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。

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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 messages = KafkaUtils.createDirectStream(

jssc,

String.class,

String.class,

StringDecoder.class,

StringDecoder.class,

kafkaParams,

topicsSet

);

messages.foreachRDD(

new Function, Void>() {

@Override

public Void call(JavaPairRDD rdd) throws Exception {

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

JavaRDD 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 messages = KafkaUtils.createDirectStream(

jssc,

String.class,

String.class,

StringDecoder.class,

StringDecoder.class,

kafkaParams,

topicsSet

);

final AtomicReference offsetRanges=new AtomicReference();

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

@Override

public JavaPairRDD call(JavaPairRDD rdd) throws Exception {

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

offsetRanges.set(offsets);

return rdd;

}

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

@Override

public String call(Tuple2 tuple2) {

return tuple2._2();

}

});

lines.foreachRDD(new Function, Void>() {

@Override

public Void call(JavaRDD 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 messages = KafkaUtils.createDirectStream(

jssc,

String.class,

String.class,

StringDecoder.class,

StringDecoder.class,

kafkaParams,

topicsSet

);

messages.transform(new Function, JavaRDD>() {

@Override

public JavaRDD call(JavaPairRDD rdd) throws Exception {

return rdd.values（）;

}

}).foreachRDD(new Function, Void>() {

@Override

public Void call(JavaRDD 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 messages = KafkaUtils.createDirectStream(

jssc,

String.class,

String.class,

StringDecoder.class,

StringDecoder.class,

kafkaParams,

topicsSet

);

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

@Override

public String call(Tuple2 tuple2) {

return tuple2._2();

}

}).foreachRDD(new Function, Void>() {

@Override

public Void call(JavaRDD 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，欢迎关注创新互联行业资讯频道。

名称栏目：在SparkStreamingjob中如何读取Kafkamessages及其offsetRange
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