在Spark Streaming job中如何讀取Kafka messages及其offsetRange

本篇文章為大家展示了在Spark Streaming job中如何讀取Kafka messages及其offsetRange，內(nèi)容簡明扼要并且容易理解，絕對能使你眼前一亮，通過這篇文章的詳細介紹希望你能有所收獲。

在Spark Streaming job中讀取Kafka topic(s)中的messages時，有時我們會需要同步記錄下每次讀取的messages的offsetRange。要達到這一目的，下面這兩段代碼（代碼1和代碼2）都是正確的，而且是等價的。

代碼1（正確）：

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

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;

}

});

代碼2（正確）：

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

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，下面這兩段代碼（代碼3和代碼4）是錯誤的，它們都會拋出一個exception：java.lang.ClassCastException: org.apache.spark.rdd.MapPartitionsRDD cannot be cast to org.apache.spark.streaming.kafka.HasOffsetRanges

代碼3（錯誤）：

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

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;

}

});

代碼4（錯誤）：

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

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;

}

});

上述內(nèi)容就是在Spark Streaming job中如何讀取Kafka messages及其offsetRange，你們學到知識或技能了嗎？如果還想學到更多技能或者豐富自己的知識儲備，歡迎關(guān)注億速云行業(yè)資訊頻道。