Hi,
You seem to be creating a new RDD for each element in your files RDD. What
I would suggest is to load and process only one sequence file in your Spark
job, then just execute multiple spark jobs to process each sequence file.
With regard to your question of where to view the logs inside the closures,
you should be able to see them in the executor log (via the Spark UI, in
the Executors page).
HTH,
Deng
On Fri, Oct 30, 2015 at 1:20 PM, Vinoth Sankar <vinoth9...@gmail.com> wrote:
> Hi Adrian,
>
> Yes. I need to load all files and process it in parallel. Following code
> doesn't seem working(Here I used map, even tried foreach) ,I just
> downloading the files from HDFS to local system and printing the logs count
> in each file. Its not throwing any Exceptions,but not working. Files are
> not getting downloaded. I even didn't get that LOGGER print. Same code
> works if I iterate the files, but its not Parallelized. How do I get my
> code Parallelized and Working.
>
> JavaRDD<String> files = sparkContext.parallelize(fileList);
>
> files.map(new Function<String, Void>()
> {
> public static final long serialVersionUID = 1L;
>
> @Override
> public Void call(String hdfsPath) throws Exception
> {
> JavaPairRDD<IntWritable, BytesWritable> hdfsContent =
> sc.sequenceFile(hdfsPath, IntWritable.class, BytesWritable.class);
> JavaRDD<Message> logs = hdfsContent.map(new Function<Tuple2<IntWritable,
> BytesWritable>, Message>()
> {
> public Message call(Tuple2<IntWritable, BytesWritable> tuple2) throws
> Exception
> {
> BytesWritable value = tuple2._2();
> BytesWritable tmp = new BytesWritable();
> tmp.setCapacity(value.getLength());
> tmp.set(value);
> return (Message) getProtos(1, tmp.getBytes());
> }
> });
>
> String path = "/home/sas/logsfilterapp/temp/" + hdfsPath.substring(26);
>
> Thread.sleep(2000);
> logs.saveAsObjectFile(path);
>
> LOGGER.log(Level.INFO, "HDFS Path : {0} Count : {1}", new Object[] {
> hdfsPath, logs.count() });
> return null;
> }
> });
>
>
>
> Note : In another scenario also i didn't get the logs which are present
> inside map,filter closures. But logs outside these closures are getting
> printed as usual. If i can't get the logger prints inside these closures
> how do i debug them ?
>
> Thanks
> Vinoth Sankar
>
> On Wed, Oct 28, 2015 at 8:29 PM Adrian Tanase <atan...@adobe.com> wrote:
>
>> The first line is distributing your fileList variable in the cluster as a
>> RDD, partitioned using the default partitioner settings (e.g. Number of
>> cores in your cluster).
>>
>> Each of your workers would one or more slices of data (depending on how
>> many cores each executor has) and the abstraction is called partition.
>>
>> What is your use case? If you want to load the files and continue
>> processing in parallel, then a simple .map should work.
>> If you want to execute arbitrary code based on the list of files that
>> each executor received, then you need to use .foreach that will get
>> executed for each of the entries, on the worker.
>>
>> -adrian
>>
>> From: Vinoth Sankar
>> Date: Wednesday, October 28, 2015 at 2:49 PM
>> To: "user@spark.apache.org"
>> Subject: How do I parallize Spark Jobs at Executor Level.
>>
>> Hi,
>>
>> I'm reading and filtering large no of files using Spark. It's getting
>> parallized at Spark Driver level only. How do i make it parallelize to
>> Executor(Worker) Level. Refer the following sample. Is there any way to
>> paralleling iterate the localIterator ?
>>
>> Note : I use Java 1.7 version
>>
>> JavaRDD<String> files = javaSparkContext.parallelize(fileList)
>> Iterator<String> localIterator = files.toLocalIterator();
>>
>> Regards
>> Vinoth Sankar
>>
>
