Flink Stream SQL Join程序
场景说明
假定某个Flink业务1每秒就会收到1条消息记录，消息记录某个用户的基本信息，包括名字、性别、年龄。另有一个Flink业务2会不定时收到1条消息记录，消息记录该用户的名字、职业信息。
基于某些业务要求，开发的Flink应用程序实现功能：实时的以根据业务2中消息记录的用户名字作为关键字，对两个业务数据进行联合查询。
数据规划
- 业务1的数据存储在Kafka组件中。向Kafka组件发送数据（需要有Kafka权限用户），并从Kafka组件接收数据。Kafka配置参见样例数据规划章节。
- 业务2的数据通过socket接收消息记录，可使用netcat命令用户输入模拟数据源。
- 使用Linux命令netcat -l -p <port>，启动一个简易的文本服务器。
- 启动应用程序连接netcat监听的port成功后，向netcat终端输入数据信息。
开发思路
- 启动Flink Kafka Producer应用向Kafka发送数据。
- 启动Flink Kafka Consumer应用从Kafka接收数据，构造Table1，保证topic与producer一致。
- 从soket中读取数据，构造Table2。
- 使用Flink SQL对Table1和Table2进行联合查询，并进行打印。
Java样例代码
功能介绍
在Flink应用中，调用flink-connector-kafka模块的接口，生产并消费数据。
代码样例
用户在开发前需要使用对接安全模式的FusionInsight Kafka，则需要引入FusionInsight的kafka-client-0.11.x.x.jar，该jar包可在FusionInsight client目录下获取。
下面列出producer和consumer，以及Flink Stream SQL Join使用主要逻辑代码作为演示。
完整代码参见com.huawei.bigdata.flink.examples.WriteIntoKafka和com.huawei.bigdata.flink.examples.SqlJoinWithSocket
Java样例代码
- 每秒钟往Kafka中生产一条用户信息，用户信息有姓名、年龄、性别组成。
//producer代码
public class WriteIntoKafka {
public static void main(String[] args) throws Exception {
// 打印出执行flink run的参考命令
System.out.println("use command as: ");
System.out.println("./bin/flink run --class com.huawei.bigdata.flink.examples.WriteIntoKafka" +
" /opt/test.jar --topic topic-test -bootstrap.servers 10.91.8.218:21005");
System.out.println("./bin/flink run --class com.huawei.bigdata.flink.examples.WriteIntoKafka" +
" /opt/test.jar --topic topic-test -bootstrap.servers 10.91.8.218:21007 --security.protocol SASL_PLAINTEXT --sasl.kerberos.service.name kafka");
System.out.println("./bin/flink run --class com.huawei.bigdata.flink.examples.WriteIntoKafka" +
" /opt/test.jar --topic topic-test -bootstrap.servers 10.91.8.218:21008 --security.protocol SSL --ssl.truststore.location /home/truststore.jks --ssl.truststore.password huawei");
System.out.println("./bin/flink run --class com.huawei.bigdata.flink.examples.WriteIntoKafka" +
" /opt/test.jar --topic topic-test -bootstrap.servers 10.91.8.218:21009 --security.protocol SASL_SSL --sasl.kerberos.service.name kafka --ssl.truststore.location /home/truststore.jks --ssl.truststore.password huawei");
System.out.println("******************************************************************************************");
System.out.println("<topic> is the kafka topic name");
System.out.println("<bootstrap.servers> is the ip:port list of brokers");
System.out.println("******************************************************************************************");
// 构造执行环境
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// 设置并发度
env.setParallelism(1);
// 解析运行参数
ParameterTool paraTool = ParameterTool.fromArgs(args);
// 构造流图，将自定义Source生成的数据写入Kafka
DataStream<String> messageStream = env.addSource(new SimpleStringGenerator());
FlinkKafkaProducer010 producer = new FlinkKafkaProducer010<>(new FlinkKafkaProducer010<>(paraTool.get("topic"),
new SimpleStringSchema(),
paraTool.getProperties()));
messageStream.addSink(producer);
// 调用execute触发执行
env.execute();
}
// 自定义Source，每隔1s持续产生消息
public static class SimpleStringGenerator implements SourceFunction<String> {
static final String[] NAME = {"Carry", "Alen", "Mike", "Ian", "John", "Kobe", "James"};
static final String[] SEX = {"MALE", "FEMALE"};
static final int COUNT = NAME.length;
boolean running = true;
Random rand = new Random(47);
@Override
//rand随机产生名字，性别，年龄的组合信息
public void run(SourceContext<String> ctx) throws Exception {
while (running) {
int i = rand.nextInt(COUNT);
int age = rand.nextInt(70);
String sexy = SEX[rand.nextInt(2)];
ctx.collect(NAME[i] + "," + age + "," + sexy);
thread.sleep(1000);
}
}
@Override
public void cancel() {
running = false;
}
}
}2.生成Table1和Table2，并使用Join对Table1和Table2进行联合查询，打印输出结果。
public class SqlJoinWithSocket {
public static void main(String[] args) throws Exception{
final String hostname;
final int port;
System.out.println("use command as: ");
System.out.println("flink run --class com.huawei.bigdata.flink.examples.SqlJoinWithSocket" +
" /opt/test.jar --topic topic-test -bootstrap.servers xxxx.xxx.xxx.xxx:21005 --hostname xxx.xxx.xxx.xxx --port xxx");
System.out.println("flink run --class com.huawei.bigdata.flink.examples.SqlJoinWithSocket" +
" /opt/test.jar --topic topic-test -bootstrap.servers xxxx.xxx.xxx.xxx:21007 --security.protocol SASL_PLAINTEXT --sasl.kerberos.service.name kafka"
+ "--hostname xxx.xxx.xxx.xxx --port xxx");
System.out.println("flink run --class com.huawei.bigdata.flink.examples.SqlJoinWithSocket" +
" /opt/test.jar --topic topic-test -bootstrap.servers xxxx.xxx.xxx.xxx:21008 --security.protocol SSL --ssl.truststore.location /home/truststore.jks "
+ "--ssl.truststore.password huawei --hostname xxx.xxx.xxx.xxx --port xxx");
System.out.println("******************************************************************************************");
System.out.println("<topic> is the kafka topic name");
System.out.println("<bootstrap.servers> is the ip:port list of brokers");
System.out.println("******************************************************************************************");
try {
final ParameterTool params = ParameterTool.fromArgs(args);
hostname = params.has("hostname") ? params.get("hostname") : "localhost";
port = params.getInt("port");
} catch (Exception e) {
System.err.println("No port specified. Please run 'FlinkStreamSqlJoinExample " +
"--hostname <hostname> --port <port>', where hostname (localhost by default) " +
"and port is the address of the text server");
System.err.println("To start a simple text server, run 'netcat -l -p <port>' and " +
"type the input text into the command line");
return;
}
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
StreamTableEnvironment tableEnv = TableEnvironment.getTableEnvironment(env);
//基于EventTime进行处理
env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
env.setParallelism(1);
ParameterTool paraTool = ParameterTool.fromArgs(args);
//Stream1，从Kafka中读取数据
DataStream<Tuple3<String, String, String>> kafkaStream = env.addSource(new FlinkKafkaConsumer010<>(paraTool.get("topic"),
new SimpleStringSchema(),
paraTool.getProperties())).map(new MapFunction<String, Tuple3<String, String, String>>() {
@Override
public Tuple3<String, String, String> map(String s) throws Exception {
String[] word = s.split(",");
return new Tuple3<>(word[0], word[1], word[2]);
}
});
//将Stream1注册为Table1
tableEnv.registerDataStream("Table1", kafkaStream, "name, age, sexy, proctime.proctime");
//Stream2，从Socket中读取数据
DataStream<Tuple2<String, String>> socketStream = env.socketTextStream(hostname, port, "\n").
map(new MapFunction<String, Tuple2<String, String>>() {
@Override
public Tuple2<String, String> map(String s) throws Exception {
String[] words = s.split("\\s");
if (words.length < 2) {
return new Tuple2<>();
}
return new Tuple2<>(words[0], words[1]);
}
});
//将Stream2注册为Table2
tableEnv.registerDataStream("Table2", socketStream, "name, job, proctime.proctime");
//执行SQL Join进行联合查询
Table result = tableEnv.sqlQuery("SELECT t1.name, t1.age, t1.sexy, t2.job, t2.proctime as shiptime\n" +
"FROM Table1 AS t1\n" +
"JOIN Table2 AS t2\n" +
"ON t1.name = t2.name\n" +
"AND t1.proctime BETWEEN t2.proctime - INTERVAL '1' SECOND AND t2.proctime + INTERVAL '1' SECOND");
//将查询结果转换为Stream，并打印输出
tableEnv.toAppendStream(result, Row.class).print();
env.execute();
}
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