Load data by using flink-connector-starrocks

This topic describes how to load data from Apache Flink® to StarRocks.


The flink-connector-jdbc tool provided by Apache Flink® may not meet your performance requirements in certain scenarios. Therefore we provide a new connector named flink-connector-starrocks, which can cache data and then load data at a time by using Stream Load.


To load data from Apache Flink® into StarRocks by using flink-connector-starrocks, perform the following steps:

  1. Download the source code of flink-connector-starrocks.

  2. Find a file named pom.xml. Add the following code snippet to pom.xml and replace x.x.x in the code snippet with the latest version number of flink-connector-starrocks.

        <!-- for flink-1.11, flink-1.12 -->
        <!-- for flink-1.13 -->
  3. Use one of the following methods to load data

    • Load data as raw JSON string streams.

      // -------- sink with raw json string stream --------
      fromElements(new String[]{
          "{\"score\": \"99\", \"name\": \"stephen\"}",
          "{\"score\": \"100\", \"name\": \"lebron\"}"
              // the sink options
                  .withProperty("jdbc-url", "jdbc:mysql://fe1_ip:query_port,fe2_ip:query_port,fe3_ip:query_port?xxxxx")
                  .withProperty("load-url", "fe1_ip:http_port;fe2_ip:http_port;fe3_ip:http_port")
                  .withProperty("username", "xxx")
                  .withProperty("password", "xxx")
                  .withProperty("table-name", "xxx")
                  .withProperty("database-name", "xxx")
                  .withProperty("sink.properties.format", "json")
                  .withProperty("sink.properties.strip_outer_array", "true")
    // -------- sink with stream transformation --------

    class RowData {

        public int score;

        public String name;

        public RowData(int score, String name) {





        new RowData[]{

            new RowData(99, "stephen"),

            new RowData(100, "lebron")




            // the table structure


                .field("score", DataTypes.INT())

                .field("name", DataTypes.VARCHAR(20))


            // the sink options


                .withProperty("jdbc-url", "jdbc:mysql://fe1_ip:query_port,fe2_ip:query_port,fe3_ip:query_port?xxxxx")

                .withProperty("load-url", "fe1_ip:http_port;fe2_ip:http_port;fe3_ip:http_port")

                .withProperty("username", "xxx")

                .withProperty("password", "xxx")

                .withProperty("table-name", "xxx")

                .withProperty("database-name", "xxx")

                .withProperty("sink.properties.format", "csv")  

                .withProperty("sink.properties.column_separator", "\\x01")

                .withProperty("sink.properties.row_delimiter", "\\x02")


            // set the slots with streamRowData

            (slots, streamRowData) -> {

                slots[0] = streamRowData.score;

                slots[1] = streamRowData.name;




- Load data as tables.  

    // create a table with `structure` and `properties`

    // Needed: Add `com.starrocks.connector.flink.table.StarRocksDynamicTableSinkFactory` to: `src/main/resources/META-INF/services/org.apache.flink.table.factories.Factory`



            "name VARCHAR," +

            "score BIGINT" +

        ") WITH ( " +

            "'connector' = 'starrocks'," +

            "'jdbc-url'='jdbc:mysql://fe1_ip:query_port,fe2_ip:query_port,fe3_ip:query_port?xxxxx'," +

            "'load-url'='fe1_ip:http_port;fe2_ip:http_port;fe3_ip:http_port'," +

            "'database-name' = 'xxx'," +

            "'table-name' = 'xxx'," +

            "'username' = 'xxx'," +

            "'password' = 'xxx'," +

            "'sink.buffer-flush.max-rows' = '1000000'," +

            "'sink.buffer-flush.max-bytes' = '300000000'," +

            "'sink.buffer-flush.interval-ms' = '5000'," +

            "'sink.properties.column_separator' = '\\x01'," +

            "'sink.properties.row_delimiter' = '\\x02'," +

            "'sink.max-retries' = '3'" +

            "'sink.properties.*' = 'xxx'" + // stream load properties like `'sink.properties.columns' = 'k1, v1'`



The following table describes the sink options that you can configure when you load data as tables.

OptionRequiredDefault valueData typeDescription
connectorYesNONESTRINGThe connector that you want to use. The value must be starrocks.
jdbc-urlYesNONESTRINGThe URL that is used to query data from StarRocks.
load-urlYesNONESTRINGThe URL that is used to load all data in a time. Format: fe_ip:http_port;fe_ip:http_port.
database-nameYesNONESTRINGThe name of the StarRocks database into which you want to load data.
table-nameYesNONESTRINGThe name of the table that you want to use to load data into StarRocks.
usernameYesNONESTRINGThe username of the account that you want to use to load data into StarRocks.
passwordYesNONESTRINGThe password of the preceding account.
sink.semanticNoat-least-onceSTRINGThe semantics that is supported by your sink. Valid values: at-least-once and exactly-once. If you specify the value as exactly-once, sink.buffer-flush.max-bytes, sink.buffer-flush.max-bytes, and sink.buffer-flush.interval-ms are invalid.
sink.buffer-flush.max-bytesNo94371840(90M)STRINGThe maximum size of data that can be loaded into StarRocks at a time. Valid values: 64 MB to 10 GB.
sink.buffer-flush.max-rowsNo500000STRINGThe maximum number of rows that can be loaded into StarRocks at a time. Valid values: 64000 to 5000000.
sink.buffer-flush.interval-msNo300000STRINGThe interval at which data is flushed. Valid values: 1000 to 3600000. Unit: ms.
sink.max-retriesNo1STRINGThe number of times that the system retries to perform the Stream Load. Valid values: 0 to 10.
sink.connect.timeout-msNo1000STRINGThe period of time after which the stream load times out. Valid values: 100 to 60000. Unit: ms.
sink.properties.*NoNONESTRINGThe properties of the stream load. The properties include k1, k2, and k3.

Usage notes

When you load data from Apache Flink® into StarRocks, take note of the following points:

  • If you specify the exactly-once semantics, the two-phase commit (2PC) protocol must be supported to ensure efficient data loading. StarRocks does not support this protocol. Therefore we need to rely on Apache Flink® to achieve exactly-once. The overall process is as follows:

    1. Save data and its label at each checkpoint that is completed at a specific checkpoint interval.

    2. After data and labels are saved, block the flushing of data cached in the state at the first invoke after each checkpoint is completed.

      If StarRocks unexpectedly exits, the operators for Apache Flink® sink streaming are blocked for a long time and Apache Flink® issues a monitoring alert or shuts down.

  • By default, data is loaded in the CSV format. You can set the sink.properties.row_delimiter parameter to \\x02 to specify a row separator and set the sink.properties.column_separator parameter to \\x01 to specify a column separator.

  • If data loading pauses, you can increase the memory of the Flink task.

  • If the preceding code runs as expected and StarRocks can receive data, but the data loading fails, check whether your machine can access the HTTP port of the backends (BEs) in your StarRocks cluster. If you can successfully ping the HTTP port returned by the execution of the SHOW BACKENDS command in your StarRocks cluster, your machine can access the HTTP port of the backends (BEs) in your StarRocks cluster. For example, a machine has a public IP address and a private IP address, the HTTP ports of frontends (FEs) and BEs can be accessed through the public IP address of the FEs and BEs, the IP address that is bounded with your StarRocks cluster is the private IP address, and the value of loadurl for the Flink task is the HTTP port of the public IP address of the FEs. The FEs forwards the data loading task to the private IP address of the BEs. In this example, if the machine cannot ping the private IP address of the BEs, the data loading fails.