HTTP/2 302 server: nginx date: Tue, 19 Aug 2025 02:07:03 GMT content-type: text/plain; charset=utf-8 content-length: 0 x-archive-redirect-reason: found capture at 20101111170552 location: https://web.archive.org/web/20101111170552/https://answers.oreilly.com/rss/tags/hadoop/ server-timing: captures_list;dur=0.669282, exclusion.robots;dur=0.024449, exclusion.robots.policy;dur=0.011347, esindex;dur=0.015251, cdx.remote;dur=6.645082, LoadShardBlock;dur=153.911682, PetaboxLoader3.datanode;dur=54.632625, PetaboxLoader3.resolve;dur=74.737905 x-app-server: wwwb-app219 x-ts: 302 x-tr: 194 server-timing: TR;dur=0,Tw;dur=0,Tc;dur=0 set-cookie: wb-p-SERVER=wwwb-app219; 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: Tue, 19 Aug 2025 02:07:04 GMT content-type: text/xml; charset=UTF-8 content-length: 5693 x-archive-orig-date: Thu, 11 Nov 2010 17:05:51 GMT x-archive-orig-server: Apache/2.2.11 (Unix) mod_ssl/2.2.11 OpenSSL/0.9.8e-fips-rhel5 mod_auth_passthrough/2.1 mod_bwlimited/1.4 FrontPage/5.0.2.2635 PHP/5.2.8 x-archive-orig-x-powered-by: PHP/5.2.8 x-archive-orig-set-cookie: answers_session_id=deleted; expires=Wed, 11-Nov-2009 17:05:50 GMT; path=/; domain=.oreilly.com; httponly x-archive-orig-set-cookie: answers_session_id=deleted; expires=Wed, 11-Nov-2009 17:05:50 GMT; path=/; domain=.oreilly.com; httponly x-archive-orig-expires: Thu 11 Nov 2010 05:05:54 PM GMT GMT x-archive-orig-cache-control: must-revalidate, post-check=0, pre-check=0 x-archive-orig-pragma: public x-archive-orig-content-length: 5693 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: Thu, 11 Nov 2010 17:05:52 GMT link: ; rel="original", ; rel="timemap"; type="application/link-format", ; rel="timegate", ; rel="first memento"; datetime="Thu, 11 Nov 2010 17:05:52 GMT", ; rel="memento"; datetime="Thu, 11 Nov 2010 17:05:52 GMT", ; rel="next memento"; datetime="Mon, 29 Apr 2013 12:19:14 GMT", ; rel="last memento"; datetime="Thu, 03 Oct 2013 06:45:18 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: 52_18_20101111114253_crawl102-c/52_18_20101111164551_crawl100.arc.gz server-timing: captures_list;dur=0.651198, exclusion.robots;dur=0.025481, exclusion.robots.policy;dur=0.012526, esindex;dur=0.014573, cdx.remote;dur=8.822238, LoadShardBlock;dur=131.134074, PetaboxLoader3.datanode;dur=101.391658, PetaboxLoader3.resolve;dur=233.023128, load_resource;dur=268.929536 x-app-server: wwwb-app219 x-ts: 200 x-tr: 441 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=() accept-ranges: bytes https://answers.oreilly.com/tag/hadoop Sun, 31 Oct 2010 16:08:37 +0000 60 https://answers.oreilly.com/topic/2183-how-to-install-hadoop-hbase/ The following excerpt from Hadoop: The Definitive Guide, Second Edition gives a step by step guide to installing HBase.Download a stable release from an Apache Download Mirror and unpack it on your lo... Sun, 31 Oct 2010 16:08:36 +0000 https://answers.oreilly.com/topic/2183-how-to-install-hadoop-hbase/ https://answers.oreilly.com/topic/2170-an-example-hadoop-implementation/ In the following excerpt from Hadoop: The Definitive Guide, Second Edition we take a look at an example for implementing Hadoop in a step by step process.Let’s look at a simple example by writing th... Wed, 27 Oct 2010 15:16:54 +0000 https://answers.oreilly.com/topic/2170-an-example-hadoop-implementation/ https://answers.oreilly.com/topic/2154-how-to-run-hadoop-in-the-cloud/ Thu, 21 Oct 2010 12:33:25 +0000 https://answers.oreilly.com/topic/2154-how-to-run-hadoop-in-the-cloud/ 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/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/ 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/456-get-to-know-hadoop-filesystems/ Hadoop has an abstract notion of filesystem, of which HDFS is just one implementation. The Java abstract class org.apache.hadoop.fs.FileSystem represents a filesystem in Hadoop, and ther... Wed, 28 Oct 2009 19:33:35 +0000 https://answers.oreilly.com/topic/456-get-to-know-hadoop-filesystems/ 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/