DESCRIPTION: Adds citus_stat_counters view that can be used to query
stat counters that Citus collects while the feature is enabled, which is
controlled by citus.enable_stat_counters. citus_stat_counters() can be
used to query the stat counters for the provided database oid and
citus_stat_counters_reset() can be used to reset them for the provided
database oid or for the current database if nothing or 0 is provided.
Today we don't persist stat counters on server shutdown. In other words,
stat counters are automatically reset in case of a server restart.
Details on the underlying design can be found in header comment of
stat_counters.c and in the technical readme.
-------
Here are the details about what we track as of this PR:
For connection management, we have three statistics about the inter-node
connections initiated by the node itself:
* **connection_establishment_succeeded**
* **connection_establishment_failed**
* **connection_reused**
While the first two are relatively easier to understand, the third one
covers the case where a connection is reused. This can happen when a
connection was already established to the desired node, Citus decided to
cache it for some time (see citus.max_cached_conns_per_worker &
citus.max_cached_connection_lifetime), and then reused it for a new
remote operation. Here are the other important details about these
connection statistics:
1. connection_establishment_failed doesn't care about the connections
that we could establish but are lost later in the transaction. Plus, we
cannot guarantee that the connections that are counted in
connection_establishment_succeeded were not lost later.
2. connection_establishment_failed doesn't care about the optional
connections (see OPTIONAL_CONNECTION flag) that we gave up establishing
because of the connection throttling rules we follow (see
citus.max_shared_pool_size & citus.local_shared_pool_size). The reaason
for this is that we didn't even try to establish these connections.
3. For the rest of the cases where a connection failed for some reason,
we always increment connection_establishment_failed even if the caller
was okay with the failure and know how to recover from it (e.g., the
adaptive executor knows how to fall back local execution when the target
node is the local node and if it cannot establish a connection to the
local node). The reason is that even if it's likely that we can still
serve the operation, we still failed to establish the connection and we
want to track this.
4. Finally, the connection failures that we count in
connection_establishment_failed might be caused by any of the following
reasons and for now we prefer to _not_ further distinguish them for
simplicity:
a. remote node is down or cannot accept any more connections, or
overloaded such that citus.node_connection_timeout is not enough to
establish a connection
b. any internal Citus error that might result in preparing a bad
connection string so that libpq fails when parsing the connection string
even before actually trying to establish a connection via connect() call
c. broken citus.node_conninfo or such Citus configuration that was
incorrectly set by the user can also result in similar outcomes as in b
d. internal waitevent set / poll errors or OOM in local node
We also track two more statistics for query execution:
* **query_execution_single_shard**
* **query_execution_multi_shard**
And more importantly, both query_execution_single_shard and
query_execution_multi_shard are not only tracked for the top-level
queries but also for the subplans etc. The reason is that for some
queries, e.g., the ones that go through recursive planning, after Citus
performs the heavy work as part of subplans, the work that needs to be
done for the top-level query becomes quite straightforward. And for such
query types, it would be deceiving if we only incremented the query stat
counters for the top-level query. Similarly, for non-pushable INSERT ..
SELECT and MERGE queries, we perform separate counter increments for the
SELECT / source part of the query besides the final INSERT / MERGE
query.
DESCRIPTION: Drops PG14 support
1. Remove "$version_num" != 'xx' from configure file
2. delete all PG_VERSION_NUM = PG_VERSION_XX references in the code
3. Look at pg_version_compat.h file, remove all _compat functions etc
defined specifically for PGXX differences
4. delete all PG_VERSION_NUM >= PG_VERSION_(XX+1), PG_VERSION_NUM <
PG_VERSION_(XX+1) ifs in the codebase
5. delete ruleutils_xx.c file
6. cleanup normalize.sed file from pg14 specific lines
7. delete all alternative output files for that particular PG version,
server_version_ge variable helps here
This is prep work for successful compilation with PG17
PG17added foreach_ptr, foreach_int and foreach_oid macros
Relevant PG commit
14dd0f27d7cd56ffae9ecdbe324965073d01a9ff
14dd0f27d7
We already have these macros, but they are different with the
PG17 ones because our macros take a DECLARED variable, whereas
the PG16 macros declare a locally-scoped loop variable themselves.
Hence I am renaming our macros to foreach_declared_
I am separating this into its own PR since it touches many files. The
main compilation PR is https://github.com/citusdata/citus/pull/7699
DESCRIPTION: Fix performance issue when creating distributed tables and many already exist
EnsureSequenceTypeSupported was doing an O(number of distributed tables)
operation. This can become very slow with lots of Citus tables, which
now happens much more frequently in practice due to schema based sharding.
Partially addresses #7022
This change refactors the code by using generate_qualified_relation_name
from id instead of using a sequence of functions to generate the
relation name.
Fixes#6602
This change adds a script to programatically group all includes in a
specific order. The script was used as a one time invocation to group
and sort all includes throught our formatted code. The grouping is as
follows:
- System includes (eg. `#include<...>`)
- Postgres.h (eg. `#include "postgres.h"`)
- Toplevel imports from postgres, not contained in a directory (eg.
`#include "miscadmin.h"`)
- General postgres includes (eg . `#include "nodes/..."`)
- Toplevel citus includes, not contained in a directory (eg. `#include
"citus_verion.h"`)
- Columnar includes (eg. `#include "columnar/..."`)
- Distributed includes (eg. `#include "distributed/..."`)
Because it is quite hard to understand the difference between toplevel
citus includes and toplevel postgres includes it hardcodes the list of
toplevel citus includes. In the same manner it assumes anything not
prefixed with `columnar/` or `distributed/` as a postgres include.
The sorting/grouping is enforced by CI. Since we do so with our own
script there are not changes required in our uncrustify configuration.
Since in PG16, truncate triggers are supported on foreign tables, we add
the citus_truncate_trigger to Citus foreign tables as well, such that the TRUNCATE
command is propagated to the table's single local shard as well.
Note that TRUNCATE command was working for foreign tables even before this
commit: see https://github.com/citusdata/citus/pull/7170#issuecomment-1706240593 for details
This commit also adds tests with user-enabled truncate triggers on Citus foreign tables:
both trigger on the shell table and on its single foreign local shard.
Relevant PG commit:
https://github.com/postgres/postgres/commit/3b00a94
**Problem:**
Previously we always used an outside superuser connection to overcome
permission issues for the current user while propagating dependencies.
That has mainly 2 problems:
1. Visibility issues during dependency propagation, (metadata connection
propagates some objects like a schema, and outside transaction does not
see it and tries to create it again)
2. Security issues (it is preferrable to use current user's connection
instead of extension superuser)
**Solution (high level):**
Now, we try to make a smarter decision on whether should we use an
outside superuser connection or current user's metadata connection. We
prefer using current user's connection if any of the objects, which is
already propagated in the current transaction, is a dependency for a
target object. We do that since we assume if current user has
permissions to create the dependency, then it can most probably
propagate the target as well.
Our assumption is expected to hold most of the times but it can still be
wrong. In those cases, transaction would fail and user should set the
GUC `citus.create_object_propagation` to `deferred` to work around it.
**Solution:**
1. We track all objects propagated in the current transaction (we can
handle subtransactions),
2. We propagate dependencies via the current user's metadata connection
if any dependency is created in the current transaction to address
issues listed above. Otherwise, we still use an outside superuser
connection.
DESCRIPTION: Fixes some object propagation errors seen with transaction
blocks.
Fixes https://github.com/citusdata/citus/issues/6614
---------
Co-authored-by: Nils Dijk <nils@citusdata.com>
Allow using generated identity column based on int/smallint when
creating a distributed table so that applications that rely on
those data types don't break.
Inserting into / modifying such columns from workers is not allowed
but it's better than not allowing such columns altogether.
* Currently we do not allow any Citus tables other than Citus local
tables inside a regular schema before executing
`citus_schema_distribute`.
* `citus_schema_undistribute` expects only single shard distributed
tables inside a tenant schema.
DESCRIPTION: Adds the udf `citus_schema_distribute` to convert a regular
schema into a tenant schema.
DESCRIPTION: Adds the udf `citus_schema_undistribute` to convert a
tenant schema back to a regular schema.
---------
Co-authored-by: Onur Tirtir <onurcantirtir@gmail.com>
DESCRIPTION: Adds citus.enable_schema_based_sharding GUC that allows
sharding the database based on schemas when enabled.
* Refactor the logic that automatically creates Citus managed tables
* Refactor CreateSingleShardTable() to allow specifying colocation id
instead
* Add support for schema-based-sharding via a GUC
### What this PR is about:
Add **citus.enable_schema_based_sharding GUC** to enable schema-based
sharding. Each schema created while this GUC is ON will be considered
as a tenant schema. Later on, regardless of whether the GUC is ON or
OFF, any table created in a tenant schema will be converted to a
single shard distributed table (without a shard key). All the tenant
tables that belong to a particular schema will be co-located with each
other and will have a shard count of 1.
We introduce a new metadata table --pg_dist_tenant_schema-- to do the
bookkeeping for tenant schemas:
```sql
psql> \d pg_dist_tenant_schema
Table "pg_catalog.pg_dist_tenant_schema"
┌───────────────┬─────────┬───────────┬──────────┬─────────┐
│ Column │ Type │ Collation │ Nullable │ Default │
├───────────────┼─────────┼───────────┼──────────┼─────────┤
│ schemaid │ oid │ │ not null │ │
│ colocationid │ integer │ │ not null │ │
└───────────────┴─────────┴───────────┴──────────┴─────────┘
Indexes:
"pg_dist_tenant_schema_pkey" PRIMARY KEY, btree (schemaid)
"pg_dist_tenant_schema_unique_colocationid_index" UNIQUE, btree (colocationid)
psql> table pg_dist_tenant_schema;
┌───────────┬───────────────┐
│ schemaid │ colocationid │
├───────────┼───────────────┤
│ 41963 │ 91 │
│ 41962 │ 90 │
└───────────┴───────────────┘
(2 rows)
```
Colocation id column of pg_dist_tenant_schema can never be NULL even
for the tenant schemas that don't have a tenant table yet. This is
because, we assign colocation ids to tenant schemas as soon as they
are created. That way, we can keep associating tenant schemas with
particular colocation groups even if all the tenant tables of a tenant
schema are dropped and recreated later on.
When a tenant schema is dropped, we delete the corresponding row from
pg_dist_tenant_schema. In that case, we delete the corresponding
colocation group from pg_dist_colocation as well.
### Future work for 12.0 release:
We're building schema-based sharding on top of the infrastructure that
adds support for creating distributed tables without a shard key
(https://github.com/citusdata/citus/pull/6867).
However, not all the operations that can be done on distributed tables
without a shard key necessarily make sense (in the same way) in the
context of schema-based sharding. For example, we need to think about
what happens if user attempts altering schema of a tenant table. We
will tackle such scenarios in a future PR.
We will also add a new UDF --citus.schema_tenant_set() or such-- to
allow users to use an existing schema as a tenant schema, and another
one --citus.schema_tenant_unset() or such-- to stop using a schema as
a tenant schema in future PRs.
Add tests for ddl coverage:
* indexes
* partitioned tables + indexes with long names
* triggers
* foreign keys
* statistics
* grant & revoke statements
* truncate & vacuum
* create/test/drop view that depends on a dist table with no shard key
* policy & rls test
* alter table add/drop/alter_type column (using sequences/different data
types/identity columns)
* alter table add constraint (not null, check, exclusion constraint)
* alter table add column with a default value / set default / drop
default
* alter table set option (autovacuum)
* indexes / constraints without names
* multiple subcommands
Adds support for
* Creating new partitions after distributing (with null key) the parent
table
* Attaching partitions to a distributed table with null distribution key
(and automatically distribute the new partition with null key as well)
* Detaching partitions from it
With this PR, we allow creating distributed tables with without
specifying a shard key via create_distributed_table(). Here are the
the important details about those tables:
* Specifying `shard_count` is not allowed because it is assumed to be 1.
* We mostly call such tables as "null shard-key" table in code /
comments.
* To avoid doing a breaking layout change in create_distributed_table();
instead of throwing an error, it will inform the user that
`distribution_type`
param is ignored unless it's explicitly set to NULL or 'h'.
* `colocate_with` param allows colocating such null shard-key tables to
each other.
* We define this table type, i.e., NULL_SHARD_KEY_TABLE, as a subclass
of
DISTRIBUTED_TABLE because we mostly want to treat them as distributed
tables in terms of SQL / DDL / operation support.
* Metadata for such tables look like:
- distribution method => DISTRIBUTE_BY_NONE
- replication model => REPLICATION_MODEL_STREAMING
- colocation id => **!=** INVALID_COLOCATION_ID (distinguishes from
Citus local tables)
* We assign colocation groups for such tables to different nodes in a
round-robin fashion based on the modulo of "colocation id".
Note that this PR doesn't care about DDL (except CREATE TABLE) / SQL /
operation (i.e., Citus UDFs) support for such tables but adds a
preliminary
API.
.. rather than having it in user facing functions. That way, we
can use the same logic for creating Citus tables from other places
too.
This would be useful for creating tenant tables via a simple function
call in the utility hook, for schema-based sharding purposes.
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:
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.
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.
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.
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.
DESCRIPTION: Extend cleanup process for replication artifacts
This PR adds new cleanup record types for:
* Subscriptions
* Replication slots
* Publications
* Users created for subscriptions
We add records for these object types, to `pg_dist_cleanup` during
creation phase. Once the operation is done, in case of success or
failure, we iterate those records and drop the objects. With this PR we
will not be dropping any of these objects during the operation. In
short, we will always be deferring the drop.
One thing that's worth mentioning is that we sort cleanup records before
processing (dropping) them, because of dependency relations among those
objects, e.g a subscription might depend on a publication. Therefore, we
always drop subscriptions before publications.
We have some renames in this PR:
* `TryDropOrphanedShards` -> `TryDropOrphanedResources`
* `DropOrphanedShardsForCleanup` -> `DropOrphanedResourcesForCleanup`
* `run_try_drop_marked_shards` -> `run_try_drop_marked_resources`
as these functions now process replication artifacts as well.
This PR drops function `DropAllLogicalReplicationLeftovers` and its all
usages, since now we rely on the deferring drop mechanism.
DESCRIPTION: Makes sure to disallow triggers that depend on extensions
We were already doing so for `ALTER trigger DEPENDS ON EXTENSION`
commands. However, we also need to disallow creating Citus tables
having such triggers already, so this PR fixes that.
DESCRIPTION: Fixes floating exception during
create_distributed_table_concurrently.
Fixes#6332.
During create_distributed_table_concurrently, when there is no active
primary node, it fails with floating exception. We added similar check
with create_distributed_table. It will fail with proper message if
current active node is less than replication factor.
PG15 allows numeric scale to be negative or greater than precision. This
causes issues and we may end up routing queries to a wrong shard due to
differing hash results after rounding.
Formerly, when specifying NUMERIC(precision, scale), the scale had to be
in the range [0, precision], which was per SQL spec. PG15 extends the
range of allowed scales to [-1000, 1000].
A negative scale implies rounding before the decimal point. For
example, a column might be declared with a scale of -3 to round values
to the nearest thousand. Note that the display scale remains
non-negative, so in this case the display scale will be zero, and all
digits before the decimal point will be displayed.
Relevant PG commit: 085f931f52494e1f304e35571924efa6fcdc2b44
Added create_distributed_table_concurrently which is nonblocking variant of create_distributed_table.
It bases on the split API which takes advantage of logical replication to support nonblocking split operations.
Co-authored-by: Marco Slot <marco.slot@gmail.com>
Co-authored-by: aykutbozkurt <aykut.bozkurt1995@gmail.com>
There are 3 different ways that a sequence can be interacting
with tables. (1) and (2) are already supported. This commit adds
support for (3).
(1) column DEFAULT nextval('seq'):
The dependency is roughly like below,
and ExpandCitusSupportedTypes() is responsible
for finding the depending sequences.
schema <--- table <--- column <---- default value
^ |
|------------------ sequence <--------|
(2) serial columns: Bigserial/small serial etc:
The dependency is roughly like below,
and ExpandCitusSupportedTypes() is responsible
for finding the depending sequences.
schema <--- table <--- column <---- default value
^ |
| |
sequence <--------|
(3) Sequence OWNED BY table.column: Added support for
this type of resolution in this commit.
The dependency is almost like the following, and
ExpandCitusSupportedTypes() is NOT responsible for finding
the dependency.
schema <--- table <--- column
^
|
sequence
DESCRIPTION: Fix reference table lock contention
Dropping and creating reference tables unintentionally blocked on each other due to the use of an ExclusiveLock for both the Drop and conditionally copying existing reference tables to (new) nodes.
The patch does the following:
- Lower lock lever for dropping (reference) tables to `ShareLock` so they don't self conflict
- Treat reference tables and distributed tables equally and acquire the colocation lock when dropping any table that is in a colocation group
- Perform the precondition check for copying reference tables twice, first time with a lower lock that doesn't conflict with anything. Could have been a NoLock, however, in preparation for dropping a colocation group, it is an `AccessShareLock`
During normal operation the first check will always pass and we don't have to escalate that lock. Making it that we won't be blocked on adding and remove reference tables. Only after a node addition the first `create_reference_table` will still need to acquire an `ExclusiveLock` on the colocation group to perform the copy.
It turns out that create_distributed_table
and citus_move/copy_shard_placement does not
work well concurrently.
To fix that, we need to acquire a lock, which
sounds like a good use of colocation lock.
However, the current usage of colocation lock is
limited to higher level UDFs like rebalance_table_shards
etc. Those usage of lock is still useful, but
we cannot acquire the same lock on citus_move_shard_placement
etc. because the coordinator connects to itself to acquire
the lock. Hence, the high level UDF blocks itself.
To fix that, we use one more colocation lock, with the placements
are the main objects to consider.
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.
Before this commit, we erroneously converted the sequence
type to the column's type it is used. However, it is possible
that the sequence is used in an expression which then converted
to a type that cannot be a sequence, such as text.
With this commit, we only try this conversion if the column
type is a supported sequence type (e.g., smallint, int and bigint).
Note that we do this conversion because if the column type is a
bigint and the sequence is NOT a bigint, users would be in trouble
because sequences would generate values that are out of the range
of the column. (The other ways are already not supported such as
the column is int and the sequence is bigint would fail on the worker.)
In other words, with this commit, we scope this optimization only
when the target column type is a supported sequence type. Otherwise,
we let users to more freely use the sequences.
Onur Tirtir
Naisila Puka
Jelte Fennema-Nio
eaydingol
Nils Dijk
aykut-bozkurt
zhjwpku
Ahmet Gedemenli
Gokhan Gulbiz
rajeshkt78
Marco Slot
Hanefi Onaldi
Onder Kalaci
Teja Mupparti
aykutbozkurt
Halil Ozan Akgul
Jelte Fennema
Burak Velioglu