You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 3 Next »

Status

Current state: "Under Discussion"

Discussion thread: TBD (<- link to https://mail-archives.apache.org/mod_mbox/flink-dev/)

JIRA: TBD

Released: <Flink Version>

Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).

Motivation

With the efforts in FLIP-24 and FLIP-91, Flink SQL client supports submitting queries 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 queries, 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 queries and savepoints through pure SQL in SQL client.

Public Interfaces

  • New Flink SQL Statements

Proposed Changes

Architecture Overview

The overall architecture of Flink SQL client 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.

Query Lifecycle Statements

Query 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.

SHOW QUERIES

SHOW QUERIES  statements list the queries in the Flink cluster, which is similar to flink list in CLI.

Syntax: SHOW QUERIES
SHOW QUERIES

The result contains three columns: query_id (namely Flink job id), query_name (namely job name), and status.

Result: SHOW QUERIES
+----------------------------------+-------------+----------|
|            query_id              | query_name  |  status  |
+----------------------------------+-------------+----------|
| cca7bc1061d61cf15238e92312c2fc20 |    query1   |  RUNNING |
| 0f6413c33757fbe0277897dd94485f04 |    query2   |  FAILED  |
+----------------------------------+-------------+----------|

STOP QUERY

STOP QUERY statements stop a non-terminated query, which is similar to `flink stop` in CLI. As stop command has a `--drain` option, we should introduce a table config like `sql-client.stop-with-drain` to support the same functionality.

Syntax: STOP QUERY
STOP QUERY <query_id>

The result would the savepoint path.

Result: STOP QUERY
+--------------------------------------------------------|
|            savepoint_path                              |
+--------------------------------------------------------|
| /tmp/flink-savepoints/savepoint-cca7bc-bb1e257f0dab    |
+--------------------------------------------------------|

CANCEL QUERY

CANCEL QUERY  statements cancel a non-terminated query, which is similar to `flink cancel` in CLI. 

Syntax: SHOW QUERIES
CANCEL QUERY <query_id>

Since CANCEL QUERY doesn’t trigger a savepoint, the result would be a simple OK, like the one returned by DDL.

TRIGGER SAVEPOINT

TRIGGER SAVEPOINT  statements trigger savepoints for the specified query, which is similar to `flink savepoint` in CLI.

Syntax: TRIGGER SAVEPOINT
TRIGGER SAVEPOINT <query_id>

The result would the savepoint path.

Result: TIGGER SAVEPOINT
+------------------------------------------------------|
|            savepoint_path                            |
+------------------------------------------------------|
| /tmp/flink-savepoints/savepoint-cca7bc-bb1e257f0dab  |
+------------------------------------------------------|

DISPOSE SAVEPOINT

DISPOSE SAVEPOINT statements delete the specified savepoint, which is similar to `flink savepoint –dispose` in CLI.

Syntax:

DISPOSE SAVEPOINT <savepoint_path>

Syntax: DISPOSE SAVEPOINT
DISPOSE SAVEPOINT <savepoint_path>

The result would be a simple OK.

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.

SQL operator

SQL operation

SqlShowQueries

ShowQueriesOperation

SqlStopQuery

StopQueryOperation

SqlCancelQuery

CancelQueryOperation

SqlTriggerSavepoint

TriggerSavepointOperation

SqlDisposeSavepoint

DisposeSavepointOperation

Executor

Executor would need to convert the query lifecycle operations into ClusterClient commands.

SQL operation

Cluster Client Command

ShowQueriesOperation

ClusterClient#listJobs

StopQueryOperation

ClusterClient#stoplWithSavepoint

CancelQueryOperation

ClusterClient#cancel

TriggerSavepointOperation

ClusterClient#triggerSavepoint

DisposeSavepointOperation

ClusterClient#disposeSavepoint

Implementation Plan

The implementation plan would be simple:

  1. Support the new statements and operations in SQL parser and Planner.
  2. Extend Executor to support the new operations.

Rejected Alternatives

An alternatives 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:

  1. 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. 
  2. 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.
  • No labels