We need to break sequence dependency for a table while creating the
table during non-transactional metadata sync to ensure idempotency of
the creation of the table.
**Problem:**
When we send `SELECT
pg_catalog.worker_drop_sequence_dependency(logicalrelid::regclass::text)
FROM pg_dist_partition` to workers during the non-transactional sync,
table might not be in `pg_dist_partition` at worker, and sequence
dependency is not broken at the worker.
**Solution:**
We break sequence dependency via `SELECT
pg_catalog.worker_drop_sequence_dependency(logicalrelid::regclass::text)`
for each table while creating it at the workers. It is safe to send
since the udf is a no-op when there is no sequence dependency.
DESCRIPTION: Fixes a bug related to sequence idempotency at
non-transactional sync.
Fixes https://github.com/citusdata/citus/issues/6888.
(cherry picked from commit 8cb69cfd13)
This PR updates the tenant stats implementation to set partitionKeyValue
and colocationId in ExecuteLocalTaskListExtended, in addition to
LocallyExecuteTaskPlan. This ensures that tenant stats can be properly
gathered regardless of the code path taken. The changes were initially
made while testing stored procedure calls for tenant stats.
(cherry picked from commit 8782ea1582)
Fixed 3 flaky tests in failure tests which caused flakiness in other
tests due to changed node and group sequence ids during node
addition-removal.
(cherry picked from commit 3286ec59e9)
This PR adds CPU usage to `citus_stat_tenants` monitor.
CPU usage is tracked in periods, similar to query counts.
(cherry picked from commit 9ba70696f7)
Fixes the bug that causes updating the citus_stat_tenants periods
incorrectly.
`TimestampDifferenceExceeds` expects the difference in milliseconds but
it was microseconds, this is fixed.
`tenantStats->lastQueryTime` was updated during monitoring too, now it's
updated only when there are tenant queries.
(cherry picked from commit 8b50e95dc8)
DESCRIPTION: Adds control for background task executors involving a node
### Background and motivation
Nonblocking concurrent task execution via background workers was
introduced in [#6459](https://github.com/citusdata/citus/pull/6459), and
concurrent shard moves in the background rebalancer were introduced in
[#6756](https://github.com/citusdata/citus/pull/6756) - with a hard
dependency that limits to 1 shard move per node. As we know, a shard
move consists of a shard moving from a source node to a target node. The
hard dependency was used because the background task runner didn't have
an option to limit the parallel shard moves per node.
With the motivation of controlling the number of concurrent shard
moves that involve a particular node, either as source or target, this
PR introduces a general new GUC
citus.max_background_task_executors_per_node to be used in the
background task runner infrastructure. So, why do we even want to
control and limit the concurrency? Well, it's all about resource
availability: because the moves involve the same nodes, extra
parallelism won’t make the rebalance complete faster if some resource is
already maxed out (usually cpu or disk). Or, if the cluster is being
used in a production setting, the moves might compete for resources with
production queries much more than if they had been executed
sequentially.
### How does it work?
A new column named nodes_involved is added to the catalog table that
keeps track of the scheduled background tasks,
pg_dist_background_task. It is of type integer[] - to store a list
of node ids. It is NULL by default - the column will be filled by the
rebalancer, but we may not care about the nodes involved in other uses
of the background task runner.
Table "pg_catalog.pg_dist_background_task"
Column | Type
============================================
job_id | bigint
task_id | bigint
owner | regrole
pid | integer
status | citus_task_status
command | text
retry_count | integer
not_before | timestamp with time zone
message | text
+nodes_involved | integer[]
A hashtable named ParallelTasksPerNode keeps track of the number of
parallel running background tasks per node. An entry in the hashtable is
as follows:
ParallelTasksPerNodeEntry
{
node_id // The node is used as the hash table key
counter // Number of concurrent background tasks that involve node node_id
// The counter limit is citus.max_background_task_executors_per_node
}
When the background task runner assigns a runnable task to a new
executor, it increments the counter for each of the nodes involved with
that runnable task. The limit of each counter is
citus.max_background_task_executors_per_node. If the limit is reached
for any of the nodes involved, this runnable task is skipped. And then,
later, when the running task finishes, the background task runner
decrements the counter for each of the nodes involved with the done
task. The following functions take care of these increment-decrement
steps:
IncrementParallelTaskCountForNodesInvolved(task)
DecrementParallelTaskCountForNodesInvolved(task)
citus.max_background_task_executors_per_node can be changed in the
fly. In the background rebalancer, we simply give {source_node,
target_node} as the nodesInvolved input to the
ScheduleBackgroundTask function. The rest is taken care of by the
general background task runner infrastructure explained above. Check
background_task_queue_monitor.sql and
background_rebalance_parallel.sql tests for detailed examples.
#### Note
This PR also adds a hard node dependency if a node is first being used
as a source for a move, and then later as a target. The reason this
should be a hard dependency is that the first move might make space for
the second move. So, we could run out of disk space (or at least
overload the node) if we move the second shard to it before the first
one is moved away.
Fixes https://github.com/citusdata/citus/issues/6716
DESCRIPTION: PR description that will go into the change log, up to 78
characters
---------
Co-authored-by: Hanefi Onaldi <Hanefi.Onaldi@microsoft.com>
Fixes flakiness in multi_metadata_sync test
https://app.circleci.com/pipelines/github/citusdata/citus/31863/workflows/ea937480-a4cc-4646-815c-bb2634361d98/jobs/1074457
```diff
SELECT
logicalrelid, repmodel
FROM
pg_dist_partition
WHERE
logicalrelid = 'mx_test_schema_1.mx_table_1'::regclass
OR logicalrelid = 'mx_test_schema_2.mx_table_2'::regclass;
logicalrelid | repmodel
-----------------------------+----------
- mx_test_schema_1.mx_table_1 | s
mx_test_schema_2.mx_table_2 | s
+ mx_test_schema_1.mx_table_1 | s
(2 rows)
```
This is a simple issue of missing `ORDER BY` clauses. I went ahead and
added some other missing ones in the same file as well. Also, I replaced
existing `ORDER BY logicalrelid` with `ORDER BY logicalrelid::text`, in
order to compare names, not OIDs.
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>
Over the last few months run_test.py got more and more complex. This
refactors the code in `run_test.py` to be better understandable. Mostly
this splits up separate pieces of logic into separate functions.
In CI we would sometimes get this failure:
```diff
-- The original shard is marked for deferred drop with policy_type = 2.
-- The previous shard should be dropped at the beginning of the second split call
SELECT * from pg_dist_cleanup;
record_id | operation_id | object_type | object_name | node_group_id | policy_type
-----------+--------------+-------------+--------------------------------------------------------------------------+---------------+-------------
+ 60 | 778 | 3 | citus_shard_split_slot_18_21216_778 | 16 | 0
512 | 778 | 1 | citus_split_shard_by_split_points_deferred_schema.table_to_split_8981001 | 16 | 2
-(1 row)
+(2 rows)
```
Replication slots sometimes cannot be deleted right away. Which is hard
to resolve, but luckily we can filter these cleanup records out easily
by filtering by policy_type.
While debugging this issue I learnt that we did not use
`GetNextCleanupRecordId` in all places where we created cleanup
records. This caused test failures when running tests multiple times,
when they set `citus.next_cleanup_record_id`. I tried fixing that by
calling GetNextCleanupRecordId in all places but that caused many
other tests to fail due to deadlocks. So, instead this adresses
that issue by using `ALTER SEQUENCE ... RESTART` instead of
`citus.next_cleanup_record_id`. In a follow up PR we should
probably get rid of `citus.next_cleanup_record_id`, since it's
only used in one other file.
DESCRIPTION: Fix an issue that caused some queries with custom
aggregates to fail
While playing around with https://github.com/pgvector/pgvector I noticed
that the AVG query was broken. That's because we treat it as any other
AVG by breaking it down in SUM and COUNT, but there are no SUM/COUNT
functions in this case, but there is a perfectly usable combinefunc.
This PR changes our aggregate logic to prefer custom aggregates with a
combinefunc even if they have a common name.
Co-authored-by: Marco Slot <marco.slot@gmail.com>
For some tests such as upgrade tests and arbitrary config tests we set
up the citus cluster using Python. This setup is slightly different from
the perl based setup script (`multi_regress.pl`). Most importantly it
uses replication factor 1 by default.
This changes our run_test.py script to be able to run a schedule using
python instead of `multi_regress.pl`, for the tests that require it.
For now arbitrary config tests are still not runnable with
`run_test.py`, but this brings us one step closer to being able to do
that.
Fixes#6804
Having as little Perl as possible in our repo seems a worthy goal. Sadly
Postgres its Perl based TAP infrastructure was the only way in which we
could
run tests that were hard to do using only SQL commands. This change adds
infrastructure to run such "application style tests" using python and
converts all our existing Perl TAP tests to this new infrastructure.
Some of the helper functions that are added in this PR are currently
unused. Most of these will be used by the CDC PR that depends on this.
Some others are there because they were needed by the PgBouncer test
framework that this is based on, and the functions seemed useful enough
to citus testing to keep.
The main features of the test suite are:
1. Application style tests using a programming language that our
developers know how to write.
2. Caching of Citus clusters in-between tests using the ["fixture"
pattern][fixture] from `pytest` to achieve speedy tests. To make this
work in practice any changes made during a test are automatically
undone. Schemas, replication slots, subscriptions, publications are
dropped at the end of each test. And any changes made by `ALTER SYSTEM`
or manually editing of `pg_hba.conf` are undone too.
3. Automatic parallel execution of tests using the `-n auto` flag that's
added by `pytest-xdist`. This improved the speed of tests greatly with
the similar test framework I created for PgBouncer. Right now it doesn't
help much yet though, since this PR only adds two tests (one of which
takes ~10 times longer than the other).
Possible future improvements are:
1. Clean up even more things at the end of each test (e.g. users that
were created). These are fairly easy to add, but I have not done so yet
since they were not needed yet for this PR or the CDC PR. So I would not
be able to test the cleanup easily.
2. Support for query block detection similar to what we can now do using
isolation tests.
[fixture]: https://docs.pytest.org/en/6.2.x/fixture.html
Add new metadata sync methods which uses MemorySyncContext api so that during the sync we can
- free memory to prevent OOM,
- use either transactional or nontransactional modes according to the GUC .
This pull request proposes a change to the logic used for propagating
identity columns to worker nodes in citus. Instead of creating a
dependent sequence for each identity column and changing its default
value to `nextval(seq)/worker_nextval(seq)`, this update will pass the
identity columns as-is to the worker nodes.
Please note that there are a few limitations to this change.
1. Only bigint identity columns will be allowed in distributed tables to
ensure compatibility with the DDL from any node functionality. Our
current distributed sequence implementation only allows insert
statements from all nodes for bigint sequences.
2. `alter_distributed_table` and `undistribute_table` operations will
not be allowed for tables with identity columns. This is because we do
not have a proper way of keeping sequence states consistent across the
cluster.
DESCRIPTION: Prevents using identity columns on data types other than
`bigint` on distributed tables
DESCRIPTION: Prevents using `alter_distributed_table` and
`undistribute_table` UDFs when a table has identity columns
DESCRIPTION: Fixes a bug that prevents enforcing identity column
restrictions on worker nodes
Depends on #6740Fixes#6694
DESCRIPTION: This PR removes the task dependencies between shard moves
for which the shards belong to different colocation groups. This change
results in scheduling multiple tasks in the RUNNABLE state. Therefore it
is possible that the background task monitor can run them concurrently.
Previously, all the shard moves planned in a rebalance operation took
dependency on each other sequentially.
For instance, given the following table and shards
colocation group 1 colocation group 2
table1 table2 table3 table4 table 5
shard11 shard21 shard31 shard41 shard51
shard12 shard22 shard32 shard42 shard52
if the rebalancer planner returned the below set of moves
` {move(shard11), move(shard12), move(shard41), move(shard42)}`
background rebalancer scheduled them such that they depend on each other
sequentially.
```
{move(reftables) if there is any, none}
|
move( shard11)
|
move(shard12)
| {move(shard41)<--- move(shard12)} This is an artificial dependency
move(shard41)
|
move(shard42)
```
This results in artificial dependencies between otherwise independent
moves.
Considering that the shards in different colocation groups can be moved
concurrently, this PR changes the dependency relationship between the
moves as follows:
```
{move(reftables) if there is any, none} {move(reftables) if there is any, none}
| |
move(shard11) move(shard41)
| |
move(shard12) move(shard42)
```
---------
Co-authored-by: Jelte Fennema <jelte.fennema@microsoft.com>
Description:
Implementing CDC changes using Logical Replication to avoid
re-publishing events multiple times by setting up replication origin
session, which will add "DoNotReplicateId" to every WAL entry.
- shard splits
- shard moves
- create distributed table
- undistribute table
- alter distributed tables (for some cases)
- reference table operations
The citus decoder which will be decoding WAL events for CDC clients,
ignores any WAL entry with replication origin that is not zero.
It also maps the shard names to distributed table names.
Today we allow planning the queries that reference non-colocated tables
if the shards that query targets are placed on the same node. However,
this may not be the case, e.g., after rebalancing shards because it's
not guaranteed to have those shards on the same node anymore.
This commit adds citus.enable_non_colocated_router_query_pushdown GUC
that can be used to disallow planning such queries via router planner,
when it's set to false. Note that the default value for this GUC will be
"true" for 11.3, but we will alter it to "false" on 12.0 to not
introduce
a breaking change in a minor release.
Closes#692.
Even more, allowing such queries to go through router planner also
causes
generating an incorrect plan for the DML queries that reference
distributed
tables that are sharded based on different replication factor settings.
For
this reason, #6779 can be closed after altering the default value for
this
GUC to "false", hence not now.
DESCRIPTION: Adds `citus.enable_non_colocated_router_query_pushdown` GUC
to ensure generating a consistent distributed plan for the queries that
reference non-colocated distributed tables (when set to "false", the
default is "true").
Soon I will be doing some changes related to #692 in router planner
and those changes require updating ~5/6 tests related to router
planning. And to make those test files runnable by run_test.py
multiple times, we need to make some other tests (that they're
run in parallel / they badly depend on) ready for run_test.py too.
This would be useful for testing #6773. This is because, given that
#6773
only adds support for router / fast-path queries, theoretically almost
all
the tests that we have in that test file should work for null-shard-key
tables too (and they indeed do).
I deliberately did not replace multi_router_planner_fast_path.sql with
the one that I'm adding into arbitrary configs because we might still
want to see when we're able to go through fast-path planning for the
usual distributed tables (the ones that have a shard key).
DESCRIPTION: Check before logicalrep for rebalancer, error if needed
Check if we can use logical replication or not, in case of shard
transfer mode = auto, before executing the shard moves. If we can't,
error out. Before this PR, we used to error out in the middle of shard
moves:
```sql
set citus.shard_count = 4; -- just to get the error sooner
select citus_remove_node('localhost',9702);
create table t1 (a int primary key);
select create_distributed_table('t1','a');
create table t2 (a bigint);
select create_distributed_table('t2','a');
select citus_add_node('localhost',9702);
select rebalance_table_shards();
NOTICE: Moving shard 102008 from localhost:9701 to localhost:9702 ...
NOTICE: Moving shard 102009 from localhost:9701 to localhost:9702 ...
NOTICE: Moving shard 102012 from localhost:9701 to localhost:9702 ...
ERROR: cannot use logical replication to transfer shards of the relation t2 since it doesn't have a REPLICA IDENTITY or PRIMARY KEY
```
Now we check and error out in the beginning, without moving the shards.
fixes: #6727
ci/fix_styles.sh were complaining about `black` and `isort` packages are
not found even if I `pipenv install --dev` due to broken lock file. I
regenerated the lock file and now it works fine. We also wanted to
upgrade required python version for the pipfile.
Fixes#6672
2) Move all MERGE related routines to a new file merge_planner.c
3) Make ConjunctionContainsColumnFilter() static again, and rearrange the code in MergeQuerySupported()
4) Restore the original format in the comments section.
5) Add big serial test. Implement latest set of comments
This implements the phase - II of MERGE sql support
Support routable query where all the tables in the merge-sql are distributed, co-located, and both the source and
target relations are joined on the distribution column with a constant qual. This should be a Citus single-task
query. Below is an example.
SELECT create_distributed_table('t1', 'id');
SELECT create_distributed_table('s1', 'id', colocate_with => ‘t1’);
MERGE INTO t1
USING s1 ON t1.id = s1.id AND t1.id = 100
WHEN MATCHED THEN
UPDATE SET val = s1.val + 10
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED THEN
INSERT (id, val, src) VALUES (s1.id, s1.val, s1.src)
Basically, MERGE checks to see if
There are a minimum of two distributed tables (source and a target).
All the distributed tables are indeed colocated.
MERGE relations are joined on the distribution column
MERGE .. USING .. ON target.dist_key = source.dist_key
The query should touch only a single shard i.e. JOIN AND with a constant qual
MERGE .. USING .. ON target.dist_key = source.dist_key AND target.dist_key = <>
If any of the conditions are not met, it raises an exception.
(cherry picked from commit 44c387b978)
This implements MERGE phase3
Support pushdown query where all the tables in the merge-sql are Citus-distributed, co-located, and both
the source and target relations are joined on the distribution column. This will generate multiple tasks
which execute independently after pushdown.
SELECT create_distributed_table('t1', 'id');
SELECT create_distributed_table('s1', 'id', colocate_with => ‘t1’);
MERGE INTO t1
USING s1
ON t1.id = s1.id
WHEN MATCHED THEN
UPDATE SET val = s1.val + 10
WHEN MATCHED THEN
DELETE
WHEN NOT MATCHED THEN
INSERT (id, val, src) VALUES (s1.id, s1.val, s1.src)
*The only exception for both the phases II and III is, UPDATEs and INSERTs must be done on the same shard-group
as the joined key; for example, below scenarios are NOT supported as the key-value to be inserted/updated is not
guaranteed to be on the same node as the id distribution-column.
MERGE INTO target t
USING source s ON (t.customer_id = s.customer_id)
WHEN NOT MATCHED THEN - -
INSERT(customer_id, …) VALUES (<non-local-constant-key-value>, ……);
OR this scenario where we update the distribution column itself
MERGE INTO target t
USING source s On (t.customer_id = s.customer_id)
WHEN MATCHED THEN
UPDATE SET customer_id = 100;
(cherry picked from commit fa7b8949a8)
In #6720 I'm adding a `pytest` based testing framework. This adds the
dependencies for those. They have already been [merged into our docker
files][the-process-merge] in the the-process repo preparation for #6720.
But by not having them on our citus main branch it is impossible to
make changes to the Pipfile, because our CI Dockerfiles and master
are out of date.
Since #6720 will need some more discussion and might take a few more
weeks to be merged, this takes out the Pipfile changes. By merging this
PR we can unblock new Pipfile changes.
Unblocks and partially addresses #6766
[the-process-merge]: https://github.com/citusdata/the-process/pull/117
In the past, having columnar tables in the cluster was causing pg
upgrades to fail when attempting to access columnar metadata. This is
because, pg_dump doesn't see objects that we use for columnar-am related
booking as the dependencies of the tables using columnar-am.
To fix that; in #5456, we inserted some "normal dependency" edges (from
those objects to columnar-am) into pg_depend.
This helped us ensuring the existency of a class of metadata objects
--such as columnar.storageid_seq-- and helped fixing #5437.
However, the normal-dependency edges that we added for indexes on
columnar metadata tables --such columnar.stripe_pkey-- didn't help at
all because they were indeed causing dependency loops (#5510) and
pg_dump was not able to take those dependency edges into the account.
For this reason, this commit deletes those dependency edges so that
pg_dump stops complaining about them. Note that it's not critical to
delete those edges from pg_depend since they're not breaking pg upgrades
but were triggering some warning messages. And given that backporting
a sql change into older versions is hard a lot, we skip backporting
this.
This commit hides port numbers in upgrade_columnar_after because the
port numbers assigned to nodes in upgrade schedule differ from the ones
that flaky test detector assigns.
When run_test.py is run for an upgrade_.*_after.sql then, then
automatically run the corresponding uprade_.*_before.sql file first.
This is because all those upgrade_.*_after.sql files depend on the
objects created in upgrade_.*_before.sql files by definition.
So that we can run the tests that require fake_fdw by using minimal
schedule too.
Also move multi_create_fdw.sql up in multi_1_schedule to make it
available to more tests.
aykut-bozkurt
Gokhan Gulbiz
Halil Ozan Akgül
Onur Tirtir
Naisila Puka
Ahmet Gedemenli
Jelte Fennema
Marco Slot
aykutbozkurt
Emel Şimşek
Marco Slot
Teja Mupparti
rajeshkt78