https://github.com/christian-konrad/mapreduce-invertedindexer-example

Simplified example of an Inverted Indexer for plain text documents built on Hadoop's MapReduce framework.

https://github.com/christian-konrad/mapreduce-invertedindexer-example

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example hadoop hadoop-mapreduce inverted-index mapreduce
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Simplified example of an Inverted Indexer for plain text documents built on Hadoop's MapReduce framework.

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  • Host: GitHub
  • Owner: christian-konrad
  • Language: Java
  • Default Branch: master
  • Homepage:
  • Size: 61.5 KB
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example hadoop hadoop-mapreduce inverted-index mapreduce
Created about 5 years ago · Last pushed about 5 years ago
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Readme

README.md

Inverted Indexer built with MapReduce on Hadoop

This inverted indexer simply indexes all word terms (terms with only word-characters and containing min. 1 letter) of plain text files. It builds an index of term: {docName: occurenceCount}.

ℹ The generation of docIDs is omitted as we currently haven't implemented a mapping of those, so we simply return the file names. This is discouraged in general as it is too expensive and unreliable. You could implement a mapping yourself using hadoop's DistributedCache.

Prerequisitions

Edit the username in config.sh to the one of your HDFS path in the form of /user/$username. The documents to be indexed must be put into the documents directory and will be uploaded to your HDFS file system automatically on run.

⚠ You have to put hadoop to your PATH variable to run the scripts or replace hadoop with the path to your hadoop binary installation.

Run the indexer

You can compile the InvertedIndexer class and make a .jar out of it by simply running ./compile.sh in your shell. Afterwards, run it on your hadoop cluster using ./run.sh. Or, for convenience, do it all together calling ./compile_run.sh.

The inverted index output files can be found afterwards at /user/$username/InvertedIndexer/output.

Customizing the code

The project does not come with any build tool as it is compiled in the hadoop environment. To improve your coding using IntelliSense and others, simply add the following .jars to your project references, depending on the IDE you use. On VS Code, you can add them to your .vscode/settings.json or conveniently using the Java Projects view if you have the corresponding plugin installed.

  • hadoop-3.x.0\share\hadoop\mapreduce\hadoop-mapreduce-client-core-3.3.0.jar
  • hadoop-3.x.0\share\hadoop\hdfs\hadoop-hdfs-3.3.0.jar
  • hadoop-3.x.0\share\hadoop\common\hadoop-common-3.3.0.jar

Owner

  • Name: Christian Konrad
  • Login: christian-konrad
  • Kind: user
  • Location: Frankfurt, Germany
  • Company: @camunda

Product manager and software engineer living near Frankfurt am Main, Germany. My specialization is generalization.

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