LZ4m: Taking LZ4 Compression To The Next Level - Phoronix
LZ4m: Taking LZ4 Compression To The Next Level Written by Michael Larabel in Free Software on 2 June 2017 at 05:59 AM EDT. 14 Comments While LZ4 can be very fast with its compression and decompression speeds, there's a new kid on the block that appears to be even faster: LZ4m. LZ4m is a compression algorithm designed for in-memory data geared for use when dealing with data intensive applications.
Deflate vs Grip: Which Tire Pressure is Best for Vehicle?
In the fast-paced digital landscape of today, website performance is paramount. Users expect lightning-fast loading times, and search engines prioritize speed when ranking websites. One key aspect of optimizing website performance is compression. In this article, we will delve into the world of general compression techniques and how they can enhance your website’s speed and overall user experience
Previous Versions
This site contains documentation for HPE Ezmeral Data Fabric release 7.8.0, including installation, configuration, administration, and reference content, as well as content for the associated ecosystem components and drivers. This section contains information about installing and upgrading HPE Ezmeral Data Fabric software. It also contains information about how to migrate data and applications fro
LZ4 の近況を確認してみる
lz4-ruby の開発を進めるために、LZ4 の近況を確認してみたところ、 それなりに活発に開発されているようで変更点が多かったため、メモを兼ねてエントリにまとめてみました。 r76 から r113 までの変更履歴を追う形で、主だった変更を列挙していきます。 API が増えた r76 の時点ではマクロを含めて 6 個だった API が、r113 では obsolete を除いても 36 個と大幅に増えました。 LZ4 の基本機能は以前とはそう変わらないものの、後述するストリーム処理用 API など、 利用シーンごとに適した API を拡充しているようです。 liblz4 が作成されるようになった r111 より。 以前の LZ4 は Makefile はあれど make してもライブラリは生成されず、 そのためアプリケーションから LZ4 の圧縮・伸長機能を利用しようとすると、 アプリケ
LZ4 explained
At popular request, this post tries to explain the LZ4 inner workings, in order to allow any programmer to develop its own version, potentially using another language than the one provided on Google Code (which is C). The most important design principle behind LZ4 has been simplicity. It allows for an easy code, and fast execution. Let's start with the compressed data format. The compressed block
Compression Options in Hadoop - A Tale of Tradeoffs
Yahoo! is one of the most-visited web sites in the world. It runs one of the largest private cloud infrastructures, one that operates on petabytes of data every day. Being able to store and manage that data well is essential to the efficient functioning of Yahoo!`s Hadoop clusters. A key component that enables this efficient operation is data compression. With regard to compression algorithms, the
LZ4 into Hadoop-MapReduce
After a very fast evaluation, LZ4 has been recently integrated into the Apache project Hadoop - MapReduce. This is an important news, since, in my humble opinion, Hadoop is among the most advanced and ambitious projects to date (an opinion which is shared by some). It also serves as an excellent illustration of LZ4 usage, as an in-memory compression algorithm for big server applications. But firs
DSIRNLP #3 LZ4 の速さの秘密に迫ってみる
8. Agenda 1. What is LZ4 ? 2. Dictionary compression 3. Why fast ? 4. Conclusion 8
Quick Benchmark: Gzip vs Bzip2 vs LZMA vs XZ vs LZ4 vs LZO - CatchChallenger wiki
Selected archives I have selected: Source of the kernel to test source compression Stream protocol with flush Test conditions Tests were run on a desktop: Intel Core i5 CPU 750 at 2.67GHz 8GB of DDR3 memory tmpfs as ram disk is used Linux kernel 3.3.2, gentoo amd64 CFLAGS: -pipe -O2 -g -floop-block -floop-interchange -fgraphite bzip2-1.0.6-r3, xz-utils-5.0.3, gzip-1.4 Only normal mode will be test
ドラゴンクエストXは「世界は一つ」を実現するためにどのようなサーバ構成にしているのか？
スクウェア・エニックスの人気RPG「ドラゴンクエスト」シリーズの最新作「ドラゴンクエストX（ドラクエ10）」はシリーズ初のオンライン作品となりましたが、その舞台裏は一体どうなっていたのか。ゲームの世界観を支えるサーバシステムがどのように構成されているのかということや、ドラゴンクエストⅩならではの仕組みや機能から開発の苦労話まで、株式会社スクウェア・エニックス開発部プログラマ森山朋輝さんが語っています。 タイトル | CEDEC 2012 | Computer Entertaintment Developers Conference http://cedec.cesa.or.jp/2012/program/NW/C12_P0040.html 森山朋輝： 皆様、本日はお集まり頂きどうもありがとうございます。このセッションを担当させて頂きます、株式会社スクウェア・エニックス開発部所属の森山朋輝と
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Testing PGO with LZ4 and Zstd codecs
GitHub - inikep/lizard: Lizard (formerly LZ5) is an efficient compressor with very fast decompression. It achieves compression ratio that is comparable to zip/zlib and zstd/brotli (at low and medium compression levels) at decompression speed of 1000 MB/s
GitHub - airlift/aircompressor: A port of Snappy, LZO, LZ4, and Zstandard to Java
LZ4 Data Compression - Brutal Deluxe Software
MongoDBの慎ましい手法によるデータの圧縮
GitHub - lz4/lz4: Extremely Fast Compression algorithm