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Flink CDC有做过MYSQL -> HIVE 的同步吗?

Flink CDC有做过MYSQL -> HIVE 的同步吗??image.png

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真的很搞笑 2023-10-02 06:56:23 210 0
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  • 存在即是合理

    Flink CDC可以用于MySQL到Hive的数据同步。以下是一个示例:

    1. 首先,需要在pom.xml文件中添加Flink CDC和MySQL JDBC驱动的依赖项:
    <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-connector-mysql-cdc</artifactId>
        <version>2.1.0</version>
    </dependency>
    <dependency>
        <groupId>mysql</groupId>
        <artifactId>mysql-connector-java</artifactId>
        <version>8.0.23</version>
    </dependency>
    
    1. 然后,在Flink程序中创建源表和目标表:
    import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
    import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
    import org.apache.flink.table.api.DataTypes;
    import org.apache.flink.table.descriptors.*;
    import org.apache.flink.table.sources.DynamicTableSource;
    import org.apache.flink.table.sources.StreamTableSource;
    import org.apache.flink.types.Row;
    
    public class MySqlToHiveSync {
        public static void main(String[] args) throws Exception {
            // 创建流处理执行环境
            StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
            StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);
    
            // 创建源表,使用Flink CDC连接器从MySQL中读取数据
            String mySqlDdl = "CREATE TABLE my_sql_source (" +
                    " id INT NOT NULL," +
                    " name STRING," +
                    " age INT," +
                    " PRIMARY KEY (id) NOT ENFORCED" +
                    ") WITH (" +
                    " 'connector' = 'mysql-cdc'," +
                    " 'hostname' = 'localhost'," +
                    " 'port' = '3306'," +
                    " 'username' = 'root'," +
                    " 'password' = 'password'," +
                    " 'database-name' = 'test'," +
                    " 'table-name' = 'user'" +
                    ")";
            DynamicTableSource mySqlSource = new SourceTableFactory().createTableSource(mySqlDdl, new String[]{"id", "name", "age"}, new DataTypes[]{DataTypes.INT(), DataTypes.STRING(), DataTypes.INT()});
            tableEnv.registerTableSource("my_sql_source", mySqlSource);
    
            // 创建目标表,将数据写入Hive中
            String hiveDdl = "CREATE TABLE my_hive_sink (" +
                    " id INT," +
                    " name STRING," +
                    " age INT" +
                    ") STORED AS parquet TBLPROPERTIES ('parquet.compression'='SNAPPY') LOCATION '/user/hive/warehouse/my_hive_sink';";
            DynamicTableSink hiveSink = new SinkTableFactory().createTableSink(hiveDdl, new String[]{"id", "name", "age"}, new DataTypes[]{DataTypes.INT(), DataTypes.STRING(), DataTypes.INT()});
            tableEnv.registerTableSink("my_hive_sink", hiveSink);
    
            // 将源表中的数据插入到目标表中,并执行作业
            tableEnv.executeSql("INSERT INTO my_hive_sink SELECT * FROM my_sql_source");
        }
    }
    

    这个示例程序将从MySQL中的user表中读取数据,并将其插入到Hive中的my_hive_sink表中。请根据实际情况修改MySQL和Hive连接的配置信息。

    2023-10-23 15:09:51
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