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最新评论
-
jpsb:
...
为什么需要分布式? -
leibnitz:
hi guy, this is used as develo ...
compile hadoop-2.5.x on OS X(macbook) -
string2020:
撸主真土豪,在苹果里面玩大数据.
compile hadoop-2.5.x on OS X(macbook) -
youngliu_liu:
怎样运行这个脚本啊??大牛,我刚进入搜索引擎行业,希望你能不吝 ...
nutch 数据增量更新 -
leibnitz:
also, there is a similar bug ...
2。hbase CRUD--Lease in hbase
其实,全网抓取比intranet区别再于,
前者提供了较为多的urls入口,
没有使用crawl-urlfilter.txt 中并没有限制哪些url ,(如果没有使用crawl命令)
并通过逐步处理的方式得以可按的局面;
在1.3,还有此区别,
如默认的fetcher.parse是false,使得每次fetch后必须有一个parse step,刚开始老是看不懂为什么tutorial中这样做。。
其次是,此版本不再有crawl-urlfiter.txt,而是用regex-urlfilter.txt替换。
在recrawl时的区别见nutch 数据增量更新
其实这个过程可以说是nutch对hadoop的利用的最深体会,我是这样认为的。想想看,当初,hadoop是内嵌在Nutch中,作为其中的一个功能模块。现在版本的nutch将hadop分离出来,但在分布式抓取时又得将它(配置文件,jar等)放回Nutch下。刚开始时老想nutch怎样结合hadoop进行分布式抓取;但分布式搜索还是有些不一样的,因为后者即使也是分布式,但它利用的hdfs对nutch是透明的。
install processes:
a.configure hadoop to run on cluster mode;
b.put all the config files belong hadoop(master and slaves) to conf dir of nutch(s) respectively;
c.execute the crawl command (SHOULD use individual commands to do INSTEAD OF 'craw',as 'crawl' is used for intranet usually)
here are the jobs belong this step:
Available Jobs | ||||
Job tracker Host Name | Job tracker Start time | Job Id | Name | User |
master | Mon Nov 07 20:50:54 CST 2011 | job_201111072050_0001 | inject crawl-url | hadoop |
master | Mon Nov 07 20:50:54 CST 2011 | job_201111072050_0002 | crawldb crawl/dist/crawldb | hadoop |
master | Mon Nov 07 20:50:54 CST 2011 | job_201111072050_0003 | generate: select from crawl/dist/crawldb | hadoop |
master | Mon Nov 07 20:50:54 CST 2011 | job_201111072050_0004 | generate: partition crawl/dist/segments/2011110720 | hadoop |
master | Mon Nov 07 20:50:54 CST 2011 | job_201111072050_0005 | fetch crawl/dist/segments/20111107205746 | hadoop |
master | Mon Nov 07 20:50:54 CST 2011 | job_201111072050_0006 | crawldb crawl/dist/crawldb(update db actually
) |
hadoop |
master | Mon Nov 07 20:50:54 CST 2011 | job_201111072050_0007 | linkdb crawl/dist/linkdb | hadoop |
master | Mon Nov 07 20:50:54 CST 2011 | job_201111072050_0008 | index-lucene crawl/dist/indexes | hadoop |
master | Mon Nov 07 20:50:54 CST 2011 | job_201111072050_0009 | dedup 1: urls by time | hadoop |
master | Mon Nov 07 20:50:54 CST 2011 | job_201111072050_0010 | dedup 2: content by hash | hadoop |
master | Mon Nov 07 20:50:54 CST 2011 | job_201111072050_0011 |
dedup 3: delete from index(es) |
hadoop |
* the jobs above with same color is ONE step beong the crawl command;
* job 2 :将sortjob結果作为输入(与已有的current数据合并),生成新的crawldb;所以可以有重复的urls,在reduce中会去重 ?
* job 4:由于存在多台crawlers,所以需要利用partition来划分urls(by host by default),来避免重复让一台机来抓取 ;
here is the output of resulst:
hadoop@leibnitz-laptop:/xxxxxxxxx$ hadoop fs -lsr crawl/dist/
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:00 /user/hadoop/crawl/dist/crawldb
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:00 /user/hadoop/crawl/dist/crawldb/current
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:00 /user/hadoop/crawl/dist/crawldb/current/part-00000
-rw-r--r-- 2 hadoop supergroup 6240 2011-11-07 21:00 /user/hadoop/crawl/dist/crawldb/current/part-00000/data
-rw-r--r-- 2 hadoop supergroup 215 2011-11-07 21:00 /user/hadoop/crawl/dist/crawldb/current/part-00000/index
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:00 /user/hadoop/crawl/dist/crawldb/current/part-00001
-rw-r--r-- 2 hadoop supergroup 7779 2011-11-07 21:00 /user/hadoop/crawl/dist/crawldb/current/part-00001/data
-rw-r--r-- 2 hadoop supergroup 218 2011-11-07 21:00 /user/hadoop/crawl/dist/crawldb/current/part-00001/index
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:07 /user/hadoop/crawl/dist/index
-rw-r--r-- 2 hadoop supergroup 369 2011-11-07 21:07 /user/hadoop/crawl/dist/index/_2.fdt
-rw-r--r-- 2 hadoop supergroup 20 2011-11-07 21:07 /user/hadoop/crawl/dist/index/_2.fdx
-rw-r--r-- 2 hadoop supergroup 71 2011-11-07 21:07 /user/hadoop/crawl/dist/index/_2.fnm
-rw-r--r-- 2 hadoop supergroup 1836 2011-11-07 21:07 /user/hadoop/crawl/dist/index/_2.frq
-rw-r--r-- 2 hadoop supergroup 14 2011-11-07 21:07 /user/hadoop/crawl/dist/index/_2.nrm
-rw-r--r-- 2 hadoop supergroup 4922 2011-11-07 21:07 /user/hadoop/crawl/dist/index/_2.prx
-rw-r--r-- 2 hadoop supergroup 171 2011-11-07 21:07 /user/hadoop/crawl/dist/index/_2.tii
-rw-r--r-- 2 hadoop supergroup 11234 2011-11-07 21:07 /user/hadoop/crawl/dist/index/_2.tis
-rw-r--r-- 2 hadoop supergroup 20 2011-11-07 21:07 /user/hadoop/crawl/dist/index/segments.gen
-rw-r--r-- 2 hadoop supergroup 284 2011-11-07 21:07 /user/hadoop/crawl/dist/index/segments_2
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000
-rw-r--r-- 2 hadoop supergroup 223 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000/_0.fdt
-rw-r--r-- 2 hadoop supergroup 12 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000/_0.fdx
-rw-r--r-- 2 hadoop supergroup 71 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000/_0.fnm
-rw-r--r-- 2 hadoop supergroup 991 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000/_0.frq
-rw-r--r-- 2 hadoop supergroup 9 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000/_0.nrm
-rw-r--r-- 2 hadoop supergroup 2813 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000/_0.prx
-rw-r--r-- 2 hadoop supergroup 100 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000/_0.tii
-rw-r--r-- 2 hadoop supergroup 5169 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000/_0.tis
-rw-r--r-- 2 hadoop supergroup 0 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000/index.done
-rw-r--r-- 2 hadoop supergroup 20 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000/segments.gen
-rw-r--r-- 2 hadoop supergroup 240 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00000/segments_2
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001
-rw-r--r-- 2 hadoop supergroup 150 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001/_0.fdt
-rw-r--r-- 2 hadoop supergroup 12 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001/_0.fdx
-rw-r--r-- 2 hadoop supergroup 71 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001/_0.fnm
-rw-r--r-- 2 hadoop supergroup 845 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001/_0.frq
-rw-r--r-- 2 hadoop supergroup 9 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001/_0.nrm
-rw-r--r-- 2 hadoop supergroup 2109 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001/_0.prx
-rw-r--r-- 2 hadoop supergroup 106 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001/_0.tii
-rw-r--r-- 2 hadoop supergroup 6226 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001/_0.tis
-rw-r--r-- 2 hadoop supergroup 0 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001/index.done
-rw-r--r-- 2 hadoop supergroup 20 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001/segments.gen
-rw-r--r-- 2 hadoop supergroup 240 2011-11-07 21:04 /user/hadoop/crawl/dist/indexes/part-00001/segments_2
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:01 /user/hadoop/crawl/dist/linkdb
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:01 /user/hadoop/crawl/dist/linkdb/current
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:01 /user/hadoop/crawl/dist/linkdb/current/part-00000
-rw-r--r-- 2 hadoop supergroup 8131 2011-11-07 21:01 /user/hadoop/crawl/dist/linkdb/current/part-00000/data
-rw-r--r-- 2 hadoop supergroup 215 2011-11-07 21:01 /user/hadoop/crawl/dist/linkdb/current/part-00000/index
drwxr-xr-x - hadoop supergroup 0 2011-11-07 21:01 /user/hadoop/crawl/dist/linkdb/current/part-00001
-rw-r--r-- 2 hadoop supergroup 11240 2011-11-07 21:01 /user/hadoop/crawl/dist/linkdb/current/part-00001/data
-rw-r--r-- 2 hadoop supergroup 218 2011-11-07 21:01 /user/hadoop/crawl/dist/linkdb/current/part-00001/index
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/content
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/content/part-00000
-rw-r--r-- 2 hadoop supergroup 13958 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/content/part-00000/data
-rw-r--r-- 2 hadoop supergroup 213 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/content/part-00000/index
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/content/part-00001
-rw-r--r-- 2 hadoop supergroup 6908 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/content/part-00001/data
-rw-r--r-- 2 hadoop supergroup 224 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/content/part-00001/index
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/crawl_fetch
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/crawl_fetch/part-00000
-rw-r--r-- 2 hadoop supergroup 255 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/crawl_fetch/part-00000/data
-rw-r--r-- 2 hadoop supergroup 213 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/crawl_fetch/part-00000/index
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/crawl_fetch/part-00001
-rw-r--r-- 2 hadoop supergroup 266 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/crawl_fetch/part-00001/data
-rw-r--r-- 2 hadoop supergroup 224 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/crawl_fetch/part-00001/index
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:58 /user/hadoop/crawl/dist/segments/20111107205746/crawl_generate
-rw-r--r-- 2 hadoop supergroup 255 2011-11-07 20:58 /user/hadoop/crawl/dist/segments/20111107205746/crawl_generate/part-00000
-rw-r--r-- 2 hadoop supergroup 86 2011-11-07 20:58 /user/hadoop/crawl/dist/segments/20111107205746/crawl_generate/part-00001
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/crawl_parse
-rw-r--r-- 2 hadoop supergroup 6819 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/crawl_parse/part-00000
-rw-r--r-- 2 hadoop supergroup 8302 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/crawl_parse/part-00001
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_data
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_data/part-00000
-rw-r--r-- 2 hadoop supergroup 2995 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_data/part-00000/data
-rw-r--r-- 2 hadoop supergroup 213 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_data/part-00000/index
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_data/part-00001
-rw-r--r-- 2 hadoop supergroup 1917 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_data/part-00001/data
-rw-r--r-- 2 hadoop supergroup 224 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_data/part-00001/index
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_text
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_text/part-00000
-rw-r--r-- 2 hadoop supergroup 3669 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_text/part-00000/data
-rw-r--r-- 2 hadoop supergroup 213 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_text/part-00000/index
drwxr-xr-x - hadoop supergroup 0 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_text/part-00001
-rw-r--r-- 2 hadoop supergroup 2770 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_text/part-00001/data
-rw-r--r-- 2 hadoop supergroup 224 2011-11-07 20:59 /user/hadoop/crawl/dist/segments/20111107205746/parse_text/part-00001/index
从以上分析可得,除了merged index外,其它目录都存在两份-对应两台crawlers.
利用这两份索引 ,就可以实现分布式搜索了。
剩下问题:为什么网上介绍的分步方式都没有使用dedup命令?
从 nutch 数据增量更新
上可知, 分布式抓取也应该使用这个dedup命令。
see also
http://wiki.apache.org/nutch/NutchTutorial
http://mr-lonely-hp.iteye.com/blog/1075395
发表评论
-
搜索引擎有多聪明?
2017-02-11 13:56 305ref:https://www.seozac.com/seo/ ... -
搜索引擎中的信息处理和概率论
2017-02-06 15:57 462info theory and maths use ... -
java-jvm usage analytics
2015-07-15 12:28 885as mentioned in title,i wil ... -
some new features in jdk7 and jdk8
2015-04-02 17:16 368jdk7和8的一些新特性介绍 JAVA 8 新特性详解 ... -
java nio tutorial
2015-01-09 17:25 560a simple,easily understandab ... -
The History of Java Technology
2014-08-14 11:19 614Since 1995, Java has changed ... -
jvm crash - jlong_disjoint_arraycopy
2014-05-21 15:56 3404when we are accessing some ... -
再议jvm调优技巧
2013-10-11 10:43 824一.调优原则 1.heap size尽量不太大,合 ... -
3。hbase rpc/ipc/proxy通信机制
2013-07-15 15:12 1301一。RPC VS IPC (relationship/di ... -
How to deal with concurrent mode failures in the Hotspot JVM
2013-04-12 13:56 909When using the Concurrent Low ... -
jvm 参数调优
2013-03-19 16:19 1113首先,保留几张有用的收集算法图(JDK5.0中J ... -
nutch 几种搜索布署
2011-12-29 13:21 8721。这是最简单的一种布署方式,通常用于简单测试。 ... -
nutch搜索架构关键类
2011-12-13 00:19 14todo -
nutch结合hadoop解説 RPC机制
2011-12-13 00:18 894todo -
nutch搜索架构关键类
2011-12-13 00:17 1139在整个crawl->recrawl ... -
访问hadoop数据时注意相对路径问题
2011-12-07 00:30 1423今天在nutch配置分布式搜索时出现搜索不到結果,背景是: ... -
nutch 发布时要注意的问题
2011-12-04 23:40 1859在利用Nutch自身的ant打 ... -
nutch 中的trie tree 算法简介
2011-11-18 14:18 945todoo -
nutch 配置文件详解
2011-11-17 16:58 2169下面来分析 一下,conf目录下各文件的作用是怎样的: cr ... -
nutch 分布式搜索-cluster-hdfs index
2011-10-17 02:14 1369此过程也很简单,步骤是: a.put the indexes ...
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总的来说,Nutch爬虫的工作流程和文件格式设计旨在实现高效、分布式的网页抓取,并为后续的搜索服务提供基础。通过对WebDB、segment和index的理解,我们可以更好地掌握Nutch如何构建和管理其爬取的互联网数据。
Nutch 是一个开源的搜索引擎项目,其核心功能...Nutch的这种设计使得爬虫和搜索器可以分布式部署在不同的硬件上,提高整体性能和可扩展性。了解Nutch的文件格式和工作流程对于管理和优化大规模的Web抓取任务至关重要。
Nutch使用Hadoop进行分布式处理,能够处理海量数据,适合大型网站的爬取需求。 1.1 URL管理和调度:Nutch使用URL数据库存储待抓取的网页,并通过一个策略算法(如FIFO或Priority Queue)决定下一个要抓取的URL。 ...
Nutch 是一个开源的网络爬虫项目,主要设计用于抓取、索引和搜索互联网上的网页。它由 Apache 软件基金会开发,并且是 Hadoop 的一部分,这意味着它能够利用分布式计算来处理大规模的数据抓取任务。Nutch 提供了一套...
5. **分布式爬虫**:分布式爬虫涉及多线程或多进程爬取、任务调度、链接去重、爬虫集群等技术,如使用Apache Nutch或Scrapy等开源框架,实现大规模、高效的数据抓取。 6. **新闻聚合**:新闻聚合可能涉及HTML解析...
它可以利用Hadoop框架进行分布式索引和搜索,处理海量数据。 在研究和使用Nutch-2.1源代码时,你可以深入了解搜索引擎的各个组成部分,如爬虫的实现、索引过程的细节、查询处理的算法等,这对于提升自己的搜索引擎...
1. **Nutch介绍**:Nutch是一个基于Java的开源Web爬虫,它能够抓取互联网上的网页,并对抓取的数据进行索引和搜索。Nutch的设计目标是提供可扩展性和高效率,适合大规模的Web数据处理。 2. **增量索引**:在Nutch中...