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![Sorting Petabytes with MapReduce - The Next Episode](https://cdn-ak-scissors.b.st-hatena.com/image/square/dbd55ab0448c50716670c90c91b4abc554bb62fd/height=288;version=1;width=512/https%3A%2F%2Fresearch.google%2Fstatic%2Fimages%2Fblog%2Fgoogle-ai-meta.png)
個人的な興味というより,雑用絡みで眺めた論文の紹介.機械学習アルゴリズムを並列分散化するという話が最近流行っているようだ.全然網羅的ではないけど,誰かの役に立つかも知れないので,幾つかメモしておく.まず古典的にはこれ, Map-reduce for machine learning on multicore (NIPS 2006) 古典的な機械学習アルゴリズム(バッチ学習)の多くは,Statistical Query Model で記述できて,それらは summation form で記述できる (から,MapReduce で並列化できる).実装は Mahout.ただ最近は,バッチアルゴリズムで解ける問題には多くの場合対応するオンラインアルゴリズムが提案されていて,バッチアルゴリズムを並列化することのメリットはあまり無い.オンラインアルゴリズムだとパラメタが連続的に更新されるので,MapR
HBase + Map-Reduce is a really awesome combination. In all the back and forths about NoSQL - one of the things that’s often missed out is how convenient it is to be able to do scalable data analysis directly against large online data sets (that new distributed databases like HBase allow). This is a particularly fun and feasible prospect now that frameworks like Hive allow users to express such ana
Cloud9 was designed to serve as both a teaching tool and to support research in text processing. It was used in "cloud computing" courses at the University of Maryland in Spring 2008 and Fall 2008. The library itself is available via anonymous Subversion checkout. Like Hadoop itself, Cloud9 is distributed under the Apache License. Starting Points Subversion access: https://subversion.u
MapReduce advantages over parallel databases include storage-system independence and fine-grain fault tolerance for large jobs. Mapreduce is a programming model for processing and generating large data sets.4 Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs and a reduce function that merges all intermediate values associated with the sa
The newest and most up-to-date version (May 2010) this blog post is available at http://mapreducebook.org An updated and extended version of this blog post can be found here. Motivation Learn from academic literature about how the mapreduce parallel model and hadoop implementation is used to solve algorithmic problems. Disclaimer: this is work in progress (look for updates) Input Data – Academic P
A Comparison of Approaches to Large-Scale Data Analysis: MapReduce vs. DBMS Benchmarks Overview 04/14/2009 - SIGMOD 2009 Paper The following information is meant to provide documentation on how others can recreate the benchmark trials used in our SIGMOD 2009 paper. Our experiments were conducted on a 100-node cluster at the University of Wisconsin-Madison; each node had a single 2.40 GHz Intel Cor
Amazon Elastic MapReduceを使ってみた 2009-04-03 (Fri) 3:06 Amazon EC2 連日のEC2ネタです。本日、AmazonからElastic MapReduceというサービスがリリースされました。大規模データ処理技術が一気に民間の手に下りてくる、まさに革命的なサービスだと思います。 Amazon Elastic MapReduce Amazon ElasticMapReduce 紹介ビデオ With Hadoop, Amazon Adds A Web-Scale Data Processing Engine To Its Cloud Computer by techcrunch.com Elastic MapReduceは、Googleの基盤技術の一つであるMapReduceを時間単位課金で実行できるサービスです。MapReduceについては以
1 Hadoop Map-Reduce – Tuning and Debugging Arun C Murthy acmurthy@apache.org Yahoo! CCDI 2 Topical Matters… • Who doesn’t know Map-Reduce?! • Peek inside your MR application… • Tuning • Debug (god forbid!) Counters … • Often MR applications have countable ‘events’ • For e.g. the Map-Reduce framework ‘counts’ the bytes read/write on HDFS and the local filesystem • To define your own: – sta
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Dare Obasanjo's weblog "You can buy cars but you can't buy respect in the hood" - Curtis Jackson Navigation for Google Scalability Conference Trip Report: Using MapReduce on Large Geographic Datasets - Dare Obasanjo's weblog Content Sidebar Footer These are my notes from the talk Using MapReduce on Large Geographic Datasets by Barry Brummit. Most of this talk was a repetition of the material in th
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