我有一些spark代码,它从hdfs读取两个文件(头文件和正文文件),将rdd[string]减少到单个分区,然后使用gzip编解码器将结果写入压缩文件:
spark.sparkContext.textFile("path_to_header.txt,path_to_body.txt")
.coalesce(1)
.saveAsTextFile("output_path", classOf[GzipCodec])
这是100%的预期效果。我们现在被要求为无法解压*.gzip文件的windows用户支持zip压缩。显然,zip格式本机不受支持,所以我尝试推出自己的压缩编解码器。
我在运行代码时遇到了“zipexception:no current zip entry”异常,但是:
Exception occured while exporting org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 16.0 failed 2 times, most recent failure: Lost task 0.1 in stage 16.0 (TID 675, xxxxxxx.xxxxx.xxx, executor 16): java.util.zip.ZipException: no current ZIP entry
at java.util.zip.ZipOutputStream.write(Unknown Source)
at io.ZipCompressorStream.write(ZipCompressorStream.java:23)
at java.io.DataOutputStream.write(Unknown Source)
at org.apache.hadoop.mapred.TextOutputFormat$LineRecordWriter.writeObject(TextOutputFormat.java:81)
at org.apache.hadoop.mapred.TextOutputFormat$LineRecordWriter.write(TextOutputFormat.java:102)
at org.apache.spark.SparkHadoopWriter.write(SparkHadoopWriter.scala:95)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$7.apply$mcV$sp(PairRDDFunctions.scala:1205)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$7.apply(PairRDDFunctions.scala:1203)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$7.apply(PairRDDFunctions.scala:1203)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1348)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1211)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1190)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
我创建了一个扩展defaultcodec的zipcodec类:
public class ZipCodec extends DefaultCodec {
@Override
public CompressionOutputStream createOutputStream(final OutputStream out, final Compressor compressor) throws IOException {
return new ZipCompressorStream(new ZipOutputStream(out));
}
以及zipcompressorstream,它扩展了compressorstream:
public class ZipCompressorStream extends CompressorStream {
public ZipCompressorStream(final ZipOutputStream out) {
super(out);
}
@Override
public void write(final int b) throws IOException {
out.write(b);
}
@Override
public void write(final byte[] data, final int offset, final int length) throws IOException {
out.write(data, offset, length);
}
我们目前正在使用spark 1.6.0和hadoop 2.6.0-cdh5.8.2
有什么想法吗?
提前谢谢!
1条答案
按热度按时间xtfmy6hx1#
zip是一种容器格式,而gzip只是一种类似流的格式(用于存储一个文件)。这就是为什么在装箱一个新的zip文件时,您需要首先启动一个条目(给出一个名称),然后在写入之后关闭该条目,然后再关闭一个容器。参见此处示例:https://www.programcreek.com/java-api-examples/?class=java.util.zip.zipoutputstream&method=putnextentry