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Quick Start

How to use​

The installation of the one-stop platform streampark-console has been introduced in detail in the previous chapter. In this chapter, let's see how to quickly deploy and run a job with streampark-console. The official structure and specification) and projects developed with streampark are well supported. Let's use streampark-quickstart to quickly start the journey of streampark-console

streampark-quickstart is a sample program for developing Flink by StreamPark. For details, please refer to:

Deploy DataStream tasks​

The following example demonstrates how to deploy a DataStream application

Deploy the FlinkSql task​

The following example demonstrates how to deploy a FlinkSql application

  • The flink sql used in the project demonstration is as follows
CREATE TABLE user_log (
    user_id VARCHAR,
    item_id VARCHAR,
    category_id VARCHAR,
    behavior VARCHAR,
    ts TIMESTAMP(3)
 ) WITH (
'connector' = 'kafka', -- Using the kafka connector
'properties.group.id' = 'group01' ,
'topic' = 'user_behavior',  -- kafka topic
'properties.bootstrap.servers'='kafka-1:9092,kafka-2:9092,kafka-3:9092',
'scan.startup.mode' = 'earliest-offset', -- Read from start offset
'format' = 'json'  -- The data source format is json
 );

CREATE TABLE pvuv_sink (
    dt VARCHAR,
    pv BIGINT,
    uv BIGINT,
    PRIMARY KEY (dt,pv,uv) NOT ENFORCED
 ) WITH (
'connector' = 'jdbc', -- using jdbc connector
'url' = 'jdbc:mysql://test-mysql:3306/test', -- jdbc url
'table-name' = 'pvuv_sink', -- Table Name
'username' = 'root', -- username
'password' = '123456', --password
'sink.buffer-flush.max-rows' = '1' -- Default 5000, changed to 1 for demonstration
 );

INSERT INTO pvuv_sink
SELECT
  DATE_FORMAT(ts, 'yyyy-MM-dd HH:00') dt,
  COUNT(*) AS pv,
  COUNT(DISTINCT user_id) AS uv
FROM user_log
GROUP BY DATE_FORMAT(ts, 'yyyy-MM-dd HH:00');
  • The maven dependencies are used as follows

<dependency>
    <groupId>mysql</groupId>
    <artifactId>mysql-connector-java</artifactId>
    <version>5.1.48</version>
</dependency>

<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-sql-connector-kafka_2.11</artifactId>
    <version>1.14.6</version>
</dependency>

<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-connector-jdbc_2.11</artifactId>
    <version>1.14.6</version>
</dependency>


  • The data sent by Kafka simulation is as follows

{"user_id": "543462", "item_id":"1715", "category_id": "1464116", "behavior": "pv", "ts":"2021-02-01 01:00:00"}
{"user_id": "662867", "item_id":"2244074","category_id":"1575622","behavior": "pv", "ts":"2021-02-01 01:00:00"}
{"user_id": "662867", "item_id":"2244074","category_id":"1575622","behavior": "pv", "ts":"2021-02-01 01:00:00"}
{"user_id": "662867", "item_id":"2244074","category_id":"1575622","behavior": "learning flink", "ts":"2021-02-01 01:00:00"}

Task start process​

The task startup flow chart is as follows


streampark-console submit task process

Regarding the concept of the project, Development Mode, savepoint, NoteBook, custom jar management, task release, task recovery, parameter configuration, parameter comparison, multi-version management and more tutorials and documents will be continuously updated. ..