Thanks for the quick reply. I will be unable to collect more data until
Monday though, but I will update the thread accordingly.
I am using Spark 1.4.0. Were there any related issues reported? I wasn't
able to find any, but I may have overlooked something. I have also updated
the original question to include the relevant Java files, maybe the issue
is hidden there somewhere.
Ted Yu yuzhih...@gmail.com schrieb am Fr., 31. Juli 2015 um 18:09 Uhr:
Can you call collect() and log the output to get more clue what is left ?
Which Spark release are you using ?
Cheers
On Fri, Jul 31, 2015 at 9:01 AM, Warfish sebastian.ka...@gmail.com
wrote:
Hi everyone,
I work with Spark for a little while now and have encountered a strange
problem that gives me headaches, which has to do with the JavaRDD.subtract
method. Consider the following piece of code:
public static void main(String[] args) {
//context is of type JavaSparkContext; FILE is the filepath to my
input file
JavaRDDString rawTestSet = context.textFile(FILE);
JavaRDDString rawTestSet2 = context.textFile(FILE);
//Gives 0 everytime - Correct
System.out.println(rawTestSetMinusRawTestSet2= +
rawTestSet.subtract(rawTestSet2).count());
//SearchData is a custom POJO that holds my data
JavaRDDSearchData testSet = convert(rawTestSet);
JavaRDDSearchData testSet2= convert(rawTestSet);
JavaRDDSearchData testSet3= convert(rawTestSet2);
//These calls give numbers !=0 on cluster mode - Incorrect
System.out.println(testSetMinuesTestSet2 = +
testSet.subtract(testSet2).count());
System.out.println(testSetMinuesTestSet3 = +
testSet.subtract(testSet3).count());
System.out.println(testSet2MinuesTestSet3 = +
testSet2.subtract(testSet3).count());
}
private static JavaRDDSearchData convert(JavaRDDString input) {
return input.filter(new Matches(myRegex))
.map(new DoSomething())
.map(new Split(mySplitParam))
.map(new ToMap())
.map(new Clean())
.map(new ToSearchData());
}
In this code, I read a file (usually from HDFS, but applies to disk as
well)
and then convert the Strings into custom objects to hold the data using a
chain of filter- and map-operations. These objects are simple POJOs with
overriden hashCode() and equal() functions. I then apply the subtract
method
to several JavaRDDs that contain exact equal data.
Note: I have omitted the POJO code and the filter- and map-functions to
make
the code more concise, but I can post it later if the need arises.
In the main method shown above are several calls of the subtract method,
all
of which should give empty RDDs as results because the data in all RDDs
should be exactly the same. This works for Spark in local mode, however
when
executing the code on a cluster the second block of subtract calls does
not
result in empty sets, which tells me that it is a more complicated issue.
The input data on local and cluster mode was exactly the same.
Can someone shed some light on this issue? I feel like I'm overlooking
something rather obvious.
--
View this message in context:
http://apache-spark-user-list.1001560.n3.nabble.com/Issues-with-JavaRDD-subtract-JavaRDD-method-in-local-vs-cluster-mode-tp24099.html
Sent from the Apache Spark User List mailing list archive at Nabble.com.
-
To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
For additional commands, e-mail: user-h...@spark.apache.org
