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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.

About

A simple integer compression library in Java

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GitHub - roysamit/JavaFastPFOR: A simple integer compression library in Java · GitHub
Skip to content

Repository files navigation

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.

About

A simple integer compression library in Java

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1 watching

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Force GitHub README to respect dark mode (function() { var style = document.createElement('style'); style.textContent = ' .markdown-body { color-scheme: dark light; } .markdown-body pre { background: #161b22 !important; } .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; } .markdown-body table th, .markdown-body table td { border-color: #30363d !important; } .markdown-body img { background: #0d1117; } .markdown-body blockquote { border-left-color: #8b949e; } .markdown-body hr { border-color: #30363d; } '; document.head.appendChild(style); })(); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - roysamit/JavaFastPFOR: A simple integer compression library in Java · GitHub
Skip to content

Repository files navigation

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.

About

A simple integer compression library in Java

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Watchers

1 watching

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Highlight search terms from Google/DuckDuckGo/Bing referrer (function() { var ref = document.referrer; var terms = []; if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) { var url = new URL(ref); var q = url.searchParams.get('q') || url.searchParams.get('p'); if (q) { terms = q.split(/\s+/).filter(function(t) { return t.length > 2; }); } } if (terms.length === 0) return; var style = document.createElement('style'); style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }'; document.head.appendChild(style); function highlight(node) { if (node.nodeType === 3) { // text node var text = node.textContent; var found = false; terms.forEach(function(term) { var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - roysamit/JavaFastPFOR: A simple integer compression library in Java · GitHub
Skip to content

Repository files navigation

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.

About

A simple integer compression library in Java

Resources

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0 stars

Watchers

1 watching

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Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ' GitHub - roysamit/JavaFastPFOR: A simple integer compression library in Java · GitHub
Skip to content

Repository files navigation

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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A simple integer compression library in Java

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - roysamit/JavaFastPFOR: A simple integer compression library in Java · GitHub
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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.

About

A simple integer compression library in Java

Resources

Stars

0 stars

Watchers

1 watching

Forks

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Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - roysamit/JavaFastPFOR: A simple integer compression library in Java · GitHub
Skip to content

Repository files navigation

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.

About

A simple integer compression library in Java

Resources

Stars

0 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Universal Dark Mode - works on any site (function() { var enabled = true; function applyDarkMode() { if (!enabled) return; // Create style element if it doesn't exist var style = document.getElementById('universal-dark-mode-style'); if (!style) { style = document.createElement('style'); style.id = 'universal-dark-mode-style'; document.head.appendChild(style); } // Dark mode CSS - inverts colors but preserves images/video style.textContent = ' /* Invert everything except media */ html { filter: invert(1) hue-rotate(180deg) !important; background: #1a1a2e !important; } /* Restore images, videos, iframes, canvas */ img, video, iframe, canvas, svg, picture, [style*="background-image"] { filter: invert(1) hue-rotate(180deg) !important; } /* Preserve specific elements that should not be inverted */ .no-dark-mode, .no-dark-mode *, [data-theme="light"], [data-theme="light"], .ace_editor, .ace_editor *, .CodeMirror, .CodeMirror *, .monaco-editor, .monaco-editor *, .markdown-body pre, .markdown-body pre *, .highlight, .highlight *, pre code, pre code * { filter: none !important; } /* Fix common UI elements */ .modal, .popup, .dropdown-menu, .tooltip, .popover { filter: invert(1) hue-rotate(180deg) !important; background: #2d2d44 !important; border-color: #444 !important; } /* Scrollbars */ ::-webkit-scrollbar { background: #1a1a2e !important; } ::-webkit-scrollbar-thumb { background: #444 !important; } ::-webkit-scrollbar-thumb:hover { background: #555 !important; } /* Selection */ ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; } ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; } '; } function removeDarkMode() { var style = document.getElementById('universal-dark-mode-style'); if (style) style.remove(); } // Toggle with Alt+Shift+D document.addEventListener('keydown', function(e) { if (e.altKey && e.shiftKey && e.key === 'D') { e.preventDefault(); enabled = !enabled; if (enabled) { applyDarkMode(); console.log('[Universal Dark Mode] Enabled'); } else { removeDarkMode(); console.log('[Universal Dark Mode] Disabled'); } } }); // Apply on load applyDarkMode(); // Re-apply on dynamic content var observer = new MutationObserver(function(mutations) { if (enabled && !document.getElementById('universal-dark-mode-style')) { applyDarkMode(); } }); observer.observe(document.head, { childList: true }); console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle'); })(); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })(); GitHub - roysamit/JavaFastPFOR: A simple integer compression library in Java · GitHub
Skip to content

Repository files navigation

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.

About

A simple integer compression library in Java

Resources

Stars

0 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages