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The following page has been changed by OwenOMalley: http://wiki.apache.org/lucene-hadoop/RandomWriter ------------------------------------------------------------------------------ '''RandomWriter''' example - ''RandomWriter" example implements a distributed random writer. Each map takes a file name as input and writes one Gig of random data to the DFS sequence file by generating multiple records, each with a random key and a random value. A mapper does not emit any output and the reduce phase is null. + ''RandomWriter'' example writes random data to DFS using Map/Reduce. Each map takes a file name as input and writes one Gig of random data to the DFS sequence file by generating multiple records, each with a random key and a random value. A mapper does not emit any output and the reduce phase is not used. + + The specifics of the generated data are configurable. The configuration variables are: + + || Name || Default Value || Description || + || test.randomwriter.maps_per_host || 10 || Number of maps/host || + || test.randomwrite.bytes_per_map || 1024*1024*1024 || Number of bytes written/map || + || test.randomwrite.min_key || 10 || minimum size of the key in bytes || + || test.randomwrite.max_key || 1000 || maximum size of the key in bytes || + || test.randomwrite.min_value || 0 || minimum size of the value || + || test.randomwrite.max_value || 20000 || maximum size of the value || + This example uses a useful pattern for dealing with Hadoop's constraints on !InputSplits. Since each input split can only consist of a file and byte range and we want to control how many maps there are (and we don't really have any inputs), we create a directory with a set of artificial files, each of which contains the filename that we want a given map to write to. Then, using the text line reader and this "fake" input directory, we generate exactly the right number of maps. Each map gets a single record that is the filename, to which it is supposed to write its output.
