SQL Client

Flink’s Table & SQL API makes it possible to work with queries written in the SQL language, but these queries need to be embedded within a table program that is written in either Java or Scala. Moreover, these programs need to be packaged with a build tool before being submitted to a cluster. This more or less limits the usage of Flink to Java/Scala programmers.

The SQL Client aims to provide an easy way of writing, debugging, and submitting table programs to a Flink cluster without a single line of Java or Scala code. The SQL Client CLI allows for retrieving and visualizing real-time results from the running distributed application on the command line.

Animated demo of the Flink SQL Client CLI running table programs on a cluster

Getting Started

This section describes how to setup and run your first Flink SQL program from the command-line.

The SQL Client is bundled in the regular Flink distribution and thus runnable out-of-the-box. It requires only a running Flink cluster where table programs can be executed. For more information about setting up a Flink cluster see the Cluster & Deployment part. If you simply want to try out the SQL Client, you can also start a local cluster with one worker using the following command:

  1. ./bin/start-cluster.sh

Starting the SQL Client CLI

The SQL Client scripts are also located in the binary directory of Flink. In the future, a user will have two possibilities of starting the SQL Client CLI either by starting an embedded standalone process or by connecting to a remote SQL Client Gateway. At the moment only the embedded mode is supported, and default mode is embedded. You can start the CLI by calling:

  1. ./bin/sql-client.sh

or explicitly use embedded mode:

  1. ./bin/sql-client.sh embedded

See SQL Client startup options below for more details.

Running SQL Queries

For validating your setup and cluster connection, you can enter the simple query below and press Enter to execute it.

  1. SET 'sql-client.execution.result-mode' = 'tableau';
  2. SET 'execution.runtime-mode' = 'batch';
  3. SELECT
  4. name,
  5. COUNT(*) AS cnt
  6. FROM
  7. (VALUES ('Bob'), ('Alice'), ('Greg'), ('Bob')) AS NameTable(name)
  8. GROUP BY name;

The SQL client will retrieve the results from the cluster and visualize them (you can close the result view by pressing the Q key):

  1. +-------+-----+
  2. | name | cnt |
  3. +-------+-----+
  4. | Alice | 1 |
  5. | Bob | 2 |
  6. | Greg | 1 |
  7. +-------+-----+

The SET command allows you to tune the job execution and the sql client behaviour. See SQL Client Configuration below for more details.

After a query is defined, it can be submitted to the cluster as a long-running, detached Flink job. The configuration section explains how to declare table sources for reading data, how to declare table sinks for writing data, and how to configure other table program properties.

Getting help

The documentation of the SQL client commands can be accessed by typing the HELP command.

See also the general SQL documentation.

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Configuration

SQL Client startup options

The SQL Client can be started with the following optional CLI commands. They are discussed in detail in the subsequent paragraphs.

  1. ./bin/sql-client.sh --help
  2. Mode "embedded" (default) submits Flink jobs from the local machine.
  3. Syntax: [embedded] [OPTIONS]
  4. "embedded" mode options:
  5. -f,--file <script file> Script file that should be executed.
  6. In this mode, the client will not
  7. open an interactive terminal.
  8. -h,--help Show the help message with
  9. descriptions of all options.
  10. -hist,--history <History file path> The file which you want to save the
  11. command history into. If not
  12. specified, we will auto-generate one
  13. under your user's home directory.
  14. -i,--init <initialization file> Script file that used to init the
  15. session context. If get error in
  16. execution, the sql client will exit.
  17. Notice it's not allowed to add query
  18. or insert into the init file.
  19. -j,--jar <JAR file> A JAR file to be imported into the
  20. session. The file might contain
  21. user-defined classes needed for the
  22. execution of statements such as
  23. functions, table sources, or sinks.
  24. Can be used multiple times.
  25. -l,--library <JAR directory> A JAR file directory with which every
  26. new session is initialized. The files
  27. might contain user-defined classes
  28. needed for the execution of
  29. statements such as functions, table
  30. sources, or sinks. Can be used
  31. multiple times.
  32. -pyarch,--pyArchives <arg> Add python archive files for job. The
  33. archive files will be extracted to
  34. the working directory of python UDF
  35. worker. For each archive file, a
  36. target directory be specified. If the
  37. target directory name is specified,
  38. the archive file will be extracted to
  39. a directory with the
  40. specified name. Otherwise, the
  41. archive file will be extracted to a
  42. directory with the same name of the
  43. archive file. The files uploaded via
  44. this option are accessible via
  45. relative path. '#' could be used as
  46. the separator of the archive file
  47. path and the target directory name.
  48. Comma (',') could be used as the
  49. separator to specify multiple archive
  50. files. This option can be used to
  51. upload the virtual environment, the
  52. data files used in Python UDF (e.g.:
  53. --pyArchives
  54. file:///tmp/py37.zip,file:///tmp/data
  55. .zip#data --pyExecutable
  56. py37.zip/py37/bin/python). The data
  57. files could be accessed in Python
  58. UDF, e.g.: f = open('data/data.txt',
  59. 'r').
  60. -pyexec,--pyExecutable <arg> Specify the path of the python
  61. interpreter used to execute the
  62. python UDF worker (e.g.:
  63. --pyExecutable
  64. /usr/local/bin/python3). The python
  65. UDF worker depends on Python 3.6+,
  66. Apache Beam (version == 2.27.0), Pip
  67. (version >= 7.1.0) and SetupTools
  68. (version >= 37.0.0). Please ensure
  69. that the specified environment meets
  70. the above requirements.
  71. -pyfs,--pyFiles <pythonFiles> Attach custom files for job.
  72. The standard resource file suffixes
  73. such as .py/.egg/.zip/.whl or
  74. directory are all supported. These
  75. files will be added to the PYTHONPATH
  76. of both the local client and the
  77. remote python UDF worker. Files
  78. suffixed with .zip will be extracted
  79. and added to PYTHONPATH. Comma (',')
  80. could be used as the separator to
  81. specify multiple files (e.g.:
  82. --pyFiles
  83. file:///tmp/myresource.zip,hdfs:///$n
  84. amenode_address/myresource2.zip).
  85. -pyreq,--pyRequirements <arg> Specify a requirements.txt file which
  86. defines the third-party dependencies.
  87. These dependencies will be installed
  88. and added to the PYTHONPATH of the
  89. python UDF worker. A directory which
  90. contains the installation packages of
  91. these dependencies could be specified
  92. optionally. Use '#' as the separator
  93. if the optional parameter exists
  94. (e.g.: --pyRequirements
  95. file:///tmp/requirements.txt#file:///
  96. tmp/cached_dir).
  97. -s,--session <session identifier> The identifier for a session.
  98. 'default' is the default identifier.
  99. -u,--update <SQL update statement> Deprecated Experimental (for testing
  100. only!) feature: Instructs the SQL
  101. Client to immediately execute the
  102. given update statement after starting
  103. up. The process is shut down after
  104. the statement has been submitted to
  105. the cluster and returns an
  106. appropriate return code. Currently,
  107. this feature is only supported for
  108. INSERT INTO statements that declare
  109. the target sink table.Please use
  110. option -f to submit update statement.

SQL Client Configuration

You can configure the SQL client by setting the options below, or any valid Flink configuration entry:

  1. SET 'key' = 'value';
KeyDefaultTypeDescription
sql-client.display.max-column-width

Streaming
30IntegerWhen printing the query results, this parameter determines the number of characters shown on screen before truncating.This only applies to columns with variable-length types (e.g. STRING) in streaming mode.Fixed-length types and all types in batch mode are printed using a deterministic column width
sql-client.execution.max-table-result.rows

Batch Streaming
1000000IntegerThe number of rows to cache when in the table mode. If the number of rows exceeds the specified value, it retries the row in the FIFO style.
sql-client.execution.result-mode

Batch Streaming
TABLE

Enum

Determines how the query result should be displayed.

Possible values:
  • “TABLE”: Materializes results in memory and visualizes them in a regular, paginated table representation.
  • “CHANGELOG”: Visualizes the result stream that is produced by a continuous query.
  • “TABLEAU”: Display results in the screen directly in a tableau format.
sql-client.verbose

Batch Streaming
falseBooleanDetermine whether to output the verbose output to the console. If set the option true, it will print the exception stack. Otherwise, it only output the cause.

SQL client result modes

The CLI supports three modes for maintaining and visualizing results.

The table mode materializes results in memory and visualizes them in a regular, paginated table representation. It can be enabled by executing the following command in the CLI:

  1. SET 'sql-client.execution.result-mode' = 'table';

The result of a query would then look like this, you can use the keys indicated at the bottom of the screen as well as the arrows keys to navigate and open the various records:

  1. name age isHappy dob height
  2. user1 20 true 1995-12-03 1.7
  3. user2 30 true 1972-08-02 1.89
  4. user3 40 false 1983-12-23 1.63
  5. user4 41 true 1977-11-13 1.72
  6. user5 22 false 1998-02-20 1.61
  7. user6 12 true 1969-04-08 1.58
  8. user7 38 false 1987-12-15 1.6
  9. user8 62 true 1996-08-05 1.82
  10. Q Quit + Inc Refresh G Goto Page N Next Page O Open Row
  11. R Refresh - Dec Refresh L Last Page P Prev Page

The changelog mode does not materialize results and visualizes the result stream that is produced by a continuous query consisting of insertions (+) and retractions (-).

  1. SET 'sql-client.execution.result-mode' = 'changelog';

The result of a query would then look like this:

  1. op name age isHappy dob height
  2. +I user1 20 true 1995-12-03 1.7
  3. +I user2 30 true 1972-08-02 1.89
  4. +I user3 40 false 1983-12-23 1.63
  5. +I user4 41 true 1977-11-13 1.72
  6. +I user5 22 false 1998-02-20 1.61
  7. +I user6 12 true 1969-04-08 1.58
  8. +I user7 38 false 1987-12-15 1.6
  9. +I user8 62 true 1996-08-05 1.82
  10. Q Quit + Inc Refresh O Open Row
  11. R Refresh - Dec Refresh

The tableau mode is more like a traditional way which will display the results in the screen directly with a tableau format. The displaying content will be influenced by the query execution type (execution.type).

  1. SET 'sql-client.execution.result-mode' = 'tableau';

The result of a query would then look like this:

  1. +----+--------------------------------+-------------+---------+------------+--------------------------------+
  2. | op | name | age | isHappy | dob | height |
  3. +----+--------------------------------+-------------+---------+------------+--------------------------------+
  4. | +I | user1 | 20 | true | 1995-12-03 | 1.7 |
  5. | +I | user2 | 30 | true | 1972-08-02 | 1.89 |
  6. | +I | user3 | 40 | false | 1983-12-23 | 1.63 |
  7. | +I | user4 | 41 | true | 1977-11-13 | 1.72 |
  8. | +I | user5 | 22 | false | 1998-02-20 | 1.61 |
  9. | +I | user6 | 12 | true | 1969-04-08 | 1.58 |
  10. | +I | user7 | 38 | false | 1987-12-15 | 1.6 |
  11. | +I | user8 | 62 | true | 1996-08-05 | 1.82 |
  12. +----+--------------------------------+-------------+---------+------------+--------------------------------+
  13. Received a total of 8 rows

Note that when you use this mode with streaming query, the result will be continuously printed on the console. If the input data of this query is bounded, the job will terminate after Flink processed all input data, and the printing will also be stopped automatically. Otherwise, if you want to terminate a running query, just type CTRL-C in this case, the job and the printing will be stopped.

All these result modes can be useful during the prototyping of SQL queries. In all these modes, results are stored in the Java heap memory of the SQL Client. In order to keep the CLI interface responsive, the changelog mode only shows the latest 1000 changes. The table mode allows for navigating through bigger results that are only limited by the available main memory and the configured maximum number of rows (sql-client.execution.max-table-result.rows).

Attention Queries that are executed in a batch environment, can only be retrieved using the table or tableau result mode.

Initialize Session Using SQL Files

A SQL query needs a configuration environment in which it is executed. SQL Client supports the -i startup option to execute an initialization SQL file to setup environment when starting up the SQL Client. The so-called initialization SQL file can use DDLs to define available catalogs, table sources and sinks, user-defined functions, and other properties required for execution and deployment.

An example of such a file is presented below.

  1. -- Define available catalogs
  2. CREATE CATALOG MyCatalog
  3. WITH (
  4. 'type' = 'hive'
  5. );
  6. USE CATALOG MyCatalog;
  7. -- Define available database
  8. CREATE DATABASE MyDatabase;
  9. USE MyDatabase;
  10. -- Define TABLE
  11. CREATE TABLE MyTable(
  12. MyField1 INT,
  13. MyField2 STRING
  14. ) WITH (
  15. 'connector' = 'filesystem',
  16. 'path' = '/path/to/something',
  17. 'format' = 'csv'
  18. );
  19. -- Define VIEW
  20. CREATE VIEW MyCustomView AS SELECT MyField2 FROM MyTable;
  21. -- Define user-defined functions here.
  22. CREATE FUNCTION foo.bar.AggregateUDF AS myUDF;
  23. -- Properties that change the fundamental execution behavior of a table program.
  24. SET 'execution.runtime-mode' = 'streaming'; -- execution mode either 'batch' or 'streaming'
  25. SET 'sql-client.execution.result-mode' = 'table'; -- available values: 'table', 'changelog' and 'tableau'
  26. SET 'sql-client.execution.max-table-result.rows' = '10000'; -- optional: maximum number of maintained rows
  27. SET 'parallelism.default' = '1'; -- optional: Flink's parallelism (1 by default)
  28. SET 'pipeline.auto-watermark-interval' = '200'; --optional: interval for periodic watermarks
  29. SET 'pipeline.max-parallelism' = '10'; -- optional: Flink's maximum parallelism
  30. SET 'table.exec.state.ttl' = '1000'; -- optional: table program's idle state time
  31. SET 'restart-strategy' = 'fixed-delay';
  32. -- Configuration options for adjusting and tuning table programs.
  33. SET 'table.optimizer.join-reorder-enabled' = 'true';
  34. SET 'table.exec.spill-compression.enabled' = 'true';
  35. SET 'table.exec.spill-compression.block-size' = '128kb';

This configuration:

  • connects to Hive catalogs and uses MyCatalog as the current catalog with MyDatabase as the current database of the catalog,
  • defines a table MyTableSource that can read data from a CSV file,
  • defines a view MyCustomView that declares a virtual table using a SQL query,
  • defines a user-defined function myUDF that can be instantiated using the class name,
  • uses streaming mode for running statements and a parallelism of 1,
  • runs exploratory queries in the table result mode,
  • and makes some planner adjustments around join reordering and spilling via configuration options.

When using -i <init.sql> option to initialize SQL Client session, the following statements are allowed in an initialization SQL file:

  • DDL(CREATE/DROP/ALTER),
  • USE CATALOG/DATABASE,
  • LOAD/UNLOAD MODULE,
  • SET command,
  • RESET command.

When execute queries or insert statements, please enter the interactive mode or use the -f option to submit the SQL statements.

Attention If SQL Client receives errors during initialization, SQL Client will exit with error messages.

Dependencies

The SQL Client does not require setting up a Java project using Maven, Gradle, or sbt. Instead, you can pass the dependencies as regular JAR files that get submitted to the cluster. You can either specify each JAR file separately (using --jar) or define entire library directories (using --library). For connectors to external systems (such as Apache Kafka) and corresponding data formats (such as JSON), Flink provides ready-to-use JAR bundles. These JAR files can be downloaded for each release from the Maven central repository.

The full list of offered SQL JARs can be found on the connection to external systems page.

You can refer to the configuration section for information on how to configure connector and format dependencies.

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Use SQL Client to submit job

SQL Client allows users to submit jobs either within the interactive command line or using -f option to execute sql file.

In both modes, SQL Client supports to parse and execute all types of the Flink supported SQL statements.

Interactive Command Line

In interactive Command Line, the SQL Client reads user inputs and executes the statement terminated by a semicolon (;).

SQL Client will print success message if the statement is executed successfully. When getting errors, SQL Client will also print error messages. By default, the error message only contains the error cause. In order to print the full exception stack for debugging, please set the sql-client.verbose to true through command SET 'sql-client.verbose' = 'true';.

Execute SQL Files

SQL Client supports to execute a SQL script file with the -f option. SQL Client will execute statements one by one in the SQL script file and print execution messages for each executed statements. Once a statement fails, the SQL Client will exit and all the remaining statements will not be executed.

An example of such a file is presented below.

  1. CREATE TEMPORARY TABLE users (
  2. user_id BIGINT,
  3. user_name STRING,
  4. user_level STRING,
  5. region STRING,
  6. PRIMARY KEY (user_id) NOT ENFORCED
  7. ) WITH (
  8. 'connector' = 'upsert-kafka',
  9. 'topic' = 'users',
  10. 'properties.bootstrap.servers' = '...',
  11. 'key.format' = 'csv',
  12. 'value.format' = 'avro'
  13. );
  14. -- set sync mode
  15. SET 'table.dml-sync' = 'true';
  16. -- set the job name
  17. SET 'pipeline.name' = 'SqlJob';
  18. -- set the queue that the job submit to
  19. SET 'yarn.application.queue' = 'root';
  20. -- set the job parallelism
  21. SET 'parallelism.default' = '100';
  22. -- restore from the specific savepoint path
  23. SET 'execution.savepoint.path' = '/tmp/flink-savepoints/savepoint-cca7bc-bb1e257f0dab';
  24. INSERT INTO pageviews_enriched
  25. SELECT *
  26. FROM pageviews AS p
  27. LEFT JOIN users FOR SYSTEM_TIME AS OF p.proctime AS u
  28. ON p.user_id = u.user_id;

This configuration:

  • defines a temporal table source users that reads from a CSV file,
  • set the properties, e.g job name,
  • set the savepoint path,
  • submit a sql job that load the savepoint from the specified savepoint path.

Attention Compared to the interactive mode, SQL Client will stop execution and exits when there are errors.

Execute a set of SQL statements

SQL Client execute each INSERT INTO statement as a single Flink job. However, this is sometimes not optimal because some part of the pipeline can be reused. SQL Client supports STATEMENT SET syntax to execute a set of SQL statements. This is an equivalent feature with StatementSet in Table API. The STATEMENT SET syntax encloses one or more INSERT INTO statements. All statements in a STATEMENT SET block are holistically optimized and executed as a single Flink job. Joint optimization and execution allows for reusing common intermediate results and can therefore significantly improve the efficiency of executing multiple queries.

Syntax

  1. EXECUTE STATEMENT SET
  2. BEGIN
  3. -- one or more INSERT INTO statements
  4. { INSERT INTO|OVERWRITE <select_statement>; }+
  5. END;

Attention The statements of enclosed in the STATEMENT SET must be separated by a semicolon (;). The old syntax BEGIN STATEMENT SET; ... END; is deprecated, may be removed in the future version.

SQL CLI

  1. Flink SQL> CREATE TABLE pageviews (
  2. > user_id BIGINT,
  3. > page_id BIGINT,
  4. > viewtime TIMESTAMP,
  5. > proctime AS PROCTIME()
  6. > ) WITH (
  7. > 'connector' = 'kafka',
  8. > 'topic' = 'pageviews',
  9. > 'properties.bootstrap.servers' = '...',
  10. > 'format' = 'avro'
  11. > );
  12. [INFO] Execute statement succeed.
  13. Flink SQL> CREATE TABLE pageview (
  14. > page_id BIGINT,
  15. > cnt BIGINT
  16. > ) WITH (
  17. > 'connector' = 'jdbc',
  18. > 'url' = 'jdbc:mysql://localhost:3306/mydatabase',
  19. > 'table-name' = 'pageview'
  20. > );
  21. [INFO] Execute statement succeed.
  22. Flink SQL> CREATE TABLE uniqueview (
  23. > page_id BIGINT,
  24. > cnt BIGINT
  25. > ) WITH (
  26. > 'connector' = 'jdbc',
  27. > 'url' = 'jdbc:mysql://localhost:3306/mydatabase',
  28. > 'table-name' = 'uniqueview'
  29. > );
  30. [INFO] Execute statement succeed.
  31. Flink SQL> EXECUTE STATEMENT SET
  32. > BEGIN
  33. >
  34. > INSERT INTO pageview
  35. > SELECT page_id, count(1)
  36. > FROM pageviews
  37. > GROUP BY page_id;
  38. >
  39. > INSERT INTO uniqueview
  40. > SELECT page_id, count(distinct user_id)
  41. > FROM pageviews
  42. > GROUP BY page_id;
  43. >
  44. > END;
  45. [INFO] Submitting SQL update statement to the cluster...
  46. [INFO] SQL update statement has been successfully submitted to the cluster:
  47. Job ID: 6b1af540c0c0bb3fcfcad50ac037c862

SQL File

  1. CREATE TABLE pageviews (
  2. user_id BIGINT,
  3. page_id BIGINT,
  4. viewtime TIMESTAMP,
  5. proctime AS PROCTIME()
  6. ) WITH (
  7. 'connector' = 'kafka',
  8. 'topic' = 'pageviews',
  9. 'properties.bootstrap.servers' = '...',
  10. 'format' = 'avro'
  11. );
  12. CREATE TABLE pageview (
  13. page_id BIGINT,
  14. cnt BIGINT
  15. ) WITH (
  16. 'connector' = 'jdbc',
  17. 'url' = 'jdbc:mysql://localhost:3306/mydatabase',
  18. 'table-name' = 'pageview'
  19. );
  20. CREATE TABLE uniqueview (
  21. page_id BIGINT,
  22. cnt BIGINT
  23. ) WITH (
  24. 'connector' = 'jdbc',
  25. 'url' = 'jdbc:mysql://localhost:3306/mydatabase',
  26. 'table-name' = 'uniqueview'
  27. );
  28. EXECUTE STATEMENT SET
  29. BEGIN
  30. INSERT INTO pageview
  31. SELECT page_id, count(1)
  32. FROM pageviews
  33. GROUP BY page_id;
  34. INSERT INTO uniqueview
  35. SELECT page_id, count(distinct user_id)
  36. FROM pageviews
  37. GROUP BY page_id;
  38. END;

Execute DML statements sync/async

By default, SQL Client executes DML statements asynchronously. That means, SQL Client will submit a job for the DML statement to a Flink cluster, and not wait for the job to finish. So SQL Client can submit multiple jobs at the same time. This is useful for streaming jobs, which are long-running in general.

SQL Client makes sure that a statement is successfully submitted to the cluster. Once the statement is submitted, the CLI will show information about the Flink job.

  1. Flink SQL> INSERT INTO MyTableSink SELECT * FROM MyTableSource;
  2. [INFO] Table update statement has been successfully submitted to the cluster:
  3. Cluster ID: StandaloneClusterId
  4. Job ID: 6f922fe5cba87406ff23ae4a7bb79044

Attention The SQL Client does not track the status of the running Flink job after submission. The CLI process can be shutdown after the submission without affecting the detached query. Flink’s restart strategy takes care of the fault-tolerance. A query can be cancelled using Flink’s web interface, command-line, or REST API.

However, for batch users, it’s more common that the next DML statement requires waiting until the previous DML statement finishes. In order to execute DML statements synchronously, you can set table.dml-sync option to true in SQL Client.

  1. Flink SQL> SET 'table.dml-sync' = 'true';
  2. [INFO] Session property has been set.
  3. Flink SQL> INSERT INTO MyTableSink SELECT * FROM MyTableSource;
  4. [INFO] Submitting SQL update statement to the cluster...
  5. [INFO] Execute statement in sync mode. Please wait for the execution finish...
  6. [INFO] Complete execution of the SQL update statement.

Attention If you want to terminate the job, just type CTRL-C to cancel the execution.

Start a SQL Job from a savepoint

Flink supports to start the job with specified savepoint. In SQL Client, it’s allowed to use SET command to specify the path of the savepoint.

  1. Flink SQL> SET 'execution.savepoint.path' = '/tmp/flink-savepoints/savepoint-cca7bc-bb1e257f0dab';
  2. [INFO] Session property has been set.
  3. -- all the following DML statements will be restroed from the specified savepoint path
  4. Flink SQL> INSERT INTO ...

When the path to savepoint is specified, Flink will try to restore the state from the savepoint when executing all the following DML statements.

Because the specified savepoint path will affect all the following DML statements, you can use RESET command to reset this config option, i.e. disable restoring from savepoint.

  1. Flink SQL> RESET execution.savepoint.path;
  2. [INFO] Session property has been reset.

For more details about creating and managing savepoints, please refer to Job Lifecycle Management.

Define a Custom Job Name

SQL Client supports to define job name for queries and DML statements through SET command.

  1. Flink SQL> SET 'pipeline.name' = 'kafka-to-hive';
  2. [INFO] Session property has been set.
  3. -- all the following DML statements will use the specified job name.
  4. Flink SQL> INSERT INTO ...

Because the specified job name will affect all the following queries and DML statements, you can also use RESET command to reset this configuration, i.e. use default job names.

  1. Flink SQL> RESET pipeline.name;
  2. [INFO] Session property has been reset.

If the option pipeline.name is not specified, SQL Client will generate a default name for the submitted job, e.g. insert-into_<sink_table_name> for INSERT INTO statements.

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Limitations & Future

The current SQL Client only supports embedded mode. In the future, the community plans to extend its functionality by providing a REST-based SQL Client Gateway, see more in FLIP-24 and FLIP-91.

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