A shard move would fail if there was an orphaned version of the shard on
the target node. With this change before actually fail, we try to clean
up orphaned shards to see if that fixes the issue.
Sometimes the background daemon doesn't cleanup orphaned shards quickly
enough. It's useful to have a UDF to trigger this removal when needed.
We already had a UDF like this but it was only used during testing. This
exposes that UDF to users. As a safety measure it cannot be run in a
transaction, because that would cause the background daemon to stop
cleaning up shards while this transaction is running.
* Add user-defined sequence support for MX
* Remove default part when propagating to workers
* Fix ALTER TABLE with sequences for mx tables
* Clean up and add tests
* Propagate DROP SEQUENCE
* Removing function parts
* Propagate ALTER SEQUENCE
* Change sequence type before propagation & cleanup
* Revert "Propagate ALTER SEQUENCE"
This reverts commit 2bef64c5a29f4e7224a7f43b43b88e0133c65159.
* Ensure sequence is not used in a different column with different type
* Insert select tests
* Propagate rename sequence stmt
* Fix issue with group ID cache invalidation
* Add ALTER TABLE ALTER COLUMN TYPE .. precaution
* Fix attnum inconsistency and add various tests
* Add ALTER SEQUENCE precaution
* Remove Citus hook
* More tests
Co-authored-by: Marco Slot <marco.slot@gmail.com>
We have a slightly different behavior when using truncate_local_data_after_distributing_table UDF on metadata synced clusters. This PR aims to add tests to cover such cases.
We allow distributing tables with data that have foreign keys to reference tables only on metadata synced clusters. This is the reason why some of my earlier tests failed when run on a single node Citus cluster.
The current default citus settings for tests are not really best
practice anymore. However, we keep them because lots of tests depend on
them.
I noticed that I created the same test harness for new tests I added all
the time. This is a simple script that generates that harness, given a
name for the test.
To run:
src/test/regress/bin/create_test.py my_awesome_test
Without this change the rebalancer progress monitor gets the shard sizes
from the `shardlength` column in `pg_dist_placement`. This column needs to
be updated manually by calling `citus_update_table_statistics`.
However, `citus_update_table_statistics` could lead to distributed
deadlocks while database traffic is on-going (see #4752).
To work around this we don't use `shardlength` column anymore. Instead
for every rebalance we now fetch all shard sizes on the fly.
Two additional things this does are:
1. It adds tests for the rebalance progress function.
2. If a shard move cannot be done because a source or target node is
unreachable, then we error in stop the rebalance, instead of showing
a warning and continuing. When using the by_disk_size rebalance
strategy it's not safe to continue with other moves if a specific
move failed. It's possible that the failed move made space for the
next move, and because the failed move never happened this space now
does not exist.
3. Adds two new columns to the result of `get_rebalancer_progress` which
shows the size of the shard on the source and target node.
Fixes#4930
DESCRIPTION: Add support for ALTER DATABASE OWNER
This adds support for changing the database owner. It achieves this by marking the database as a distributed object. By marking the database as a distributed object it will look for its dependencies and order the user creation commands (enterprise only) before the alter of the database owner. This is mostly important when adding new nodes.
By having the database marked as a distributed object it can easily understand for which `ALTER DATABASE ... OWNER TO ...` commands to propagate by resolving the object address of the database and verifying it is a distributed object, and hence should propagate changes of owner ship to all workers.
Given the ownership of the database might have implications on subsequent commands in transactions we force sequential mode for transactions that have a `ALTER DATABASE ... OWNER TO ...` command in them. This will fail the transaction with meaningful help when the transaction already executed parallel statements.
By default the feature is turned off since roles are not automatically propagated, having it turned on would cause hard to understand errors for the user. It can be turned on by the user via setting the `citus.enable_alter_database_owner`.
We often change result types of functions slightly. Our downgrade tests
wouldn't notice these changes. This change adds them to the description
of these items.
An example of an SQL change that isn't caught without this change and is
caught with the get_rebalance_progress change in this PR:
https://github.com/citusdata/citus/pull/4963
It was possible to block maintenance daemon by taking an SHARE ROW
EXCLUSIVE lock on pg_dist_placement. Until the lock is released
maintenance daemon would be blocked.
We should not block the maintenance daemon under any case hence now we
try to get the pg_dist_placement lock without waiting, if we cannot get
it then we don't try to drop the old placements.
DESCRIPTION: introduce `citus.local_hostname` GUC for connections to the current node
Citus once in a while needs to connect to itself for some systems operations. This used to be hardcoded to `localhost`. The hardcoded hostname causes some issues, for example in environments where `sslmode=verify-full` is required. It is not always desirable or even feasible to get `localhost` as an alt name on the certificate.
By introducing a GUC to use when connecting to the current instance the user has more control what network path is used and what hostname is required to be present in the server certificate.
Every move in the rebalancer algorithm results in an improvement in the
balance. However, even if the improvement in the balance was very small
the move was still chosen. This is especially problematic if the shard
itself is very big and the move will take a long time.
This changes the rebalancer algorithm to take the relative size of the
balance improvement into account when choosing moves. By default a move
will not be chosen if it improves the balance by less than half of the
size of the shard. An extra argument is added to the rebalancer
functions so that the user can decide to lower the default threshold if
the ignored move is wanted anyway.
* Columnar: introduce columnar storage API.
This new API is responsible for the low-level storage details of
columnar; translating large reads and writes into individual block
reads and writes that respect the page headers and emit WAL. It's also
responsible for the columnar metapage, resource reservations (stripe
IDs, row numbers, and data), and truncation.
This new API is not used yet, but will be used in subsequent
forthcoming commits.
* Columnar: add columnar_storage_info() for debugging purposes.
* Columnar: expose ColumnarMetadataNewStorageId().
* Columnar: always initialize metapage at creation time.
This avoids the complexity of dealing with tables where the metapage
has not yet been initialized.
* Columnar: columnar storage upgrade/downgrade UDFs.
Necessary upgrade/downgrade step so that new code doesn't see an old
metapage.
* Columnar: improve metadata.c comment.
* Columnar: make ColumnarMetapage internal to the storage API.
Callers should not have or need direct access to the metapage.
* Columnar: perform resource reservation using storage API.
* Columnar: implement truncate using storage API.
* Columnar: implement read/write paths with storage API.
* Columnar: add storage tests.
* Revert "Columnar: don't include stripe reservation locks in lock graph."
This reverts commit c3dcd6b9f8.
No longer needed because the columnar storage API takes care of
concurrency for resource reservation.
* Columnar: remove unnecessary lock when reserving.
No longer necessary because the columnar storage API takes care of
concurrent resource reservation.
* Add simple upgrade tests for storage/ branch
* fix multi_extension.out
Co-authored-by: Onur Tirtir <onurcantirtir@gmail.com>
* When moving a shard to a new node ensure there is enough space
* Add WairForMiliseconds time utility
* Add more tests and increase readability
* Remove the retry loop and use a single udf for disk stats
* Address review
* address review
Co-authored-by: Jelte Fennema <github-tech@jeltef.nl>
This allows running the following command to update the expected files
with normalized output files for upgrade tests too:
```bash
cp src/test/regress/{results,expected}/upgrade_rebalance_strategy_before.out
```
The comment of DropMarkedShards described the behaviour that after a
failure we would continue trying to drop other shards. However the code
did not do this and would stop after the first failure. Instead of
simply fixing the comment I fixed the code, because the described
behaviour is more useful. Now a single shard that cannot be removed yet
does not block others from being removed.
Recently two new normalization line deletion rules have been added that
don't match the start of a line:
```
/local tables that are added to metadata but not chained with reference tables via foreign keys might be automatically converted back to postgres tables$/d
/Consider setting citus.enable_local_reference_table_foreign_keys to 'off' to disable this behavior$/d
```
Because `diff-filter` used `regex.match` these lines were not removed
when creating a new diff. This could cause some confusing diffs, where
the wrong lines were shown as changed. This fixes that by using
`regex.search` instead of `regex.match`.
As long as the VALUES clause contains constant values, we should not
recursively plan the queries/CTEs.
This is a follow-up work of #1805. So, we can easily apply OUTER join
checks as if VALUES clause is a reference table/immutable function.
* Fix problews with concurrent calls of DropMarkedShards
When trying to enable `citus.defer_drop_after_shard_move` by default it
turned out that DropMarkedShards was not safe to call concurrently.
This could especially cause big problems when also moving shards at the
same time. During tests it was possible to trigger a state where a shard
that was moved would not be available on any of the nodes anymore after
the move.
Currently DropMarkedShards is only called in production by the
maintenaince deamon. Since this is only a single process triggering such
a race is currently impossible in production settings. In future changes
we will want to call DropMarkedShards from other places too though.
* Add some isolation tests
Co-authored-by: Jelte Fennema <github-tech@jeltef.nl>
This commit adds support for long partition names for distributed tables:
- ALTER TABLE dist_table ATTACH PARTITION ..
- CREATE TABLE .. PARTITION OF dist_table ..
Note: create_distributed_table UDF does not support long table and
partition names, and is not covered in this commit
* Introduce 3 partitioned size udfs
* Add tests for new partition size udfs
* Fix type incompatibilities
* Convert UDFs into pure sql functions
* Fix function comment
* Columnar: use clause Vars for chunk group filtering.
This solves #4780 and also provides a cleaner separation between chunk
group filtering and projection pushdown.
* Columnar: sort and deduplicate Vars pulled from clauses.
* Columnar: cleanup variable names.
* Columnar: remove alternate test output.
* Columnar: do not recurse when looking for whereClauseVars.
Co-authored-by: Jeff Davis <jefdavi@microsoft.com>
comparable to https://github.com/citusdata/tools/pull/88
this patch adds checks to the perl script running the testing harness of citus to start the postgres instances via the fixopen binary when present to work around `Interrupted System` call errors on OSX Big Sur.
Earlier versions of Citus (pre 9.0) had a bug where a user was able to get in a situation where a foreign key between two non-colocated tables was allowed. This was caused by the wrongful scoping together with only setting to on of a boolean variable in a loop, causing the `true` from an earlier iteration to leak into a new iteration.
This was 'by accident' solved in a refactor that was executed in the preparation of the 9.0 release. Only recently we had a user running into this and it was tracked down to this behaviour.
Given the dire situation a user could get them self into when running into this bug we have backported a fix to the latest 8.3 release branch.
To make sure this regression does not happen anymore in the future I propose we add the tests from the backport to our mainline.
For reference: https://github.com/citusdata/citus/pull/4840
With https://github.com/citusdata/citus/pull/4806 we enabled
2PC for any non-read-only local task. However, if the execution
is a single task, enabling 2PC (CoordinatedTransactionShouldUse2PC)
hits an assertion as we are not in a coordinated transaction.
There is no downside of using a coordinated transaction for single
task local queries.
Because setting the flag doesn't necessarily mean that we'll
use 2PC. If connections are read-only, we will not use 2PC.
In other words, we'll use 2PC only for connections that modified
any placements.
Before this commit, Citus used 2PC no matter what kind of
local query execution happens.
For example, if the coordinator has shards (and the workers as well),
even a simple SELECT query could start 2PC:
```SQL
WITH cte_1 AS (SELECT * FROM test LIMIT 10) SELECT count(*) FROM cte_1;
```
In this query, the local execution of the shards (and also intermediate
result reads) triggers the 2PC.
To prevent that, Citus now distinguishes local reads and local writes.
And, Citus switches to 2PC only if a modification happens. This may
still lead to unnecessary 2PCs when there is a local modification
and remote SELECTs only. Though, we handle that separately
via #4587.
Postgres keeps AFTER trigger state for each transaction, because we can have deferred AFTER triggers which will be fired at the end of a transaction. Postgres cleans up this state at the end of transaction.
Postgres processes ON COMMIT triggers after cleaning-up the AFTER trigger states. So if we fire any triggers in ON COMMIT, the AFTER trigger state won't be cleaned-up properly and the transaction state will be left in an inconsistent state, which might result in assertion failure.
So with this commit, we remove foreign keys between columnar metadata tables and enforce constraints between them manually when dropping columnar tables.
* Skip 2PC for readonly connections in a transaction
* Use ConnectionModifiedPlacement() function
* Remove the second check of ConnectionModifiedPlacement()
* Add order by to prevent flaky output
* Test using pg_dist_transaction
With this commit, we make sure to prevent infinite recursion for queries
in the format: [subquery with a UNION ALL] JOIN [table or subquery]
Also, fixes a bug where we pushdown UNION ALL below a JOIN even if the
UNION ALL is not safe to pushdown.
* Reimplement citus_update_table_statistics
* Update stats for the given table not colocation group
* Add tests for reimplemented citus_update_table_statistics
* Use coordinated transaction, merge with citus_shard_sizes functions
* Update the old master_update_table_statistics as well
* Use translated vars in postgres 13 as well
Postgres 13 removed translated vars with pg 13 so we had a special logic
for pg 13. However it had some bug, so now we copy the translated vars
before postgres deletes it. This also simplifies the logic.
* fix rtoffset with pg >= 13
/*
* The physical planner assumes that all worker queries would have
* target list entries based on the fact that at least the column
* on the JOINs have to be on the target list. However, there is
* an exception to that if there is a cartesian product join and
* there is no additional target list entries belong to one side
* of the JOIN. Once we support cartesian product join, we should
* remove this error.
*/
When executing alter_table / undistribute_table udf's, we should not try
to change sequence dependencies on MX workers if new table wouldn't
require syncing metadata.
Previously, we were checking that for input table. But in some cases, the
fact that input table requires syncing metadata doesn't imply the same
for resulting table (e.g when undistributing a Citus table).
Even more, doing that was giving an unexpected error when undistributing
a Citus table so this commit actually fixes that.
It seems that we need to consider only pseudo constants while doing some
shortcuts in planning. For example there could be a false clause but it
can contribute to the result in which case it will not be a pseudo
constant.
We would exclude tables without relationRestriction from conversion
candidates in local-distributed table joins. This could leave a leftover
local table which should have been converted to a subquery.
Ideally I would expect that in each call to CreateDistributedPlan we
would pass a new plan id, but that seems like a bigger change.
/*
* Colocated intermediate results are just files and not required to use
* the same connections with their co-located shards. So, we are free to
* use any connection we can get.
*
* Also, the current connection re-use logic does not know how to handle
* intermediate results as the intermediate results always truncates the
* existing files. That's why, we use one connection per intermediate
* result.
*/
We do not include dummy column if original task didn't return any
columns.
Otherwise, number of columns that original task returned wouldn't
match number of columns returned by worker_save_query_explain_analyze.
When COPY is used for copying into co-located files, it was
not allowed to use local execution. The primary reason was
Citus treating co-located intermediate results as co-located
shards, and COPY into the distributed table was done via
"format result". And, local execution of such COPY commands
was not implemented.
With this change, we implement support for local execution with
"format result". To do that, we use the buffer for every file
on shardState->copyOutState, similar to how local copy on
shards are implemented. In fact, the logic is similar to
local copy on shards, but instead of writing to the shards,
Citus writes the results to a file.
The logic relies on LOCAL_COPY_FLUSH_THRESHOLD, and flushes
only when the size exceeds the threshold. But, unlike local
copy on shards, in this case we write the headers and footers
just once.
* Sort results in citus_shards and give raw size
Sort results so that it is consistent and also similar to citus_tables.
Use raw size in the output so that doing operations on the size is
easier.
* Change column ordering
With #4338, the executor is smart enough to failover to
local node if there is not enough space in max_connections
for remote connections.
For COPY, the logic is different. With #4034, we made COPY
work with the adaptive connection management slightly
differently. The cause of the difference is that COPY doesn't
know which placements are going to be accessed hence requires
to get connections up-front.
Similarly, COPY decides to use local execution up-front.
With this commit, we change the logic for COPY on local nodes:
Try to reserve a connection to local host. This logic follows
the same logic (e.g., citus.local_shared_pool_size) as the
executor because COPY also relies on TryToIncrementSharedConnectionCounter().
If reservation to local node fails, switch to local execution
Apart from this, if local execution is disabled, we follow the
exact same logic for multi-node Citus. It means that if we are
out of the connection, we'd give an error.
It seems that we were not considering the case where coordinator was
added to the cluster as a worker in the optimization of intermediate
results.
This could lead to errors when coordinator was added as a worker.
pg_get_tableschemadef_string doesn't know how to deparse identity
columns so we cannot reflect those columns when creating table
from scratch. For this reason, we don't allow using alter_table udfs
with tables having any identity cols.
pg_get_tableschemadef_string doesn't know how to deparse identity
columns so we cannot reflect those columns when creating shell
relation.
For this reason, we don't allow adding local tables -having identity cols-
to metadata.
Postgres doesn't allow inserting into columns having GENERATED ALWAYS
AS (...) STORED expressions.
For this reason, when executing undistribute_table or an alter_* udf,
we should skip copying such columns.
This is not bad since Postgres would already generate such columns.
Enables an overall plan to be parallel (e.g. over a partition
hierarchy), even though an individual ColumnarScan is not
parallel-aware.
Co-authored-by: Jeff Davis <jefdavi@microsoft.com>
Previously, if columnar.enable_custom_scan was false, parallel paths
could remain, leading to an unexpected error.
Also, ensure that cheapest_parameterized_paths is cleared if a custom
scan is used.
Co-authored-by: Jeff Davis <jefdavi@microsoft.com>
When finding columns owning sequences, we shouldn't rely on atthasdef
since it might be true when column has GENERATED ALWAYS AS (...)
STORED expression.
* Fix partition column index issue
We send column names to worker_hash/range_partition_table methods, and
in these methods we check the column name index from tuple descriptor.
Then this index is used to decide the bucket that the current row will
be sent for the repartition.
This becomes a problem when there are the same column names in the
tupleDescriptor. Then we can choose the wrong index. Hence the
partitioned data will be put to wrong workers. Then the result could
miss some data because workers might contain different range of data.
An example:
TupleDescriptor contains "trip_id", "car_id", "car_id" for one table.
It contains only "car_id" for the other table. And assuming that the
tables will be partitioned by car_id, it is not certain what should be
used for deciding the bucket number for the first table. Assuming value
2 goes to bucket 2 and value 3 goes to bucket 3, it is not certain which
bucket "1 2 3" (trip_id, car_id, car_id) row will go to.
As a solution we send the index of partition column in targetList
instead of the column name.
The old API is kept so that if workers upgrade work, it still works
(though it will have the same bug)
* Use the same method so that backporting is easier
Fixing a division by zero in the cost calculations for scanning a columnar table.
Due to how the columns in a columnar table are counted an empty table would result in a division by zero. Instead this patch keeps the column selection ratio on zero when this happens, resulting in an accurate cost of zero pages to scan a columnar table.
fixes#4589
* Make undistribute_table() and citus_create_local_table() work with columnar
* Rename and use LocallyExecuteUtilityTask for UDF check
* Remove 'local' references in ExecuteUtilityCommand
/*
* Creating Citus local tables relies on functions that accesses
* shards locally (e.g., ExecuteAndLogDDLCommand()). As long as
* we don't teach those functions to access shards remotely, we
* cannot relax this check.
*/
Logical replication status can take wal_receiver_status_interval
seconds to get updated. Default is 10s, which means tests in
which logical replication is used can take a long time to finish.
We reduce it to 1 second to speed these tests up.
Logical replication apply launcher launches workers every
wal_retrieve_retry_interval, so if we have many shard moves with
logical replication consecutively, they will be throttled by this
parameter. Default is 5s, we reduce it to 1s so we finish tests
faster.
The reason behind skipping postgres tables is that we support
foreign keys between postgres tables and reference tables
(without converting postgres tables to citus local tables)
when enable_local_reference_table_foreign_keys is false or
when coordinator is not added to metadata.
When enabled any foreign keys between local tables and reference
tables supported by converting the local table to a citus local
table.
When the coordinator is not in the metadata, the logic is disabled
as foreign keys are not allowed in this configuration.
If relation is not involved in any foreign key relationships,
foreign key graph would not return any relations for given
relationId as expected.
But even if it's the case, we should still undistribute the table
itself.
DESCRIPTION: Add tests to verify crash recovery for columnar tables
Based on the Postgres TAP tooling we add a new test suite to the array of test suites for citus. It is modelled after `src/test/recovery` in the postgres project and takes the same place in our repository. It uses the perl modules defined in the postgres project to control the postgres nodes.
The test we add here focus on crash recovery. Our follower tests should cover the streaming replication behaviour.
It is hooked to our CI for both postgres 12 and postgres 13. We omit the recovery tests for postgres 11 as we do not have support for the columnar table access method.
* Stronger check for triggers on columnar tables (#4493).
Previously, we used a simple ProcessUtility_hook. Change to use an
object_access_hook instead.
* Replace alter_table_set_access_method test on partition with foreign key
Co-authored-by: Jeff Davis <jefdavi@microsoft.com>
Co-authored-by: Marco Slot <marco.slot@gmail.com>
With citus shard helper view, we can easily see:
- where each shard is, which node, which port
- what kind of table it belongs to
- its size
With such a view, we can see shards that have a size bigger than some
value, which could be useful. Also debugging can be easier in production
as well with this view.
Fetch shards in one go per node
The previous implementation was slow because it would do a lot of round
trips, one per shard to be exact. Hence it is improved so that we fetch
all the shard_name, shard-size pairs per node in one go.
Construct shards_names, sizes query on coordinator
* Replace master_add_node with citus_add_node
* Replace master_activate_node with citus_activate_node
* Replace master_add_inactive_node with citus_add_inactive_node
* Use master udfs in old scripts
* Replace master_add_secondary_node with citus_add_secondary_node
* Replace master_disable_node with citus_disable_node
* Replace master_drain_node with citus_drain_node
* Replace master_remove_node with citus_remove_node
* Replace master_set_node_property with citus_set_node_property
* Replace master_unmark_object_distributed with citus_unmark_object_distributed
* Replace master_update_node with citus_update_node
* Replace master_update_shard_statistics with citus_update_shard_statistics
* Replace master_update_table_statistics with citus_update_table_statistics
* Rename master_conninfo_cache_invalidate to citus_conninfo_cache_invalidate
Rename master_dist_local_group_cache_invalidate to citus_dist_local_group_cache_invalidate
* Replace master_copy_shard_placement with citus_copy_shard_placement
* Replace master_move_shard_placement with citus_move_shard_placement
* Rename master_dist_node_cache_invalidate to citus_dist_node_cache_invalidate
* Rename master_dist_object_cache_invalidate to citus_dist_object_cache_invalidate
* Rename master_dist_partition_cache_invalidate to citus_dist_partition_cache_invalidate
* Rename master_dist_placement_cache_invalidate to citus_dist_placement_cache_invalidate
* Rename master_dist_shard_cache_invalidate to citus_dist_shard_cache_invalidate
* Drop master_modify_multiple_shards
* Rename master_drop_all_shards to citus_drop_all_shards
* Drop master_create_distributed_table
* Drop master_create_worker_shards
* Revert old function definitions
* Add missing revoke statement for citus_disable_node
CREATE TABLE does not invalidate foreign key graph but some other set of
ddl commands do.
Previously, as we run multi_foreign_key & multi_foreign_key_relation_graph
in parallel, it's possible that multi_foreign_key invalidates foreign key
graph via some ddl commands and create table test in
multi_foreign_key_relation_graph becomes flaky.
So we un-parallelize those two tests.
* Rethrow original concurrent index creation failure message
* Alter test outputs for concurrent index creation
* Detect duplicate table failure in concurrent index creation
* Add test for conc. index creation w/out duplicates
* Prevent deadlock for long named partitioned index creation on single node
* Create IsSingleNodeCluster function
* Use both local and sequential execution
On top of our foreign key graph, implement the infrastructure to get
list of relations that are connected to input relation via a foreign key
graph.
We need this to support cascading create_citus_local_table &
undistribute_table operations.
Also add regression tests to see what our foreign key graph is able to
capture currently.
Attribute number in a subquery RTE and relation RTE means different
things. In a relation attribute number will point to the column number
in the table definition including the dropped columns as well however in
subquery, it means the index in the target list. When we convert a
relation RTE to subquery RTE we should either correct all the relevant
attribute numbers or we can just add a dummy column for the dropped
columns. We choose the latter in this commit because it is practically
too vulnerable to update all the vars in a query.
Another thing this commit fixes is that in case a join restriction
clause list contains a false clause, we should just returns a false
clause instead of the whole list, because the whole list will contain
restrictions from other RTEs as well and this breaks the query, which
can be seen from the output changes, now it is much simpler.
Also instead of adding single tests for dropped columns, we choose to
run the whole mixed queries with tables with dropped columns, this
revealed some bugs already, which are fixed in this commit.
It seems that there are only very few cases where that is useful, and
for now we prefer not having that check. This means that we might
perform some unnecessary checks, but that should be rare and not
performance critical.
Instead of sending NULL's over a network, we now convert the subqueries
in the form of:
SELECT t.a, NULL, NULL FROM (SELECT a FROM table)t;
And we recursively plan the inner part so that we don't send the NULL's
over network. We still need the NULLs in the outer subquery because we
currently don't have an easy way of updating all the necessary places in
the query.
Add some documentation for how the conversion is done
Baseinfo also has pushed down filters etc, so it makes more sense to use
BaseRestrictInfo to determine what columns have constant equality
filters.
Also RteIdentity is used for removing conversion candidates instead of
rteIndex.
It seems that most of the updates were broken, we weren't aware of it
because there wasn't any data in the tables. They are broken mostly
because local tables do not have a shard id and some code paths should
be updated with that information, currently when there is an invalid
shard id, it is assumed to be pruned.
Consider local tables in router planner
In case there is a local table, the shard id will not be valid and there
are some checks that rely on shard id, we should skip these in case of
local tables, which is handled with a dummy placement.
Add citus local table dist table join tests
add local-dist table mixed joins tests
AllDataLocallyAccessible and ContainsLocalTableSubqueryJoin are removed.
We can possibly remove ModifiesLocalTableWithRemoteCitusLocalTable as
well. Though this removal has a side effect that now when all the data
is locally available, we could still wrap a relation into a subquery, I
guess that should be resolved in the router planner itself.
Add more tests
When we wrap an RTE to subquery we are updating the variables varno's as
1, however we should also update the varno's of vars in quals.
Also some other small code quality improvements are done.
The previous algorithm was not consistent and it could convert different
RTEs based on the table orders in the query. Now we convert local tables
if there is a distributed table which doesn't have a unique index. So if
there are 4 tables, local1, local2, dist1, dist2_with_pkey then we will
convert local1 and local2 in `auto` mode. Converting a distributed table
is not that logical because as there is a distributed table without a
unique index, we will need to convert the local tables anyway. So
converting the distributed table with pkey is redundant.
Remove FillLocalAndDistributedRTECandidates and use
ShouldConvertLocalTableJoinsToSubqueries, which simplifies things as we
rely on a single function to decide whether we should continue
converting RTE to subquery.
We should not recursively plan an already routable plannable query. An
example of this is (SELECT * FROM local JOIN (SELECT * FROM dist) d1
USING(a));
So we let the recursive planner do all of its work and at the end we
convert the final query to to handle unsupported joins. While doing each
conversion, we check if it is router plannable, if so we stop.
Only consider range table entries that are in jointree
If a range table is not in jointree then there is no point in
considering that because we are trying to convert range table entries to
subqueries for join use case.
Check equality in quals
We want to recursively plan distributed tables only if they have an
equality filter on a unique column. So '>' and '<' operators will not
trigger recursive planning of distributed tables in local-distributed
table joins.
Recursively plan distributed table only if the filter is constant
If the filter is not a constant then the join might return multiple rows
and there is a chance that the distributed table will return huge data.
Hence if the filter is not constant we choose to recursively plan the
local table.
When doing local-distributed table joins we convert one of them to
subquery. The current policy is that we convert distributed tables to
subquery if it has a unique index on a column that has unique
index(primary key also has a unique index).
UPDATEs on partitioned tables that affect only row partitions should
succeed, the rest should fail.
Also rename CStoreScan to ColumnarScan to make the error message more
relevant.
When Citus needs to parallelize queries on the local node (e.g., the node
executing the distributed query and the shards are the same), we need to
be mindful about the connection management. The reason is that the client
backends that are running distributed queries are competing with the client
backends that Citus initiates to parallelize the queries in order to get
a slot on the max_connections.
In that regard, we implemented a "failover" mechanism where if the distributed
queries cannot get a connection, the execution failovers the tasks to the local
execution.
The failover logic is follows:
- As the connection manager if it is OK to get a connection
- If yes, we are good.
- If no, we fail the workerPool and the failure triggers
the failover of the tasks to local execution queue
The decision of getting a connection is follows:
/*
* For local nodes, solely relying on citus.max_shared_pool_size or
* max_connections might not be sufficient. The former gives us
* a preview of the future (e.g., we let the new connections to establish,
* but they are not established yet). The latter gives us the close to
* precise view of the past (e.g., the active number of client backends).
*
* Overall, we want to limit both of the metrics. The former limit typically
* kics in under regular loads, where the load of the database increases in
* a reasonable pace. The latter limit typically kicks in when the database
* is issued lots of concurrent sessions at the same time, such as benchmarks.
*/
When distributing a columnar table, as well as changing options on a distributed columnar table, this patch will forward the settings from the coordinator to the workers.
For propagating options changes on an already distributed table this change is pretty straight forward. Before applying the change in options locally we will create a `DDLJob` that contains a call to `alter_columnar_table_set(...)` for every shard placement with all settings of the current table. This goes both for setting an option as well as resetting. This will reset the values to the defaults configured on the coordinator. Having the effect that the coordinator is authoritative on the settings and makes sure the shards have the same settings set as the table on the coordinator.
When a columnar table is distributed it is using the `TableDDLCommand` infra structure to create a new kind of `TableDDLCommand`. This new type, called a `TableDDLCommandFunction` contains a context and 2 function pointers to execute. One function returns the command as applied on the table, the second function will return the sql command to apply to a shard with a given shard id. The schema name is ignored as it will use the fully qualified name of the shard in the same schema as the base table.
Multi-row execution already uses sequential execution. When shards
are local, using local execution is profitable as it avoids
an extra connection establishment to the local node.
Join test gets too many clients error too frequently hence we should
not run anything concurrently with that. Hopefully this will fix the
flakiness of test.
This is to avoid flaky changes like the following in test outputs:
-CPU: user: 0.00 s, system: 0.00 s, elapsed: 0.00 s.
+CPU: user: 0.00 s, system: 0.00 s, elapsed: 0.02 s.
Columnar options were by accident linked to the relfilenode instead of the regclass/relation oid. This PR moves everything related to columnar options to their own catalog table.
Considering the adaptive connection management
improvements that we plan to roll soon, it makes it
very helpful to know the number of active client
backends.
We are doing this addition to simplify yhe adaptive connection
management for single node Citus. In single node Citus, both the
client backends and Citus parallel queries would compete to get
slots on Postgres' `max_connections` on the same Citus database.
With adaptive connection management, we have the counters for
Citus parallel queries. That helps us to adaptively decide
on the remote executions pool size (e.g., throttle connections
if necessary).
However, we do not have any counters for the total number of
client backends on the database. For single node Citus, we
should consider all the client backends, not only the remote
connections that Citus does.
Of course Postgres internally knows how many client
backends are active. However, to get that number Postgres
iterates over all the backends. For examaple, see [pg_stat_get_db_numbackends](8e90ec5580/src/backend/utils/adt/pgstatfuncs.c (L1240))
where Postgres iterates over all the backends.
For our purpuses, we need this information on every connection
establishment. That's why we cannot affort to do this kind of
iterattion.
CitusTableTypeIdList() function iterates on all the entries of pg_dist_partition
and loads all the metadata in to the cache. This can be quite memory intensive
especially when there are lots of distributed tables.
When partitioned tables are used, it is common to have many distributed tables
given that each partition also becomes a distributed table.
CitusTableTypeIdList() is used on every CREATE TABLE .. PARTITION OF.. command
as well. It means that, anytime a partition is created, Citus loads all the
metadata to the cache. Note that Citus typically only loads the accessed table's
metadata to the cache.
* Move local execution after the remote execution
Before this commit, when both local and remote tasks
exist, the executor was starting the execution with
local execution. There is no strict requirements on
this.
Especially considering the adaptive connection management
improvements that we plan to roll soon, moving the local
execution after to the remote execution makes more sense.
The adaptive connection management for single node Citus
would look roughly as follows:
- Try to connect back to the coordinator for running
parallel queries.
- If succeeds, go on and execute tasks in parallel
- If fails, fallback to the local execution
So, we'll use local execution as a fallback mechanism. And,
moving it after to the remote execution allows us to implement
such further scenarios.
Before this commit, we let AdaptiveExecutorPreExecutorRun()
to be effective multiple times on every FETCH on cursors.
That does not affect the correctness of the query results,
but adds significant overhead.
TableAM API doesn't allow us to pass around a state variable along all of the tuple inserts belonging to the same command. We require this in columnar store, since we batch them, and when we have enough rows we flush them as stripes.
To do that, we keep a (relfilenode) -> stack of (subxact id, TableWriteState) global mapping.
**Inserts**
Whenever we want to insert a tuple, we look up for the relation's relfilenode in this mapping. If top of the stack matches current subtransaction, we us the existing TableWriteState. Otherwise, we allocate a new TableWriteState and push it on top of stack.
**(Sub)Transaction Commit/Aborts**
When the subtransaction or transaction is committed, we flush and pop all entries matching current SubTransactionId.
When the subtransaction or transaction is committed, we pop all entries matching current SubTransactionId and discard them without flushing.
**Reads**
Since we might have unwritten rows which needs to be read by a table scan, we flush write states on SELECTs. Since flushing the write state of upper transactions in a subtransaction will cause metadata being written in wrong subtransaction, we ERROR out if any of the upper subtransactions have unflushed rows.
**Table Drops**
We record in which subtransaction the table was dropped. When committing a subtransaction in which table was dropped, we propagate the drop to upper transaction. When aborting a subtransaction in which table was dropped, we mark table as not deleted.
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