最近在项目中遇到二次排序的需求,和平常开发spark的application一样,开始查看API,编码,调试,验证结果。由于之前对spark的API使用过,知道API中的sortByKey()可以自定义排序规则,通过实现自定义的排序规则来实现二次排序。
这里为了说明问题,举了一个简单的例子,key是由两部分组成的,我们这里按key的第一部分的降序排,key的第二部分升序排,具体如下:

 JavaSparkContext javaSparkContext = new JavaSparkContext(sparkConf);

 List<Integer> data = Arrays.asList(5, 1, 1, 4, 4, 2, 2);

 JavaRDD<Integer> javaRDD = javaSparkContext.parallelize(data);

 final Random random = new Random(100);

 JavaPairRDD javaPairRDD = javaRDD.mapToPair(new PairFunction<Integer, String, Integer>() {
@Override
public Tuple2<String, Integer> call(Integer integer) throws Exception {
return new Tuple2<String, Integer>(Integer.toString(integer) + " " + random.nextInt(10),random.nextInt(10));
}
}); JavaPairRDD<String,Integer> sortByKeyRDD = javaPairRDD.sortByKey(new Comparator<String>() {
@Override
public int compare(String o1, String o2) {
String []o1s = o1.split(" ");
String []o2s = o2.split(" ");
if(o1s[0].compareTo(o2s[0]) == 0)
return o1s[1].compareTo(o2s[1]);
else
return -o1s[0].compareTo(o2s[0]);
}
});
System.out.println("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" + sortByKeyRDD.collect());

上面编码从语法上没有什么问题,可是运行下报了如下错误:

java.lang.reflect.InvocationTargetException at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:606) at org.apache.spark.serializer.SerializationDebugger$ObjectStreamClassMethods$.getObjFieldValues$extension(SerializationDebugger.scala:248) at org.apache.spark.serializer.SerializationDebugger$SerializationDebugger.visitSerializable(SerializationDebugger.scala:158) at org.apache.spark.serializer.SerializationDebugger$SerializationDebugger.visit(SerializationDebugger.scala:107) at org.apache.spark.serializer.SerializationDebugger$SerializationDebugger.visitSerializable(SerializationDebugger.scala:166) at org.apache.spark.serializer.SerializationDebugger$SerializationDebugger.visit(SerializationDebugger.scala:107) at org.apache.spark.serializer.SerializationDebugger$SerializationDebugger.visitSerializable(SerializationDebugger.scala:166) at org.apache.spark.serializer.SerializationDebugger$SerializationDebugger.visit(SerializationDebugger.scala:107) at org.apache.spark.serializer.SerializationDebugger$.find(SerializationDebugger.scala:66) at org.apache.spark.serializer.SerializationDebugger$.improveException(SerializationDebugger.scala:41) at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:47) at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:81) at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:312) at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:305) at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:132) at org.apache.spark.SparkContext.clean(SparkContext.scala:1891) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1764) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1779) at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:885) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109) at org.apache.spark.rdd.RDD.withScope(RDD.scala:286) at org.apache.spark.rdd.RDD.collect(RDD.scala:884) at org.apache.spark.api.java.JavaRDDLike$class.collect(JavaRDDLike.scala:335) at org.apache.spark.api.java.AbstractJavaRDDLike.collect(JavaRDDLike.scala:47)
因此,我再次去查看相应的spark Java API文档,但是我没有发现任何指明错误的地方。好吧,那只能扒下源码吧,在javaPairRDD中
def sortByKey(comp: Comparator[K], ascending: Boolean): JavaPairRDD[K, V] = { implicit val ordering = comp // Allow implicit conversion of Comparator to Ordering. fromRDD(new OrderedRDDFunctions[K, V, (K, V)](rdd).sortByKey(ascending)) }

其实在OrderedRDDFunctions类中有个变量ordering它是隐形的:private val ordering = implicitly[Ordering[K]]。他就是默认的排序规则,我们自己重写的comp就修改了默认的排序规则。到这里还是没有发现问题,但是发现类OrderedRDDFunctions extends Logging with Serializable,又回到上面的报错信息,扫描到“serializable”!!!因此,返回上述代码,查看Comparator interface实现,发现原来是它没有extend Serializable,故只需创建一个 serializable的comparator就可以:public interface SerializableComparator<T> extends Comparator<T>, Serializable { }
具体如下:
 private static class Comp implements Comparator<String>,Serializable{
@Override
public int compare(String o1, String o2) {
String []o1s = o1.split(" ");
String []o2s = o2.split(" ");
if(o1s[0].compareTo(o2s[0]) == 0)
return o1s[1].compareTo(o2s[1]);
else
return -o1s[0].compareTo(o2s[0]);
}
}
JavaPairRDD<String,Integer> sortByKeyRDD = javaPairRDD.sortByKey(new Comp());

总结下,在spark的Java API中,如果需要使用Comparator接口,须注意是否需要序列化,如sortByKey(),repartitionAndSortWithinPartitions()等都是需要序列化的。

原文引自:

https://www.jianshu.com/p/37231b87de81?utm_campaign=maleskine&utm_content=note&utm_medium=pc_all_hots&utm_source=recommendation

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