Flink 异步IO访问外部数据（mysql篇）

　　最近看了大佬的博客，突然想起Async I/O方式是Blink 推给社区的一大重要功能，可以使用异步的方式获取外部数据，想着自己实现以下，项目上用的时候，可以不用现去找了。

　　最开始想用scala 实现一个读取 hbase数据的demo，参照官网demo：　　

/**
 * An implementation of the 'AsyncFunction' that sends requests and sets the callback.
 */
class AsyncDatabaseRequest extends AsyncFunction[String, (String, String)] {

    /** The database specific client that can issue concurrent requests with callbacks */
    lazy val client: DatabaseClient = new DatabaseClient(host, post, credentials)

    /** The context used for the future callbacks */
    implicit lazy val executor: ExecutionContext = ExecutionContext.fromExecutor(Executors.directExecutor())


    override def asyncInvoke(str: String, resultFuture: ResultFuture[(String, String)]): Unit = {

        // issue the asynchronous request, receive a future for the result
        val resultFutureRequested: Future[String] = client.query(str)

        // set the callback to be executed once the request by the client is complete
        // the callback simply forwards the result to the result future
        resultFutureRequested.onSuccess {
            case result: String => resultFuture.complete(Iterable((str, result)))
        }
    }
}

// create the original stream
val stream: DataStream[String] = ...

// apply the async I/O transformation
val resultStream: DataStream[(String, String)] =
    AsyncDataStream.unorderedWait(stream, new AsyncDatabaseRequest(), 1000, TimeUnit.MILLISECONDS, 100)

失败了，上图标红的部分实现不了

1、Future 找不到可以用的实现类

2、unorderedWait 一直报错

源码example 里面也有Scala 的案例

def main(args: Array[String]) {
    val timeout = 10000L

    val env = StreamExecutionEnvironment.getExecutionEnvironment

    val input = env.addSource(new SimpleSource())

    val asyncMapped = AsyncDataStream.orderedWait(input, timeout, TimeUnit.MILLISECONDS, 10) {
      (input, collector: ResultFuture[Int]) =>
        Future {
          collector.complete(Seq(input))
        } (ExecutionContext.global)
    }

    asyncMapped.print()

    env.execute("Async I/O job")
  }

主要部分是这样的，菜鸡表示无力，想继承RichAsyncFunction，可以使用open 方法初始化链接。

网上博客翻了不少，大部分是翻译官网的原理，案例也没有可以执行的，苦恼。

失败了。

转为java版本的，昨天在群里问，有个大佬给我个Java版本的： https://github.com/perkinls/flink-local-train/blob/c8b4efe33620352aea0100adef4fae2a068a3b65/src/main/scala/com/lp/test/asyncio/AsyncIoSideTableJoinMysqlJava.java 还没看过，因为Java版的官网的案例能看懂。

下面开始上mysql 版本的源码（hbase 的还没测试过，本机的hbase 挂了）：

业务如下：

接收kafka数据，转为user对象，调用async，使用user.id 查询对应的phone，放回user对象，输出

主类：

import com.alibaba.fastjson.JSON;
import com.venn.common.Common;
import org.apache.flink.formats.json.JsonNodeDeserializationSchema;
import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.node.ObjectNode;
import org.apache.flink.streaming.api.datastream.AsyncDataStream;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import java.util.concurrent.TimeUnit;


class AsyncMysqlRequest {

    public static void main(String[] args) throws Exception {

        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        FlinkKafkaConsumer<ObjectNode> source = new FlinkKafkaConsumer<>("async", new JsonNodeDeserializationSchema(), Common.getProp());

        // 接收kafka数据，转为User 对象
        DataStream<User> input = env.addSource(source).map(value -> {
            String id = value.get("id").asText();
            String username = value.get("username").asText();
            String password = value.get("password").asText();

            return new User(id, username, password);
        });
        // 异步IO 获取mysql数据, timeout 时间 1s，容量 100（超过100个请求，会反压上游节点）
        DataStream async = AsyncDataStream.unorderedWait(input, new AsyncFunctionForMysqlJava(), 1000, TimeUnit.MICROSECONDS, 100);

        async.map(user -> {

            return JSON.toJSON(user).toString();
        })
        .print();

        env.execute("asyncForMysql");

    }
}

函数类：

import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.functions.async.ResultFuture;
import org.apache.flink.streaming.api.functions.async.RichAsyncFunction;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.util.ArrayList;
import java.util.List;

public class AsyncFunctionForMysqlJava extends RichAsyncFunction<User, User> {

    // 链接
    private static String jdbcUrl = "jdbc:mysql://192.168.229.128:3306?useSSL=false";
    private static String username = "root";
    private static String password = "123456";
    private static String driverName = "com.mysql.jdbc.Driver";


    java.sql.Connection conn;
    PreparedStatement ps;
    Logger logger = LoggerFactory.getLogger(AsyncFunctionForMysqlJava.class);

    /**
     * open 方法中初始化链接
     * @param parameters
     * @throws Exception
     */
    @Override
    public void open(Configuration parameters) throws Exception {
        logger.info("async function for hbase java open ...");
        super.open(parameters);

        Class.forName(driverName);
        conn = DriverManager.getConnection(jdbcUrl, username, password);
        ps = conn.prepareStatement("select phone from async.async_test where id = ?");
    }

    /**
     * use user.getId async get user phone
     *
     * @param user
     * @param resultFuture
     * @throws Exception
     */
    @Override
    public void asyncInvoke(User user, ResultFuture<User> resultFuture) throws Exception {
        // 使用 user id 查询
        ps.setString(1, user.getId());
        ResultSet rs = ps.executeQuery();
        String phone = null;
        if (rs.next()) {
            phone = rs.getString(1);
        }
        user.setPhone(phone);
        List<User> list = new ArrayList();
        list.add(user);
        // 放回 result 队列
        resultFuture.complete(list);
    }

    @Override
    public void timeout(User input, ResultFuture<User> resultFuture) throws Exception {
        logger.info("Async function for hbase timeout");
        List<User> list = new ArrayList();
        list.add(input);
        resultFuture.complete(list);
    }

    /**
     * close function
     *
     * @throws Exception
     */
    @Override
    public void close() throws Exception {
        logger.info("async function for hbase java close ...");
        super.close();
        conn.close();
    }
}

测试数据如下：

{"id" : 1, "username" : "venn", "password" : 1561709530935}
{"id" : 2, "username" : "venn", "password" : 1561709536029}
{"id" : 3, "username" : "venn", "password" : 1561709541033}
{"id" : 4, "username" : "venn", "password" : 1561709546037}
{"id" : 5, "username" : "venn", "password" : 1561709551040}
{"id" : 6, "username" : "venn", "password" : 1561709556044}
{"id" : 7, "username" : "venn", "password" : 1561709561048}

执行结果如下：

1> {"password":"1561709536029","phone":"12345678911","id":"2","username":"venn"}
1> {"password":"1561709541033","phone":"12345678912","id":"3","username":"venn"}
1> {"password":"1561709546037","phone":"12345678913","id":"4","username":"venn"}
1> {"password":"1561709551040","id":"5","username":"venn"} # 关联不上，原样返回
1> {"password":"1561709556044","id":"6","username":"venn"}
1> {"password":"1561709561048","id":"7","username":"venn"}

hbase、redis或其他实现类似，继承AsyncStreamFunction，实现方法

Flink 异步IO访问外部数据（mysql篇）

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