roughly the same, to simplify the table only added INNER joins.
* 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
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.
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.
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
* Not take ShareUpdateExlusiveLock on pg_dist_transaction
We were taking ShareUpdateExlusiveLock on pg_dist_transaction during
recovery to prevent multiple recoveries happening concurrenly. VACUUM(
not FULL) also takes ShareUpdateExclusiveLock, and they can conflict. It
seems that VACUUM will skip the table if there is a conflicting lock
already taken unless it is doing the vacuum to prevent id wraparound, in
which case there can be a deadlock. I guess the deadlock happens if:
- VACUUM takes a lock on pg_dist_transaction and is done for id
wraparound problem
- The transaction in the maintenance tries to take a lock but
cannot as that conflicts with the lock acquired by VACUUM
- The transaction in the maintenance daemon has a very old xid hence
VACUUM cannot proceed.
If we take a row exclusive lock in transaction recovery then it wouldn't
conflict with VACUUM hence it could proceed so the deadlock would be
resolved. To prevent concurrent transaction recoveries happening, an
advisory lock is taken with ShareUpdateExlusiveLock as before.
* Use CITUS_OPERATIONS tag
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.
Introduce table entry utility functions
Citus table cache entry utilities are introduced so that we can easily
extend existing functionality with minimum changes, specifically changes
to these functions. For example IsNonDistributedTableCacheEntry can be
extended for citus local tables without the need to scan the whole
codebase and update each relevant part.
* Introduce utility functions to find the type of tables
A table type can be a reference table, a hash/range/append distributed
table. Utility methods are created so that we don't have to worry about
how a table is considered as a reference table etc. This also makes it
easy to extend the table types.
* Add IsCitusTableType utilities
* Rename IsCacheEntryCitusTableType -> IsCitusTableTypeCacheEntry
* Change citus table types in some checks
FindNodeCheck is not clear about what the function is doing. They are
renamed to FindNodeMatchingCheckFunctionXXX. Also for choosing elements in these
functions, CheckNodeFunc type is introduced.
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
Commit on postgres side:
05d8449e73694585b59f8b03aaa087f04cc4679a
Command on postgres side:
git log --all --grep="hashutils"
include common/hashfn.h for pg >= 13
tag_hash was moved from hsearch.h to hashutils.h then to hashfn.h
Commits on Postgres side:
9341c783cc42ffae5860c86bdc713bd47d734ffd
With PG13 heap_* (heap_open, heap_close etc) are replaced with table_*
(table_open, table_close etc).
It is better to use the new table access methods in the codebase and
define the macros for the previous versions as we can easily remove the
macro without having to change the codebase when we drop the support for
the old version.
Commits that introduced this change on Postgres:
f25968c49697db673f6cd2a07b3f7626779f1827
e0c4ec07284db817e1f8d9adfb3fffc952252db0
4b21acf522d751ba5b6679df391d5121b6c4a35f
Command to see relevant commits on Postgres side:
git log --all --grep="heap_open"
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
* 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
* 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
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.
In #3901 the "Data received from worker(s)" sections were added to EXPLAIN
ANALYZE. After merging @pykello posted some review comments. This addresses
those comments as well as fixing a other issues that I found while addressing
them. The things this does:
1. Fix `EXPLAIN ANALYZE EXECUTE p1` to not increase received data on every
execution
2. Fix `EXPLAIN ANALYZE EXECUTE p1(1)` to not return 0 bytes as received data
allways.
3. Move `EXPLAIN ANALYZE` specific logic to `multi_explain.c` from
`adaptive_executor.c`
4. Change naming of new explain sections to `Tuple data received from node(s)`.
Firstly because a task can reference the coordinator too, so "worker(s)" was
incorrect. Secondly to indicate that this is tuple data and not all network
traffic that was performed.
5. Rename `totalReceivedData` in our codebase to `totalReceivedTupleData` to
make it clearer that it's a tuple data counter, not all network traffic.
6. Actually add `binary_protocol` test to `multi_schedule` (woops)
7. Fix a randomly failing test in `local_shard_execution.sql`.
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
Sadly this does not actually work yet for binary protocol data, because
when doing EXPLAIN ANALYZE we send two commands at the same time. This
means we cannot use `SendRemoteCommandParams`, and thus cannot use the
binary protocol. This can still be useful though when using the text
protocol, to find out that a lot of data is being sent.
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 wrap worker tasks in worker_save_query_explain_analyze() so we can fetch
their explain output later by a call worker_last_saved_explain_analyze().
Fixes#3519Fixes#2347Fixes#2613Fixes#621
Implements a new `TupleDestination` interface to allow custom tuple processing per task.
This can be specially useful if a task contains multiple queries. An example of this EXPLAIN
ANALYZE, where it needs to add some UDF calls to the query to fetch the explain output
from worker after fetching the actual query results.
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
* Not append empty task in ExtractLocalAndRemoteTasks
ExtractLocalAndRemoteTasks extracts the local and remote tasks. If we do
not have a local task the localTaskPlacementList will be NIL, in this
case we should not append anything to local tasks. Previously we would
first check if a task contains a single placement or not, now we first
check if there is any local task before doing anything.
* fix copy of node task
Task node has task query, which might contain a list of strings in its
fields. We were using postgres copyObject for these lists. Postgres
assumes that each element of list will be a node type. If it is not a
node type it will error.
As a solution to that, a new macro is introduced to copy a list of
strings.
This copies over fixes from reference counting branch,
all CitusTableCacheEntry data may be freed when a GetCitusTableCacheEntry call occurs for its relationId
This fix is not complete, but reference counting is being deferred until 9.4
CopyShardInterval: remove dest parameter, always return newly allocated object
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
aykutbozkurt
Jelte Fennema
Gledis Zeneli
Onder Kalaci
gledis69
Teja Mupparti
Jeff Davis
Marco Slot
Ahmet Gedemenli
Burak Velioglu
Önder Kalacı
naisila
Nils Dijk
Philip Dubé
Naisila Puka
Halil Ozan Akgul
Sait Talha Nisanci
Hanefi Onaldi
Onur Tirtir
Hadi Moshayedi
Benjamin Satzger
Philip Dubé