kafka streams的join实例

本文简单介绍一下kafka streams的join操做app

join

A join operation merges two streams based on the keys of their data records, and yields a new stream. A join over record streams usually needs to be performed on a windowing basis because otherwise the number of records that must be maintained for performing the join may grow indefinitely.ide

实例

KStreamBuilder builder = new KStreamBuilder();
        KStream<String, String> left = builder.stream("intpu-left");
        KStream<String, String> right = builder.stream("intpu-right");

        KStream<String, String> all = left.selectKey((key, value) -> value.split(",")[1])
                .join(right.selectKey((key, value) -> value.split(",")[0]), new ValueJoiner<String, String, String>() {
            @Override
            public String apply(String value1, String value2) {
                return value1 + "--" + value2;
            }
        }, JoinWindows.of(30000));

        all.print();

因为join操做是根据key来,因此一般通常要再次映射一下key测试

测试

sh bin/kafka-topics.sh --create --topic intpu-left --replication-factor 1 --partitions 3 --zookeeper localhost:2181

sh bin/kafka-topics.sh --create --topic intpu-right --replication-factor 1 --partitions 3 --zookeeper localhost:2181


sh bin/kafka-console-producer.sh --broker-list localhost:9092 --topic intpu-left
sh bin/kafka-console-producer.sh --broker-list localhost:9092 --topic intpu-right

左边输入诸如ui

1,a
2,b
3,c
3,c
4,d
1,a
2,b
3,c
1,a
2,b
3,c
4,e
5,h
6,f
7,g

右边输入诸如code

a,hello
b,world
c,hehehe
c,aaa
d,eee
a,cccc
b,aaaaaa
c,332435
a,dddd
b,2324
c,ddddd
e,23453
h,2222222
f,0o0o0o0
g,ssss

输出实例orm

[KSTREAM-MERGE-0000000014]: a , 1,a--a,dddd
[KSTREAM-MERGE-0000000014]: b , 2,b--b,2324
2017-10-17 22:17:34.578  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing all tasks because the commit interval 30000ms has elapsed
2017-10-17 22:17:34.578  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing task StreamTask 0_0
2017-10-17 22:17:34.585  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing task StreamTask 0_1

join类别

这里使用的是inner join,也有left join,也有outer join。若是要记录在时间窗口没有匹配上的记录,能够使用outer join,额外存储下来,而后再根据已经匹配的记录再过滤一次。kafka

输出实例it

[KSTREAM-MERGE-0000000014]: f , null--f,ddddddd
[KSTREAM-MERGE-0000000014]: f , 4,f--f,ddddddd
2017-10-17 22:31:12.530  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing all tasks because the commit interval 30000ms has elapsed
2017-10-17 22:31:12.530  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing task StreamTask 0_0
2017-10-17 22:31:12.531  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing task StreamTask 0_1
2017-10-17 22:31:12.531  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing task StreamTask 1_0
2017-10-17 22:31:12.531  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing task StreamTask 0_2
2017-10-17 22:31:12.533  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing task StreamTask 1_1
2017-10-17 22:31:12.533  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing task StreamTask 2_0
2017-10-17 22:31:12.539  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing task StreamTask 1_2
2017-10-17 22:31:12.540  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing task StreamTask 2_1
2017-10-17 22:31:12.541  INFO   --- [ StreamThread-1] o.a.k.s.p.internals.StreamThread         : stream-thread [StreamThread-1] Committing task StreamTask 2_2
[KSTREAM-MERGE-0000000014]: g , 5,g--null
[KSTREAM-MERGE-0000000014]: h , 6,h--null
[KSTREAM-MERGE-0000000014]: h , 6,h--h,ddddddd

小结

kafka streams的join操做,很是适合不一样数据源的实时匹配操做。io

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