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With the efforts in FLIP-24 and FLIP-91, Flink SQL client supports submitting SQL jobs but lacks further support for their lifecycles afterward which is crucial for streaming use cases. That means Flink SQL client users have to turn to other clients (e.g. CLI) or APIs (e.g. REST API) to manage the jobs, like triggering savepoints or canceling queries, which makes the user experience of SQL client incomplete.
Therefore, this proposal aims to complete the capability of SQL client by adding query lifecycle statements. With these statements, users could manage SQL jobs and savepoints through pure SQL in SQL client.
- New Flink SQL Statements
The overall architecture of Flink SQL client/gateway would be as follow:
Most parts are remained unchanged, only SQL Parser and Planner need to be modified to support new statements, and a new component ClusterClientFactory is introduced in Executor to enable direct access to Flink clusters.
SQL Job Lifecycle Statements
SQL job lifecycle statements mainly interact with deployments (clusters and jobs) and have few connections with Table/SQL concepts, thus it’d be better to keep them SQL-client-only like jar statements.
- The keyword for Flink SQL jobs was `QUERY`, and now is updated as `JOB`.
- All the <job_id> and <savepoint_path> should be string literals (wrapped in single quotes), otherwise it's hard to parse them.
SHOW RUNNING FLINK SQL JOBS
This statement lists the queries in the Flink cluster, which is similar to flink list in CLI.
The result contains four columns: job_id (namely Flink job ID), job_name, status, start/end time, duration, and a link to the job's web UI address.
STOP A RUNNING FLINK SQL JOB
This statement stops a non-terminated SQL, which is similar to `flink stop` and `flink cancel` in CLI.
The result would the savepoint path.
There're two related options to control the fine-grained behavior:
1. WITH SAVEPOINT
If specified, the stop statement stops a SQL job with a savepoint, which is similar to `flink stop` in CLI.
Otherwise, the stop statement stops a SQL job ungracefully, just like `flink cancel` In CLI. Since an ungrateful drop doesn’t trigger a savepoint, the result would be a simple OK, like the one returned by DDL.
2. WITH DRAIN
If specified, the stop statement stops a SQL job and increases the watermark to MAX_WATERMARK to trigger all the timers, which is similar to `flink stop .. --drain` in CLI.
CREATE A SAVEPOINT
This statement triggers savepoints for the specified SQL job, which is similar to `flink savepoint` in CLI.
The result would the savepoint path.
This statement shows all savepoints in a best-effort manner (since the savepoints are managed by users and outlive Flink clusters, the job manager may not know about all savepoints).
The result would be savepoint paths.
DROP A SAVEPOINT
This statement deletes the specified savepoint, which is similar to `flink savepoint –dispose` in CLI.
The result would be a simple OK.
COMPLETE USAGE EXAMPLE
SQL Parser & Planner
To support the new statements, we need to introduce new SQL operators for SQL parser and new SQL operations for the planner.
Executor would need to convert the query lifecycle operations into ClusterClient commands.
Cluster Client Command
ClusterClient#stopWithSavepoint | ClusterClient#cancel
In addition, to interact with the clusters, Executor should be able to create ClusterClient through ClusterClientFactory, thus a ClusterClientServiceLoader would be added to Executor.
The implementation plan would be simple:
- Support the new statements and operations in SQL parser and Planner.
- Extend Executor to support the new operations.
Compatibility, Deprecation, and Migration Plan
This FLIP introduces new SQL keywords, which may cause troubles for the existing SQLs. Users need to escape the new keywords if they use them as SQL identifiers.
The new keywords are:
- JOB (new)
- JOBS (new)
- STOP (new)
- DRAIN (new)
- SAVEPOINT (already reserved)
- SAVEPOINTS (already reserved)
Book Keep Query Status in SQL Gateway
An alternative approach to query monitoring is that the SQL client or gateway book keeps every query and is responsible for updating the query status through polling or callbacks. In that way, the query status is better maintained, and we wouldn’t lose track of the queries in cases that they’re cleaned up by the cluster or the cluster is unavailable.
However, there’re 2 major concerns:
- Table/SQL API should provide the same capabilities as its peer DataStream API, thus show queries statement implement should be aligned with flink list in CLI as well.
- Maintaining query status at the client/gateway side requires additional work but brings little extra user value, since the client/gateway doesn’t persist metadata at the moment.
Savepoint Syntax: SAVEPOINT / RELEASE SAVEPOINT
An alternative syntax of savepoints is like:
But there are mainly two concerns:
- Generally speaking, SAVEPOINT is more appropriate to be followed by a savepoint identifier instead of a job identifier.
- The statements are often used within database transaction blocks, so it would be kind of unnatural to be used alone.