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Examples
The classic map-reduce example is to compute word frequency in a text corpus:
fm map -i "/etext/*" "sed -f words.sed | fm split -n 9 |> sort | uniq -c"
Let’s walk through this example step-by-step: First, the FileMap command is “fm”. You must always specify a sub-command and in this case it is “map”, which is used to specify and execute a computation. The “-i” option specifies a wildcard expression that specifies the input files to process. These files need to have been stored in advance into the replicated, virtual filesystem provided by FileMap. To do so, use commands like this:
fm mkdir /etext
fm store /tmp/*.txt /etext/
If you want to follow along, you can download a few e-texts from Project Gutenberg:
cd /tmp
for f in shplk10 sread10 spoem10 mysky10 leave10 gryms10; do wget --user-agent='definitely-not-wget' http://www.gutenberg.org/dirs/etext05/$f.txt; done
The remainder of the command is an execution pipeline that is applied to each input file. While the Unix pipe (|) symbol is used, each element of the pipeline is actually passed an input filename (the original or intermediate results) and has its stdout and stderr saved in files.
The first pipeline element uses sed to extract a list of words, one per line, from a text document. The words.sed script is as follows:
s/[\"\(\'\-\/]*\([a-zA-Z]*\) */\1\
/g
The “fm split” command partitions an input file into a specified number of files (9 in this case). In this case, a hash is computed on each input line to determine which output partition the line belongs to. Importantly, the same input word always gets put in the same partition. Commands that know how to partition data use the FMOUTPUT environment variable to obtain the output filename base. To that base, they add an extension number for the partition (in this case .1 through .9).
The |> operator is a reduce operation. First, all of the input files prior to this point in the pipeline are redistributed among the nodes. All files with the same suffix will be stored to the same node(s). The command on the right-hand side of the |> operator is responsible for reducing all of the input files for a given partition. This means that it will be executed with a list of input files constituting a partition. Each partition is processed separately (in parallel). In the case of the Unix sort command, it produces a single sorted output from multiple inputs.
Finally, the output of each sorted partition is passed to a “uniq -c” instance, which is the Unix command to tally up the number of identical consecutive lines (words in this case). The “fm map” command implicitly concatenates the outputs of the last stage of the pipeline and outputs them to stdout. In this case, this prints our final word frequency list.
Let’s do some directory listings to look at the input and intermediate files. The format is very similar to traditional POSIX ls, but with a few differences. First, the second column, which would be a hard-link count normally, shows which nodes contained the file or directory (* means all nodes). If more than one node contains a file of the same size, permissions, and ownership, then the file’s modification time is not shown (since it is unlikely to be the same for all nodes). Also, directories are always considered to have a 0 size.
$ ./fm ls -n /etext/* /etext/* /etext/*/* /etext/*/*/* /etext/*/*/*/* /etext/*/*/*/*/* /reduce/*/* /reduce/*/*/* reduce/*/*/*/* reduce/*/*/*/*/* | grep '^-' -rw-r--r-- 20a mfisk ydata 8.3e4 May 18 2003 /etext/gryms10.txt -rwxrwxr-x 20a mfisk ydata 8.9e4 Jan 02 17:25 /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0 -rwxrwxr-x 10b,20a mfisk ydata 0 - /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/0 -rw-rw-r-- 20a,24a mfisk ydata 1.6e4 - /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/1 -rw-rw-r-- 20a,26a mfisk ydata 1.1e4 - /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/2 -rw-rw-r-- 10a,20a mfisk ydata 8.9e3 - /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/3 -rw-rw-r-- 20a,21a mfisk ydata 7.6e3 - /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/4 -rw-rw-r-- 10a,20a mfisk ydata 7.2e3 - /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/5 -rw-rw-r-- 10b,20a mfisk ydata 1e4 - /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/6 -rw-rw-r-- 10b,20a mfisk ydata 9.7e3 - /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/7 -rw-rw-r-- 20a,32a mfisk ydata 5.8e3 - /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/8 -rw-rw-r-- 20a,29a mfisk ydata 1.3e4 - /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/9 -rw-rw-r-- 20a mfisk ydata 2.4e2 Jan 02 17:25 /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/status -rwxrwxr-x 20a mfisk ydata 0 Jan 02 17:25 /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/stderr -rw-rw-r-- 20a mfisk ydata 2.2e2 Jan 02 17:25 /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/status -rwxrwxr-x 20a mfisk ydata 0 Jan 02 17:25 /etext/gryms10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/stderr -rw-r--r-- 23a mfisk ydata 1.2e5 Jun 28 2003 /etext/mysky10.txt -rwxrwxr-x 23a mfisk ydata 1.3e5 Jan 02 17:25 /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0 -rwxrwxr-x 10b,23a mfisk ydata 0 - /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/0 -rw-rw-r-- 23a,24a mfisk ydata 2.1e4 - /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/1 -rw-rw-r-- 23a,26a mfisk ydata 1.7e4 - /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/2 -rw-rw-r-- 10a,23a mfisk ydata 1.4e4 - /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/3 -rw-rw-r-- 21a,23a mfisk ydata 1.4e4 - /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/4 -rw-rw-r-- 10a,23a mfisk ydata 1.2e4 - /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/5 -rw-rw-r-- 10b,23a mfisk ydata 1.4e4 - /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/6 -rw-rw-r-- 10b,23a mfisk ydata 1.2e4 - /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/7 -rw-rw-r-- 23a,32a mfisk ydata 9.7e3 - /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/8 -rw-rw-r-- 23a,29a mfisk ydata 1.8e4 - /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/9 -rw-rw-r-- 23a mfisk ydata 2.5e2 Jan 02 17:26 /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/status -rwxrwxr-x 23a mfisk ydata 0 Jan 02 17:26 /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/stderr -rw-rw-r-- 23a mfisk ydata 2.3e2 Jan 02 17:25 /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/status -rwxrwxr-x 23a mfisk ydata 0 Jan 02 17:25 /etext/mysky10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/stderr -rw-r--r-- 23a mfisk ydata 5.4e5 Jul 25 2003 /etext/shplk10.txt -rwxrwxr-x 23a mfisk ydata 5.7e5 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/etext/spoem10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/9 -rw-rw-r-- 10b mfisk ydata 2.4e2 Jan 02 17:25 /etext/spoem10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/status -rwxrwxr-x 10b mfisk ydata 0 Jan 02 17:25 /etext/spoem10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/stderr -rw-rw-r-- 10b mfisk ydata 2.3e2 Jan 02 17:25 /etext/spoem10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/status -rwxrwxr-x 10b mfisk ydata 0 Jan 02 17:25 /etext/spoem10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/stderr -rw-r--r-- 18a mfisk ydata 6.9e5 Sep 03 2003 /etext/sread10.txt -rwxrwxr-x 18a mfisk ydata 7.3e5 Jan 02 17:25 /etext/sread10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0 -rwxrwxr-x 10b,18a mfisk ydata 0 - /etext/sread10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/0 -rw-rw-r-- 18a,24a mfisk ydata 1.3e5 - /etext/sread10.txt.d/sed=20=2Df=20=7E=2Fwords=2Esed/0.d/fm=20split=20=2Dn=209/1 -rw-rw-r-- 18a,26a mfisk ydata 1.1e5 - 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As you see, the output of a map operation is put in a file whose name is the map operation and whose location is a subdirectory of the input file (subdirectories have the same name as the input file, but with a .d added to the end). For example, the input file /etext/gryms10.txt was used as an input, the output will be under “gryms10.txt.d”. Since the command run was “sed -f ~/words.sed” operation, the stdout of that operation would be “/etext/gryms10.txt.d/sed -f ~/words.sed/0”. To simplify filenames, the Quoted-Printable encoding is used for all but simple alphanumeric characters in the filename. Thus, the actual file name is sed=20=2Df=20=7E=2Fwords=2Esed/0. In addition, you will find a file with the name stderr that contains the stderr output from the process and a status file created at completion containing statistics about the execution of the process. At the completion of a map operation, any stderr files for any stage of the entire pipeline are displayed.
Since the output of the sed stage was used as input to the “fm split” stage, a “sed=20=2Df=20words=2Esed/0.d” directory is created. Any command can create multiple output files to support additional downstream parallelism. “fm split” is one of these “partitioning” commands. So in addition to the 0 file for stdout, “fm split” creates a number of output files numbered 1 through 9. (All map commands are run with their current working directory set to the output directory).
The reduce operator, “|>” triggers an implicit “fm _local restore” stage that redistributes the data so that all files with the same name reside on the same node for the reduce operation. The reduce operation itself is placed in a new directory since it is derived from multiple inputs. Each stage of a pipeline is called a job and the “fm jobs” command will list any currently-running jobs. The reduce output is placed in a subdirectory in /reduce which is named by the job-id. (Job IDs are digests of the internal job description files which can be found in /jobs). Reduce operations are run with a list of files as their arguments. In our case, one instance of sort will get all of the 0 inputs, another instance will get all of the 1 inputs, and so on.
The output of the reduce operation is input to the final pipeline stages using this the same process as the initial map operations. When the final stage of the pipeline completes, all of the final output files will be concatenated together and delivered on stdout.