When introducing non-blocking shard split functionality it was based
heavily on the non-blocking shard moves. However, differences between
usage was slightly to big to be able to reuse the existing functions
easily. So, most logical replication code was simply copied to dedicated
shard split functions and modified for that purpose.
This PR tries to create a more generic logical replication
infrastructure that can be used by both shard splits and shard moves.
There's probably more code sharing possible in the future, but I believe
this is at least a good start and addresses the lowest hanging fruit.
This also adds a CreateSimpleHash function that makes creating the
most common type of hashmap common.
When using `citus.replicate_reference_tables_on_activate = off`,
reference tables need to be replicated later. This can be done using the
`replicate_reference_tables()` UDF. However, this function only allowed
blocking replication. This changes the function to default to logical
replication instead, and allows choosing any of our existing shard
transfer modes.
DESCRIPTION: Use faster custom copy logic for non-blocking shard moves
Non-blocking shard moves consist of two main phases:
1. Initial data copy
2. Catchup phase
This changes the first of these phases significantly. Previously we used the
copy logic provided by postgres subscriptions. This meant we didn't have
to implement it ourselves, but it came with the downside of little control.
When implementing shard splits we needed more control to even make it
work, so we implemented our own logic for copying data between nodes.
This PR starts using that logic for non-blocking shard moves. Doing so
has four main advantages:
1. It uses COPY in binary format when possible, which is cheaper to encode
and decode. Furthermore it very often results in less data that needs to
be sent over the network.
2. It allows us to create the primary key (or other replica identity) after doing
the initial data copy. This should give some speed up over the total run,
because creating an index is bulk is much faster than incrementally building it.
3. It doesn't require a replication slot per parallel copy. Increasing the maximum
number of replication slots uses resources in postgres, even if they are not used.
So reducing the number of replication slots that shard moves need is nice.
4. Logical replication table_sync workers are slow to start up, so if lots of shards
need to be copied that can make it quite slow. This can happen easily when
combining Postgres partitioning with Citus.
The new shard copy code that was created for shard splits has some
advantages over the old shard copy code. The old code was using
worker_append_table_to_shard, which wrote to disk twice. And it also
didn't use binary copy when that was possible. Both of these issues
were fixed in the new copy code. This PR starts using this new copy
logic also for shard moves, not just for shard splits.
On my local machine I created a single shard table like this.
```sql
set citus.shard_count = 1;
create table t(id bigint, a bigint);
select create_distributed_table('t', 'id');
INSERT into t(id, a) SELECT i, i from generate_series(1, 100000000) i;
```
I then turned `fsync` off to make sure I wasn't bottlenecked by disk.
Finally I moved this shard between nodes with `citus_move_shard_placement`
with `block_writes`.
Before this PR a move took ~127s, after this PR it took only ~38s. So for this
small test this resulted in spending ~70% less time.
And I also tried the same test for a table that contained large strings:
```sql
set citus.shard_count = 1;
create table t(id bigint, a bigint, content text);
select create_distributed_table('t', 'id');
INSERT into t(id, a, content) SELECT i, i, 'aunethautnehoautnheaotnuhetnohueoutnehotnuhetncouhaeohuaeochgrhgd.athbetndairgexdbuhaobulrhdbaetoausnetohuracehousncaoehuesousnaceohuenacouhancoexdaseohusnaetobuetnoduhasneouhaceohusnaoetcuhmsnaetohuacoeuhebtokteaoshetouhsanetouhaoug.lcuahesonuthaseauhcoerhuaoecuh.lg;rcydabsnetabuesabhenth' from generate_series(1, 20000000) i;
```
While testing 5670dffd33, I realized
that we have a missing RecordNonDistTableAccessesForTask() for
local utility commands.
Although we don't have to record the relation access for local
only cases, we really want to keep the behaviour for scale-out
be the same with single node on all aspects. We wouldn't want
any single node complex transaction to work on single machine,
but not on multi node cluster. Hence, we apply the same restrictions.
For example, on a distributed cluster, the following errors, and
after this commit this errors locally as well
```SQL
CREATE TABLE ref(a int primary key);
INSERT INTO ref VALUES (1);
CREATE TABLE dist(a int REFERENCES ref(a));
SELECT create_reference_table('ref');
SELECT create_distributed_table('dist', 'a');
BEGIN;
SELECT * FROM dist;
TRUNCATE ref CASCADE;
ERROR: cannot execute DDL on table "ref" because there was a parallel SELECT access to distributed table "dist" in the same transaction
HINT: Try re-running the transaction with "SET LOCAL citus.multi_shard_modify_mode TO 'sequential';"
COMMIT;
```
We also add the comprehensive test suite and run the same locally.
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.
Before this commit, we required multiple copies of the
same stringInfo if we needed to append/prepend data to
the stringInfo. Now, we optionally get prefix/postfix.
For large string operations, this can save up to %10
memory.
Previously, CreateFixPartitionShardIndexNames() created all
the relevant query strings for all the shards, and executed
the large query string. And, in terms of the memory consumption,
this huge command (and its ExprContext generated while running
the command) is the main bottleneck/
With this change, we are reducing the total amount of memory
usage to almost 1/shard_count.
On my local machine, a distributed partitioned table with 120 partitions,
each 32 shards, the total memory consumption reduced from ~3GB
to ~0.1GB. And, the total execution time increased from ~28 seconds
to ~30 seconds. This seems like a good trade-off.
We used to only check whether the PID is valid
or not. However, Postgres does not necessarily
set the PID of the backend to 0 when it exists.
Instead, we need to be able to check it from procArray.
IsBackendPid() is what pg_stat_activity also relies
on for a similar purpose.
use RecurseObjectDependencies api to find if an object is citus depended
make vanilla tests runnable to see if citus_depended function is working correctly
citus_locks combines the pg_locks views from all nodes and adds
global_pid, nodeid, and relation_name. The columns of citus_locks don't
change based on the Postgres version, however the pg_locks's columns do.
Postgres 14 added one more column to pg_locks (waitstart timestamptz).
citus_locks has the most expansive column set, including the newly added
column. If citus_locks is queried in a Postgres version where pg_locks
doesn't have some columns, the values for those columns in citus_locks
will be NULL
DESCRIPTION:
This PR extends support for Partitioned and Columnar tables in blocking 'citus_split_shard_by_split_points' workflow.
Columnar Support : No special handling required. Just removing checks that fails split for columnar table and adding test coverage.
Partitioned Table Support :
Skip copying of parent table as they are empty, The partitions contain data and are treated as co-located shards that will be copied separately.
Attach partitions to parent on destination after inserting new shard metadata and before creating foreign key constraints.
MISC:
Fix Bug #4949 where Blocking shard moves fails if there is a foreign key between partitioned distributed tables (from child to parent).
TEST:
Added new test 'citus_split_shards_columnar_partitioned' for splitting 'partitioned' and 'columnar + partitioned' table.
Added new test 'shard_move_constraints_blocking' to add coverage for shard move bug fix.
Updated test 'citus_split_shard_by_split_points_negative' to allow columnar and partitioned table.
* Remove if conditions with PG_VERSION_NUM < 13
* Remove server_above_twelve(&eleven) checks from tests
* Fix tests
* Remove pg12 and pg11 alternative test output files
* Remove pg12 specific normalization rules
* Some more if conditions in the code
* Change RemoteCollationIdExpression and some pg12/pg13 comments
* Remove some more normalization rules
* Blocking split setup
* Add missing type
* Missing API from Metadata Sync
* Shard Split e2e code
* Worker Split Copy DestReceiver skeleton
* Basic destreceiver code
* worker_split_copy UDF
* UDF calling
* Split points are text
* Isolate Tenant and Split Shard Unification
* Fixing executor and misc
* Reindent code
* Fixing UDF definitions
* Hello World Local Copy works
* Remote copy hello world works
* Local and Remote binary test
* Fixing text local copy and adding tests
* Hello World shard split works
* Negative tests
* Blocking Split workflow works
* Refactor
* Bug fix
* Reindent
* Cleaning up and adding comments
* Basic test for shard split workflow
* ReIndent
* Circle CI integration
* Removing include causing circle-ci build failure
* Remove SplitCopyDestReceiver and use PartitionedResultDestReceiver
* Add support for citus.enable_binary_protocol
* Reindent
* Fix build break
* Update Test
* Cleanup on catch
* Addressing open comments
* Update downgrade script and quote schema/table in COPY statement
* Fix metadata sync issue. Update regression test
* Isolation test and bug fix
* Add Isolation test, fix foreign constraint deadlock issue
* Misc code review comments
* Test name needing to be quoted
* Refactor code from review comments
* Explaining shardGroupSplitIntervalListList
* Fix upgrade & downgrade
* Fix broken test
* Test fix Round 2
* Fixing bug and modifying test appropriately
* Fully qualify copy udf name. Run Reindent
* Address PR comments
* Fix null handling when creating AuxiliaryStructures
* Ensure local copy is triggered in tests
* Limit max shards that can be created with split
* Test failure fix
* Remove split_mode and use shard_transfer_mode instead'
* Fix test failure
* Fix test failure
* Fixing permission issue when splitting non-superuser owned tables
* Fix test expected output
* Remove extra space
* Fix test
* attempt to fix test
* Addressing Marco's PR comment
* Only clean shards created by workflow
* Remove from merge
* Update test
Similar to #5897, one more step for running Citus with PG 15.
This PR at least make Citus run with PG 15. I have not tried running the tests with PG 15.
Shmem changes are based on 4f2400cb3f
Compile breaks are mostly due to #6008
* Support upgrade and downgrade and separate columnar as citus_columnar extension
Co-authored-by: Yanwen Jin <yanwjin@microsoft.com>
Co-authored-by: Jeff Davis <jeff@j-davis.com>
* Added more regression tests for more vacuum options,
* Fixed deadlock for unqualified vacuum when there is only 1 worker,
* Supported lock_skipped for vacuum.
This PR makes all of the features open source that were previously only
available in Citus Enterprise.
Features that this adds:
1. Non blocking shard moves/shard rebalancer
(`citus.logical_replication_timeout`)
2. Propagation of CREATE/DROP/ALTER ROLE statements
3. Propagation of GRANT statements
4. Propagation of CLUSTER statements
5. Propagation of ALTER DATABASE ... OWNER TO ...
6. Optimization for COPY when loading JSON to avoid double parsing of
the JSON object (`citus.skip_jsonb_validation_in_copy`)
7. Support for row level security
8. Support for `pg_dist_authinfo`, which allows storing different
authentication options for different users, e.g. you can store
passwords or certificates here.
9. Support for `pg_dist_poolinfo`, which allows using connection poolers
in between coordinator and workers
10. Tracking distributed query execution times using
citus_stat_statements (`citus.stat_statements_max`,
`citus.stat_statements_purge_interval`,
`citus.stat_statements_track`). This is disabled by default.
11. Blocking tenant_isolation
12. Support for `sslkey` and `sslcert` in `citus.node_conninfo`
The error comes due to the datum jsonb in pg_dist_metadata_node.metadata being 0 in some scenarios. This is likely due to not copying the data when receiving a datum from a tuple and pg deciding to deallocate that memory when the table that the tuple was from is closed.
Also fix another place in the code that might have been susceptible to this issue.
I tested on both multi-vg and multi-1-vg and the test were successful.
altering the distributed table.
To be able to alter view's owner without enforcing sequential mode.
Alter view process functions have been udpated to use metadata
connection.
Do not obtain AccessShareLock before acquiring the distributed locks.
Acquiring an AccessShareLock ensures that the relations which we are trying to get a distributed lock on will not be dropped in the time between when the LOCK command is issued and the LOCK commands are send to the worker. However, this also leads to distributed deadlocks in such scenarios:
```sql
-- for dist lock acquiring order coor, w1, w2
-- on w2
LOCK t1 IN ACCESS EXLUSIVE MODE;
-- acquire AccessShareLock locally on t1 to ensure it is not dropped while we get ready to distribute the lock
-- concurrently on w1
LOCK t1 IN ACCESS EXLUSIVE MODE;
-- acquire AccessShareLock locally on t1 to ensure it is not dropped while we get ready to distribute the lock
-- acquire dist lock on coor, w1, gets blocked on local AccessShareLock on w2
-- on w2 continuation of the execution above
-- starts to acquire dist locks and gets blocked on the coor by the lock acquired by w1
-- distributed deadlock
```
We opt for avoiding such deadlocks with the cost of the possibility of running into errors when the relations on which we are trying to acquire locks on get dropped.
It is often useful to be able to sync the metadata in parallel
across nodes.
Also citus_finalize_upgrade_to_citus11() uses
start_metadata_sync_to_primary_nodes() after this commit.
Note that this commit does not parallelize all pieces of node
activation or metadata syncing. Instead, it tries to parallelize
potenially large parts of metadata, which is the objects and
distributed tables (in general Citus tables).
In the future, it would be nice to sync the reference tables
in parallel across nodes.
Create ~720 distributed tables / ~23450 shards
```SQL
-- declaratively partitioned table
CREATE TABLE github_events_looooooooooooooong_name (
event_id bigint,
event_type text,
event_public boolean,
repo_id bigint,
payload jsonb,
repo jsonb,
actor jsonb,
org jsonb,
created_at timestamp
) PARTITION BY RANGE (created_at);
SELECT create_time_partitions(
table_name := 'github_events_looooooooooooooong_name',
partition_interval := '1 day',
end_at := now() + '24 months'
);
CREATE INDEX ON github_events_looooooooooooooong_name USING btree (event_id, event_type, event_public, repo_id);
SELECT create_distributed_table('github_events_looooooooooooooong_name', 'repo_id');
SET client_min_messages TO ERROR;
```
across 1 node: almost same as expected
```SQL
SELECT start_metadata_sync_to_primary_nodes();
Time: 15664.418 ms (00:15.664)
select start_metadata_sync_to_node(nodename,nodeport) from pg_dist_node;
Time: 14284.069 ms (00:14.284)
```
across 7 nodes: ~3.5x improvement
```SQL
SELECT start_metadata_sync_to_primary_nodes();
┌──────────────────────────────────────┐
│ start_metadata_sync_to_primary_nodes │
├──────────────────────────────────────┤
│ t │
└──────────────────────────────────────┘
(1 row)
Time: 25711.192 ms (00:25.711)
-- across 7 nodes
select start_metadata_sync_to_node(nodename,nodeport) from pg_dist_node;
Time: 82126.075 ms (01:22.126)
```
* Bug fix for bug #5876. Memset MetadataCacheSystem every time there is an abort
* Created an ObjectAccessHook that saves the transactionlevel of when citus was created and will clear metadatacache if that transaction level is rolled back. Added additional tests to make sure metadatacache is cleared
Columnar: support relation options with ALTER TABLE.
Use ALTER TABLE ... SET/RESET to specify relation options rather than
alter_columnar_table_set() and alter_columnar_table_reset().
Not only is this more ergonomic, but it also allows better integration
because it can be treated like DDL on a regular table. For instance,
citus can use its own ProcessUtility_hook to distribute the new
settings to the shards.
DESCRIPTION: Columnar: support relation options with ALTER TABLE.
In the past (pre-11), we allowed removing worker nodes
that had active placements for replicated distributed
table, without even checking if there are any other
replicas of the same placement.
However, with #5469, we prevent disabling nodes via a hard
error when there is the last active placement of shard, as we
do for reference tables. Note that otherwise, we'd allow
users to lose data.
As of today, the NOTICE is completely irrelevant.
First worker node has a special meaning for modifications on the replicated tables
It is used to acquire a remote lock, such that the modifications are serialized.
With this commit, we make sure that we do not let any distributed query to see a
different 'first worker node' while first worker node is disabled.
Note that, maybe implicitly mentioned above, when first worker node is disabled,
the first worker node changes, that's why we have to handle the situation.
Before this commit, we had:
```SQL
SELECT citus_disable_node(nodename, nodeport, force boolean DEFAULT false)
```
Where, we allow forcing to disable first worker node with
`force:=true`. However, it entails the risk for losing
data / diverging placement data etc.
With `force` flag, we control disabling the first worker node,
and with `async` flag we control whether the changes are done
via bg worker or immediately.
```SQL
SELECT citus_disable_node(nodename, nodeport, force boolean DEFAULT false, sync boolean DEFAULT false)
```
Where we can achieve all the following:
| Mode | Data loss possibility | Can run in 2PC | Handle multiple node failures | Immediately effective |
| --- |--- |--- |--- |--- |
| force:false, sync: false | false | true | true | false |
| force:false, sync: true | false | false | false | true |
| force:true, sync: false | true | true | true | false |
| force:true, sync: true | false | false | false | true |
There are two problems in this area. First, when there are expressions
on the index name, we should call `transformIndexExpression()` before
generating the index name. That is what Postgres does.
Second, because of 40c24bfef9
PG 13 and PG 14 generates different names for indexes with function calls even for local PG tables.
Assume we have:
```SQL
create table t(id int);
select create_distributed_table('t', 'id');
create index ON t (my_very_boring_function(id));
```
On PG 13, the name of the index is `t_expr_idx`
```SQL
\d t
Table "public.t"
┌────────┬─────────┬───────────┬──────────┬─────────┐
│ Column │ Type │ Collation │ Nullable │ Default │
├────────┼─────────┼───────────┼──────────┼─────────┤
│ id │ integer │ │ │ │
└────────┴─────────┴───────────┴──────────┴─────────┘
Indexes:
"t_expr_idx" btree (my_very_boring_function(id::bigint))
```
On PG 14, the name of the index is `t_my_very_boring_function_idx`
```SQL
\d t
Table "public.t"
┌────────┬─────────┬───────────┬──────────┬─────────┐
│ Column │ Type │ Collation │ Nullable │ Default │
├────────┼─────────┼───────────┼──────────┼─────────┤
│ id │ integer │ │ │ │
└────────┴─────────┴───────────┴──────────┴─────────┘
Indexes:
"t_my_very_boring_function_idx" btree (my_very_boring_function(id::bigint))
```
The second issue is not very critical. The important part is that
we adjust regression tests to drop all the indexes, which ensures
the index names are sane on any version.
Jelte Fennema
Marco Slot
Teja Mupparti
aykut-bozkurt
Ahmet Gedemenli
Sameer Awasekar
aykutbozkurt
Onder Kalaci
Naisila Puka
Hanefi Onaldi
Nitish Upreti
ywj
Halil Ozan Akgul
Burak Velioglu
Gledis Zeneli
Burak Velioglu
Ying Xu
jeff-davis
gledis69