HTTP/2 302 server: nginx date: Thu, 07 Aug 2025 21:10:08 GMT content-type: text/plain; charset=utf-8 content-length: 0 x-archive-redirect-reason: found capture at 20130602201403 location: https://web.archive.org/web/20130602201403/https://answers.oreilly.com/rss/tags/MapReduce/ server-timing: captures_list;dur=0.681447, exclusion.robots;dur=0.025710, exclusion.robots.policy;dur=0.010781, esindex;dur=0.014516, cdx.remote;dur=51.552661, LoadShardBlock;dur=153.255707, PetaboxLoader3.datanode;dur=109.611811 x-app-server: wwwb-app218 x-ts: 302 x-tr: 237 server-timing: TR;dur=0,Tw;dur=0,Tc;dur=0 set-cookie: wb-p-SERVER=wwwb-app218; path=/ x-location: All x-rl: 0 x-na: 0 x-page-cache: MISS server-timing: MISS x-nid: DigitalOcean referrer-policy: no-referrer-when-downgrade permissions-policy: interest-cohort=() HTTP/2 200 server: nginx date: Thu, 07 Aug 2025 21:10:09 GMT content-type: text/xml; charset=UTF-8 x-archive-orig-date: Sun, 02 Jun 2013 20:14:04 GMT x-archive-orig-server: Apache x-archive-orig-expires: Sun 02 Jun 2013 08:14:05 PM GMT GMT x-archive-orig-cache-control: must-revalidate, post-check=0, pre-check=0 x-archive-orig-pragma: public x-archive-orig-set-cookie: answers_session_id=5c7d23a9cc7092aaf13b1ba39f1ef8b1; path=/; domain=.oreilly.com; httponly x-archive-orig-set-cookie: answers_session_id=5c7d23a9cc7092aaf13b1ba39f1ef8b1; path=/; domain=.oreilly.com; httponly x-archive-orig-connection: close cache-control: max-age=1800 x-archive-guessed-content-type: text/xml x-archive-guessed-charset: utf-8 memento-datetime: Sun, 02 Jun 2013 20:14:03 GMT link: ; rel="original", ; rel="timemap"; type="application/link-format", ; rel="timegate", ; rel="first memento"; datetime="Sun, 02 Jun 2013 20:14:03 GMT", ; rel="memento"; datetime="Sun, 02 Jun 2013 20:14:03 GMT", ; rel="next memento"; datetime="Mon, 03 Jun 2013 03:37:01 GMT", ; rel="last memento"; datetime="Mon, 03 Jun 2013 03:37:01 GMT" content-security-policy: default-src 'self' 'unsafe-eval' 'unsafe-inline' data: blob: archive.org web.archive.org web-static.archive.org wayback-api.archive.org athena.archive.org analytics.archive.org pragma.archivelab.org wwwb-events.archive.org x-archive-src: WIDE-20130602192220-crawl457/WIDE-20130602195457-00190.warc.gz server-timing: captures_list;dur=0.508193, exclusion.robots;dur=0.020538, exclusion.robots.policy;dur=0.008708, esindex;dur=0.012165, cdx.remote;dur=19.857872, LoadShardBlock;dur=122.537090, PetaboxLoader3.datanode;dur=145.405520, load_resource;dur=609.991536, PetaboxLoader3.resolve;dur=510.306744 x-app-server: wwwb-app218 x-ts: 200 x-tr: 782 server-timing: TR;dur=0,Tw;dur=0,Tc;dur=0 x-location: All x-rl: 0 x-na: 0 x-page-cache: MISS server-timing: MISS x-nid: DigitalOcean referrer-policy: no-referrer-when-downgrade permissions-policy: interest-cohort=() https://answers.oreilly.com/tag/MapReduce Fri, 15 Oct 2010 01:57:19 +0000 60 https://answers.oreilly.com/topic/2141-how-mapreduce-works-with-hadoop/ In this excerpt from Hadoop: The Definitive Guide, Second Edition, we look at how MapReduce in Hadoop works in detail. This knowledge provides a good foundation for writing more advanced MapReduce pro... Fri, 15 Oct 2010 01:57:19 +0000 https://answers.oreilly.com/topic/2141-how-mapreduce-works-with-hadoop/ https://answers.oreilly.com/topic/1396-running-a-couchdb-query-using-mapreduce/ Fri, 23 Apr 2010 21:45:23 +0000 https://answers.oreilly.com/topic/1396-running-a-couchdb-query-using-mapreduce/ https://answers.oreilly.com/topic/1048-why-couchdb/ In this excerpt from CouchDB: The Definitive Guide the authors urge developers to kick back and get to know this document-oriented database and its RESTful interface. Apache CouchDB is one of a new... Tue, 02 Feb 2010 21:24:54 +0000 https://answers.oreilly.com/topic/1048-why-couchdb/ https://answers.oreilly.com/topic/852-big-data-a-link-roundup/ Tue, 08 Dec 2009 08:07:19 +0000 https://answers.oreilly.com/topic/852-big-data-a-link-roundup/ https://answers.oreilly.com/topic/462-practical-techniques-for-developing-with-pig-and-hadoop/ There are some practical techniques that are worth knowing about when you are developing and running Pig programs. This section covers some of them.ParallelismWhen running in Hadoop mode... Wed, 28 Oct 2009 20:46:33 +0000 https://answers.oreilly.com/topic/462-practical-techniques-for-developing-with-pig-and-hadoop/ https://answers.oreilly.com/topic/460-how-to-benchmark-a-hadoop-cluster/ Is the cluster set up correctly? The best way to answer this question is empirically: run some jobs and confirm that you get the expected results. Benchmarks make good tests, as you also... Wed, 28 Oct 2009 20:24:37 +0000 https://answers.oreilly.com/topic/460-how-to-benchmark-a-hadoop-cluster/ https://answers.oreilly.com/topic/459-anatomy-of-a-mapreduce-job-run-with-hadoop/ You can run a MapReduce job with a single line of code: JobClient.runJob(conf). It’s very short, but it conceals a great deal of processing behind the scenes. This section uncov... Wed, 28 Oct 2009 20:16:06 +0000 https://answers.oreilly.com/topic/459-anatomy-of-a-mapreduce-job-run-with-hadoop/ https://answers.oreilly.com/topic/457-introduction-to-mapreduce-workflows/ So far in this chapter, you have seen the mechanics of writing a program using MapReduce. We haven’t yet considered how to turn a data processing problem into the MapReduce mode... Wed, 28 Oct 2009 19:47:56 +0000 https://answers.oreilly.com/topic/457-introduction-to-mapreduce-workflows/ https://answers.oreilly.com/topic/455-get-started-analyzing-data-with-hadoop/ To take advantage of the parallel processing that Hadoop provides, we need to express our query as a MapReduce job. After some local, small-scale testing, we will be able to run it on a ... Wed, 28 Oct 2009 19:14:33 +0000 https://answers.oreilly.com/topic/455-get-started-analyzing-data-with-hadoop/