The reason we should use ActiveReadableNodeList instead of ActiveReadableNonCoordinatorNodeList is that if coordinator is added to cluster as a worker, it should be counted as well. Otherwise if there is only coordinator in the cluster, the count will be 0, hence we get a warning.
In MultiTaskTrackerExecute, we should connect to coordinator if it is
added to the cluster because it will also be assigned tasks.
ActiveReadableWorkerNodeList doesn't include coordinator, however if
coordinator is added as a worker, we should also include that while
planning. The current methods are very easily misusable and this
requires a refactoring to make the distinction between methods that
include coordinator and that don't very explicit as they can introduce
subtle/major bugs pretty easily.
We were using ALL_WORKERS TargetWorkerSet while sending temporary schema
creation and cleanup. We(well mostly I) thought that ALL_WORKERS would also include coordinator when it is added as a worker. It turns out that it was FILTERING OUT the coordinator even if it is added as a worker to the cluster.
So to have some context here, in repartitions, for each jobId we create
(at least we were supposed to) a schema in each worker node in the cluster. Then we partition each shard table into some intermediate files, which is called the PARTITION step. So after this partition step each node has some intermediate files having tuples in those nodes. Then we fetch the partition files to necessary worker nodes, which is called the FETCH step. Then from the files we create intermediate tables in the temporarily created schemas, which is called a MERGE step. Then after evaluating the result, we remove the temporary schemas(one for each job ID in each node) and files.
If node 1 has file1, and node 2 has file2 after PARTITION step, it is
enough to either move file1 from node1 to node2 or vice versa. So we
prune one of them.
In the MERGE step, if the schema for a given jobID doesn't exist, the
node tries to use the `public` schema if it is a superuser, which is
actually added for testing in the past.
So when we were not sending schema creation comands for each job ID to
the coordinator(because we were using ALL_WORKERS flag, and it doesn't
include the coordinator), we would basically not have any schemas for
repartitions in the coordinator. The PARTITION step would be executed on
the coordinator (because the tasks are generated in the planner part)
and it wouldn't give us any error because it doesn't have anything to do
with the temporary schemas(that we didn't create). But later two things
would happen:
- If by chance the fetch is pruned on the coordinator side, we the other
nodes would fetch the partitioned files from the coordinator and execute
the query as expected, because it has all the information.
- If the fetch tasks are not pruned in the coordinator, in the MERGE
step, the coordinator would either error out saying that the necessary
schema doesn't exist, or it would try to create the temporary tables
under public schema ( if it is a superuser). But then if we had the same
task ID with different jobID it would fail saying that the table already
exists, which is an error we were getting.
In the first case, the query would work okay, but it would still not do
the cleanup, hence we would leave the partitioned files from the
PARTITION step there. Hence ensure_no_intermediate_data_leak would fail.
To make things more explicit and prevent such bugs in the future,
ALL_WORKERS is named as ALL_NON_COORD_WORKERS. And a new flag to return
all the active nodes is added as ALL_DATA_NODES. For repartition case,
we don't use the only-reference table nodes but this version makes the
code simpler and there shouldn't be any significant performance issue
with that.
DESCRIPTION: Force aliases in deparsing for queries with anonymous column references
Fixes: #3985
The root cause has todo with discrepancies in the query tree we create. I think in the future we should spend some time on categorising all changes we made to ruleutils and see if we can change the data structure `query` we pass to the deparser to have an actual valid postgres query for the deparser to render.
For now the fix is to keep track, besides changing the names of the entries in the target list, also if we have a reference to an anonymous columns. If there are anonymous columns we set the `printaliases` flag to true which forces the deparser to add the aliases.
Static analysis found an issue where we could dereference `NULL`, because
`CreateDummyPlacement` could return `NULL` when there were no workers. This
PR changes it so that it never returns `NULL`, which was intended by
@marcocitus when doing this change: https://github.com/citusdata/citus/pull/3887/files#r438136433
While adding tests for citus on a single node I also added some more basic
tests and it turns out we error out on repartition joins. This has been
present since `shouldhaveshards` was introduced and is not trivial to fix.
So I created a separate issue for this: https://github.com/citusdata/citus/issues/3996
I recently forgot to add tests to a schedule in two of my PRs. One of
these was caught by review, but the other one was not. This adds a
script to causes CI to ensure that each test in the repo is included in
at least one schedule.
Three tests were found that were currently not part of a schedule. This PR
adds those three tests to a schedule as well and it also fixes some small
issues with these tests.
It was possible to get an assertion error, if a DML command was
cancelled that opened a connection and then "ROLLBACK TO SAVEPOINT" was
used to continue the transaction. The reason for this was that canceling
the transaction might leave the `claimedExclusively` flag on for (some
of) it's connections.
This caused an assertion failure because `CanUseExistingConnection`
would return false and a new connection would be opened, and then there
would be two connections doing DML for the same placement. Which is
disallowed. That this situation caused an assertion failure instead of
an error, means that without asserts this could possibly result in some
visibility bugs, similar to the ones described
https://github.com/citusdata/citus/issues/3867
This is so we don't need to calculate it twice in
insert_select_executor.c and multi_explain.c, which can
cause discrepancy if an update in one of them is not
reflected in the other site.
* Not set TaskExecution with adaptive executor
Adaptive executor is using a utility method from task tracker for
repartition joins, however adaptive executor doesn't need taskExecution.
It is only used by task tracker. This causes a problem when explain
analyze is used because what taskExecution is pointing to might be
random.
We solve this by not setting taskExecution from adaptive executor. So it
will stay NULL as set by CreateTask.
* use same memory context as task for taskExecution
Co-authored-by: Jelte Fennema <github-tech@jeltef.nl>
In #3901 the "Data received from worker(s)" sections were added to EXPLAIN
ANALYZE. After merging @pykello posted some review comments. This addresses
those comments as well as fixing a other issues that I found while addressing
them. The things this does:
1. Fix `EXPLAIN ANALYZE EXECUTE p1` to not increase received data on every
execution
2. Fix `EXPLAIN ANALYZE EXECUTE p1(1)` to not return 0 bytes as received data
allways.
3. Move `EXPLAIN ANALYZE` specific logic to `multi_explain.c` from
`adaptive_executor.c`
4. Change naming of new explain sections to `Tuple data received from node(s)`.
Firstly because a task can reference the coordinator too, so "worker(s)" was
incorrect. Secondly to indicate that this is tuple data and not all network
traffic that was performed.
5. Rename `totalReceivedData` in our codebase to `totalReceivedTupleData` to
make it clearer that it's a tuple data counter, not all network traffic.
6. Actually add `binary_protocol` test to `multi_schedule` (woops)
7. Fix a randomly failing test in `local_shard_execution.sql`.
Sadly this does not actually work yet for binary protocol data, because
when doing EXPLAIN ANALYZE we send two commands at the same time. This
means we cannot use `SendRemoteCommandParams`, and thus cannot use the
binary protocol. This can still be useful though when using the text
protocol, to find out that a lot of data is being sent.
Due to the problem described in #3908 we don't cover the tdigest integration (and other extensions) on CI.
Due to this a bug got in the patch due to a change in `EXPLAIN VERBOSE` being merged concurrently with the tdigest integration. This PR fixes the test output that missed the newly added information.
* Insert select with master query
* Use relid to set custom_scan_tlist varno
* Reviews
* Fixes null check
Co-authored-by: Marco Slot <marco.slot@gmail.com>
This can save a lot of data to be sent in some cases, thus improving
performance for which inter query bandwidth is the bottleneck.
There's some issues with enabling this as default, so that's currently not done.
DESCRIPTION: Adds support to partially push down tdigest aggregates
tdigest extensions: https://github.com/tvondra/tdigest
This PR implements the partial pushdown of tdigest calculations when possible. The extension adds a tdigest type which can be combined into the same structure. There are several aggregate functions that can be used to get;
- a quantile
- a list of quantiles
- the quantile of a hypothetical value
- a list of quantiles for a list of hypothetical values
These function can work both on values or tdigest types.
Since we can create tdigest values either by combining them, or based on a group of values we can rewrite the aggregates in such a way that most of the computation gets delegated to the compute on the shards. This both speeds up the percentile calculations because the values don't have to be sorted while at the same time making the transfer size from the shards to the coordinator significantly less.
We still recursively plan some cases, eg:
- INSERTs
- SELECT FOR UPDATE when reference tables in query
- Everything must be same single shard & replication model
We wrap worker tasks in worker_save_query_explain_analyze() so we can fetch
their explain output later by a call worker_last_saved_explain_analyze().
Fixes#3519Fixes#2347Fixes#2613Fixes#621
Implements worker_save_query_explain_analyze and worker_last_saved_explain_analyze.
worker_save_query_explain_analyze executes and returns results of query while
saving its EXPLAIN ANALYZE to be fetched later.
worker_last_saved_explain_analyze returns the saved EXPLAIN ANALYZE result.
Append IF NOT EXISTS to CREATE SERVER commands generated by
pg_get_serverdef_string function when deparsing an existing server
object that a foreign table depends.
Sait Talha Nisanci
Nils Dijk
Hadi Moshayedi
Jelte Fennema
Philip Dubé
Marco Slot
Onur Tirtir
Hanefi Önaldı
Halil Ozan Akgül
Onder Kalaci