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courses:mapreduce-tutorial:step-11 [2012/01/25 15:46]
straka vytvořeno |
courses:mapreduce-tutorial:step-11 [2012/01/31 09:39] (current)
straka Change Perl commandline syntax. |
| ====== MapReduce Tutorial : ====== | ====== MapReduce Tutorial : Initialization and cleanup of MR tasks, performance of combiners ====== |
| | |
| | During the mapper or reducer task execution the following steps take place: |
| | * Perl script is executed in the current directory, ie. in the directory where the job was executed / submitted from. |
| | * Mapper/Reducer object is constructed. |
| | * Method ''setup($self, $context)'' is called on this object. The ''$context'' can be already used to produce (key, value) pairs or increment counters. |
| | * Method ''map'' or ''reduce'' is called for all input values. |
| | * Method ''cleanup($self, $context'') is called after all (key, value) pairs of this task are processed. Again, the ''$context'' can be used to produce (key, value) pairs or increment counters. |
| | * Perl script finishes. |
| | |
| | The ''setup'' and ''cleanup'' methods are very useful for initialization and cleanup of the tasks. |
| | |
| | Please note that complex initialization should not be performed during construction of Mapper and Reducer objects, as these are constructed every time the script is executed. |
| | |
| | ===== Exercise ===== |
| | |
| | Improve the {{:courses:mapreduce-tutorial:step-5-solution1.txt|step-11-wc-without-combiner.pl}} script by manually combining the results in the Mapper -- create a hash of word occurrences, populate it during the ''map'' calls without outputting results and finally output all (key, value) pairs in the ''cleanup'' method. |
| | |
| | wget --no-check-certificate 'https://wiki.ufal.ms.mff.cuni.cz/_media/courses:mapreduce-tutorial:step-5-solution1.txt' -O 'step-11-wc-without-combiner.pl' |
| | # NOW EDIT THE FILE |
| | # $EDITOR step-11-exercise.pl |
| | rm -rf step-11-out-wout; time perl step-11-wc-without-combiner.pl /home/straka/wiki/cs-text-medium/ step-11-out-wout |
| | less step-11-out-wout/part-* |
| | |
| | Measure the improvement. |
| | |
| | ==== Solution ==== |
| | You can also download the solution {{:courses:mapreduce-tutorial:step-11-solution.txt|step-11-wc-with-perl-hash.pl}} and check the correct output. |
| | |
| | wget --no-check-certificate 'https://wiki.ufal.ms.mff.cuni.cz/_media/courses:mapreduce-tutorial:step-11-solution.txt' -O 'step-11-wc-with-perl-hash.pl' |
| | # NOW VIEW THE FILE |
| | # $EDITOR step-11-solution.pl |
| | rm -rf step-11-out-with-hash; time perl step-11-wc-with-perl-hash.pl /home/straka/wiki/cs-text-medium/ step-11-out-with-hash |
| | less step-11-out-with-hash/part-* |
| | |
| | |
| | ===== Combiners and Perl API performance ===== |
| | |
| | As you have seen, the combiners are not very efficient when using the Perl API. This is a problem of the Perl API -- reading and writing the (key, value) pairs is relatively slow and a combiner does not help -- it in fact increases the number of (key, value) pairs that need to be read/written. |
| | |
| | This is even more obvious with larger input data: |
| | ^ Script ^ Time to complete on ''/home/straka/wiki/cs-text'' ^ Commands ^ |
| | | {{:courses:mapreduce-tutorial:step-5-solution1.txt|step-11-wc-without-combiner.pl}} | 5mins, 4sec | <html><pre>wget --no-check-certificate 'https://wiki.ufal.ms.mff.cuni.cz/_media/courses:mapreduce-tutorial:step-5-solution1.txt' -O 'step-11-wc-without-combiner.pl'<br>rm -rf step-11-out-wout; time perl step-11-wc-without-combiner.pl /home/straka/wiki/cs-text/ step-11-out-wout</pre></html> | |
| | | {{:courses:mapreduce-tutorial:step-10.txt|step-11-wc-with-combiner.pl}} | 5mins, 33sec | <html><pre>wget --no-check-certificate 'https://wiki.ufal.ms.mff.cuni.cz/_media/courses:mapreduce-tutorial:step-10.txt' -O 'step-11-wc-with-combiner.pl'<br>rm -rf step-11-out-with-combiner; time perl step-11-wc-with-combiner.pl /home/straka/wiki/cs-text/ step-11-out-with-combiner</pre></html>| |
| | | {{:courses:mapreduce-tutorial:step-11-solution.txt|step-11-wc-with-perl-hash.pl}} | 2mins, 24sec | <html><pre>wget --no-check-certificate 'https://wiki.ufal.ms.mff.cuni.cz/_media/courses:mapreduce-tutorial:step-11-solution.txt' -O 'step-11-wc-with-perl-hash.pl'<br>rm -rf step-11-out-with-perl-hash; time perl step-11-wc-with-perl-hash.pl /home/straka/wiki/cs-text/ step-11-out-with-perl-hash</pre></html>| |
| | |
| | |
| | For comparison, here are times of Java solutions: |
| | ^ Program ^ Time to complete on ''/home/straka/wiki/cs-text'' ^ Size of map output ^ |
| | | Wordcount without combiner | 2mins, 26sec | 367MB | |
| | | Wordcount with combiner | 1min, 51sec | 51MB | |
| | | Wordcount with hash in mapper | 1min, 14sec | 51MB | |
| | Using the combiner is beneficial, although combining the word occurrences in mapper manually is still faster. |
| | |
| | ---- |
| | |
| | <html> |
| | <table style="width:100%"> |
| | <tr> |
| | <td style="text-align:left; width: 33%; "></html>[[step-10|Step 10]]: Combiners.<html></td> |
| | <td style="text-align:center; width: 33%; "></html>[[.|Overview]]<html></td> |
| | <td style="text-align:right; width: 33%; "></html>[[step-12|Step 12]]: Additional output from mappers and reducers.<html></td> |
| | </tr> |
| | </table> |
| | </html> |
