检测网站打开速度,wordpress主题6,模板规格,策划书封面1.Flink数据源 Flink可以从各种数据源获取数据#xff0c;然后构建DataStream 进行处理转换。source就是整个数据处理程序的输入端。 数据集合数据文件Socket数据kafka数据自定义Source 2.案例
2.1.从集合中获取数据 创建 FlinkSource_List 类#xff0c;再创建个 Student 类…1.Flink数据源 Flink可以从各种数据源获取数据然后构建DataStream 进行处理转换。source就是整个数据处理程序的输入端。 数据集合数据文件Socket数据kafka数据自定义Source 2.案例
2.1.从集合中获取数据 创建 FlinkSource_List 类再创建个 Student 类姓名、年龄、性别三个属性就行反正测试用
package com.qiyu;import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;import java.util.ArrayList;/*** author MR.Liu* version 1.0* data 2023-10-18 16:13*/
public class FlinkSource_List {public static void main(String[] args) throws Exception {StreamExecutionEnvironment env StreamExecutionEnvironment.getExecutionEnvironment();env.setParallelism(1);ArrayListStudent clicks new ArrayList();clicks.add(new Student(Mary,25,1));clicks.add(new Student(Bob,26,2));DataStreamStudent stream env.fromCollection(clicks);stream.print();env.execute();}
}运行结果 Student{nameMary, age25, sex1} Student{nameBob, age26, sex2} 2.2.从文件中读取数据
文件数据 spark hello world kafka spark hadoop spark package com.qiyu;import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;/*** author MR.Liu* version 1.0* data 2023-10-18 16:31*/
public class FlinkSource_File {public static void main(String[] args) throws Exception {StreamExecutionEnvironment env StreamExecutionEnvironment.getExecutionEnvironment();env.setParallelism(1);DataStreamString stream env.readTextFile(input/words.txt);stream.print();env.execute();}
}运行结果没做任何处理 spark hello world kafka spark hadoop spark 2.3.从Socket中读取数据
package com.qiyu;import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;/*** author MR.Liu* version 1.0* data 2023-10-18 17:41*/
public class FlinkSource_Socket {public static void main(String[] args) throws Exception {StreamExecutionEnvironment env StreamExecutionEnvironment.getExecutionEnvironment();// 2. 读取文本流DataStreamSourceString lineDSS env.socketTextStream(192.168.220.130,7777);lineDSS.print();env.execute();}
}运行结果
服务器上执行 nc -lk 7777
疯狂输出 控制台打印结果 6 hello 7 world 2.4.从Kafka中读取数据
pom.xml 添加Kafka连接依赖 dependencygroupIdorg.apache.flink/groupIdartifactIdflink-connector-kafka_${scala.binary.version}/artifactIdversion${flink.version}/version/dependency
package com.qiyu;import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;import java.util.Properties;/*** author MR.Liu* version 1.0* data 2023-10-19 10:01*/
public class FlinkSource_Kafka {public static void main(String[] args) throws Exception {StreamExecutionEnvironment env StreamExecutionEnvironment.getExecutionEnvironment();env.setParallelism(1);Properties properties new Properties();properties.setProperty(bootstrap.servers, hadoop102:9092);properties.setProperty(group.id, consumer-group);properties.setProperty(key.deserializer,org.apache.kafka.common.serialization.StringDeserializer);properties.setProperty(value.deserializer,org.apache.kafka.common.serialization.StringDeserializer);properties.setProperty(auto.offset.reset, latest);DataStreamSourceString stream env.addSource(new FlinkKafkaConsumerString(clicks, new SimpleStringSchema(), properties));stream.print(Kafka);env.execute();}
}启动 zk 和kafka
创建topic
bin/kafka-topics.sh --create --bootstrap-server hadoop102:9092 --replication-factor 1 --partitions 1 --topic clicks
生产者、消费者命令
bin/kafka-console-producer.sh --bootstrap-server hadoop102:9092 --topic clicks
bin/kafka-console-consumer.sh --bootstrap-server hadoop102:9092 --topic clicks --from-beginning
启动生产者命令后疯狂输入 运行java类运行结果和生产者输入的是一样的 Kafka flinks Kafka hadoop Kafka hello Kafka nihaop 2.5.从自定义Source中读取数据 大多数情况下前面几个数据源已经满足需求了。但是遇到特殊情况我们需要自定义的数据源。实现方式如下 1.编辑自定义源Source
package com.qiyu;import org.apache.flink.streaming.api.functions.source.SourceFunction;import java.util.Calendar;
import java.util.Random;/*** author MR.Liu* version 1.0* data 2023-10-19 10:37*//**** 主要实现2个方法 run() 和 cancel()*/
public class FlinkSource_Custom implements SourceFunctionStudent {// 声明一个布尔变量作为控制数据生成的标识位private Boolean running true;Overridepublic void run(SourceContextStudent sourceContext) throws Exception {Random random new Random(); // 在指定的数据集中随机选取数据String[] name {Mary, Alice, Bob, Cary};int[] sex {1,2};int age 0;while (running) {sourceContext.collect(new Student(name[random.nextInt(name.length)],sex[random.nextInt(sex.length)],random.nextInt(100)));// 隔 1 秒生成一个点击事件方便观测Thread.sleep(1000);}}Overridepublic void cancel() {running false;}
}2.编写主程序
package com.qiyu;import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;/*** author MR.Liu* version 1.0* data 2023-10-19 10:46*/
public class FlinkSource_Custom2 {public static void main(String[] args) throws Exception {StreamExecutionEnvironment env StreamExecutionEnvironment.getExecutionEnvironment();env.setParallelism(1);
//有了自定义的 source function调用 addSource 方法DataStreamSourceStudent stream env.addSource(new FlinkSource_Custom());stream.print(SourceCustom);env.execute();}
}运行主程序运行结果 SourceCustom Student{nameMary, age1, sex46} SourceCustom Student{nameCary, age2, sex52} SourceCustom Student{nameBob, age1, sex14} SourceCustom Student{nameAlice, age1, sex84} SourceCustom Student{nameAlice, age2, sex82} SourceCustom Student{nameCary, age1, sex28} .............
