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
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
Evaluation of cloudera impala 1.1
This document evaluates the performance of Cloudera Impala 1.1 using two clusters. It finds that RCFile with Snappy compression provides the fastest performance for both Hive and Impala on the clusters for reading-only workloads. Parquet with Snappy may be fastest for larger tables. Issues were identified with memory limits during Parquet table creation and were later fixed. The evaluation shows I
Hadoop Hive - ORC Files
ORC File Format File Structure Stripe Structure HiveQLSyntax Serialization and Compression Integer Column Serialization String Column Serialization Compression ORC File Format The Optimized Row Columnar (ORC) file format provides a highly efficient way to store Hive data. It was designed to overcome limitations of the other Hive file formats. Using ORC files improves performance when Hive is readi
MongoDBã®æ…Žã¾ã—ã„手法ã«ã‚ˆã‚‹ãƒ‡ãƒ¼ã‚¿ã®åœ§ç¸®
MongoDBã¯éžå¸¸ã«ä¾¿åˆ©ãªNoSQLプãƒãƒ€ã‚¯ãƒˆã§ã™ãŒã€ã‚る程度ã®è¦æ¨¡ã§é‹ç”¨ã—よã†ã¨ã™ã‚‹ã¨ãƒ‡ãƒ¼ã‚¿ã‚µã‚¤ã‚ºã®è‚¥å¤§åŒ–ã«æ‚©ã¾ã•ã‚Œã¾ã™ã€‚ MongoDBã¯ã‚‚ã¨ã‚‚ã¨å¯Œè±ªçš„ãªä½œã‚Šã®ã‚¢ãƒ—リケーションãªã®ã§ãƒ‡ãƒ¼ã‚¿ã‚µã‚¤ã‚ºã‚’ä»–Storageよりも多ã‚ã«ä½¿ç”¨ã—ã¾ã™ã—ã€ã‹ã¤æ¨™æº–ã§ã¯ãƒ‡ãƒ¼ã‚¿ã®åœ§ç¸®ã‚’サãƒãƒ¼...
Compression algorithm that produces url safe data
I'm looking to store cookie data in a compact form. Is there such a thing as a compression algorithm that produces URL safe output? Currently my approach is String jsonData = GSON.toJson(data); byte[] cookieBinaryData = jsonData.getBytes("UTF-8"); byte[] cookieSnappyData = Snappy.compress(cookieBinaryData); String cookieBase64Data = new Base64(true).encodeToString(cookieSnappyData); From this cook
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スクウェア・エニックスã®äººæ°—RPG「ドラゴンクエストã€ã‚·ãƒªãƒ¼ã‚ºã®æœ€æ–°ä½œã€Œãƒ‰ãƒ©ã‚´ãƒ³ã‚¯ã‚¨ã‚¹ãƒˆX（ドラクエ10）ã€ã¯ã‚·ãƒªãƒ¼ã‚ºåˆã®ã‚ªãƒ³ãƒ©ã‚¤ãƒ³ä½œå“ã¨ãªã‚Šã¾ã—ãŸãŒã€ãã®èˆžå°è£ã¯ä¸€ä½“ã©ã†ãªã£ã¦ã„ãŸã®ã‹ã€‚ゲームã®ä¸–界観を支ãˆã‚‹ã‚µãƒ¼ãƒã‚·ã‚¹ãƒ†ãƒ ãŒã©ã®ã‚ˆã†ã«æ§‹æˆã•ã‚Œã¦ã„ã‚‹ã®ã‹ã¨ã„ã†ã“ã¨ã‚„ã€ãƒ‰ãƒ©ã‚´ãƒ³ã‚¯ã‚¨ã‚¹ãƒˆâ…©ãªã‚‰ã§ã¯ã®ä»•çµ„ã¿ã‚„機能ã‹ã‚‰é–‹ç™ºã®è‹¦åŠ´è©±ã¾ã§ã€æ ªå¼ä¼šç¤¾ã‚¹ã‚¯ã‚¦ã‚§ã‚¢ãƒ»ã‚¨ãƒ‹ãƒƒã‚¯ã‚¹é–‹ç™ºéƒ¨ãƒ—ãƒã‚°ãƒ©ãƒžæ£®å±±æœ‹è¼ã•ã‚“ãŒèªžã£ã¦ã„ã¾ã™ã€‚ タイトル | CEDEC 2012 | Computer Entertaintment Developers Conference http://cedec.cesa.or.jp/2012/program/NW/C12_P0040.html 森山朋è¼ï¼š 皆様ã€æœ¬æ—¥ã¯ãŠé›†ã¾ã‚Šé ‚ãã©ã†ã‚‚ã‚ã‚ŠãŒã¨ã†ã”ã–ã„ã¾ã™ã€‚ã“ã®ã‚»ãƒƒã‚·ãƒ§ãƒ³ã‚’担当ã•ã›ã¦é ‚ãã¾ã™ã€æ ªå¼ä¼šç¤¾ã‚¹ã‚¯ã‚¦ã‚§ã‚¢ãƒ»ã‚¨ãƒ‹ãƒƒã‚¯ã‚¹é–‹ç™ºéƒ¨æ‰€å±žã®æ£®å±±æœ‹è¼ã¨
MessagePackã§åœ§ç¸®ã‚’サãƒãƒ¼ãƒˆã—ã¦ç¯€é›»ã™ã‚‹ï¼
Kazuki Ohta @kzk_mover suma先生ã‹ã£ã‘㈠RT @suma90h: 節電ã¨ã‹ã¡ã¾ã¡ã¾è¨€ã£ã¦ãªã„ã§MessagePackã§æ—¥æœ¬ã‚’æ•‘ãˆãŸã‚‰ã‚ˆã„ã®ã§ã¯ãªã„ã‹ã¨! 2011-03-24 02:01:55 Nobuyuki Kubota @nobu_k http://quakememe.jp/ ã®èƒŒå¾Œã§ã¯MessagePackãŒå‹•ãã¾ãã£ã¦ã¾ã™ï¼ RT @suma90h: 節電ã¨ã‹ã¡ã¾ã¡ã¾è¨€ã£ã¦ãªã„ã§MessagePackã§æ—¥æœ¬ã‚’æ•‘ãˆãŸã‚‰ã‚ˆã„ã®ã§ã¯ãªã„ã‹ã¨! 2011-03-24 02:04:15
Snappy servay
2. google-snappy Snappy is a compression/decompression library. It does not aim for maximum compression, or compatibility with any other compression library; instead, it aims for very high speeds and reasonable compression. For instance, compared to the fastest mode of zlib, Snappy is an order of magnitude faster for most inputs, but the resulting compressed files are anywhere from 20% to 100% big
Google Snappy (Twitter JSONã®åœ§ç¸®ï¼‰
以å‰ã®ãƒ–ãƒã‚° ã§Snappyを試ã—ã¦ã¿ãŸå†…容を記載ã—ã¾ã—ãŸãŒã€åœ§ç¸®å¯¾è±¡ã®ãƒ‡ãƒ¼ã‚¿ã¯Snappyライブラリã«åŒæ¢±ã®ãƒ†ã‚¹ãƒˆãƒ‡ãƒ¼ã‚¿ã ã£ãŸã®ã§ã€å®Ÿéš›çš„ãªãƒ‡ãƒ¼ã‚¿ã‚’用ã„ã‚‹ã¨ã©ã®ç¨‹åº¦ã®åœ§ç¸®çŽ‡ã«ãªã‚‹ã‹è¦‹ã¦ã¿ãŸã‹ã£ãŸã®ã§è©¦ã—ã¦ã¿ã¾ã—ãŸã€‚ 一番手軽ã«è©¦ã›ã‚‹ã®ãŒTwitterã®Streaming API...
GitHub - ning/jvm-compressor-benchmark: Benchmark suite for data compression library on the JVM
Overview This project is focus on building a comprehensive benchmark for comparing time and space efficiency of open source compression codecs on JVM platform. Codecs to include need to be accesible from Java (and thereby from any JVM language) via either pure Java interface or JNI; and need to support either basic block mode (byte array in, byte array out), or streaming code (InputStream in, Outp
Cloudera Blog
In an era where artificial intelligence (AI) is reshaping enterprises across the globe—be it in healthcare, finance, or manufacturing—it’s hard to overstate the transformation that AI has had on businesses, regardless of industry or size. At Cloudera, we recognize the urgent need for bold steps to harness this potential and dramatically accelerate the time to […] Read blog post
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GitHub - airlift/aircompressor: A port of Snappy, LZO, LZ4, and Zstandard to Java
GitHub - prometheus/prometheus: The Prometheus monitoring system and time series database.
GitHub - google/leveldb: LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.
GitHub - decster/jnicompressions: Java port(JNI) of Snappy & LZ4 compression codec
GitHub - dain/snappy: Port of Snappy to Java
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