在Flink SQL中批处理读取Kafka中的数据,可以使用以下步骤:

  1. 导入所需的依赖库:
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-connector-kafka_2.11</artifactId>
    <version>1.13.0</version>
</dependency>
  1. 创建一个Flink批处理作业,并设置执行环境:
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
  1. 创建一个TableEnvironment,用于执行SQL查询:
BatchTableEnvironment tEnv = BatchTableEnvironment.create(env);
  1. 定义Kafka连接属性:
Properties properties = new Properties();
properties.setProperty("bootstrap.servers", "localhost:9092");
properties.setProperty("group.id", "flink-group");
  1. 注册Kafka表:
String kafkaSourceDDL = "CREATE TABLE kafka_source (\n" +
        "  field1 STRING,\n" +
        "  field2 INT\n" +
        ") WITH (\n" +
        "  'connector' = 'kafka',\n" +
        "  'topic' = 'input-topic',\n" +
        "  'properties.bootstrap.servers' = 'localhost:9092',\n" +
        "  'properties.group.id' = 'flink-group',\n" +
        "  'format' = 'json'\n" +
        ")";
tEnv.executeSql(kafkaSourceDDL);
  1. 执行SQL查询:
String query = "SELECT field1, field2 FROM kafka_source";
Table result = tEnv.sqlQuery(query);
  1. 将查询结果转换为DataSet:
DataSet<Row> resultSet = tEnv.toDataSet(result, Row.class);
  1. 打印结果:
resultSet.print();
  1. 提交作业:
env.execute("Kafka Batch Processing");

以上步骤将创建一个Flink批处理作业,将Kafka中的数据读取到DataSet中,并打印结果。请根据实际情况修改Kafka连接属性和SQL查询语句

Flinksql批处理如何读取Kafka中的数据

原文地址: https://www.cveoy.top/t/topic/iuOF 著作权归作者所有。请勿转载和采集!

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