Description: Support round-robin `task_assignment_policy` for queries to reference tables.
This PR allows users to query multiple placements of shards in a round robin fashion. When `citus.task_assignment_policy` is set to `'round-robin'` the planner will use a round robin scheduling feature when multiple shard placements are available.
The primary use-case is spreading the load of reference table queries to all the nodes in the cluster instead of hammering only the first placement of the reference table. Since reference tables share the same path for selecting the shards with single shard queries that have multiple placements (`citus.shard_replication_factor > 1`) this setting also allows users to spread the query load on these shards.
For modifying queries we do not apply a round-robin strategy. This would be negated by an extra reordering step in the executor for such queries where a `first-replica` strategy is enforced.
In recent postgres builds you cannot set client_min_messages to
values higher then ERROR, if will silently set it to ERROR if so.
During some tests we would set it to fatal to hide random values
(eg. pid's of processes) from the test output. This patch will use
different tactics for hiding these values.
After Fast ALTER TABLE ADD COLUMN with a non-NULL default in PG11, physical heaps might not contain all attributes after a ALTER TABLE ADD COLUMN happens. heap_getattr() returns NULL when the physical tuple doesn't contain an attribute. So we should use heap_deform_tuple() in these cases, which fills in the missing attributes.
Our catalog tables evolve over time, and an upgrade might involve some ALTER TABLE ADD COLUMN commands.
Note that we don't need to worry about postgres catalog tables and we can use heap_getattr() for them, because they only change between major versions.
This also fixes#2453.
I'm pretty sure a lot of this test functionality may be covered in some
of our existing regression tests, but I've included them to ensure we
put all failure-based tests under our new testing method for that kind
of test.
Didn't include lower replication factor, as (for a single-shard mod.),
it's indistinguishable from modifying a reference table. So these all
test modifications which hit a single, replicated shard.
Fairly straightforward; verified that modifications fail atomically if
a worker is down or fails mid-transaction (i.e. all workers need to ack
modifications to reference tables in order to persist changes).
Including several examples from #1926. I couldn't understand why the
recover_prepared_transactions "should be an error", and EXPLAIN has
changed since the original bug (so that it runs EXPLAINs in txns, I
think for EXPLAIN ANALYZE to not have side effects); other than that,
most of the reported bugs now error out rather than crash or return
an empty result set.
VACUUM runs outside of a transaction, so the failure modes for it are
somewhat straightforward, though ANALYZE runs in a 1pc transaction and
multi-table VACUUM can fail between statements (PG 11 and higher).
Tests various failure points during a multi-shard modification within
a transaction with multiple statements. Verifies three cases:
* Reference tables (single shard, many placements)
* Normal table with replication factor two
* Multi-shard table with no replication
In the replication-factor case, we expect shard health to be affected
in some transactions; most others fail the transaction entirely and
all we need verify is that no effects of the transaction are visible.
Had trouble testing the final PREPARE/COMMIT/ROLLBACK phase of the 2pc,
in particular because the error message produced includes the PID of
the backend, which is unpredictable.
Drop schema command fails in mx mode if there
is a partitioned table with active partitions.
This is due to fact that sql drop trigger receives
all the dropped objects including partitions. When
we call drop table on parent partition, it also drops
the partitions on the mx node. This causes the drop
table command on partitions to fail on mx node because
they are already dropped when the partition parent was
dropped.
With this work we did not require the table to exist on
worker_drop_distributed_table.
PG now allows foreign keys on partitioned tables.
Each foreign key constraint on partitioned table
is propagated down to partitions.
We used to create all constraints on shards when we are creating
a new shard, or when just simply moving a shard from one worker
to another. We also used the same logic when creating a copy of
coordinator table in mx node.
With this change we create the constraint on worker node only if
it is not an inherited constraint.
We used to set the execution mode in the truncate trigger. However,
when multiple tables are truncated with a single command, we could
set the execution mode very late. Instead, now set the execution mode
on the utility hook.
By setting the CPU tuple cost so high, we were triggering JIT. Instead,
we should use parallel_tuple_cost.
See: rhaas.blogspot.com/2018/06/using-forceparallelmode-correctly.html
With this commit, we all partitioned distributed tables with
replication factor > 1. However, we also have many restrictions.
In summary, we disallow all kinds of modifications (including DDLs)
on the partition tables. Instead, the user is allowed to run the
modifications over the parent table.
The necessity for such a restriction have two aspects:
- We need to acquire shard resource locks appropriately
- We need to handle marking partitions INVALID in case
of any failures. Note that, in theory, the parent table
should also become INVALID, which is too aggressive.
Reason for the failure is that PG11 introduced a new relation kind
RELKIND_PARTITIONED_INDEX to be used for partitioned indices.
We expanded our check to cover that case.
This commit uses *_walker instead of *_mutator for performance reasons.
Given that we're only updating a functionId in the tree, the approach
seems fine.
PG11 introduced PROCEDURE concept similar to FUNCTION
Procedure's allow committing/rolling back behavior.
This commmit adds regression tests for procedure calls.
With this commit, we implement two views that are very similar
to pg_stat_activity, but showing queries that are involved in
distributed queries:
- citus_dist_stat_activity: Shows all the distributed queries
- citus_worker_stat_activity: Shows all the queries on the shards
that are initiated by distributed queries.
Both views have the same columns in the outputs. In very basic terms, both of the views
are meant to provide some useful insights about the distributed
transactions within the cluster. As the names reveal, both views are similar to pg_stat_activity.
Also note that these views can be pretty useful on Citus MX clusters.
Note that when the views are queried from the worker nodes, they'd not show the distributed
transactions that are initiated from the coordinator node. The reason is that the worker
nodes do not know the host/port of the coordinator. Thus, it is advisable to query the
views from the coordinator.
If we bucket the columns that the views returns, we'd end up with the following:
- Hostnames and ports:
- query_hostname, query_hostport: The node that the query is running
- master_query_host_name, master_query_host_port: The node in the cluster
initiated the query.
Note that for citus_dist_stat_activity view, the query_hostname-query_hostport
is always the same with master_query_host_name-master_query_host_port. The
distinction is mostly relevant for citus_worker_stat_activity. For example,
on Citus MX, a users starts a transaction on Node-A, which starts worker
transactions on Node-B and Node-C. In that case, the query hostnames would be
Node-B and Node-C whereas the master_query_host_name would Node-A.
- Distributed transaction related things:
This is mostly the process_id, distributed transactionId and distributed transaction
number.
- pg_stat_activity columns:
These two views get all the columns from pg_stat_activity. We're basically joining
pg_stat_activity with get_all_active_transactions on process_id.
This test's output changes depending on which worker is
picked for explain (e.g., worker port in the output changes).
Given that the test is only aiming to ensure that CTEs inside
CTEs work fine in DML queries, it should be fine to get rid of
the EXPLAIN. The output is verified to be correct as well.
Marco Slot
Onder Kalaci
Nils Dijk
Nils Dijk
Hadi Moshayedi
Jason Petersen
Hadi Moshayedi
Murat Tuncer
velioglu
Brian Cloutier