LZ4m: Taking LZ4 Compression To The Next Level - Phoronix
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How LZ4 works ·
Warning: This is the blog I wrote as a kid. Most of what is written here is probably wrong. Tue, Oct 25, 2016 LZ4 is a really fast compression algorithm with a reasonable compression ratio, but unfortunately there is limited documentation on how it works. The only explanation (not spec, explanation) can be found on the author's blog, but I think it is less of an explanation and more of an informal
School - JA-VA Code
Java – the most common programming language, it is not difficult to learn, so it is suitable for those who first approached the study of programming. Introduction Java course is designed for those who are just starting their way in the IT industry and have no idea about the basics of programming. During the course, students will learn to create Java applications and gain an understanding of OOP pr
Previous Versions
This site contains documentation for HPE Ezmeral Data Fabric release 7.6.1, 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
Scaling the Facebook data warehouse to 300 PB
At Facebook, we have unique storage scalability challenges when it comes to our data warehouse. Our warehouse stores upwards of 300 PB of Hive data, with an incoming daily rate of about 600 TB. In the last year, the warehouse has seen a 3x growth in the amount of data stored. Given this growth trajectory, storage efficiency is and will continue to be a focus for our warehouse infrastructure. There
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
Linuxカーネル3.11リリース、安全な一時ファイルを作成するフラグや細かな新機能追加が行われる | OSDN Magazine
Linus Torvalds氏は9月2日、Linuxカーネル3.11を発表した。安全な一時ファイルを作成できる「O_TEMPFILE」フラグの導入やNFS 4.2のサポート、swapページを圧縮して格納する「Zswap」といった新機能の追加などが行われている。 6月末に公開された3.10に続くリリースとなり、約2か月での最新版リリースとなる。このバージョンは、今年で発表から20年を迎えた「Windows for Workgroup 3.11」にちなんで「Linux for Workgroups」というコード名が付けられていた。ロゴもペンギンがWindowsの旧マークの旗を持ったデザインとなっている。なお、正式リリースを発表したTorvalds氏は直前の7回目リリース候補（RC7）公開を告知しなかったことを認めている。 新機能としては、安全に一時ファイルを作成するための「O_TEMPFILE
Using memcached with LZ4 - tokuhirom's blog
Cache::Memcached::Fast uses Compress::Zlib by default to use compression. It's bit slow on high traffic environment. I got a Compress::Zlib as a bottleneck in our web application. In this case, you can use Compress::LZ4 for better performance. I'm using this as following form: use Cache::Memcached::Fast; use Compress::LZ4; my $memcache = Cache::Memcached::Fast->new(+{ %{config->cache}, utf8 => 1,
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
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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
chango/hustle · GitHub - A column oriented, embarrassingly distributed relational event database.
LZ4 Data Compression - Brutal Deluxe Software
smack [documentation]
DSIRNLP #3 LZ4 の速さの秘密に迫ってみる
MongoDBの慎ましい手法によるデータの圧縮
