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Both sides previous revision Previous revision 2012/02/06 14:52 dusek 2012/02/06 13:26 straka 2012/02/06 13:25 straka 2012/02/06 13:24 straka 2012/02/06 13:24 straka 2012/02/06 13:24 straka 2012/02/06 13:23 straka 2012/02/06 13:11 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 09:22 straka 2012/02/06 09:01 straka 2012/02/06 08:55 straka 2012/02/06 08:50 straka 2012/02/06 08:41 straka 2012/02/06 08:40 straka 2012/02/06 08:28 straka 2012/02/06 08:26 straka 2012/02/06 08:21 straka 2012/02/06 08:21 straka 2012/02/06 08:20 straka 2012/02/06 08:20 straka 2012/02/06 08:18 straka 2012/02/06 08:13 straka 2012/02/06 08:10 straka 2012/02/06 08:09 straka 2012/02/06 08:03 straka 2012/02/06 08:03 straka 2012/02/06 08:02 straka 2012/02/06 07:59 straka vytvořeno Go Next revision		Previous revision 2012/02/06 14:52 dusek 2012/02/06 13:26 straka 2012/02/06 13:25 straka 2012/02/06 13:24 straka 2012/02/06 13:24 straka 2012/02/06 13:24 straka 2012/02/06 13:23 straka 2012/02/06 13:11 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 13:10 straka 2012/02/06 09:22 straka 2012/02/06 09:01 straka 2012/02/06 08:55 straka 2012/02/06 08:50 straka 2012/02/06 08:41 straka 2012/02/06 08:40 straka 2012/02/06 08:28 straka 2012/02/06 08:26 straka 2012/02/06 08:21 straka 2012/02/06 08:21 straka 2012/02/06 08:20 straka 2012/02/06 08:20 straka 2012/02/06 08:18 straka 2012/02/06 08:13 straka 2012/02/06 08:10 straka 2012/02/06 08:09 straka 2012/02/06 08:03 straka 2012/02/06 08:03 straka 2012/02/06 08:02 straka 2012/02/06 07:59 straka vytvořeno Go Next revision Both sides next revision
courses:mapreduce-tutorial:step-31 [2012/02/06 08:50] straka		courses:mapreduce-tutorial:step-31 [2012/02/06 13:10] straka
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	It is crucial that all the mappers run simultaneously. This can be achieved using the ''/net/projects/hadoop/bin/compute-splitsize'' script: for given Hadoop input and requested number of mappers, it computes the appropriate splitsize.		It is crucial that all the mappers run simultaneously. This can be achieved using the ''/net/projects/hadoop/bin/compute-splitsize'' script: for given Hadoop input and requested number of mappers, it computes the appropriate splitsize.
-	When the computation finishes, only one of the mappers should print the results, as all of them have the same results. For simplicity, the ''cooperate'' method has ''boolean shouldWrite'' argument, which is set in exactly one mapper.	+	When the computation finishes, only one of the mappers should print the results, as all of them have the same results. For simplicity, the ''cooperate'' method has ''boolean writeResults'' argument, which is set in exactly one mapper.
	===== Example =====		===== Example =====
Line 102:		Line 102:
	You can run the example locally using:		You can run the example locally using:
	wget --no-check-certificate 'https://wiki.ufal.ms.mff.cuni.cz/_export/code/courses:mapreduce-tutorial:step-31?codeblock=0' -O Sum.java		wget --no-check-certificate 'https://wiki.ufal.ms.mff.cuni.cz/_export/code/courses:mapreduce-tutorial:step-31?codeblock=0' -O Sum.java
-	make -f /net/projects/hadoop/java/Makefile Sum.java	+	make -f /net/projects/hadoop/java/Makefile Sum.jar
	rm -rf step-31-out; /net/projects/hadoop/bin/hadoop Sum.jar /net/projects/hadoop/examples/inputs/numbers-small step-31-out		rm -rf step-31-out; /net/projects/hadoop/bin/hadoop Sum.jar /net/projects/hadoop/examples/inputs/numbers-small step-31-out
	less step-31-out/part-*		less step-31-out/part-*
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	* ''clusters.file'' -- file where to read the initial clusters from		* ''clusters.file'' -- file where to read the initial clusters from
	You can download and compile it using:		You can download and compile it using:
-	wget --no-check-certificate 'https://wiki.ufal.ms.mff.cuni.cz/_media/courses:mapreduce-tutorial:step-31-exercise3.txt' -O KMeans.java.java	+	wget --no-check-certificate 'https://wiki.ufal.ms.mff.cuni.cz/_media/courses:mapreduce-tutorial:step-31-exercise3.txt' -O KMeans.java
	# NOW VIEW THE FILE		# NOW VIEW THE FILE
-	# $EDITOR KMeans.java.java	+	# $EDITOR KMeans.java
-	make -f /net/projects/hadoop/java/Makefile KMeans.java.java	+	make -f /net/projects/hadoop/java/Makefile KMeans.java
-	You can run it using //C// machines on the following input data:	+	You can run it using specified number of machines on the following input data:
-	* ''/net/projects/hadoop/examples/inputs/points-small'': <code>rm -rf step-31-out; /net/projects/hadoop/bin/hadoop KMeans.java.jar -Dclusters.num=50 -Dclusters.file=/net/projects/hadoop/examples/inputs/points-small/points.txt -c C `/net/projects/hadoop/bin/compute-splitsize /net/projects/hadoop/examples/inputs/points-small C` /net/projects/hadoop/examples/inputs/points-small step-31-out</code>	+	* ''/net/projects/hadoop/examples/inputs/points-small'':
-	* ''/net/projects/hadoop/examples/inputs/points-medium'': <code>rm -rf step-31-out; /net/projects/hadoop/bin/hadoop KMeans.java.jar -Dclusters.num=100 -Dclusters.file=/net/projects/hadoop/examples/inputs/points-medium/points.txt -c C `/net/projects/hadoop/bin/compute-splitsize /net/projects/hadoop/examples/inputs/points-medium C` /net/projects/hadoop/examples/inputs/points-medium step-31-out</code>	+	<code>M=machines; K=50; INPUT=/net/projects/hadoop/examples/inputs/points-small/points.txt
-	* ''/net/projects/hadoop/examples/inputs/points-large'': <code>rm -rf step-31-out; /net/projects/hadoop/bin/hadoop KMeans.java.jar -Dclusters.num=200 -Dclusters.file=/net/projects/hadoop/examples/inputs/points-large/points.txt -c C `/net/projects/hadoop/bin/compute-splitsize /net/projects/hadoop/examples/inputs/points-large C` /net/projects/hadoop/examples/inputs/points-large step-31-out</code>	+	rm -rf step-31-out; /net/projects/hadoop/bin/hadoop KMeans.jar -Dclusters.num=$K -Dclusters.file=$INPUT [-jt jobtracker | -c $M] `/net/projects/hadoop/bin/compute-splitsize $INPUT $M` $INPUT step-31-out</code>
		+	* ''/net/projects/hadoop/examples/inputs/points-medium'':
		+	<code>M=machines; K=100; INPUT=/net/projects/hadoop/examples/inputs/points-medium/points.txt
		+	rm -rf step-31-out; /net/projects/hadoop/bin/hadoop KMeans.jar -Dclusters.num=$K -Dclusters.file=$INPUT [-jt jobtracker | -c $M] `/net/projects/hadoop/bin/compute-splitsize $INPUT $M` $INPUT step-31-out</code>
		+	* ''/net/projects/hadoop/examples/inputs/points-large'':
		+	<code>M=machines; K=200; INPUT=/net/projects/hadoop/examples/inputs/points-large/points.txt
		+	rm -rf step-31-out; /net/projects/hadoop/bin/hadoop KMeans.jar -Dclusters.num=$K -Dclusters.file=$INPUT [-jt jobtracker | -c $M] `/net/projects/hadoop/bin/compute-splitsize $INPUT $M` $INPUT step-31-out</code>
	Solution: {{:courses:mapreduce-tutorial:step-31-solution3.txt|KMeans.java}}.		Solution: {{:courses:mapreduce-tutorial:step-31-solution3.txt|KMeans.java}}.

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