暑假每天傍晚或晚上更新
伪恋赛高
这里提供nutch1.6的src下载：
apache-nutch-1.6-src.zip
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如果不想自己编译源代码，可以直接下载我编译后的文件，包括单机版local和依赖hadoop版deploy（64位）：
apache-nutch1.6-runtime.zip
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或者仅下载官方的deploy版
apache-nutch-1.6-bin.tar.gz
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7/20日编辑：---------------------
今天突然找到nutch各版本的下载地址：http://archive.apache.org/dist/nutch/
apache的各版本软件都可以在这里找到：http://archive.apache.org/dist/
-----------------------------------
http://wxweven.blog.163.com/blog/static/1974791152014127115626958/
在runtime文件夹中，local文件夹是不借助hadoop的nutch，在该文件夹中实现了单机mapreduce。
本地nutch一般用来做测试、调试。进入local文件夹
在conf文件夹中有很多配置nutch的文件，nutch-default.xml是默认配置，里面有很多配置的
说明。nutch-site.xml是最主要的配置，它会覆盖default中的内容。
在运行nutch前先在nutch-site.xml加入http.agent.name配置。
default中的http.agent.name的例子如下：
1 <property> 2 <name>http.agent.name</name> 3 <value></value> 4 <description>HTTP 'User-Agent' request header. MUST NOT be empty - 5 please set this to a single word uniquely related to your organization. 6 7 NOTE: You should also check other related properties: 8 9 http.robots.agents 10 http.agent.description 11 http.agent.url 12 http.agent.email 13 http.agent.version 14 15 and set their values appropriately. 16 17 </description> 18 </property>
考到site.xml，在value标签中加入请求头，这个请求头需要在浏览器中提取，
比如火狐的请求头是
Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/28.0.1500.72 Safari/537.36
这里是我的nutch-site.xml的完整内容：
1 <?xml version="1.0"?> 2 <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> 3 4 <!-- Put site-specific property overrides in this file. --> 5 6 <configuration> 7 <property> 8 <name>http.agent.name</name> 9 <value>Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/28.0.1500.72 Safari/537.36</value> 10 </property> 11 12 </configuration>
修改好配置之后就能做实验了。
运行bin中的natch程序，提示要输入命令
以下内容部分转自：http://www.blogjava.net/kxx129/archive/2009/09/05/294000.html
Crawl(爬行)： Crawl是“org.apache.nutch.crawl.Crawl”的别称，它是一个完整的爬取和索引过程命令。
使用方法：
Shell代码
bin/nutch crawl <urlDir> [-dir d] [-threads n] [-depth i] [-topN]
bin/nutch crawl <urlDir> [-dir d] [-threads n] [-depth i] [-topN]
参数说明：
<urlDir>：包括URL列表的文本文件，它是一个已存在的文件夹。
[-dir <d>]：Nutch保存爬取记录的工作目录，默认情况下值为：./crawl-[date]，其中[date]为当前目期。
[-threads <n>]：Fetcher线程数，覆盖默认配置文件中的fetcher.threads.fetch值（默认为10）。
[-depth <i>]：Nutch爬虫迭代的深度，默认值为5。
[-topN <num>]：限制每一次迭代中的前N条记录，默认值为 Integer.MAX_VALUE。
例子1：./bin/nutch crawl urls -dir data -threads 50 -depth 2 -topN 2(先不运行这个命令)
要抓取的网址存放在urls文件夹中(nutch要从urls中的文件读出来)，
抓取后的数据放在data中，
使用50个线程来抓取，迭代深度为2，每次迭代抓前2条记录
值得注意的是nutch为了优化效率，不会严格按照深度优先搜索或广度优先搜索来查找
例子2: nohup ./bin/nutch crawl urls -dir data -threads 50 -depth 2 -topN 2 &
在前边加了一个nohup， nutch会把日志写到当前目录的nohup.out中
（更详细的日志文件在logs/hadoop.log中）
在后边加了一个&，这是linux的后台运行的命令
如果出错了，在nohup.out中可以看到类似与java异常的日志
测试的时候，先生成urls文件夹，然后在里面生成url.txt
写入http://blog.tianya.cn/,表示抓取天涯博客。
url.txt不是固定的，你可以改成其他名，在urls中的所有文件都将被看作是装作url的文件被读取
可以去掉-topN，这样抓取前两层所有的url，博主试了一下，某些网页超久的，最好不要去掉
运行例子2，而一会儿后，抓取完毕，以下是我抓取的nohup.out日志，没有显示异常：
1 solrUrl is not set, indexing will be skipped... 2 crawl started in: data 3 rootUrlDir = urls 4 threads = 50 5 depth = 2 6 solrUrl=null 7 topN = 2 8 Injector: starting at 2014-07-13 20:37:26 9 Injector: crawlDb: data/crawldb 10 Injector: urlDir: urls 11 Injector: Converting injected urls to crawl db entries. 12 Injector: total number of urls rejected by filters: 1 13 Injector: total number of urls injected after normalization and filtering: 2 14 Injector: Merging injected urls into crawl db. 15 Injector: finished at 2014-07-13 20:37:57, elapsed: 00:00:30 16 Generator: starting at 2014-07-13 20:37:57 17 Generator: Selecting best-scoring urls due for fetch. 18 Generator: filtering: true 19 Generator: normalizing: true 20 Generator: topN: 2 21 Generator: jobtracker is 'local', generating exactly one partition. 22 Generator: Partitioning selected urls for politeness. 23 Generator: segment: data/segments/20140713203805 24 Generator: finished at 2014-07-13 20:38:13, elapsed: 00:00:15 25 Fetcher: Your 'http.agent.name' value should be listed first in 'http.robots.agents' property. 26 Fetcher: starting at 2014-07-13 20:38:13 27 Fetcher: segment: data/segments/20140713203805 28 Using queue mode : byHost 29 Fetcher: threads: 50 30 Fetcher: time-out divisor: 2 31 QueueFeeder finished: total 1 records + hit by time limit :0 32 Using queue mode : byHost 33 Using queue mode : byHost 34 Using queue mode : byHost 35 fetching http://blog.tianya.cn/ 36 Using queue mode : byHost 37 -finishing thread FetcherThread, activeThreads=2 38 -finishing thread FetcherThread, activeThreads=1 39 Using queue mode : byHost 40 -finishing thread FetcherThread, activeThreads=1 41 Using queue mode : byHost 42 Using queue mode : byHost 43 -finishing thread FetcherThread, activeThreads=1 44 -finishing thread FetcherThread, activeThreads=1 45 Using queue mode : byHost 46 -finishing thread FetcherThread, activeThreads=1 47 Using queue mode : byHost 48 -finishing thread FetcherThread, activeThreads=1 49 Using queue mode : byHost 50 -finishing thread FetcherThread, activeThreads=1 51 Using queue mode : byHost 52 Using queue mode : byHost 53 -finishing thread FetcherThread, activeThreads=1 54 -finishing thread FetcherThread, activeThreads=1 55 -finishing thread FetcherThread, activeThreads=1 56 Using queue mode : byHost 57 Using queue mode : byHost 58 -finishing thread FetcherThread, activeThreads=1 59 -finishing thread FetcherThread, activeThreads=1 60 Using queue mode : byHost 61 Using queue mode : byHost 62 -finishing thread FetcherThread, activeThreads=1 63 Using queue mode : byHost 64 -finishing thread FetcherThread, activeThreads=1 65 Using queue mode : byHost 66 -finishing thread FetcherThread, activeThreads=1 67 Using queue mode : byHost 68 -finishing thread FetcherThread, activeThreads=1 69 Using queue mode : byHost 70 -finishing thread FetcherThread, activeThreads=1 71 Using queue mode : byHost 72 -finishing thread FetcherThread, activeThreads=1 73 Using queue mode : byHost 74 -finishing thread FetcherThread, activeThreads=1 75 -finishing thread FetcherThread, activeThreads=1 76 Using queue mode : byHost 77 Using queue mode : byHost 78 -finishing thread FetcherThread, activeThreads=1 79 Using queue mode : byHost 80 -finishing thread FetcherThread, activeThreads=1 81 Using queue mode : byHost 82 Using queue mode : byHost 83 -finishing thread FetcherThread, activeThreads=1 84 -finishing thread FetcherThread, activeThreads=1 85 Using queue mode : byHost 86 Using queue mode : byHost 87 -finishing thread FetcherThread, activeThreads=1 88 -finishing thread FetcherThread, activeThreads=1 89 Using queue mode : byHost 90 Using queue mode : byHost 91 -finishing thread FetcherThread, activeThreads=1 92 -finishing thread FetcherThread, activeThreads=1 93 Using queue mode : byHost 94 Using queue mode : byHost 95 -finishing thread FetcherThread, activeThreads=1 96 -finishing thread FetcherThread, activeThreads=1 97 Using queue mode : byHost 98 Using queue mode : byHost 99 -finishing thread FetcherThread, activeThreads=1 100 Using queue mode : byHost 101 -finishing thread FetcherThread, activeThreads=1 102 -finishing thread FetcherThread, activeThreads=1 103 Using queue mode : byHost 104 Using queue mode : byHost 105 -finishing thread FetcherThread, activeThreads=1 106 -finishing thread FetcherThread, activeThreads=1 107 Using queue mode : byHost 108 Using queue mode : byHost 109 -finishing thread FetcherThread, activeThreads=1 110 Using queue mode : byHost 111 -finishing thread FetcherThread, activeThreads=1 112 -finishing thread FetcherThread, activeThreads=1 113 Using queue mode : byHost 114 -finishing thread FetcherThread, activeThreads=1 115 Using queue mode : byHost 116 -finishing thread FetcherThread, activeThreads=1 117 Using queue mode : byHost 118 Using queue mode : byHost 119 -finishing thread FetcherThread, activeThreads=1 120 -finishing thread FetcherThread, activeThreads=1 121 Using queue mode : byHost 122 -finishing thread FetcherThread, activeThreads=1 123 Using queue mode : byHost 124 -finishing thread FetcherThread, activeThreads=1 125 Using queue mode : byHost 126 -finishing thread FetcherThread, activeThreads=1 127 Using queue mode : byHost 128 -finishing thread FetcherThread, activeThreads=1 129 -finishing thread FetcherThread, activeThreads=1 130 Using queue mode : byHost 131 Fetcher: throughput threshold: -1 132 Fetcher: throughput threshold retries: 5 133 -finishing thread FetcherThread, activeThreads=1 134 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 135 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 136 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 137 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 138 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 139 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 140 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 141 -finishing thread FetcherThread, activeThreads=0 142 -activeThreads=0, spinWaiting=0, fetchQueues.totalSize=0 143 -activeThreads=0 144 Fetcher: finished at 2014-07-13 20:38:26, elapsed: 00:00:13 145 ParseSegment: starting at 2014-07-13 20:38:26 146 ParseSegment: segment: data/segments/20140713203805 147 Parsed (64ms):http://blog.tianya.cn/ 148 ParseSegment: finished at 2014-07-13 20:38:33, elapsed: 00:00:07 149 CrawlDb update: starting at 2014-07-13 20:38:33 150 CrawlDb update: db: data/crawldb 151 CrawlDb update: segments: [data/segments/20140713203805] 152 CrawlDb update: additions allowed: true 153 CrawlDb update: URL normalizing: true 154 CrawlDb update: URL filtering: true 155 CrawlDb update: 404 purging: false 156 CrawlDb update: Merging segment data into db. 157 CrawlDb update: finished at 2014-07-13 20:38:47, elapsed: 00:00:13 158 Generator: starting at 2014-07-13 20:38:47 159 Generator: Selecting best-scoring urls due for fetch. 160 Generator: filtering: true 161 Generator: normalizing: true 162 Generator: topN: 2 163 Generator: jobtracker is 'local', generating exactly one partition. 164 Generator: Partitioning selected urls for politeness. 165 Generator: segment: data/segments/20140713203855 166 Generator: finished at 2014-07-13 20:39:02, elapsed: 00:00:15 167 Fetcher: Your 'http.agent.name' value should be listed first in 'http.robots.agents' property. 168 Fetcher: starting at 2014-07-13 20:39:02 169 Fetcher: segment: data/segments/20140713203855 170 Using queue mode : byHost 171 Fetcher: threads: 50 172 Fetcher: time-out divisor: 2 173 QueueFeeder finished: total 2 records + hit by time limit :0 174 Using queue mode : byHost 175 Using queue mode : byHost 176 fetching http://blog.tianya.cn/blog/culture 177 Using queue mode : byHost 178 Using queue mode : byHost 179 Using queue mode : byHost 180 Using queue mode : byHost 181 Using queue mode : byHost 182 Using queue mode : byHost 183 Using queue mode : byHost 184 Using queue mode : byHost 185 Using queue mode : byHost 186 Using queue mode : byHost 187 Using queue mode : byHost 188 Using queue mode : byHost 189 Using queue mode : byHost 190 Using queue mode : byHost 191 Using queue mode : byHost 192 Using queue mode : byHost 193 Using queue mode : byHost 194 Using queue mode : byHost 195 Using queue mode : byHost 196 Using queue mode : byHost 197 Using queue mode : byHost 198 Using queue mode : byHost 199 Using queue mode : byHost 200 Using queue mode : byHost 201 Using queue mode : byHost 202 Using queue mode : byHost 203 Using queue mode : byHost 204 Using queue mode : byHost 205 Using queue mode : byHost 206 Using queue mode : byHost 207 Using queue mode : byHost 208 Using queue mode : byHost 209 Using queue mode : byHost 210 Using queue mode : byHost 211 Using queue mode : byHost 212 Using queue mode : byHost 213 Using queue mode : byHost 214 Using queue mode : byHost 215 Using queue mode : byHost 216 Using queue mode : byHost 217 Using queue mode : byHost 218 Using queue mode : byHost 219 Using queue mode : byHost 220 Using queue mode : byHost 221 Using queue mode : byHost 222 Using queue mode : byHost 223 Using queue mode : byHost 224 Using queue mode : byHost 225 Fetcher: throughput threshold: -1 226 Fetcher: throughput threshold retries: 5 227 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=1 228 * queue: http://blog.tianya.cn 229 maxThreads = 1 230 inProgress = 1 231 crawlDelay = 5000 232 minCrawlDelay = 0 233 nextFetchTime = 1405255142707 234 now = 1405255143834 235 0. http://blog.tianya.cn/blog/daren 236 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=1 237 * queue: http://blog.tianya.cn 238 maxThreads = 1 239 inProgress = 1 240 crawlDelay = 5000 241 minCrawlDelay = 0 242 nextFetchTime = 1405255142707 243 now = 1405255144838 244 0. http://blog.tianya.cn/blog/daren 245 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=1 246 * queue: http://blog.tianya.cn 247 maxThreads = 1 248 inProgress = 1 249 crawlDelay = 5000 250 minCrawlDelay = 0 251 nextFetchTime = 1405255142707 252 now = 1405255145841 253 0. http://blog.tianya.cn/blog/daren 254 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=1 255 * queue: http://blog.tianya.cn 256 maxThreads = 1 257 inProgress = 0 258 crawlDelay = 5000 259 minCrawlDelay = 0 260 nextFetchTime = 1405255151041 261 now = 1405255146844 262 0. http://blog.tianya.cn/blog/daren 263 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=1 264 * queue: http://blog.tianya.cn 265 maxThreads = 1 266 inProgress = 0 267 crawlDelay = 5000 268 minCrawlDelay = 0 269 nextFetchTime = 1405255151041 270 now = 1405255147847 271 0. http://blog.tianya.cn/blog/daren 272 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=1 273 * queue: http://blog.tianya.cn 274 maxThreads = 1 275 inProgress = 0 276 crawlDelay = 5000 277 minCrawlDelay = 0 278 nextFetchTime = 1405255151041 279 now = 1405255148852 280 0. http://blog.tianya.cn/blog/daren 281 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=1 282 * queue: http://blog.tianya.cn 283 maxThreads = 1 284 inProgress = 0 285 crawlDelay = 5000 286 minCrawlDelay = 0 287 nextFetchTime = 1405255151041 288 now = 1405255149855 289 0. http://blog.tianya.cn/blog/daren 290 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=1 291 * queue: http://blog.tianya.cn 292 maxThreads = 1 293 inProgress = 0 294 crawlDelay = 5000 295 minCrawlDelay = 0 296 nextFetchTime = 1405255151041 297 now = 1405255150858 298 0. http://blog.tianya.cn/blog/daren 299 fetching http://blog.tianya.cn/blog/daren 300 -finishing thread FetcherThread, activeThreads=49 301 -finishing thread FetcherThread, activeThreads=48 302 -finishing thread FetcherThread, activeThreads=46 303 -finishing thread FetcherThread, activeThreads=47 304 -finishing thread FetcherThread, activeThreads=45 305 -finishing thread FetcherThread, activeThreads=44 306 -finishing thread FetcherThread, activeThreads=43 307 -finishing thread FetcherThread, activeThreads=41 308 -finishing thread FetcherThread, activeThreads=42 309 -finishing thread FetcherThread, activeThreads=40 310 -finishing thread FetcherThread, activeThreads=39 311 -finishing thread FetcherThread, activeThreads=38 312 -finishing thread FetcherThread, activeThreads=37 313 -finishing thread FetcherThread, activeThreads=36 314 -finishing thread FetcherThread, activeThreads=35 315 -finishing thread FetcherThread, activeThreads=34 316 -finishing thread FetcherThread, activeThreads=33 317 -finishing thread FetcherThread, activeThreads=32 318 -finishing thread FetcherThread, activeThreads=31 319 -finishing thread FetcherThread, activeThreads=30 320 -finishing thread FetcherThread, activeThreads=29 321 -finishing thread FetcherThread, activeThreads=28 322 -finishing thread FetcherThread, activeThreads=27 323 -finishing thread FetcherThread, activeThreads=26 324 -finishing thread FetcherThread, activeThreads=25 325 -finishing thread FetcherThread, activeThreads=24 326 -finishing thread FetcherThread, activeThreads=23 327 -finishing thread FetcherThread, activeThreads=22 328 -finishing thread FetcherThread, activeThreads=21 329 -finishing thread FetcherThread, activeThreads=20 330 -finishing thread FetcherThread, activeThreads=19 331 -finishing thread FetcherThread, activeThreads=18 332 -finishing thread FetcherThread, activeThreads=17 333 -finishing thread FetcherThread, activeThreads=16 334 -finishing thread FetcherThread, activeThreads=15 335 -finishing thread FetcherThread, activeThreads=14 336 -finishing thread FetcherThread, activeThreads=13 337 -finishing thread FetcherThread, activeThreads=12 338 -finishing thread FetcherThread, activeThreads=11 339 -finishing thread FetcherThread, activeThreads=10 340 -finishing thread FetcherThread, activeThreads=9 341 -finishing thread FetcherThread, activeThreads=8 342 -finishing thread FetcherThread, activeThreads=7 343 -finishing thread FetcherThread, activeThreads=6 344 -finishing thread FetcherThread, activeThreads=5 345 -finishing thread FetcherThread, activeThreads=4 346 -finishing thread FetcherThread, activeThreads=3 347 -finishing thread FetcherThread, activeThreads=2 348 -finishing thread FetcherThread, activeThreads=1 349 -finishing thread FetcherThread, activeThreads=0 350 -activeThreads=0, spinWaiting=0, fetchQueues.totalSize=0 351 -activeThreads=0 352 Fetcher: finished at 2014-07-13 20:39:18, elapsed: 00:00:16 353 ParseSegment: starting at 2014-07-13 20:39:18 354 ParseSegment: segment: data/segments/20140713203855 355 Parsed (13ms):http://blog.tianya.cn/blog/culture 356 Parsed (3ms):http://blog.tianya.cn/blog/daren 357 ParseSegment: finished at 2014-07-13 20:39:25, elapsed: 00:00:07 358 CrawlDb update: starting at 2014-07-13 20:39:25 359 CrawlDb update: db: data/crawldb 360 CrawlDb update: segments: [data/segments/20140713203855] 361 CrawlDb update: additions allowed: true 362 CrawlDb update: URL normalizing: true 363 CrawlDb update: URL filtering: true 364 CrawlDb update: 404 purging: false 365 CrawlDb update: Merging segment data into db. 366 CrawlDb update: finished at 2014-07-13 20:39:38, elapsed: 00:00:13 367 LinkDb: starting at 2014-07-13 20:39:38 368 LinkDb: linkdb: data/linkdb 369 LinkDb: URL normalize: true 370 LinkDb: URL filter: true 371 LinkDb: internal links will be ignored. 372 LinkDb: adding segment: file:/home/lan/nutch/local/data/segments/20140713203805 373 LinkDb: adding segment: file:/home/lan/nutch/local/data/segments/20140713203855 374 LinkDb: finished at 2014-07-13 20:39:48, elapsed: 00:00:10 375 crawl finished: data
没加-topN的日志：
1 solrUrl is not set, indexing will be skipped... 2 crawl started in: data 3 rootUrlDir = urls 4 threads = 50 5 depth = 2 6 solrUrl=null 7 Injector: starting at 2014-07-14 20:52:04 8 Injector: crawlDb: data/crawldb 9 Injector: urlDir: urls 10 Injector: Converting injected urls to crawl db entries. 11 Injector: total number of urls rejected by filters: 1 12 Injector: total number of urls injected after normalization and filtering: 2 13 Injector: Merging injected urls into crawl db. 14 Injector: finished at 2014-07-14 20:52:23, elapsed: 00:00:19 15 Generator: starting at 2014-07-14 20:52:23 16 Generator: Selecting best-scoring urls due for fetch. 17 Generator: filtering: true 18 Generator: normalizing: true 19 Generator: jobtracker is 'local', generating exactly one partition. 20 Generator: Partitioning selected urls for politeness. 21 Generator: segment: data/segments/20140714205231 22 Generator: finished at 2014-07-14 20:52:39, elapsed: 00:00:15 23 Fetcher: Your 'http.agent.name' value should be listed first in 'http.robots.agents' property. 24 Fetcher: starting at 2014-07-14 20:52:39 25 Fetcher: segment: data/segments/20140714205231 26 Using queue mode : byHost 27 Fetcher: threads: 50 28 Fetcher: time-out divisor: 2 29 QueueFeeder finished: total 1 records + hit by time limit :0 30 Using queue mode : byHost 31 Using queue mode : byHost 32 Using queue mode : byHost 33 fetching http://blog.tianya.cn/ 34 Using queue mode : byHost 35 -finishing thread FetcherThread, activeThreads=2 36 -finishing thread FetcherThread, activeThreads=1 37 Using queue mode : byHost 38 -finishing thread FetcherThread, activeThreads=1 39 Using queue mode : byHost 40 -finishing thread FetcherThread, activeThreads=1 41 Using queue mode : byHost 42 -finishing thread FetcherThread, activeThreads=1 43 Using queue mode : byHost 44 -finishing thread FetcherThread, activeThreads=1 45 Using queue mode : byHost 46 -finishing thread FetcherThread, activeThreads=1 47 Using queue mode : byHost 48 -finishing thread FetcherThread, activeThreads=1 49 Using queue mode : byHost 50 -finishing thread FetcherThread, activeThreads=1 51 Using queue mode : byHost 52 -finishing thread FetcherThread, activeThreads=1 53 Using queue mode : byHost 54 Using queue mode : byHost 55 -finishing thread FetcherThread, activeThreads=1 56 Using queue mode : byHost 57 -finishing thread FetcherThread, activeThreads=1 58 -finishing thread FetcherThread, activeThreads=1 59 Using queue mode : byHost 60 -finishing thread FetcherThread, activeThreads=1 61 Using queue mode : byHost 62 -finishing thread FetcherThread, activeThreads=1 63 Using queue mode : byHost 64 Using queue mode : byHost 65 -finishing thread FetcherThread, activeThreads=1 66 Using queue mode : byHost 67 -finishing thread FetcherThread, activeThreads=1 68 -finishing thread FetcherThread, activeThreads=1 69 Using queue mode : byHost 70 -finishing thread FetcherThread, activeThreads=1 71 Using queue mode : byHost 72 Using queue mode : byHost 73 -finishing thread FetcherThread, activeThreads=1 74 Using queue mode : byHost 75 -finishing thread FetcherThread, activeThreads=1 76 -finishing thread FetcherThread, activeThreads=1 77 Using queue mode : byHost 78 -finishing thread FetcherThread, activeThreads=1 79 Using queue mode : byHost 80 Using queue mode : byHost 81 -finishing thread FetcherThread, activeThreads=1 82 -finishing thread FetcherThread, activeThreads=1 83 Using queue mode : byHost 84 -finishing thread FetcherThread, activeThreads=1 85 Using queue mode : byHost 86 Using queue mode : byHost 87 -finishing thread FetcherThread, activeThreads=1 88 -finishing thread FetcherThread, activeThreads=1 89 Using queue mode : byHost 90 Using queue mode : byHost 91 -finishing thread FetcherThread, activeThreads=1 92 -finishing thread FetcherThread, activeThreads=1 93 Using queue mode : byHost 94 Using queue mode : byHost 95 -finishing thread FetcherThread, activeThreads=1 96 Using queue mode : byHost 97 -finishing thread FetcherThread, activeThreads=1 98 -finishing thread FetcherThread, activeThreads=1 99 Using queue mode : byHost 100 Using queue mode : byHost 101 -finishing thread FetcherThread, activeThreads=1 102 -finishing thread FetcherThread, activeThreads=1 103 Using queue mode : byHost 104 -finishing thread FetcherThread, activeThreads=1 105 Using queue mode : byHost 106 Using queue mode : byHost 107 -finishing thread FetcherThread, activeThreads=1 108 Using queue mode : byHost 109 -finishing thread FetcherThread, activeThreads=1 110 Using queue mode : byHost 111 -finishing thread FetcherThread, activeThreads=1 112 Using queue mode : byHost 113 -finishing thread FetcherThread, activeThreads=1 114 Using queue mode : byHost 115 -finishing thread FetcherThread, activeThreads=1 116 Using queue mode : byHost 117 -finishing thread FetcherThread, activeThreads=1 118 -finishing thread FetcherThread, activeThreads=1 119 Using queue mode : byHost 120 -finishing thread FetcherThread, activeThreads=1 121 Using queue mode : byHost 122 -finishing thread FetcherThread, activeThreads=1 123 Using queue mode : byHost 124 -finishing thread FetcherThread, activeThreads=1 125 Using queue mode : byHost 126 -finishing thread FetcherThread, activeThreads=1 127 Using queue mode : byHost 128 -finishing thread FetcherThread, activeThreads=1 129 Fetcher: throughput threshold: -1 130 Fetcher: throughput threshold retries: 5 131 -finishing thread FetcherThread, activeThreads=1 132 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 133 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 134 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 135 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 136 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 137 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 138 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 139 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 140 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 141 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 142 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 143 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 144 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 145 -activeThreads=1, spinWaiting=0, fetchQueues.totalSize=0 146 -finishing thread FetcherThread, activeThreads=0 147 -activeThreads=0, spinWaiting=0, fetchQueues.totalSize=0 148 -activeThreads=0 149 Fetcher: finished at 2014-07-14 20:53:01, elapsed: 00:00:22 150 ParseSegment: starting at 2014-07-14 20:53:01 151 ParseSegment: segment: data/segments/20140714205231 152 Parsed (47ms):http://blog.tianya.cn/ 153 ParseSegment: finished at 2014-07-14 20:53:08, elapsed: 00:00:07 154 CrawlDb update: starting at 2014-07-14 20:53:08 155 CrawlDb update: db: data/crawldb 156 CrawlDb update: segments: [data/segments/20140714205231] 157 CrawlDb update: additions allowed: true 158 CrawlDb update: URL normalizing: true 159 CrawlDb update: URL filtering: true 160 CrawlDb update: 404 purging: false 161 CrawlDb update: Merging segment data into db. 162 CrawlDb update: finished at 2014-07-14 20:53:22, elapsed: 00:00:13 163 Generator: starting at 2014-07-14 20:53:22 164 Generator: Selecting best-scoring urls due for fetch. 165 Generator: filtering: true 166 Generator: normalizing: true 167 Generator: jobtracker is 'local', generating exactly one partition. 168 Generator: Partitioning selected urls for politeness. 169 Generator: segment: data/segments/20140714205330 170 Generator: finished at 2014-07-14 20:53:37, elapsed: 00:00:15 171 Fetcher: Your 'http.agent.name' value should be listed first in 'http.robots.agents' property. 172 Fetcher: starting at 2014-07-14 20:53:37 173 Fetcher: segment: data/segments/20140714205330 174 Using queue mode : byHost 175 Fetcher: threads: 50 176 Fetcher: time-out divisor: 2 177 Using queue mode : byHost 178 Using queue mode : byHost 179 Using queue mode : byHost 180 Using queue mode : byHost 181 Using queue mode : byHost 182 Using queue mode : byHost 183 Using queue mode : byHost 184 Using queue mode : byHost 185 Using queue mode : byHost 186 Using queue mode : byHost 187 Using queue mode : byHost 188 Using queue mode : byHost 189 fetching http://www.tianya.cn/mobile 190 Using queue mode : byHost 191 Using queue mode : byHost 192 Using queue mode : byHost 193 Using queue mode : byHost 194 fetching http://blog.tianya.cn/post-5010184-62889385-1.shtml 195 QueueFeeder finished: total 100 records + hit by time limit :0 196 Using queue mode : byHost 197 Using queue mode : byHost 198 Using queue mode : byHost 199 Using queue mode : byHost 200 Using queue mode : byHost 201 Using queue mode : byHost 202 Using queue mode : byHost 203 Using queue mode : byHost 204 Using queue mode : byHost 205 Using queue mode : byHost 206 Using queue mode : byHost 207 Using queue mode : byHost 208 Using queue mode : byHost 209 Using queue mode : byHost 210 Using queue mode : byHost 211 Using queue mode : byHost 212 Using queue mode : byHost 213 Using queue mode : byHost 214 Using queue mode : byHost 215 Using queue mode : byHost 216 Using queue mode : byHost 217 Using queue mode : byHost 218 Using queue mode : byHost 219 Using queue mode : byHost 220 Using queue mode : byHost 221 Using queue mode : byHost 222 Using queue mode : byHost 223 Using queue mode : byHost 224 Using queue mode : byHost 225 Using queue mode : byHost 226 Using queue mode : byHost 227 Using queue mode : byHost 228 Using queue mode : byHost 229 Using queue mode : byHost 230 Fetcher: throughput threshold: -1 231 Fetcher: throughput threshold retries: 5 232 -activeThreads=50, spinWaiting=48, fetchQueues.totalSize=98 233 -activeThreads=50, spinWaiting=48, fetchQueues.totalSize=98 234 -activeThreads=50, spinWaiting=48, fetchQueues.totalSize=98 235 -activeThreads=50, spinWaiting=48, fetchQueues.totalSize=98 236 -activeThreads=50, spinWaiting=48, fetchQueues.totalSize=98 237 -activeThreads=50, spinWaiting=48, fetchQueues.totalSize=98 238 -activeThreads=50, spinWaiting=48, fetchQueues.totalSize=98 239 -activeThreads=50, spinWaiting=48, fetchQueues.totalSize=98 240 -activeThreads=50, spinWaiting=48, fetchQueues.totalSize=98 241 -activeThreads=50, spinWaiting=48, fetchQueues.totalSize=98 242 -activeThreads=50, spinWaiting=48, fetchQueues.totalSize=98 243 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=98 244 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=98 245 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=98 246 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=98 247 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=98 248 fetching http://blog.tianya.cn/blog/culture 249 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=97 250 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=97 251 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=97 252 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=97 253 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=97 254 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=97 255 fetching http://blog.tianya.cn/post-4487705-62917227-1.shtml 256 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=96 257 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=96 258 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=96 259 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=96 260 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=96 261 fetching http://blog.tianya.cn/post-1119083-62403495-1.shtml 262 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=95 263 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=95 264 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=95 265 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=95 266 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=95 267 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=95 268 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=95 269 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=95 270 fetching http://blog.tianya.cn/blog/ent 271 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=94 272 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=94 273 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=94 274 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=94 275 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=94 276 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=94 277 fetching http://blog.tianya.cn/post-4598537-62971598-1.shtml 278 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=93 279 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=93 280 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=93 281 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=93 282 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=93 283 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=93 284 fetching http://blog.tianya.cn/post-5010184-62834903-1.shtml 285 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=92 286 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=92 287 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=92 288 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=92 289 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=92 290 fetching http://blog.tianya.cn/post-4877164-61406732-1.shtml 291 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=91 292 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=91 293 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=91 294 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=91 295 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=91 296 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=91 297 fetching http://blog.tianya.cn/post-78180-59109533-1.shtml 298 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=90 299 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=90 300 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=90 301 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=90 302 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=90 303 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=90 304 fetching http://blog.tianya.cn/post-4362114-63792588-1.shtml 305 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=89 306 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=89 307 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=89 308 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=89 309 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=89 310 fetching http://blog.tianya.cn/post-3961685-62977022-1.shtml 311 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=88 312 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=88 313 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=88 314 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=88 315 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=88 316 fetching http://blog.tianya.cn/post-5010184-62890806-1.shtml 317 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 318 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 319 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 320 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 321 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 322 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 323 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 324 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 325 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 326 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 327 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 328 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 329 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 330 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=87 331 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=87 332 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=87 333 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=87 334 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=87 335 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=87 336 fetching http://blog.tianya.cn/blog/mingbo 337 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=86 338 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=86 339 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=86 340 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=86 341 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=86 342 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=86 343 fetching http://blog.tianya.cn/post-959477-62971507-1.shtml 344 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=85 345 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=85 346 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=85 347 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=85 348 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=85 349 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=85 350 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=85 351 fetching http://blog.tianya.cn/post-4562315-62807399-1.shtml 352 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=84 353 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=84 354 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=84 355 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=84 356 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=84 357 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=84 358 fetching http://blog.tianya.cn/post-3941055-62934113-1.shtml 359 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=83 360 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=83 361 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=83 362 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=83 363 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=83 364 fetching http://blog.tianya.cn/blog/daren 365 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=82 366 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=82 367 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=82 368 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=82 369 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=82 370 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=82 371 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=82 372 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=82 373 fetching http://blog.tianya.cn/post-1196211-63799917-1.shtml 374 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=81 375 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=81 376 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=81 377 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=81 378 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=81 379 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=81 380 fetching http://blog.tianya.cn/post-196238-62376389-1.shtml 381 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=80 382 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=80 383 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=80 384 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=80 385 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=80 386 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=80 387 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=80 388 fetching http://blog.tianya.cn/post-4700528-62898660-1.shtml 389 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=79 390 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=79 391 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=79 392 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=79 393 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=79 394 fetching http://blog.tianya.cn/post-1119083-62958234-1.shtml 395 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=78 396 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=78 397 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=78 398 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=78 399 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=78 400 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=78 401 fetching http://blog.tianya.cn/post-1671874-62898829-1.shtml 402 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=77 403 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=77 404 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=77 405 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=77 406 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=77 407 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=77 408 fetching http://blog.tianya.cn/post-5010184-62313586-1.shtml 409 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 410 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 411 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 412 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 413 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 414 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 415 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 416 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 417 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 418 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 419 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 420 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 421 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=76 422 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=76 423 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=76 424 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=76 425 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=76 426 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=76 427 fetching http://blog.tianya.cn/post-4598537-62379563-1.shtml 428 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=75 429 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=75 430 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=75 431 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=75 432 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=75 433 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=75 434 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=75 435 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=75 436 fetching http://blog.tianya.cn/post-236764-59417277-1.shtml 437 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=74 438 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=74 439 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=74 440 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=74 441 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=74 442 fetching http://blog.tianya.cn/post-4360774-62845782-1.shtml 443 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=73 444 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=73 445 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=73 446 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=73 447 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=73 448 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=73 449 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=73 450 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=73 451 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=73 452 fetching http://blog.tianya.cn/post-196238-61158698-1.shtml 453 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=72 454 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=72 455 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=72 456 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=72 457 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=72 458 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=72 459 fetching http://blog.tianya.cn/post-3340761-62357537-1.shtml 460 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=71 461 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=71 462 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=71 463 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=71 464 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=71 465 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=71 466 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=71 467 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=71 468 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=71 469 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=71 470 fetching http://blog.tianya.cn/post-4562315-62367801-1.shtml 471 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=70 472 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=70 473 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=70 474 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=70 475 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=70 476 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=70 477 fetching http://blog.tianya.cn/post-38484-61144592-1.shtml 478 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=69 479 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=69 480 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=69 481 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=69 482 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=69 483 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=69 484 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=69 485 fetching 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crawlDelay = 5000 1162 minCrawlDelay = 0 1163 nextFetchTime = 1405343098775 1164 now = 1405343096838 1165 0. http://blog.tianya.cn/post-4598537-62971461-1.shtml 1166 1. http://blog.tianya.cn/post-4598537-62971498-1.shtml 1167 -activeThreads=50, spinWaiting=50, fetchQueues.totalSize=2 1168 * queue: http://blog.tianya.cn 1169 maxThreads = 1 1170 inProgress = 0 1171 crawlDelay = 5000 1172 minCrawlDelay = 0 1173 nextFetchTime = 1405343098775 1174 now = 1405343097840 1175 0. http://blog.tianya.cn/post-4598537-62971461-1.shtml 1176 1. http://blog.tianya.cn/post-4598537-62971498-1.shtml 1177 fetching http://blog.tianya.cn/post-4598537-62971461-1.shtml 1178 -activeThreads=50, spinWaiting=49, fetchQueues.totalSize=1 1179 * queue: http://blog.tianya.cn 1180 maxThreads = 1 1181 inProgress = 1 1182 crawlDelay = 5000 1183 minCrawlDelay = 0 1184 nextFetchTime = 1405343098775 1185 now = 1405343098843 1186 0. http://blog.tianya.cn/post-4598537-62971498-1.shtml 1187 -activeThreads=50, spinWaiting=49, 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可以看到总共用了13分钟。日志靠近最下方有parse各个网页的时间
输入这条命令：
cat nohup.out|grep elapsed
显示信息如下：
1 Injector: finished at 2014-07-14 20:52:23, elapsed: 00:00:19 2 Generator: finished at 2014-07-14 20:52:39, elapsed: 00:00:15 3 Fetcher: finished at 2014-07-14 20:53:01, elapsed: 00:00:22 4 ParseSegment: finished at 2014-07-14 20:53:08, elapsed: 00:00:07 5 CrawlDb update: finished at 2014-07-14 20:53:22, elapsed: 00:00:13 6 Generator: finished at 2014-07-14 20:53:37, elapsed: 00:00:15 7 Fetcher: finished at 2014-07-14 21:05:17, elapsed: 00:11:39 8 ParseSegment: finished at 2014-07-14 21:05:30, elapsed: 00:00:13 9 CrawlDb update: finished at 2014-07-14 21:05:43, elapsed: 00:00:13 10 LinkDb: finished at 2014-07-14 21:05:53, elapsed: 00:00:10
每次crawl都是从injector(注入url)开始，然后Generator(产生抓取列表)，接着Fetch(抓取)，然后ParseSegment(内容解析), CrawlDb update(更新CrawlDb)为一轮，最后以LinkDb结束。由于没加topN所以第二层的Fetch用了11分钟时间。
这里有一篇nutch执行crawl命令的详细步骤的文章：http://www.cnblogs.com/huligong1234/p/3515214.html
以下命令只给出例子，详细说明可参见上面的链接
readdb： readdb命令是“org.apache.nutch.crawl.CrawlDbReader”的别称，返回或者导出Crawl数据库（crawldb）中的信息。
例子1：./bin/nutch readdb data/crawldb -stats
指定抓取完成后的数据在data/crawldb中
-stats代表在java标准输出中输出信息，如url数、已抓取数、未抓取数
以下是输出信息：
1 CrawlDb statistics start: data/crawldb 2 Statistics for CrawlDb: data/crawldb 3 TOTAL urls: 1469 4 retry 0: 1469 5 min score: 0.0 6 avg score: 0.0017549354 7 max score: 1.032 8 status 1 (db_unfetched): 1368 9 status 2 (db_fetched): 97 10 status 4 (db_redir_temp): 3 11 status 5 (db_redir_perm): 1 12 CrawlDb statistics: done
例子2：./bin/nutch readdb data/crawldb -dump data/crawldb/crawldb_dump
-dump把统计信息输出到后面的文件中
例子3：./bin/nutch readdb data/crawldb -url http://zxcvbnm20111.blog.tianya.cn/
输出 http://zxcvbnm20111.blog.tianya.cn/这个url的详细信息
这个网页是在运行例子2的命令之后，在data/crawldb/crawldb_dump文件中找的
信息如下：
1 CrawlDb dump: starting 2 CrawlDb db: data/crawldb 3 CrawlDb dump: done 4 lan@Ubuntu1:~/nutch/local$ 5 lan@Ubuntu1:~/nutch/local$ ./bin/nutch readdb data/crawldb -url http://zxcvbnm20111.blog.tianya.cn/ 6 URL: http://zxcvbnm20111.blog.tianya.cn/ 7 Version: 7 8 Status: 1 (db_unfetched) 9 Fetch time: Mon Jul 14 21:05:40 CST 2014 10 Modified time: Thu Jan 01 08:30:00 CST 1970 11 Retries since fetch: 0 12 Retry interval: 2592000 seconds (30 days) 13 Score: 2.9411764E-4 14 Signature: null 15 Metadata:
例子3：./bin/nutch readdb data/crawldb -topN 10 data/crawldb/crawldb_topN 0.5
在data/crawldb/crawldb_topN文件中输出排名前十的且分值大>=0.5的url及其分值
readseg： 例子1：./bin/nutch readseg -dump data/segments/20140714205330 data/segments/dump -nocontent -nofetch -noparse -noparsedata -noparsetext
查看segments产生的信息，输出到data/segments/dump文件（在参数中少了-nogenerate，就是说只写入产生segments的信息）
如果查看fetch信息，就把-nofetch改成-nogenerate
要查看content信息，就把-nocontent改成-nogenerate
同理，还有parse、parsedata和parsetext，不再赘述
例子2： ./bin/nutch readseg -list -dir data/segments
以列表的方式显示每次产生的segments
例子3： ./bin/nutch readseg -get data/segments/20140714205231 http://blog.tianya.cn/
显示某个segments的信息，哇塞，有一大堆html代码和内容~
readlinkdb： 例子1：./bin/nutch readlinkdb data/linkdb -dump data/linkdb/dump
将linkdb的信息dump到data/linkdb/dump文件里
例子2：./bin/nutch readlinkdb data/linkdb -url http://cnrdn.com/4NJC
查看某具体url。这个url是我在上面的dump文件中复制出来的
结果将会产生和dump文件中该url下面几行一样的文字
generate -> fetch -> parse -> update db
实际上，crawl命令等于inject命令+generate命令+fetch命令+parse命令+updatedb命令+invertlinks命令：
inject: 例子1: ./bin/nutch inject data/crawldb urls
把要抓取的url注入到crawldb中。url存放在urls文件夹中的所有文件中，注入到data/crawldb中。
要保证data不存在
generate: 例子: ./bin/nutch generate data/crawldb data/segments
fetch: 例子：./bin/nutch fetch data/segments/20140716205702 -threads 3
parse: 例子：./bin/nutch parse data/segments/20140716205702
updatedb: 例子: ./bin/nutch updatedb data/crawldb -dir data/segments
mergesegs: 例子:./bin/nutch mergesegs data2/segments_all -dir data2/segments
要注意，在segments文件夹及其子文件夹中不要有自己另外生成的东西
非常有用的命令，合并之后文件变小。文件越多越大，合并效果越好。I/O越快
类似的还有mergedb、mergelinkdb命令
invertlinks： 例子：./bin/nutch invertlinks data/linkdb -dir data/segments
要注意，在segments文件夹及其子文件夹中不要有自己另外生成的东西。
计算反向链接分析新输入的segment目录，产生新的反向链接库
把新产生的反向链接库与原来的库进行合并
通过计算有多少个网页指向当前网页，来计算当前网页的分值
parsecheker: 例子1：./bin/nutch parsechecker http://apdplat.org
可以方便的查看网页中有哪些链接
例子2: ./bin/nutch parsechecker -dumpText http://apdplat.org
只查看网页中的文本
./bin/nutch domainstats data/crawldb/current host host
第一个host是输出目录，第二个host是输出选项
./bin/nutch domainstats data/crawldb/current domain domain
./bin/nutch domainstats data/crawldb/current suffix suffix
./bin/nutch domainstats data/crawldb/current tld tld
从host级别到tld级别统计信息越来越少，因为后面的url包括前面的url，
假如有网址 http://www.cnblogs.com.cn/，host是www.cnblogs.com.cn，domain是cnblogs.com.cn,suffix是顶级域名com.cn。tld是比顶级域名还高级的域名，在这里就是cn，如果url是http://www.cnblogs.com，那么tld和suffix都是com
./bin/nutch webgraph -segmentDir data/segments -webgraphdb data/webgraphdb
指定segments输入路径和webgraphdb输出路径。将在data/webgraphdb生成Outlinks、Inlinks、Nodes
分别对应输出链接及数量，输入链接及数量，url及其分值
第一次执行webgraph命令时，nodes中的所有url的分值为0，因此需要执行linkrank命令
输出链接是保存在parse_data里的，所有OutLinkDb的的输入链接是parse_data
由输出连接可以得到所有网页的输入连接，就能计算每个网页的分值
./bin/nutch nodedumper -topn 1 -inlinks -output inlinks_topn_1 -webgraphdb data/webgraphdb
查看data/webgraphdb里的文件内容，可以看到url和输入链接数量
-asSequenceFile参数是生成序列文件，因为序列文件是2进制的，这里不用
-topn，如果有相同的输出链接，只输出topn条
-inlinks，按输入链接降序排序，类似的还有-outlinks、-scores
-output，指定输出目录
-webgraphdb，指定webgraphdb路径
如果按照scores来排序，在生成的文件中，我们可以看到所有的url分值都为0，
这说明经过执行webgraph命令，所有的url分值都为0
./bin/nutch linkrank -webgraphdb data/webgraphdb
计算分值并记录起来
然后在用命令：
./bin/nutch nodedumper -topn 1 -scores -output after-inject-scores -webgraphdb data/webgraphdb
可以发现after-inject-scores文件夹里的文件内容里的url分值不再是0
./bin/nutch nodedumper -group domain sum -inlinks -output inlink_domain_sum -webgraphdb data/webgraphdb
生成分组数据
domain可以替换成host, sum可以替换成max。这个两个参数要放在-group之后
如果对上面命令再加上-topn 1，输出路径改为inlink_domain_sum_1,会发现这个文件中的有些输入连接数少了
说明nodedumper先进行分组，然后再对每个组中的top1进行求和（和等于每组的最大输入链接数）
./bin/nutch scoreupdater -crawldb data/crawldb -webgraphdb data/webgraphdb
crawl命令默认使用了opic插件来计算分值。而webgraph的计算分值方式是从1.0开始有的，
比较完善。
./bin/nutch freegen urls2 data3/segments
urls2文件夹中存放了新生成的保存url的文件,有一个url在里边：http://apdplat.org
新生成的段输出到data3/segments
这个命令可以绕过抓取庞大的crawldb库，专门去通过某些url生成segments
检查是否配置了索引插件配置是否成功：
./bin/nutch indexchecker http://www.163.com
在显示的信息中title和content比较重要
找了很久才找到3.6.2和4.2.0的下载地址。现在主页上已经不能下载。
这里是solr各版本下载地址：http://archive.apache.org/dist/lucene/solr/
这里使用的是3.6.2
配置solr
1. 把nutch的conf/schema.xml复制到solr的/example/solr/conf中，注意备份solr的schema.xml
在nutch的conf/nutch-default.xml中搜索index- ,会找到如下xml段
<property> <name>plugin.includes</name> <value>protocol-http|urlfilter-regex|parse-(html|tika)|index-(basic|anchor)|scoring-opic|urlnormalizer-(pass|regex|basic)</value> <description>Regular expression naming plugin directory names to include. Any plugin not matching this expression is excluded. In any case you need at least include the nutch-extensionpoints plugin. By default Nutch includes crawling just HTML and plain text via HTTP, and basic indexing and search plugins. In order to use HTTPS please enable protocol-httpclient, but be aware of possible intermittent problems with the underlying commons-httpclient library. </description> </property>
可以看到这是把插件include到nutch的配置，index-basic和index-anchor是其中两个插件
进入solr的/example/solr/conf/schema.xml中(即刚才拷贝的nutch的schema.xml)
同样所有index-，其中有两个段
<!-- fields for index-basic plugin --> <field name="host" type="string" stored="false" indexed="true"/> <field name="url" type="url" stored="true" indexed="true" required="true"/> <field name="content" type="text" stored="false" indexed="true"/> <field name="title" type="text" stored="true" indexed="true"/> <field name="cache" type="string" stored="true" indexed="false"/> <field name="tstamp" type="date" stored="true" indexed="false"/> <!-- fields for index-anchor plugin --> <field name="anchor" type="string" stored="true" indexed="true" multiValued="true"/>
field配置了这两个插件的字段，除了field之外，在上面还有id
2. 把solr的/example/solr/conf/solrconfig.xml中的所有的<str name="df">text</str>改成<str name="df">content</str>
默认搜索的字段应该是content
3. 启动solr。到example下运行start.jar： java -jar start.jar & (后台运行)
如果没有配置第2步，就会报错说找不到text
4. 打开浏览器访问localhost:8983
可以看到solr管理网页。solr内嵌了jetty服务器，因此能够用b/s方式管理solr
5. 回到nutch的local下输入 bin/nutch | grep solr
可以发现有三条命令：solrindex（建solr索引）、solrdedup（去重）、solrclean（去除301永久重定向、404网址）
6. 通过crawldb、linkdb和segments来把索引提交给http://localhost:8983/solr：
在local目录下输入bin/nutch solrindex http://localhost:8983/solr data/crawldb -linkdb data/linkdb -dir data/segments
输出信息中有：Indexing 3 documents
如果超过250个，就会indexing多次，这个可以在conf/nutch-default.xml或nutch-site.xml中配置solr.commit.size(default中有样例)
调高数量可以提高效率，但是更占内存
solr将会把索引保存在example/solr/data/index中
luku是lucene的索引工具箱，可以方便查看和搜索索引，便于调试
下载地址：http://code.google.com/p/luke/downloads/list
这里使用的是：lukeall-4.0.0-ALPHA.jar
将solr的example/solr/data/index目录拷贝到本地(这里我把index目录拷贝到windows桌面，luke的jar包也放在桌面)
双击jar即可运行luke。Luke会自动提示你指向索引文件夹。
如上图，有10个字段，在左下角的框中显示了schema.xml中的1个id，3个core fields，5个index-basic字段(不知道为什么少了一个cache字段)，1个index-anchor字段
选中一个字段，再点show top term可以看到具体的分词
id字段是完整的、不分词的
点击Documents标签，可以通过docments数量来查看字段
注意点一下左上角的绿色左箭头(仅仅是为了让框里有内容从而显示字段信息)，然后按绿色的右箭头：
在title字段中找一个text，比如2014。点击search标签在左上角的框中输入title:2014 ,再点search，可以搜索到索引。应该指出：可能某些title是搜不出来的，应该确保建索引时的分词器和搜索时的分词器一致！比如title=明星娱乐圈，而用Luke会把整个title给分成4个字再搜索，这样会导致搜索不出。之后会讲到设置分词器。
solr自带的分词器对中文分词不好，导致Luke搜索不到索引信息，因此使用mmseg4j
下载地址：https://code.google.com/p/mmseg4j/downloads/list
这里使用的是mmseg4j-1.8.5.zip
1. 把solr停下来。使用jps命令查看进程号, 然后输入kill -9 进程号 关掉solr
2. 删除solr的example/solr/data目录
3. 在solr的example/solr下新建lib文件夹
4. 把mmseg4j中的mmseg4j-all-1.8.5-with-dic.jar拷贝到solr的example/solr/lib中，让solr的服务器加载这个jar包
5. 修改solr的example/solr/conf/schema.xml:
把<tokenizer class="solr.WhitespaceTokenizerFactory"/>和<tokenizer class="solr.StandardTokenizerFactory"/>
替换成<tokenizer class="com.chenlb.mmseg4j.solr.MMSegTokenizerFactory" mode="complex"/>
意思就是配置solr使用mmseg4j的类进行分词，默认的分词方法对中文分词效果不好
之后再打开solr服务器，把索引注入到solr中，然后用Luke打开索引文件夹，在使用搜索中文字段时就能找到了~
可以发现Luke中Number of terms明显变小，这是因为solr配置mmseg4j后把多个汉字分成1个词，原先可能是每个汉字一个词。
另外，可以在localhost:8983/solr/admin页面的Query String: 查询框中也可以搜索，搜索语法和Luke一样，都是"字段名:要查的值"
虽然现在已经配置了solr的分词器，但是Luke还没配置mmseg4j作为分词器，
在Luke中search "title:客户端" 时，会分成3个词(现在Luke还没指定mmseg4j为分词器)，
而如果Luke配置了mmseg4j作为分词器时，会把“客户端”当成一个词
虽然luke可以搜索到索引了，solr和luke最好使用同一个分词器。
1.8.5版本跟luke4.0版本有冲突，所以luke使用1.9.1的mmseg4j，下载地址上面有。
这里使用：mmseg4j-1.9.1.v20130120-SNAPSHOT.zip
把mmseg4j-1.9.1的dist中的三个jar包解压出来，并把解压出来的data文件夹和com文件夹复制到Luke的jar中
打开Luke并指定index目录，点击search选项卡，看到右边有一个下拉框选择用来处理分词的类ComplexAnalyzer，在下拉框右边选默认字段为content
搜索：title:客户端
会发现Query Details框中分词就是”客户端”，如果是用原先没配置，会把“客户端”当成3个词
以下内容提到的solr目录均以
1. solr4.2的example/solr/中多了一个collection1文件夹。要把nutch的local/conf/schema-solr4.xml拷贝到solr4.2的example/solr/collection1的conf目录中并重命名为schema.xml
2. solr4.2不需要把schema.xml中的text换成content。怎么看应该修改成那个字段？打开shema.xml，拉到下边有这个标签：
<defaultSearchField>content</defaultSearchField>
solr4.2的这个标签就是text，所以不用改。而solr3.6.2的这个标签是content，所以得把所有的text改成content
3. 在schema.xml的fields标签中加入一个_version_标签，不然启动solr时会报错：
<field name="_version_" type="long" stored="true" indexed="true"/>
4. 启动solr，也是打开start.jar
5. 拷贝mmseg4j-1.9.1的jar。同样，也是拷贝jar就好了，把mmseg4j的dist中的jar拷贝到solr4.2的collection1的lib目录下，注意如果没有lib文件夹要先mkdir
6. 配置mmseg4j。
修改solr的example/solr/conf/schema.xml:
把<tokenizer class="solr.WhitespaceTokenizerFactory"/>和<tokenizer class="solr.StandardTokenizerFactory"/>
替换成<tokenizer class="com.chenlb.mmseg4j.solr.MMSegTokenizerFactory" mode="complex"/>
注意别把除WhitespaceTokenizerFactory和StandardTokenizerFactory之外的tokenizer给改了
之后就可以提交索引到solr了
提交索引后，可以进入localhost:8983的core admin中查看索引数等信息：
在左下角有个Core Selector下拉框可以选collection1，然后点击下方的query，在右边的界面就能够查询索引了：
在windows系统中使用虚拟机来使用linux比较重量级，
我安装的Ubuntu虚拟机需要4G内存才能跑得不那么卡。
Cygwin相比之下比较轻量级，而且能够方便地在cygwin的环境中使用windows的东西。
如果java的目录有包含空格，那么运行 nutch crawl命令时就会出错。
比如使用cygwin时，首先把apache-nutch-1.6复制到cygwin目录下的home/Administrator(取决于你的操作系统用户名)中，
打开cygwin，进入nutch的bin目录下执行./nutch crawl命令，会提示你该目录不存在(如果你的java安装在c:/Program Files/中)。
解决方法：
把整个java目录拷贝到cygwin的home/Administrator目录下，
并设置JAVA_HOME为c:/cygwin/home/Administrator/Java/jdk1.6.0_21 就好了
如果机器上有多个jdk，那就为cygin设置NUTCH_JAVA_HOME。
注意cygwin中的环境变量是windows的目录。
hadoop的教程可以在这里找到：http://www.cnblogs.com/lanhj/p/3841709.html
这里用到的nutch保存在前面用ant编译生成的deploy文件夹，即nutch把job提交给hadoop执行的版本
在nutch的conf/nutch-site.xml中加入http.agent.name的键值对(前面有)就ok啦~
当然hadoop至少要运行自带的WordCount.java成功，并且配上HADOOP_HOME环境变量才行。
还是老样子，先在deploy中生成urls文件夹，在里面生成保存url的文档
然后执行crawl命令：
bin/nutch crawl urls -dir data -threads 50 -depth 2 -topN 1
是不是报出非法输入错误？
原因是：job是hadoop执行的，hadoop默认的目录是HDFS上的目录，因此我们需要把urls上传到HDFS上：
hadoop fs -put urls /user/xxx/ hadoop fs -ls /user/xxx
第一条命令是把urls上传到HDFS的user/xxx目录下(nutch的job要求inject的urls存放在 /user/用户名/ 下)，第二条命令是看该目录下有哪些文件。
可以看到urls已经上传到HDFS了(在我的另一篇随笔中，由于我比较懒，暂时没写关于HDFS的概念、命令、api。之前做的ppt和代码都还在，有空再上传)
再次运行crawl命令，
命令执行到半的时候，可以打开http://localhost:50030(hadoop查看mapreduce和jobtracker的页面)
可以看见有Map task或Reduce task
等结束以后，再查看HDFS的/user/xxx目录，可以发现生成了data文件夹
嫌查看HDFS的文件命令麻烦，就打开localhost:80070，然后点击Browse the filesystem查看HDFS上的文件
这个网页只能查看目录以及文档，不能删除、上传、更新
localhost:50060可以查看tasktracker信息
hadoop也内嵌了jetty服务器，所以可以用网页的方式查看hadoop的情况
7月22日更新完毕