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在Spark Streaming job中如何读取Kafka messages及其offsetRange

发布时间:2021-12-15 11:07:28 来源:亿速云 阅读:102 作者:柒染 栏目:大数据

本篇文章为大家展示了在Spark Streaming job中如何读取Kafka messages及其offsetRange,内容简明扼要并且容易理解,绝对能使你眼前一亮,通过这篇文章的详细介绍希望你能有所收获。

在Spark Streaming job中读取Kafka topic(s)中的messages时,有时我们会需要同步记录下每次读取的messages的offsetRange。要达到这一目的,下面这两段代码(代码1和代码2)都是正确的,而且是等价的。

代码1(正确):

-----------------------

JavaPairInputDStream<String, String> messages = KafkaUtils.createDirectStream(

jssc,

String.class,

String.class,

StringDecoder.class,

StringDecoder.class,

kafkaParams,

topicsSet

);

messages.foreachRDD(

new Function<JavaPairRDD<String, String>, Void>() {

@Override

public Void call(JavaPairRDD<String, String> rdd) throws Exception {

OffsetRange[] offsets = ((HasOffsetRanges) rdd.rdd()).offsetRanges();

JavaRDD<String> valueRDD = rdd.values();

long msgNum = processEachRDD(valueRDD, outputFolderPath, definedDuration);

if (msgNum > 0 && zkPathRoot!= null) {

writeOffsetToZookeeper(zkClient, zkPathRoot, offsets);

}

return null;

}

});

代码2(正确):

-----------------------

JavaPairInputDStream<String, String> messages = KafkaUtils.createDirectStream(

jssc,

String.class,

String.class,

StringDecoder.class,

StringDecoder.class,

kafkaParams,

topicsSet

);

final AtomicReference<OffsetRange[]> offsetRanges=new AtomicReference();

lines = messages.transformToPair(new Function<JavaPairRDD<String, String>, JavaPairRDD<String, String>>() {

@Override

public JavaPairRDD<String, String> call(JavaPairRDD<String, String> rdd) throws Exception {

OffsetRange[] offsets = ((HasOffsetRanges) rdd.rdd()).offsetRanges();

offsetRanges.set(offsets);

return rdd;

}

}).map(new Function<Tuple2<String, String>, String>() {

@Override

public String call(Tuple2<String, String> tuple2) {

return tuple2._2();

}

});

lines.foreachRDD(new Function<JavaRDD<String>, Void>() {

@Override

public Void call(JavaRDD<String> rdd) throws Exception {

long msgNum = processEachRDD(rdd, outputFolderPath, definedDuration);

if (msgNum > 0 && zkPathRoot!= null) {

OffsetRange[] offsets = offsetRanges.get();

writeOffsetToZookeeper(zkClient, zkPathRoot, offsets);

}

return null;

}

});

但是要注意,下面这两段代码(代码3和代码4)是错误的,它们都会抛出一个exception:java.lang.ClassCastException: org.apache.spark.rdd.MapPartitionsRDD cannot be cast to org.apache.spark.streaming.kafka.HasOffsetRanges

代码3(错误):

-----------------------

JavaPairInputDStream<String, String> messages = KafkaUtils.createDirectStream(

jssc,

String.class,

String.class,

StringDecoder.class,

StringDecoder.class,

kafkaParams,

topicsSet

);

messages.transform(new Function<JavaPairRDD<String, String>, JavaRDD<String>>() {

@Override

public JavaRDD<String> call(JavaPairRDD<String, String> rdd) throws Exception {

return rdd.values();

}

}).foreachRDD(new Function<JavaRDD<String>, Void>() {

@Override

public Void call(JavaRDD<String> rdd) throws Exception {

long msgNum = processEachRDD(rdd, outputFolderPath, definedDuration);

if (msgNum > 0 && zkPathRoot!= null) {

OffsetRange[] offsets = offsetRanges.get();

writeOffsetToZookeeper(zkClient, zkPathRoot, offsets);

}

return null;

}

});

代码4(错误):

-----------------------

JavaPairInputDStream<String, String> messages = KafkaUtils.createDirectStream(

jssc,

String.class,

String.class,

StringDecoder.class,

StringDecoder.class,

kafkaParams,

topicsSet

);

messages.map(new Function<Tuple2<String, String>, String>() {

@Override

public String call(Tuple2<String, String> tuple2) {

return tuple2._2();

}

}).foreachRDD(new Function<JavaRDD<String>, Void>() {

@Override

public Void call(JavaRDD<String> rdd) throws Exception {

long msgNum = processEachRDD(rdd, outputFolderPath, definedDuration);

if (msgNum > 0 && zkPathRoot!= null) {

OffsetRange[] offsets = offsetRanges.get();

writeOffsetToZookeeper(zkClient, zkPathRoot, offsets);

}

return null;

}

});

上述内容就是在Spark Streaming job中如何读取Kafka messages及其offsetRange,你们学到知识或技能了吗?如果还想学到更多技能或者丰富自己的知识储备,欢迎关注亿速云行业资讯频道。

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