【云星数据---Apache Flink实战系列(精品版)】：Apache Flink批处理API详解与编程实战027--DateSet实用API详解027

一、Flink DateSet定制API详解(JAVA版) -004

Join

join将两个DataSet按照一定的关联度进行类似SQL中的Join操作。

执行程序：

package code.book.batch.dataset.advance.api;import org.apache.flink.api.common.functions.JoinFunction;import org.apache.flink.api.java.DataSet;import org.apache.flink.api.java.ExecutionEnvironment;import org.apache.flink.api.java.tuple.Tuple2;import org.apache.flink.api.java.tuple.Tuple3;import org.apache.flink.api.java.tuple.Tuple4;public class JoinFunction001java {    public static void main(String[] args) throws Exception {        // 1.设置运行环境，准备运行的数据        final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();        // Author (id, name, email)        DataSet<Tuple3<String, String, String>> authors = env.fromElements(                new Tuple3<>("A001", "zhangsan", "[e-mail]"),                new Tuple3<>("A001", "lisi", "[e-mail]"),                new Tuple3<>("A001", "wangwu", "[e-mail]")        );        //Archive (title, author name)        DataSet<Tuple2<String, String>> posts = env.fromElements(                new Tuple2<>("P001", "zhangsan"),                new Tuple2<>("P002", "lisi"),                new Tuple2<>("P003", "wangwu"),                new Tuple2<>("P004", "lisi")        );        // 2.用自定义的方式进行join操作        DataSet<Tuple4<String, String, String, String>> text2 = authors.join(posts).where(1).        equalTo(1).with(new JoinFunction<Tuple3<String, String, String>, Tuple2<String, String>,         Tuple4<String, String, String, String>>() {            @Override            public Tuple4<String,String,String,String> join(Tuple3<String,String,String> author,             Tuple2<String, String> post) throws Exception {                //AuthorArchive (title, id, name, email)                return new Tuple4<>(post.f0, author.f0, author.f1, author.f2);            }        });        //3.显示结果        text2.print();    }}

执行结果：

text2.print();(P003,A001,wangwu,[e-mail])(P001,A001,zhangsan,[e-mail])(P002,A001,lisi,[e-mail])(P004,A001,lisi,[e-mail])

CoGroup

将2个DataSet中的元素，按照key进行分组，一起分组2个DataSet。而groupBy值能分组一个DataSet

执行程序：

package code.book.batch.dataset.advance.api;import org.apache.flink.api.common.functions.CoGroupFunction;import org.apache.flink.api.java.DataSet;import org.apache.flink.api.java.ExecutionEnvironment;import org.apache.flink.api.java.tuple.Tuple2;import org.apache.flink.api.java.tuple.Tuple3;import org.apache.flink.api.java.tuple.Tuple4;import org.apache.flink.util.Collector;import java.util.Iterator;public class CoGroupFunction001java {    public static void main(String[] args) throws Exception {        // 1.设置运行环境，准备运行的数据        final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();        // Author (id, name, email)        DataSet<Tuple3<String, String, String>> authors = env.fromElements(                new Tuple3<>("A001", "zhangsan", "[e-mail]"),                new Tuple3<>("A001", "lisi", "[e-mail]"),                new Tuple3<>("A001", "wangwu", "[e-mail]")        );        //Post (title, author name)        DataSet<Tuple2<String, String>> posts = env.fromElements(                new Tuple2<>("P001", "zhangsan"),                new Tuple2<>("P002", "lisi"),                new Tuple2<>("P003", "wangwu"),                new Tuple2<>("P004", "lisi")        );        // 2.用自定义的方式进行coGroup操作,将相同name的Author和Post协同分组。        DataSet<Tuple4<String, String, String, String text2 = authors.coGroup(posts).where(1)        .equalTo(1).with(new CoGroupFunction<Tuple3<String, String, String>, Tuple2<String, String>,        Tuple4<String, String, String, String>>() {            @Override            public void coGroup(Iterable<Tuple3<String, String, String>> authors,            Iterable<Tuple2<String,String>> posts,Collector<Tuple4<String,String,String,String>>            collector)throws Exception {                //取出Author信息                Tuple3<String, String, String> at = null;                Iterator<Tuple3<String, String, String>> aitor = authors.iterator();                while (aitor.hasNext()) {                    at = aitor.next();                }                //取出Post信息                Tuple2<String, String> pt = null;                Iterator<Tuple2<String, String>> pitor = posts.iterator();                while (pitor.hasNext()) {                    pt = pitor.next();                }                //重新组装并发送AuthorPost信息                collector.collect(new Tuple4<>(pt.f0, at.f0, at.f1, at.f2));            }        });        //3.显示结果        text2.print();    }}

执行结果：

text2.print();(P003,A001,wangwu,[e-mail])(P004,A001,lisi,[e-mail])(P001,A001,zhangsan,[e-mail])