本文样例基于flink 1.8.0版本介绍如何通过flink读写kafka数据
完整样例代码
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.formats.csv.CsvRowDeserializationSchema;
import org.apache.flink.formats.csv.CsvRowSerializationSchema;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.Kafka010TableSink;
import org.apache.flink.streaming.connectors.kafka.Kafka010TableSource;
import org.apache.flink.streaming.connectors.kafka.KafkaTableSinkBase;
import org.apache.flink.streaming.connectors.kafka.KafkaTableSourceBase;
import org.apache.flink.streaming.connectors.kafka.partitioner.FlinkFixedPartitioner;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableSchema;
import org.apache.flink.table.api.java.StreamTableEnvironment;
import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.types.Row;
import java.util.Optional;
import java.util.Properties;
public class FlinkKafkaDemo {
public static void main(String[] args) throws Exception {
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
final StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);
final TableSchema tableSchema = new TableSchema(new String[]{"imsi", "lac", "cell"}, new TypeInformation[]{Types.STRING, Types.STRING, Types.STRING});
final TypeInformation<Row> typeInfo = tableSchema.toRowType();
final CsvRowDeserializationSchema.Builder deserSchemaBuilder = new CsvRowDeserializationSchema.Builder(typeInfo).setFieldDelimiter(',');
Properties properties = new Properties();
properties.setProperty("bootstrap.servers", "hostA:6667");
KafkaTableSourceBase kafkaTableSource = new Kafka010TableSource(
tableSchema,
"foo",
properties,
deserSchemaBuilder.build());
tableEnv.registerTableSource("KafkaCsvTable", kafkaTableSource);
Table kafkaCsvTable = tableEnv.scan("KafkaCsvTable");
Table result = kafkaCsvTable.where("lac != '5'").select("imsi,lac,cell");
DataStream ds = tableEnv.toAppendStream(result, typeInfo);
final CsvRowSerializationSchema.Builder serSchemaBuilder = new CsvRowSerializationSchema.Builder(typeInfo).setFieldDelimiter('|').setQuoteCharacter('\0').setLineDelimiter("\r");
KafkaTableSinkBase sink = new Kafka010TableSink(
result.getSchema(),
"bar",
properties,
Optional.of(new FlinkFixedPartitioner<>()),
serSchemaBuilder.build());
sink.emitDataStream(ds);
env.execute("Flink kafka demo");
}
}
另一种方式为
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.formats.csv.CsvRowDeserializationSchema;
import org.apache.flink.formats.csv.CsvRowSerializationSchema;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.*;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableSchema;
import org.apache.flink.table.api.java.StreamTableEnvironment;
import org.apache.flink.types.Row;
import java.util.Properties;
public class FlinkKafkaDemoT {
public static void main(String[] args) throws Exception {
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
final StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);
final TableSchema tableSchema = new TableSchema(new String[]{"imsi","lac","cell"}, new TypeInformation[]{Types.STRING, Types.STRING, Types.STRING});
final TypeInformation<Row> typeInfo = tableSchema.toRowType();
final CsvRowDeserializationSchema.Builder deserSchemaBuilder = new CsvRowDeserializationSchema.Builder(typeInfo).setFieldDelimiter(',');
Properties properties = new Properties();
properties.setProperty("bootstrap.servers", "hostA:6667");
FlinkKafkaConsumer010<Row> myConsumer = new FlinkKafkaConsumer010(
"foo",
deserSchemaBuilder.build(),
properties);
myConsumer.setStartFromLatest();
DataStream<Row> stream = env.addSource(myConsumer);
tableEnv.registerDataStream("KafkaCsvTable", stream);
Table kafkaCsvTable = tableEnv.scan("KafkaCsvTable");
Table result = kafkaCsvTable.where("lac != '5'").select("imsi,lac,cell");
final CsvRowSerializationSchema.Builder serSchemaBuilder = new CsvRowSerializationSchema.Builder(typeInfo).setFieldDelimiter(',').setLineDelimiter("\r");
DataStream ds = tableEnv.toAppendStream(result, typeInfo);
FlinkKafkaProducer010<Row> myProducer = new FlinkKafkaProducer010<>(
"hostA:6667",
"bar",
serSchemaBuilder.build());
myProducer.setWriteTimestampToKafka(true);
ds.addSink(myProducer);
env.execute("Flink kafka demo");
}
}
注意上面代码中，下面两个类的引用需要配置阿里的仓库
import org.apache.flink.formats.csv.CsvRowDeserializationSchema;
import org.apache.flink.formats.csv.CsvRowSerializationSchema;
pom.xml文件如下
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.woople.tutorial.flink</groupId>
<artifactId>flink-examples</artifactId>
<version>1.0-SNAPSHOT</version>
<repositories>
<repository>
<id>ali</id>
<name>ali</name>
<url>http://maven.aliyun.com/nexus/content/groups/public</url>
<releases>
<enabled>true</enabled>
</releases>
<snapshots>
<enabled>false</enabled>
</snapshots>
</repository>
</repositories>
<dependencies>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-streaming-java_2.11</artifactId>
<version>1.8.0</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-streaming-scala_2.11</artifactId>
<version>1.8.0</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-kafka-0.10_2.11</artifactId>
<version>1.8.0</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-csv</artifactId>
<version>1.8.0</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-table-planner_2.11</artifactId>
<version>1.8.0</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-java</artifactId>
<version>1.8.0</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-scala_2.11</artifactId>
<version>1.8.0</version>
</dependency>
</dependencies>
<build>
<defaultGoal>package</defaultGoal>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-resources-plugin</artifactId>
<configuration>
<encoding>UTF-8</encoding>
</configuration>
<executions>
<execution>
<goals>
<goal>copy-resources</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<version>3.2.2</version>
<executions>
<execution>
<id>eclipse-add-source</id>
<goals>
<goal>add-source</goal>
</goals>
</execution>
<execution>
<id>scala-compile-first</id>
<phase>process-resources</phase>
<goals>
<goal>compile</goal>
</goals>
</execution>
<execution>
<id>scala-test-compile-first</id>
<phase>process-test-resources</phase>
<goals>
<goal>testCompile</goal>
</goals>
</execution>
<execution>
<id>attach-scaladocs</id>
<phase>verify</phase>
<goals>
<goal>doc-jar</goal>
</goals>
</execution>
</executions>
<configuration>
<scalaVersion>2.11.8</scalaVersion>
<recompileMode>incremental</recompileMode>
<useZincServer>true</useZincServer>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.5.1</version>
<executions>
<execution>
<phase>compile</phase>
<goals>
<goal>compile</goal>
</goals>
</execution>
</executions>
<configuration>
<source>8</source>
<target>8</target>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>2.4.1</version>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
</execution>
</executions>
<configuration>
<shadedArtifactAttached>false</shadedArtifactAttached>
<filters>
<filter>
<artifact>*:*</artifact>
<excludes>
<exclude>META-INF/*.SF</exclude>
<exclude>META-INF/*.DSA</exclude>
<exclude>META-INF/*.RSA</exclude>
</excludes>
</filter>
</filters>
<finalName>${project.artifactId}-${project.version}-bundle</finalName>
</configuration>
</plugin>
</plugins>
</build>
</project>
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