DESCRIPTION: PR description that will go into the change log, up to 78
characters
---------
Co-authored-by: Hanefi Onaldi <Hanefi.Onaldi@microsoft.com>
DESCRIPTION: Adds views that monitor statistics on tenant usages
This PR adds `citus_stats_tenants` view that monitors the tenants on the
cluster.
`citus_stats_tenants` shows the node id, colocation id, tenant
attribute, read count in this period and last period, and query count in
this period and last period of the tenant.
Tenant attribute currently is the tenant's distribution column value,
later when schema based sharding is introduced, this meaning might
change.
A period is a time bucket the queries are counted by. Read and query
counts for this period can increase until the current period ends. After
that those counts are moved to last period's counts, which cannot
change. The period length can be set using 'citus.stats_tenants_period'.
`SELECT` queries are counted as _read_ queries, `INSERT`, `UPDATE` and
`DELETE` queries are counted as _write_ queries. So in the view read
counts are `SELECT` counts and query counts are `SELECT`, `INSERT`,
`UPDATE` and `DELETE` count.
The data is stored in shared memory, in a struct named
`MultiTenantMonitor`.
`citus_stats_tenants` shows the data from local tenants.
`citus_stats_tenants` show up to `citus.stats_tenant_limit` number of
tenants.
The tenants are scored based on the number of queries they run and the
recency of those queries. Every query ran increases the score of tenant
by `ONE_QUERY_SCORE`, and after every period ends the scores are halved.
Halving is done lazily.
To retain information a longer the monitor keeps up to 3 times
`citus.stats_tenant_limit` tenants. When the tenant count hits `3 *
citus.stats_tenant_limit`, last `citus.stats_tenant_limit` tenants are
removed. To see all stored tenants you can use
`citus_stats_tenants(return_all_tenants := true)`
- [x] Create collector view that gets data from all nodes. #6761
- [x] Add monitoring log #6762
- [x] Create enable/disable GUC #6769
- [x] Parse the annotation string correctly #6796
- [x] Add local queries and prepared statements #6797
- [x] Rename to citus_stat_statements #6821
- [x] Run pgbench
- [x] Fix role permissions #6812
---------
Co-authored-by: Gokhan Gulbiz <ggulbiz@gmail.com>
Co-authored-by: Jelte Fennema <github-tech@jeltef.nl>
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>
DESCRIPTION:
- The CDC decoder is refacroted into a seperate extension that can be used loaded dynamically without having to reload citus.
- CDC decoder code can be compiled using DECODER flag to work with different decoders like pgoutput and wal2json.
by default the base decode is "pgoutput".
- the dynamic_library_path config is adjusted dynamically to prefer the decoders in cdc_decoders directory in citus init
so that the users can use the replication subscription commands without having to make any config changes.
DESCRIPTION: Refactor and unify shard move and copy functions
Shard move and copy functions share a lot of code in common. This PR
unifies these functions into one, along with some helper functions. To
preserve the current behavior, we'll introduce and use an enum
parameter, and hardcoded strings for producing error/warning messages.
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 .
- Create MetadataSyncContext api to encapsulate
both transactional and nontransactional modes,
- Add a GUC to switch between metadata sync transaction modes.
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").
Because they're only interested in distributed tables. Even more,
this replaces HasDistributionKey() check with
IsCitusTableType(DISTRIBUTED_TABLE) because this doesn't make a
difference on main and sounds slightly more intuitive. Plus, this
would also allow safely using this function in
https://github.com/citusdata/citus/pull/6773.
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
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)
Decide core distribution params in CreateCitusTable to reduce the
chances of
creating Citus tables based on incorrect combinations of distribution
method
and replication model params.
Also introduce DistributedTableParams struct to encapsulate the
parameters
that are specific to distributed tables.
Now that we will soon add another table type having DISTRIBUTE_BY_NONE
as distribution method and that we want the code to interpret such
tables mostly as distributed tables, let's make the definition of those
other two table types more strict by removing
CITUS_TABLE_WITH_NO_DIST_KEY
macro.
And instead, use HasDistributionKey() check in the places where the
logic applies to all table types that have / don't have a distribution
key. In future PRs, we might want to convert some of those
HasDistributionKey() checks if logic only applies to Citus local /
reference tables, not the others.
And adding HasDistributionKey() also allows us to consider having
DISTRIBUTE_BY_NONE as the distribution method as a "table attribute"
that can apply to distributed tables too, rather something that
determines the table type.
Split the main logic that allows creating a Citus table into the
internal function CreateCitusTable().
Old CreateDistributedTable() function was assuming that it's creating
a reference table when the distribution method is DISTRIBUTE_BY_NONE.
However, soon this won't be the case when adding support for creating
single-shard distributed tables because their distribution method would
also be the same.
Now the internal method CreateCitusTable() doesn't make any assumptions
about table's replication model or such. Instead, it expects callers to
properly set all such metadata bits.
Even more, some of the parameters the old CreateDistributedTable() takes
--such as the shard count-- were not meaningful for a reference table,
and would be the same as for new table type.
DESCRIPTION: Fixes a bug in shard copy operations.
For copying shards in both shard move and shard split operations, Citus
uses the COPY statement.
A COPY all statement in the following form
` COPY target_shard FROM STDIN;`
throws an error when there is a GENERATED column in the shard table.
In order to fix this issue, we need to exclude the GENERATED columns in
the COPY and the matching SELECT statements. Hence this fix converts the
COPY and SELECT all statements to the following form:
```
COPY target_shard (col1, col2, ..., coln) FROM STDIN;
SELECT (col1, col2, ..., coln) FROM source_shard;
```
where (col1, col2, ..., coln) does not include a GENERATED column.
GENERATED column values are created in the target_shard as the values
are inserted.
Fixes#6705.
---------
Co-authored-by: Teja Mupparti <temuppar@microsoft.com>
Co-authored-by: aykut-bozkurt <51649454+aykut-bozkurt@users.noreply.github.com>
Co-authored-by: Jelte Fennema <jelte.fennema@microsoft.com>
Co-authored-by: Gürkan İndibay <gindibay@microsoft.com>
DESCRIPTION: Adds logic to distribute unbalanced shards
If the number of shard placements (for a colocation group) is less than
the number of workers, it means that some of the workers will remain
empty. With this PR, we consider these shard groups as a colocation
group, in order to make them be distributed evenly as much as possible
across the cluster.
Example:
```sql
create table t1 (a int primary key);
create table t2 (a int primary key);
create table t3 (a int primary key);
set citus.shard_count =1;
select create_distributed_table('t1','a');
select create_distributed_table('t2','a',colocate_with=>'t1');
select create_distributed_table('t3','a',colocate_with=>'t2');
create table tb1 (a bigint);
create table tb2 (a bigint);
select create_distributed_table('tb1','a');
select create_distributed_table('tb2','a',colocate_with=>'tb1');
select citus_add_node('localhost',9702);
select rebalance_table_shards();
```
Here we have two colocation groups, each with one shard group. Both
shard groups are placed on the first worker node. When we add a new
worker node and try to rebalance table shards, the rebalance planner
considers it well balanced and does nothing. With this PR, the
rebalancer tries to distribute these shard groups evenly across the
cluster as much as possible. For this example, with this PR, the
rebalancer moves one of the shard groups to the second worker node.
fixes: #6715
DESCRIPTION: Correctly report shard size in citus_shards view
When looking at citus_shards, people are interested in the actual size
that all the data related to the shard takes up on disk.
`pg_total_relation_size` is the function to use for that purpose. The
previously used `pg_relation_size` does not include indexes or TOAST.
Especially the missing toast can have enormous impact on the size of the
shown data.
2 improvements to prevent memory leaks during altering or undistributing
distributed tables with a lot of partitions and shards:
1. Free memory for each call to ConvertTable so that colocated and partition tables at
`AlterDistributedTable`, `UndistributeTable`, or
`AlterTableSetAccessMethod` will not cause an increase
in memory usage,
2. Free memory while executing attach partition commands for each partition table at
`AlterDistributedTable` to prevent an increase in memory usage.
DESCRIPTION: Fixes memory leak issue during altering distributed table
with a lot of partition and shards.
Fixes https://github.com/citusdata/citus/issues/6503.
We have memory leak during distribution of a table with a lot of
partitions as we do not release memory at ExprContext until all
partitions are not distributed. We improved 2 things to resolve the
issue:
1. We create and delete MemoryContext for each call to
`CreateDistributedTable` by partitions,
2. We rebuild the cache after we insert all the placements instead of
each placement for a shard.
DESCRIPTION: Fixes memory leak during distribution of a table with a lot
of partitions and shards.
Fixes https://github.com/citusdata/citus/issues/6572.
When auto_explain module is loaded and configured, EXPLAIN will be
implicitly run for all the supported commands. Postgres does not support
`EXPLAIN` for `ALTER` command. However, auto_explain will try to
`EXPLAIN` other supported commands internally triggered by `ALTER`.
For instance,
`ALTER TABLE target_table ADD CONSTRAINT fkey_167 FOREIGN KEY (col_1)
REFERENCES ref_table(key) ... `
command may trigger a SELECT command in the following form for foreign
key validation purpose:
`SELECT fk.col_1 FROM ONLY target_table fk LEFT OUTER JOIN ONLY
ref_table pk ON ( pk.key OPERATOR(pg_catalog.=) fk.col_1) WHERE pk.key
IS NULL AND (fk.col_1 IS NOT NULL) `
For Citus tables, the Citus utility hook should ensure that constraint
validation is skipped for shell tables but they are done for shard
tables. The reason behind this design choice can be summed up as:
- An ALTER TABLE command via coordinator node is run in a distributed
transaction.
- Citus does not support nested distributed transactions.
- A SELECT query on a distributed table (aka shell table) is also run in
a distributed transaction.
- Therefore, Citus does not support running a SELECT query on a shell
table while an ALTER TABLE command is running.
With
eadc88a800
a bug is introduced breaking the skip constraint validation behaviour of
Citus. With this change, we see that validation queries on distributed
tables are triggered within `ALTER` command adding constraints with
validation check. This regression did not cause an issue for regular use
cases since the citus executor hook blocks those queries heuristically
when there is an ALTER TABLE command in progress.
The issue is surfaced as a crash (#6424 Workers, when configured to use
auto_explain, crash during distributed transactions.) when auto_explain
is enabled. This is due to auto_explain trying to execute the SELECT
queries in a nested distributed transaction.
Now since the regression with constraint validation is fixed in
https://github.com/citusdata/citus/issues/6543, we should be able to
remove the workaround.
We should not omit to free PGResult when we receive single tuple result
from an internal backend.
Single tuple results are normally freed by our ReceiveResults for
`tupleDescriptor != NULL` flow but not for those with `tupleDescriptor
== NULL`. See PR #6722 for details.
DESCRIPTION: Fixes memory leak issue with query results that returns
single row.
Prevents memory leak during ConvertTable call for a table with a lot of
partitions.
DESCRIPTION: Fixes memory leak during undistribution and alteration of a
table with a lot of partitions.
Gokhan Gulbiz
Halil Ozan Akgül
Onur Tirtir
Marco Slot
rajeshkt78
Ahmet Gedemenli
Teja Mupparti
aykutbozkurt
Emel Şimşek
Marco Slot
Jelte Fennema
aykut-bozkurt