DESCRIPTION: Fixes memory errors, caught by valgrind, of type
"conditional jump or move depends on uninitialized value"
When running Citus tests under Postgres with valgrind, the test cases
calling into `NonBlockingShardSplit` function produce valgrind errors of
type "conditional jump or move depends on uninitialized value".
The issue is caused by creating a HTAB in a wrong way. HASH_COMPARE flag
should have been used when creating a HTAB with user defined comparison
function. In the absence of HASH_COMPARE flag, HTAB falls back into
built-in string comparison function. However, valgrind somehow discovers
that the match function is not assigned to the user defined function as
intended.
Fixes#6835
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.
DESCRIPTION:
Makefile changes to build different versions of CDC decoder for different base decoders like pgoutput and wal2json with the same name and copy it to $packagelib/cdc_decoders dir. This helps the user to use logical replication slots normally with pgoutput without being aware of CDC decoder.
1) Changed src/backend/distributed/cdc/Makefile to setup a build directory
for CDC in build-cdc-$(DECODER) dir and copy the source files (.c.h and Makefile.decoder) to
the build dir and build it for each base decoder.
2) copy the pgoutput.so and wal2json.so into the above build dir and
install them in PG packagelibdir/citus_decoders directory.
3)Added a testcase 016_cdc_wal2json.pl for testing the wal2json decoder
using pg_recv_logical_changes function.
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>
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)
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.
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
Emel Şimşek
Halil Ozan Akgül
aykut-bozkurt
Onur Tirtir
rajeshkt78
Naisila Puka
Gokhan Gulbiz
Marco Slot
Ahmet Gedemenli
Teja Mupparti
aykutbozkurt
Marco Slot