通过Flink导入数据

示例环境

本示例为使用Flink SQL、Flink CDC和DataStream三种方式将MySQL数据库test的employees表的数据，迁移至SelectDB的数据库test的employees表中。在实际使用中，请根据您的场景修改对应参数。示例环境如下：

• Flink 1.16单机环境

• Jav

• 目标库：test

• 目标表：employees

• 源数据库：test

• 源数据表：employees

环境准备

通过Flink SQL方式导入数据

1. 启动Flink SQL Client服务。

   在Flink安装目录的bin目录下，执行以下指令。

   ./sql-client.sh

2. 在Flink SQL Client上提交Flink任务，具体步骤如下。

   1. 创建MySQL源表。

      下述语句中，WITH后面的配置项为MySQL CDC Source的信息，配置项详情，请参见MySQL | Apache Flink CDC。

      CREATE TABLE employees_source (
          emp_no INT,
          birth_date DATE,
          first_name STRING,
          last_name STRING,
          gender STRING,
          hire_date DATE,
          PRIMARY KEY (`emp_no`) NOT ENFORCED
      ) WITH (
          'connector' = 'mysql-cdc',
          'hostname' = '127.0.0.1', 
          'port' = '3306',
          'username' = 'root',
          'password' = '****',
          'database-name' = 'test',
          'table-name' = 'employees'
      );

   2. 创建SelectDB结果表。

      下述语句中，WITH后面的配置项为SelectDB的信息，配置项详情，请参见Sink配置项。

      CREATE TABLE employees_sink (
          emp_no       INT ,
          birth_date   DATE,
          first_name   STRING,
          last_name    STRING,
          gender       STRING,
          hire_date    DATE
      ) 
      WITH (
        'connector' = 'doris',
        'fenodes' = 'selectdb-cn-****.selectdbfe.rds.aliyuncs.com:8080',
        'table.identifier' = 'test.employees',
        'username' = 'admin',
        'password' = '****'
      );

   3. 同步MySql源表数据至SelectDB结果表。

      INSERT INTO employees_sink SELECT * FROM employees_source;

3. 查看数据导入结果。

   连接SelectDB，执行以下语句，查看数据导入结果。

   SELECT * FROM test.employees;

通过Flink CDC方式

以下介绍如何使用Flink CDC将数据库的数据导入至SelectDB。

在Flink安装目录下，通过flink程序执行Flink CDC，语法如下：

<FLINK_HOME>/bin/flink run \
    -Dexecution.checkpointing.interval=10s \
    -Dparallelism.default=1 \
    -c org.apache.doris.flink.tools.cdc.CdcTools \
    lib/flink-doris-connector-1.16-1.5.2.jar \
    <mysql-sync-database|oracle-sync-database|postgres-sync-database|sqlserver-sync-database> \
    --database <selectdb-database-name> \
    [--job-name <flink-job-name>] \
    [--table-prefix <selectdb-table-prefix>] \
    [--table-suffix <selectdb-table-suffix>] \
    [--including-tables <mysql-table-name|name-regular-expr>] \
    [--excluding-tables <mysql-table-name|name-regular-expr>] \
    --mysql-conf <mysql-cdc-source-conf> [--mysql-conf <mysql-cdc-source-conf> ...] \
    --oracle-conf <oracle-cdc-source-conf> [--oracle-conf <oracle-cdc-source-conf> ...] \
    --sink-conf <doris-sink-conf> [--table-conf <doris-sink-conf> ...] \
    [--table-conf <selectdb-table-conf> [--table-conf <selectdb-table-conf> ...]]

<FLINK_HOME>/bin/flink run \
    -Dexecution.checkpointing.interval=10s \
    -Dparallelism.default=1 \
    -c org.apache.doris.flink.tools.cdc.CdcTools \
    lib/flink-doris-connector-1.16-1.5.2.jar \
    oracle-sync-database \
    --database test_db \
    --oracle-conf hostname=127.0.0.1 \
    --oracle-conf port=1521 \
    --oracle-conf username=admin \
    --oracle-conf password="password" \
    --oracle-conf database-name=XE \
    --oracle-conf schema-name=ADMIN \
    --including-tables "tbl1|test.*" \
    --sink-conf fenodes=selectdb-cn-****.selectdbfe.rds.aliyuncs.com:8080 \
    --sink-conf username=admin \
    --sink-conf password=****

<FLINK_HOME>/bin/flink run \
    -Dexecution.checkpointing.interval=10s \
    -Dparallelism.default=1 \
    -c org.apache.doris.flink.tools.cdc.CdcTools \
    lib/flink-doris-connector-1.16-1.5.2.jar \
    oracle-sync-database \
    --database test_db \
    --oracle-conf hostname=127.0.0.1 \
    --oracle-conf port=1521 \
    --oracle-conf username=admin \
    --oracle-conf password="password" \
    --oracle-conf database-name=XE \
    --oracle-conf schema-name=ADMIN \
    --including-tables "tbl1|test.*" \
    --sink-conf fenodes=selectdb-cn-****.selectdbfe.rds.aliyuncs.com:8080 \
    --sink-conf username=admin \
    --sink-conf password=****

<FLINK_HOME>/bin/flink run \
    -Dexecution.checkpointing.interval=10s \
    -Dparallelism.default=1 \
    -c org.apache.doris.flink.tools.cdc.CdcTools \
    lib/flink-doris-connector-1.16-1.5.2.jar \
    postgres-sync-database \
    --database db1\
    --postgres-conf hostname=127.0.0.1 \
    --postgres-conf port=5432 \
    --postgres-conf username=postgres \
    --postgres-conf password="123456" \
    --postgres-conf database-name=postgres \
    --postgres-conf schema-name=public \
    --postgres-conf slot.name=test \
    --postgres-conf decoding.plugin.name=pgoutput \
    --including-tables "tbl1|test.*" \
    --sink-conf fenodes=selectdb-cn-****.selectdbfe.rds.aliyuncs.com:8080 \
    --sink-conf username=admin \
    --sink-conf password=****

<FLINK_HOME>/bin/flink run \
    -Dexecution.checkpointing.interval=10s \
    -Dparallelism.default=1 \
    -c org.apache.doris.flink.tools.cdc.CdcTools \
    lib/flink-doris-connector-1.16-1.5.2.jar \
    sqlserver-sync-database \
    --database db1\
    --sqlserver-conf hostname=127.0.0.1 \
    --sqlserver-conf port=1433 \
    --sqlserver-conf username=sa \
    --sqlserver-conf password="123456" \
    --sqlserver-conf database-name=CDC_DB \
    --sqlserver-conf schema-name=dbo \
    --including-tables "tbl1|test.*" \
    --sink-conf fenodes=selectdb-cn-****.selectdbfe.rds.aliyuncs.com:8080 \
    --sink-conf username=admin \
    --sink-conf password=****

通过DataStream方式

1. 在Maven项目中，引入相关依赖。

   相关Maven依赖

   <properties>
           <maven.compiler.source>8</maven.compiler.source>
           <maven.compiler.target>8</maven.compiler.target>
           <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
           <scala.version>2.12</scala.version>
           <java.version>1.8</java.version>
           <flink.version>1.16.3</flink.version>
           <fastjson.version>1.2.62</fastjson.version>
           <scope.mode>compile</scope.mode>
       </properties>
       <dependencies>
           <!-- https://mvnrepository.com/artifact/com.google.guava/guava -->
           <dependency>
               <groupId>com.google.guava</groupId>
               <artifactId>guava</artifactId>
               <version>28.1-jre</version>
           </dependency>
   
           <dependency>
               <groupId>org.apache.commons</groupId>
               <artifactId>commons-lang3</artifactId>
               <version>3.14.0</version>
           </dependency>
   
           <dependency>
               <groupId>org.apache.doris</groupId>
               <artifactId>flink-doris-connector-1.16</artifactId>
               <version>1.5.2</version>
           </dependency>
   
           <dependency>
               <groupId>org.apache.flink</groupId>
               <artifactId>flink-table-api-scala-bridge_${scala.version}</artifactId>
               <version>${flink.version}</version>
           </dependency>
           <dependency>
               <groupId>org.apache.flink</groupId>
               <artifactId>flink-table-planner_${scala.version}</artifactId>
               <version>${flink.version}</version>
           </dependency>
           <dependency>
               <groupId>org.apache.flink</groupId>
               <artifactId>flink-streaming-scala_${scala.version}</artifactId>
               <version>${flink.version}</version>
           </dependency>
           <dependency>
               <groupId>org.apache.flink</groupId>
               <artifactId>flink-clients</artifactId>
               <version>${flink.version}</version>
           </dependency>
           <dependency>
               <groupId>org.apache.flink</groupId>
               <artifactId>flink-connector-jdbc</artifactId>
               <version>${flink.version}</version>
           </dependency>
           <dependency>
               <groupId>org.apache.flink</groupId>
               <artifactId>flink-connector-kafka</artifactId>
               <version>${flink.version}</version>
           </dependency>
           <dependency>
               <groupId>org.apache.doris</groupId>
               <artifactId>flink-doris-connector-1.16</artifactId>
               <version>1.5.2</version>
           </dependency>
   
           <dependency>
               <groupId>com.ververica</groupId>
               <artifactId>flink-sql-connector-mysql-cdc</artifactId>
               <version>2.4.2</version>
               <exclusions>
                   <exclusion>
                       <artifactId>flink-shaded-guava</artifactId>
                       <groupId>org.apache.flink</groupId>
                   </exclusion>
               </exclusions>
           </dependency>
   
           <dependency>
               <groupId>org.apache.flink</groupId>
               <artifactId>flink-runtime-web</artifactId>
               <version>${flink.version}</version>
           </dependency>
   
       </dependencies>

2. Java核心代码。

   下述代码中，MySql源表配置与SelectDB结果表配置的参数，与上述通过Flink SQL方式导入数据中的配置一一对应，详情请参见MySQL | Apache Flink CDC与Sink配置项。

   package org.example;
   
   import com.ververica.cdc.connectors.mysql.source.MySqlSource;
   import com.ververica.cdc.connectors.mysql.table.StartupOptions;
   import com.ververica.cdc.connectors.shaded.org.apache.kafka.connect.json.JsonConverterConfig;
   import com.ververica.cdc.debezium.JsonDebeziumDeserializationSchema;
   
   import org.apache.doris.flink.cfg.DorisExecutionOptions;
   import org.apache.doris.flink.cfg.DorisOptions;
   import org.apache.doris.flink.sink.DorisSink;
   import org.apache.doris.flink.sink.writer.serializer.JsonDebeziumSchemaSerializer;
   import org.apache.doris.flink.tools.cdc.mysql.DateToStringConverter;
   import org.apache.flink.api.common.eventtime.WatermarkStrategy;
   import org.apache.flink.streaming.api.datastream.DataStreamSource;
   import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
   
   import java.util.HashMap;
   import java.util.Map;
   import java.util.Properties;
   
   public class Main {
       public static void main(String[] args) throws Exception {
           StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
           env.setParallelism(1);
           env.enableCheckpointing(10000);
   
           Map<String, Object> customConverterConfigs = new HashMap<>();
           customConverterConfigs.put(JsonConverterConfig.DECIMAL_FORMAT_CONFIG, "numeric");
           JsonDebeziumDeserializationSchema schema =
                   new JsonDebeziumDeserializationSchema(false, customConverterConfigs);
           
           // MySql源表配置
           MySqlSource<String> mySqlSource = MySqlSource.<String>builder()
                   .hostname("rm-xxx.mysql.rds.aliyuncs***")
                   .port(3306)
                   .startupOptions(StartupOptions.initial())
                   .databaseList("db_test")
                   .tableList("db_test.employees")
                   .username("root")
                   .password("test_123")
                   .debeziumProperties(DateToStringConverter.DEFAULT_PROPS)
                   .deserializer(schema)
                   .serverTimeZone("Asia/Shanghai")
                   .build();
   
           // SelectDB 结果表配置
           DorisSink.Builder<String> sinkBuilder = DorisSink.builder();
           DorisOptions.Builder dorisBuilder = DorisOptions.builder();
           dorisBuilder.setFenodes("selectdb-cn-xxx-public.selectdbfe.rds.aliyunc****:8080")
                   .setTableIdentifier("db_test.employees")
                   .setUsername("admin")
                   .setPassword("test_123");
           DorisOptions dorisOptions = dorisBuilder.build();
   
           // 配置Stream Load相关参数 sink.properties
           Properties properties = new Properties();
           properties.setProperty("format", "json");
           properties.setProperty("read_json_by_line", "true");
           DorisExecutionOptions.Builder executionBuilder = DorisExecutionOptions.builder();
           executionBuilder.setStreamLoadProp(properties);
   
           sinkBuilder.setDorisExecutionOptions(executionBuilder.build())
                   .setSerializer(JsonDebeziumSchemaSerializer.builder().setDorisOptions(dorisOptions).build()) //serialize according to string
                   .setDorisOptions(dorisOptions);
   
           DataStreamSource<String> dataStreamSource = env.fromSource(mySqlSource, WatermarkStrategy.noWatermarks(), "MySQL Source");
           dataStreamSource.sinkTo(sinkBuilder.build());
           env.execute("MySQL to SelectDB");
       }
   }

使用Flink SQL更新部分列数据

-- enable checkpoint
SET 'execution.checkpointing.interval' = '10s';

CREATE TABLE cdc_mysql_source (
   id INT
  ,name STRING
  ,bank STRING
  ,age INT
  ,PRIMARY KEY (id) NOT ENFORCED
) WITH (
 'connector' = 'mysql-cdc',
 'hostname' = '127.0.0.1',
 'port' = '3306',
 'username' = 'root',
 'password' = 'password',
 'database-name' = 'database',
 'table-name' = 'table'
);

CREATE TABLE selectdb_sink (
    id INT,
    name STRING,
    bank STRING,
    age INT
) 
WITH (
  'connector' = 'doris',
  'fenodes' = 'selectdb-cn-****.selectdbfe.rds.aliyuncs.com:8080',
  'table.identifier' = 'database.table',
  'username' = 'admin',
  'password' = '****',
  'sink.properties.format' = 'json',
  'sink.properties.read_json_by_line' = 'true',
  'sink.properties.columns' = 'id,name,bank,age',
  'sink.properties.partial_columns' = 'true' -- 开启部分列更新
);


INSERT INTO selectdb_sink SELECT id,name,bank,age FROM cdc_mysql_source;

使用Flink SQL根据指定列删除数据

在数据源为CDC的场景中，Doris Sink会根据RowKind来区分事件的类型，对隐藏列__DORIS_DELETE_SIGN__进行赋值以达到删除的目的。在数据源为Kafka消息的场景中，Doris Sink无法直接使用RowKind来区分操作类型，需要依赖消息中的特定字段来标记操作类型，比如{"op_type":"delete",data:{...}}，针对这类数据，希望将op_type=delete的数据删除掉。此时需要根据业务逻辑判断，显式地传入隐藏列的值。下面以Flink SQL方式为例，介绍如何根据Kafka数据中的特定字段删除SelectDB中的数据。

-- 比如数据: {"op_type":"delete",data:{"id":1,"name":"zhangsan"}}
CREATE TABLE KAFKA_SOURCE(
  data STRING,
  op_type STRING
) WITH (
  'connector' = 'kafka',
  ...
);

CREATE TABLE SELECTDB_SINK(
  id INT,
  name STRING,
  __DORIS_DELETE_SIGN__ INT
) WITH (
  'connector' = 'doris',
  'fenodes' = 'selectdb-cn-****.selectdbfe.rds.aliyuncs.com:8080',
  'table.identifier' = 'db.table',
  'username' = 'admin',
  'password' = '****',
  'sink.enable-delete' = 'false',        -- false表示不从RowKind获取事件类型
  'sink.properties.columns' = 'id, name, __DORIS_DELETE_SIGN__'  -- 显示指定stream load的导入列
);

INSERT INTO SELECTDB_SINK
SELECT json_value(data,'$.id') as id,
json_value(data,'$.name') as name, 
if(op_type='delete',1,0) as __DORIS_DELETE_SIGN__ 
FROM KAFKA_SOURCE;