113 | | * grep 這個命令是擷取文件裡面特定的字元,在Hadoop example中此指令可以擷取文件中有此指定文字的字串,並作計數統計 |
114 | | |
115 | | {{{ |
116 | | /opt/hadoop$ bin/hadoop jar hadoop-*-examples.jar grep input grep_output 'dfs[a-z.]+' |
117 | | |
118 | | }}} |
119 | | |
120 | | 運作的畫面如下: |
121 | | |
122 | | {{{ |
123 | | |
124 | | 09/03/24 12:33:45 INFO mapred.FileInputFormat: Total input paths to process : 9 |
125 | | 09/03/24 12:33:45 INFO mapred.FileInputFormat: Total input paths to process : 9 |
126 | | 09/03/24 12:33:45 INFO mapred.JobClient: Running job: job_200903232025_0003 |
127 | | 09/03/24 12:33:46 INFO mapred.JobClient: map 0% reduce 0% |
128 | | 09/03/24 12:33:47 INFO mapred.JobClient: map 10% reduce 0% |
129 | | 09/03/24 12:33:49 INFO mapred.JobClient: map 20% reduce 0% |
130 | | 09/03/24 12:33:51 INFO mapred.JobClient: map 30% reduce 0% |
131 | | 09/03/24 12:33:52 INFO mapred.JobClient: map 40% reduce 0% |
132 | | 09/03/24 12:33:54 INFO mapred.JobClient: map 50% reduce 0% |
133 | | 09/03/24 12:33:55 INFO mapred.JobClient: map 60% reduce 0% |
134 | | 09/03/24 12:33:57 INFO mapred.JobClient: map 70% reduce 0% |
135 | | 09/03/24 12:33:59 INFO mapred.JobClient: map 80% reduce 0% |
136 | | 09/03/24 12:34:00 INFO mapred.JobClient: map 90% reduce 0% |
137 | | 09/03/24 12:34:02 INFO mapred.JobClient: map 100% reduce 0% |
138 | | 09/03/24 12:34:10 INFO mapred.JobClient: map 100% reduce 10% |
139 | | 09/03/24 12:34:12 INFO mapred.JobClient: map 100% reduce 13% |
140 | | 09/03/24 12:34:15 INFO mapred.JobClient: map 100% reduce 20% |
141 | | 09/03/24 12:34:20 INFO mapred.JobClient: map 100% reduce 23% |
142 | | 09/03/24 12:34:22 INFO mapred.JobClient: Job complete: job_200903232025_0003 |
143 | | 09/03/24 12:34:22 INFO mapred.JobClient: Counters: 16 |
144 | | 09/03/24 12:34:22 INFO mapred.JobClient: File Systems |
145 | | 09/03/24 12:34:22 INFO mapred.JobClient: HDFS bytes read=48245 |
146 | | 09/03/24 12:34:22 INFO mapred.JobClient: HDFS bytes written=1907 |
147 | | 09/03/24 12:34:22 INFO mapred.JobClient: Local bytes read=1549 |
148 | | 09/03/24 12:34:22 INFO mapred.JobClient: Local bytes written=3584 |
149 | | 09/03/24 12:34:22 INFO mapred.JobClient: Job Counters |
150 | | ...... |
151 | | }}} |
152 | | |
153 | | |
154 | | * 接著查看結果 |
155 | | |
156 | | {{{ |
157 | | /opt/hadoop$ bin/hadoop fs -ls grep_output |
158 | | /opt/hadoop$ bin/hadoop fs -cat grep_output/part-00000 |
159 | | }}} |
160 | | |
161 | | 結果如下 |
162 | | |
163 | | {{{ |
164 | | 3 dfs.class |
165 | | 3 dfs. |
166 | | 2 dfs.period |
167 | | 1 dfs.http.address |
168 | | 1 dfs.balance.bandwidth |
169 | | 1 dfs.block.size |
170 | | 1 dfs.blockreport.initial |
171 | | 1 dfs.blockreport.interval |
172 | | 1 dfs.client.block.write.retries |
173 | | 1 dfs.client.buffer.dir |
174 | | 1 dfs.data.dir |
175 | | 1 dfs.datanode.address |
176 | | 1 dfs.datanode.dns.interface |
177 | | 1 dfs.datanode.dns.nameserver |
178 | | 1 dfs.datanode.du.pct |
179 | | 1 dfs.datanode.du.reserved |
180 | | 1 dfs.datanode.handler.count |
181 | | 1 dfs.datanode.http.address |
182 | | 1 dfs.datanode.https.address |
183 | | 1 dfs.datanode.ipc.address |
184 | | 1 dfs.default.chunk.view.size |
185 | | 1 dfs.df.interval |
186 | | 1 dfs.file |
187 | | 1 dfs.heartbeat.interval |
188 | | 1 dfs.hosts |
189 | | 1 dfs.hosts.exclude |
190 | | 1 dfs.https.address |
191 | | 1 dfs.impl |
192 | | 1 dfs.max.objects |
193 | | 1 dfs.name.dir |
194 | | 1 dfs.namenode.decommission.interval |
195 | | 1 dfs.namenode.decommission.interval. |
196 | | 1 dfs.namenode.decommission.nodes.per.interval |
197 | | 1 dfs.namenode.handler.count |
198 | | 1 dfs.namenode.logging.level |
199 | | 1 dfs.permissions |
200 | | 1 dfs.permissions.supergroup |
201 | | 1 dfs.replication |
202 | | 1 dfs.replication.consider |
203 | | 1 dfs.replication.interval |
204 | | 1 dfs.replication.max |
205 | | 1 dfs.replication.min |
206 | | 1 dfs.replication.min. |
207 | | 1 dfs.safemode.extension |
208 | | 1 dfs.safemode.threshold.pct |
209 | | 1 dfs.secondary.http.address |
210 | | 1 dfs.servers |
211 | | 1 dfs.web.ugi |
212 | | 1 dfsmetrics.log |
213 | | |
214 | | }}} |
215 | | |
216 | | === 2.2 Hadoop運算命令 WordCount === |
217 | | |
218 | | * 如名稱,WordCount會對所有的字作字數統計,並且從a-z作排列 |
219 | | |
220 | | {{{ |
221 | | /opt/hadoop$ bin/hadoop jar hadoop-*-examples.jar wordcount input wc_output |
222 | | }}} |
223 | | |
224 | | 檢查輸出結果的方法同2.1的方法 |
225 | | |
226 | | === 2.3 更多運算命令 === |
227 | | |
228 | | 可執行的指令一覽表: |
229 | | |
230 | | || aggregatewordcount || An Aggregate based map/reduce program that counts the words in the input files. || |
231 | | || aggregatewordhist || An Aggregate based map/reduce program that computes the histogram of the words in the input files. || |
232 | | || grep || A map/reduce program that counts the matches of a regex in the input. || |
233 | | || join || A job that effects a join over sorted, equally partitioned datasets || |
234 | | || multifilewc || A job that counts words from several files. || |
235 | | || pentomino || A map/reduce tile laying program to find solutions to pentomino problems. || |
236 | | || pi || A map/reduce program that estimates Pi using monte-carlo method. || |
237 | | || randomtextwriter || A map/reduce program that writes 10GB of random textual data per node. || |
238 | | || randomwriter || A map/reduce program that writes 10GB of random data per node. || |
239 | | || sleep || A job that sleeps at each map and reduce task. || |
240 | | || sort || A map/reduce program that sorts the data written by the random writer. || |
241 | | || sudoku || A sudoku solver. || |
242 | | || wordcount || A map/reduce program that counts the words in the input files. || |
243 | | |
244 | | 請參考 [http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/examples/package-summary.html org.apache.hadoop.examples] |
245 | | |
246 | | {{{ |
247 | | #!html |
248 | | <html lang="zh-tw"><head> |
249 | | |
250 | | <meta content="text/html; charset=ISO-8859-1" http-equiv="content-type"><title>a.html</title> |
251 | | |
252 | | </head><body> |
253 | | <br> |
254 | | |
255 | | <p> |
256 | | </p><table summary="" border="1" cellpadding="3" cellspacing="0" width="100%"> |
257 | | <tbody><tr class="TableHeadingColor" bgcolor="#ccccff"> |
258 | | <th colspan="2" align="left"><font size="+2"> |
259 | | <b>Class Summary</b></font></th> |
260 | | </tr> |
261 | | <tr class="TableRowColor" bgcolor="white"> |
262 | | |
263 | | <td width="15%"><b><a href="http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/examples/AggregateWordCount.html" title="class in org.apache.hadoop.examples">AggregateWordCount</a></b></td> |
264 | | <td>This is an example Aggregated Hadoop Map/Reduce application. It |
265 | | reads the text input files, breaks each line into words and counts |
266 | | them. The output is a locally sorted list of words and the count of how |
267 | | often they occurred. To run: bin/hadoop jar hadoop-*-examples.jar |
268 | | aggregatewordcount in-dir out-dir numOfReducers textinputformat </td> |
269 | | </tr> |
270 | | <tr class="TableRowColor" bgcolor="white"> |
271 | | <td width="15%"><b><a href="http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/examples/AggregateWordHistogram.html" title="class in org.apache.hadoop.examples">AggregateWordHistogram</a></b></td> |
272 | | <td>This is an example Aggregated Hadoop Map/Reduce application. |
273 | | Computes the histogram of the words in the input texts. To run: |
274 | | bin/hadoop jar hadoop-*-examples.jar aggregatewordhist in-dir out-dir |
275 | | numOfReducers textinputformat </td> |
276 | | </tr> |
277 | | <tr class="TableRowColor" bgcolor="white"> |
278 | | <td width="15%"><b><a href="http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/examples/ExampleDriver.html" title="class in org.apache.hadoop.examples">ExampleDriver</a></b></td> |
279 | | <td>A description of an example program based on its class and a human-readable description.</td> |
280 | | </tr> |
281 | | |
282 | | <tr class="TableRowColor" bgcolor="white"> |
283 | | <td width="15%"><b><a href="http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/examples/Grep.html" title="class in org.apache.hadoop.examples">Grep</a></b></td> |
284 | | <td> </td> |
285 | | </tr> |
286 | | <tr class="TableRowColor" bgcolor="white"> |
287 | | <td width="15%"><b><a href="http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/examples/Join.html" title="class in org.apache.hadoop.examples">Join</a></b></td> |
288 | | <td>This is the trivial map/reduce program that does absolutely nothing |
289 | | other than use the framework to fragment and sort the input values. To |
290 | | run: bin/hadoop jar build/hadoop-examples.jar join [-m maps] [-r |
291 | | reduces] [-inFormat input format class] [-outFormat output format |
292 | | class] [-outKey output key class] [-outValue output value class] |
293 | | [-joinOp] [in-dir]* in-dir out-dir</inner></td> |
294 | | </tr> |
295 | | <tr class="TableRowColor" bgcolor="white"> |
296 | | <td width="15%"><b><a href="http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/examples/RandomTextWriter.html" title="class in org.apache.hadoop.examples">RandomTextWriter</a></b></td> |
297 | | <td>This program uses map/reduce to just run a distributed job where |
298 | | there is |
299 | | no interaction between the tasks and each task writes a large unsorted |
300 | | random sequence of words.To run: bin/hadoop jar |
301 | | hadoop-${version}-examples.jar randomtextwriter [-outFormat output |
302 | | format class] output</td> |
303 | | |
304 | | </tr> |
305 | | <tr class="TableRowColor" bgcolor="white"> |
306 | | <td width="15%"><b><a href="http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/examples/RandomWriter.html" title="class in org.apache.hadoop.examples">RandomWriter</a></b></td> |
307 | | <td>This program uses map/reduce to just run a distributed job where |
308 | | there is |
309 | | no interaction between the tasks and each task write a large unsorted |
310 | | random binary sequence file of BytesWritable.To run: bin/hadoop jar |
311 | | hadoop-${version}-examples.jar randomwriter [-outFormat output format |
312 | | class] output</td> |
313 | | </tr> |
314 | | <tr class="TableRowColor" bgcolor="white"> |
315 | | <td width="15%"><b><a href="http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/examples/Sort.html" title="class in org.apache.hadoop.examples">Sort<K,V></a></b></td> |
316 | | <td>This is the trivial map/reduce program that does absolutely nothing |
317 | | other than use the framework to fragment and sort the input values.To |
318 | | run: bin/hadoop jar build/hadoop-examples.jar sort [-m maps] [-r |
319 | | reduces] [-inFormat input format class] [-outFormat output format |
320 | | class] [-outKey output key class] [-outValue output value class] |
321 | | [-totalOrder pcnt num samples max splits] in-dir out-dir</td> |
322 | | </tr> |
323 | | <tr class="TableRowColor" bgcolor="white"> |
324 | | <td width="15%"><b><a href="http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/examples/WordCount.html" title="class in org.apache.hadoop.examples">WordCount</a></b></td> |
325 | | |
326 | | <td>This is an example Hadoop Map/Reduce application.</td> |
327 | | </tr> |
328 | | </tbody></table> |
329 | | </body></html> |
330 | | }}} |
331 | | |
332 | | |
333 | | == Content 3. 使用網頁Gui瀏覽資訊 == |
| 110 | == Content 2. 使用網頁Gui瀏覽資訊 == |