> ClikHouse > 使用Flink SQL读取kafka数据并通过JDBC方式写入Clickhouse实时场景的简单实例

使用Flink SQL读取kafka数据并通过JDBC方式写入Clickhouse实时场景的简单实例

ClikHouse SenLin 5年前 (2020-02-22) 1780次浏览已收录 0个评论

使用Flink SQL读取kafka数据并通过JDBC方式写入Clickhouse实时场景的简单实例

说明

读取kafka数据并且经过ETL后，通过JDBC存入clickhouse中

代码

定义POJO类：

public class Student {  private int id;  private String name;  private String password;  private int age;  private String date;  //构造，setter 和 getter 省略 }

完整代码：

final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setParallelism(1);
final StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

//###############定义消费kafka source##############
Properties props = new Properties();
props.put("bootstrap.servers", "localhost:9092");
props.put("zookeeper.connect", "localhost:2181");
props.put("group.id", "metric-group");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer","org.apache.kafka.common.serialization.StringDeserializer");
props.put("auto.offset.reset", "latest");

tableEnv.connect(new Kafka().version("0.10")
        .topic("student").properties(props).startFromLatest())
        .withFormat(new Json().deriveSchema())
        .withSchema(new Schema().field("id", Types.INT())
                                .field("name", Types.STRING())
                                .field("password", Types.STRING())
                                .field("age", Types.INT())
                                .field("date", Types.STRING()))
        .inAppendMode()
        .registerTableSource("kafkaTable");
Table result = tableEnv.sqlQuery("SELECT * FROM " +  "kafkaTable");

//###############定义clickhouse JDBC sink##############
String targetTable = "clickhouse";
TypeInformation[] fieldTypes = {BasicTypeInfo.INT_TYPE_INFO
,BasicTypeInfo.STRING_TYPE_INFO
,BasicTypeInfo.STRING_TYPE_INFO
, BasicTypeInfo.INT_TYPE_INFO
, BasicTypeInfo.STRING_TYPE_INFO};

TableSink jdbcSink =  JDBCAppendTableSink
.builder()
.setDrivername("ru.yandex.clickhouse.ClickHouseDriver")
.setDBUrl("jdbc:clickhouse://localhost:8123")
.setQuery("insert into student_local(id, name, password, age, date) values(?, ?, ?, ?, ?)")
.setParameterTypes(fieldTypes)
.setBatchSize(15)
 .build();

tableEnv.registerTableSink(targetTable
,new String[]{"id","name", "password", "age", "date"},
 new TypeInformation[]{Types.INT(), Types.STRING()
, Types.STRING(), Types.INT(), Types.STRING()}, jdbcSink);

result.insertInto(targetTable);
env.execute("Flink add sink");

POM：

<dependency>
     <groupId>org.apache.flink</groupId>
     <artifactId>flink-java</artifactId>
     <version>${flink.version}</version>
     <!--<scope>provided</scope>-->
 </dependency>
 <dependency>
     <groupId>org.apache.flink</groupId>
     <artifactId>flink-streaming-java_${scala.binary.version}</artifactId>
     <version>${flink.version}</version>
    <!-- <scope>provided</scope>-->
 </dependency>

 <dependency>
     <groupId>org.apache.flink</groupId>
     <artifactId>flink-streaming-scala_${scala.binary.version}</artifactId>
     <version>${flink.version}</version>
     <!-- <scope>provided</scope>-->
 </dependency>          
 <dependency>
     <groupId>ru.yandex.clickhouse</groupId>
     <artifactId>clickhouse-jdbc</artifactId>
     <version>0.2</version>
 </dependency>

 <dependency>
     <groupId>org.apache.httpcomponents</groupId>
     <artifactId>httpcore</artifactId>
     <version>4.4.4</version>
 </dependency>

 <dependency>
     <groupId>com.google.guava</groupId>
     <artifactId>guava</artifactId>
     <version>19.0</version>
 </dependency>

 <dependency>
     <groupId>org.apache.flink</groupId>
     <artifactId>flink-jdbc_${scala.binary.version}</artifactId>
     <version>${flink.version}</version>
 </dependency>
 <dependency>
     <groupId>org.apache.flink</groupId>
     <artifactId>flink-json</artifactId>
     <version>${flink.version}</version>
 </dependency>

 <!-- Either... -->
 <dependency>
     <groupId>org.apache.flink</groupId>
     <artifactId>flink-table-api-java-bridge_${scala.binary.version}</artifactId>
     <version>${flink.version}</version>
 </dependency>

 <!-- Add connector dependencies here. They must be in the default scope
     (compile). -->
 <!-- this is for kafka consuming -->
 <dependency>
     <groupId>org.apache.flink</groupId>
     <artifactId>flink-connector-kafka-0.10_${scala.binary.version}</artifactId>
     <version>${flink.version}</version>
 </dependency>
<dependency>
     <groupId>org.apache.flink</groupId>
     <artifactId>flink-table-planner_${scala.binary.version}</artifactId>
     <version>${flink.version}</version>
</dependency>

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