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JavaFastPFOR: A simple integer compression library in Java Build Status

License

This code is released under the Apache License Version 2.0 http://www.apache.org/licenses/.

What does this do?

It is a library to compress and uncompress arrays of integers very fast. The assumption is that most (but not all) values in your array use less than 32 bits. These sort of arrays often come up when using differential coding in databases and information retrieval (e.g., in inverted indexes or column stores).

It can decompress integers at a rate of over 1.2 billions per second (4.5 GB/s). It is significantly faster than generic codecs (such as Snappy, LZ4 and so on) when compressing arrays of integers.

Part of this library has been integrated in Parquet (http://parquet.io/). This libary is used by ClueWeb Tools (https://github.com/lintool/clueweb). This library inspired a compression scheme used by Apache Lucene (e.g., see http://lucene.apache.org/core/4_6_1/core/org/apache/lucene/util/PForDeltaDocIdSet.html ).

It is a java port of the fastpfor C++ library (https://github.com/lemire/FastPFor). There is also a Go port (https://github.com/reducedb/encoding). The C++ library is used by the zsearch engine (http://victorparmar.github.com/zsearch/) as well as in GMAP and GSNAP (http://research-pub.gene.com/gmap/).

Usage

See example.java.

Some CODECs ("integrated codecs") assume that the integers are in sorted orders and use differential coding (they compress deltas). They can be found in the package me.lemire.integercopression.differential. Most others do not.

Maven central repository

Using this code in your own project is easy with maven, just add the following code in your pom.xml file:

<dependencies>
     <dependency>
     <groupId>me.lemire.integercompression</groupId>
     <artifactId>JavaFastPFOR</artifactId>
     <version>0.0.13</version>
     </dependency>
 </dependencies>

Naturally, you should replace "version" by the version you desire.

You can also download JavaFastPFOR from the Maven central repository: http://repo1.maven.org/maven2/me/lemire/integercompression/JavaFastPFOR/

Why?

We found no library that implemented state-of-the-art integer coding techniques such as Binary Packing, NewPFD, OptPFD, Variable Byte, Simple 9 and so on in Java. We wrote one.

Authors

Main contributors

with contributions by

How does it compare to the Kamikaze PForDelta library?

In our tests, Kamikaze PForDelta is slower than our implementations. See the benchmarkresults directory for some results.

https://github.com/lemire/JavaFastPFOR/blob/master/benchmarkresults/benchmarkresults_icore7_10may2013.txt

Reference: http://sna-projects.com/kamikaze/

Requirements

A recent Java compiler. Java 7 or better is recommended.

Good instructions on installing Java 7 on Linux:

http://forums.linuxmint.com/viewtopic.php?f=42&t=93052

How fast is it?

Compile the code and execute me.lemire.integercompression.benchmarktools.Benchmark.

I recommend running all the benchmarks with the "-server" flag on a desktop machine.

Speed is always reported in millions of integers per second.

For Maven users

mvn compile

mvn exec:java

For ant users

If you use Apache ant, please try this:

$ ant Benchmark

or:

$ ant Benchmark -Dbenchmark.target=BenchmarkBitPacking

API Documentation

http://lemire.me/docs/javafastpfor/

Want to read more?

This library was a key ingredient in the best paper at ECIR 2014 :

Matteo Catena, Craig Macdonald, Iadh Ounis, On Inverted Index Compression for Search Engine Efficiency, Lecture Notes in Computer Science 8416 (ECIR 2014), 2014. http://dx.doi.org/10.1007/978-3-319-06028-6_30

We wrote a research paper which documents many of the CODECs implemented here:

Daniel Lemire and Leonid Boytsov, Decoding billions of integers per second through vectorization, Software Pratice & Experience (to appear) http://arxiv.org/abs/1209.2137

Daniel Lemire, Leonid Boytsov, Nathan Kurz, SIMD Compression and the Intersection of Sorted Integers, arXiv:1401.6399, 2014 http://arxiv.org/abs/1401.6399

Ikhtear Sharif wrote his M.Sc. thesis on this library:

Ikhtear Sharif, Performance Evaluation of Fast Integer Compression Techniques Over Tables, M.Sc. thesis, UNB 2013. http://lemire.me/fr/documents/thesis/IkhtearThesis.pdf

He also posted his slides online: http://www.slideshare.net/ikhtearSharif/ikhtear-defense

Funding

This work was supported by NSERC grant number 26143.

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