| | 12 | == Social Network : Facebook == |
| | 13 | |
| | 14 | * [http://www.linux-mag.com/id/8705/ FBCMD: Command Line for Facebook] - 可以用命令列取得 Facebook 資訊的工具，看樣子這樣要作批次處理就變簡單了。 |
| | 15 | * [http://gigaom.com/cloud/how-facebook-brings-a-new-data-center-online/ How Facebook Brings a New Data Center Online] - Facebook 最近擴充動作頻繁，這篇文章提到幾個自由軟體： |
| | 16 | * [https://github.com/facebook/flashcache/ FlashCache] - 看起來是加速 MySQL 資料庫的工具 |
| | 17 | {{{ |
| | 18 | Flashcache with MySQL allows us to achieve twice the throughput on each of |
| | 19 | our new MySQL machine...we need to run two MySQL instances on each machine... |
| | 20 | }}} |
| | 21 | * 另外有個佈署工具叫做 Kobold，不過還找不到 code。 |
| | 22 | |
| | 23 | == Hadoop == |
| | 24 | |
| | 25 | * 多數 Hadoop 的 Patch 由 Yahoo 提供。 |
| | 26 | * [[Image(http://ydn.zenfs.com/blogs/22/HadoopPatches.png,width=800)]] |
| | 27 | * 下一代的 Hadoop MapReduce 架構 - [http://developer.yahoo.com/blogs/hadoop/posts/2011/02/mapreduce-nextgen/ The Next Generation of Apache Hadoop MapReduce] |
| | 28 | * [[Image(http://ydn.zenfs.com/blogs/22/MapReduce_NextGen.jpg)]] |
| | 29 | |
| | 30 | * [http://blogs.computerworlduk.com/app-dev-and-programme-management/2011/05/big-data-technology-getting-hotter-but-still-too-hard-for-most-developers/ "Big Data" technology: getting hotter, but still too hard] |
| | 31 | * 最近在 !LinkedIn 的社群也看到一樣的問題：Hadoop 不好學、對一般企業來說太複雜了!! |
| | 32 | |
| | 33 | * [http://nosql.mypopescu.com/post/5397319531/hadoop-ecosystem-emc-netapp-mellanox-snaplogic Hadoop Ecosystem: EMC, NetApp, Mellanox, SnapLogic, DataStax] |
| | 34 | * DataStax Brisk: Hadoop and Hive on Cassandra (詳 [wiki:jazz/11-04-01 2011-04-01]) |
| | 35 | * [http://www.snaplogic.com/solutions/bigdata/ SnapLogic SnapReduce] - 這間公司目標想把 Hadoop 變成更簡單，設計了圖形化介面來作 Map / Reduce 工作的規劃。(詳 [wiki:jazz/11-05-12 2011-05-12]) |
| | 36 | * [http://www.mellanox.com/content/pages.php?pg=web_2_0 Mellanox Hadoop-Direct] - - mellanox 用硬體去加速 Hadoop 與 Memcached (詳 [wiki:jazz/11-05-12 2011-05-12]) |
| | 37 | * [http://blogs.netapp.com/exposed/2011/05/what-are-hadooplers.html NetApp Hadoop Shared DAS] ([wiki:jazz/11-05-12 2011-05-12] 有提到 !NetApp 特製的硬體 [http://www.netapp.com/us/products/storage-systems/e5400/e5400.html NetApp e5400] ，是 !NetApp 針對 Big Data 應用（Ex. Hadoop）強化 IOPS ) |
| | 38 | * [[Image(http://blogs.netapp.com/.a/6a00d8341ca27e53ef01538e5e5c80970b-pi)]] |
| | 39 | * 看了一下 Shared DAS 主要做幾件事情： |
| | 40 | {{{ |
| | 41 | #!text |
| | 42 | <1> 幫忙做背景的複本工作（用硬體 RAID 減少複本執行時間） |
| | 43 | reduce the amount of background replication tasks by employing highly efficient RAID |
| | 44 | <2> 降低 Disk I/O 的反應時間（用硬體方式提高 IOPS） |
| | 45 | NetApp E-Series Shared DAS enables significantly higher disk I/O bandwidth at lower latency |
| | 46 | <3> 減少複本個數（用硬體 RAID 減少複本個數，增加硬碟可用空間，或許跟去重複技術也有關） |
| | 47 | reducing the number of object replicas within a rack |
| | 48 | Fewer replicas mean less disks to buy or more objects stored within the same infrastructure. |
| | 49 | }}} |
| | 50 | * [http://www.greenplum.com/products/greenplum-hd EMC Greenplum HD] |
| | 51 | {{{ |
| | 52 | #!text |
| | 53 | EMC Greenplum provides fault tolerance for the Name Node and Job Tracker, |
| | 54 | both single points of failure in Hadoop. |
| | 55 | }}} |
| | 56 | |
| | 57 | * Cascalog - 基於 Clojure 寫的一個 Hadoop 查詢語言，可以方便分析師用類似 SQL 語法 / Datalog 語法做分析 |
| | 58 | * [http://nathanmarz.com/blog/introducing-cascalog-a-clojure-based-query-language-for-hado.html Introducing Cascalog: a Clojure-based query language for Hadoop] |
| | 59 | * https://github.com/nathanmarz/cascalog |
| | 60 | * <案例分享> [http://tech.backtype.com/52456836 Why Yieldbot chose Cascalog over Pig for Hadoop processing] |
| | 61 | |
