With this commit, fix_partition_shard_index_names()
works significantly faster.
For example,
32 shards, 365 partitions, 5 indexes drop from ~120 seconds to ~44 seconds
32 shards, 1095 partitions, 5 indexes drop from ~600 seconds to ~265 seconds
`queryStringList` can be really long, because it may contain #partitions * #indexes entries.
Before this change, we were actually going through the executor where each command
in the query string triggers 1 round trip per entry in queryStringList.
The aim of this commit is to avoid the round-trips by creating a single query string.
I first simply tried sending `q1;q2;..;qn` . However, the executor is designed to
handle `q1;q2;..;qn` type of query executions via the infrastructure mentioned
above (e.g., by tracking the query indexes in the list and doing 1 statement
per round trip).
One another option could have been to change the executor such that only track
the query index when `queryStringList` is provided not with queryString
including multiple `;`s . That is (a) more work (b) could cause weird edge
cases with failure handling (c) felt like coding a special case in to the executor
This UDF coordinates connectivity checks accross the whole cluster.
This UDF gets the list of active readable nodes in the cluster, and
coordinates all connectivity checks in sequential order.
The algorithm is:
for sourceNode in activeReadableWorkerList:
c = connectToNode(sourceNode)
for targetNode in activeReadableWorkerList:
result = c.execute(
"SELECT citus_check_connection_to_node(targetNode.name,
targetNode.port")
emit sourceNode.name,
sourceNode.port,
targetNode.name,
targetNode.port,
result
- result -> true -> connection attempt from source to target succeeded
- result -> false -> connection attempt from source to target failed
- result -> NULL -> connection attempt from the current node to source node failed
I suggest you use the following query to get an overview on the connectivity:
SELECT bool_and(COALESCE(result, false))
FROM citus_check_cluster_node_health();
Whenever this query returns false, there is a connectivity issue, check in detail.
To run tests in parallel use:
```bash
make check-arbitrary-configs parallel=4
```
To run tests sequentially use:
```bash
make check-arbitrary-configs parallel=1
```
To run only some configs:
```bash
make check-arbitrary-base CONFIGS=CitusSingleNodeClusterConfig,CitusSmallSharedPoolSizeConfig
```
To run only some test files with some config:
```bash
make check-arbitrary-base CONFIGS=CitusSingleNodeClusterConfig EXTRA_TESTS=dropped_columns_1
```
To get a deterministic run, you can give the random's seed:
```bash
make check-arbitrary-configs parallel=4 seed=12312
```
The `seed` will be in the output of the run.
In our regular regression tests, we can see all the details about either planning or execution but this means
we need to run the same query under different configs/cluster setups again and again, which is not really maintanable.
When we don't care about the internals of how planning/execution is done but the correctness, especially with different configs
this infrastructure can be used.
With `check-arbitrary-configs` target, the following happens:
- a bunch of configs are loaded, which are defined in `config.py`. These configs have different settings such as different shard count, different citus settings, postgres settings, worker amount, or different metadata.
- For each config, a separate data directory is created for tests in `tmp_citus_test` with the config's name.
- For each config, `create_schedule` is run on the coordinator to setup the necessary tables.
- For each config, `sql_schedule` is run. `sql_schedule` is run on the coordinator if it is a non-mx cluster. And if it is mx, it is either run on the coordinator or a random worker.
- Tests results are checked if they match with the expected.
When tests results don't match, you can see the regression diffs in a config's datadir, such as `tmp_citus_tests/dataCitusSingleNodeClusterConfig`.
We also have a PostgresConfig which runs all the test suite with Postgres.
By default configs use regular user, but we have a config to run as a superuser as well.
So the infrastructure tests:
- Postgres vs Citus
- Mx vs Non-Mx
- Superuser vs regular user
- Arbitrary Citus configs
When you want to add a new test, you can add the create statements to `create_schedule` and add the sql queries to `sql_schedule`.
If you are adding Citus UDFs that should be a NO-OP for Postgres, make sure to override the UDFs in `postgres.sql`.
You can add your new config to `config.py`. Make sure to extend either `CitusDefaultClusterConfig` or `CitusMXBaseClusterConfig`.
On the CI, upon a failure, all logfiles will be uploaded as artifacts, so you can check the artifacts tab.
All the regressions will be shown as part of the job on CI.
In your local, you can check the regression diffs in config's datadirs as in `tmp_citus_tests/dataCitusSingleNodeClusterConfig`.
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