| | 1 | [[PageOutline]] |
| | 2 | {{{ |
| | 3 | #!html |
| | 4 | <div style="text-align: center;"><big |
| | 5 | style="font-weight: bold;"><big><big> hadoop 程式開發 (eclipse plugin) </big></big></big></div> |
| | 6 | }}} |
| | 7 | = 零. 環境配置 = |
| | 8 | |
| | 9 | |
| | 10 | == 0.1 環境說明 == |
| | 11 | * ubuntu 8.10 |
| | 12 | * sun-java-6 |
| | 13 | * [http://www.java.com/zh_TW/download/linux_manual.jsp?locale=zh_TW&host=www.java.com:80 java 下載處] |
| | 14 | * [https://cds.sun.com/is-bin/INTERSHOP.enfinity/WFS/CDS-CDS_Developer-Site/en_US/-/USD/ViewProductDetail-Start?ProductRef=jdk-6u10-docs-oth-JPR@CDS-CDS_Developer JavaDoc ] |
| | 15 | * eclipse 3.3.2 |
| | 16 | * eclipse 各版本下載點 [http://archive.eclipse.org/eclipse/downloads/] |
| | 17 | * hadoop 0.18.3 |
| | 18 | * hadoop 各版本下載點 [http://ftp.twaren.net/Unix/Web/apache/hadoop/core/] |
| | 19 | |
| | 20 | == 0.2 目錄說明 == |
| | 21 | |
| | 22 | * 使用者:hadoop |
| | 23 | * 使用者家目錄: /home/hadooper |
| | 24 | * 專案目錄 : /home/hadooper/workspace |
| | 25 | * hadoop目錄: /opt/hadoop |
| | 26 | |
| | 27 | = 一、安裝 = |
| | 28 | |
| | 29 | 安裝的部份沒必要都一模一樣,僅提供參考,反正只要安裝好java , hadoop , eclipse,並清楚自己的路徑就可以了 |
| | 30 | |
| | 31 | == 1.1. 安裝java == |
| | 32 | |
| | 33 | 首先安裝java 基本套件 |
| | 34 | |
| | 35 | {{{ |
| | 36 | $ sudo apt-get install java-common sun-java6-bin sun-java6-jdk sun-java6-jre |
| | 37 | }}} |
| | 38 | |
| | 39 | == 1.1.1. 安裝sun-java6-doc == |
| | 40 | |
| | 41 | 1 將javadoc (jdk-6u10-docs.zip) 下載下來放在 /tmp/ 下 |
| | 42 | |
| | 43 | * 教學環境內,已經存在於 /home/hadooper/tools/ ,將其複製到 /tmp |
| | 44 | {{{ |
| | 45 | $ cp /home/hadooper/tools/jdk-*-docs.zip /tmp/ |
| | 46 | }}} |
| | 47 | |
| | 48 | * 或是到官方網站將javadoc (jdk-6u10-docs.zip) 下載下來放到 /tmp |
| | 49 | [https://cds.sun.com/is-bin/INTERSHOP.enfinity/WFS/CDS-CDS_Developer-Site/en_US/-/USD/ViewProductDetail-Start?ProductRef=jdk-6u10-docs-oth-JPR@CDS-CDS_Developer 下載點] |
| | 50 | [[Image(wiki:waue/2009/0617:1-1.png)]] |
| | 51 | |
| | 52 | 2 執行 |
| | 53 | |
| | 54 | {{{ |
| | 55 | $ sudo apt-get install sun-java6-doc |
| | 56 | $ sudo ln -sf /usr/share/doc/sun-java6-jdk/html /usr/lib/jvm/java-6-sun/docs |
| | 57 | }}} |
| | 58 | |
| | 59 | == 1.2. ssh 安裝設定 == |
| | 60 | |
| | 61 | [http://trac.nchc.org.tw/cloud/wiki/Hadoop_Lab1 詳見實作一] |
| | 62 | == 1.3. 安裝hadoop == |
| | 63 | [http://trac.nchc.org.tw/cloud/wiki/Hadoop_Lab1 詳見實作一] |
| | 64 | |
| | 65 | == 1.4. 安裝eclipse == |
| | 66 | |
| | 67 | * 取得檔案 eclipse 3.3.2 (假設已經下載於/home/hadooper/tools/ 內),執行下面指令: |
| | 68 | |
| | 69 | {{{ |
| | 70 | $ cd ~/tools/ |
| | 71 | $ tar -zxvf eclipse-SDK-3.3.2-linux-gtk.tar.gz |
| | 72 | $ sudo mv eclipse /opt |
| | 73 | $ sudo ln -sf /opt/eclipse/eclipse /usr/local/bin/ |
| | 74 | }}} |
| | 75 | |
| | 76 | = 二、 建立專案 = |
| | 77 | |
| | 78 | == 2.1 安裝hadoop 的 eclipse plugin == |
| | 79 | |
| | 80 | * 匯入hadoop eclipse plugin |
| | 81 | |
| | 82 | {{{ |
| | 83 | $ cd /opt/hadoop |
| | 84 | $ sudo cp /opt/hadoop/contrib/eclipse-plugin/hadoop-0.18.3-eclipse-plugin.jar /opt/eclipse/plugins |
| | 85 | }}} |
| | 86 | |
| | 87 | 補充: 可斟酌參考eclipse.ini內容(非必要) |
| | 88 | |
| | 89 | {{{ |
| | 90 | $ sudo cat /opt/eclipse/eclipse.ini |
| | 91 | }}} |
| | 92 | |
| | 93 | {{{ |
| | 94 | #!sh |
| | 95 | -showsplash |
| | 96 | org.eclipse.platform |
| | 97 | -vmargs |
| | 98 | -Xms40m |
| | 99 | -Xmx256m |
| | 100 | }}} |
| | 101 | |
| | 102 | == 2.2 開啟eclipse == |
| | 103 | |
| | 104 | * 打開eclipse |
| | 105 | |
| | 106 | {{{ |
| | 107 | $ eclipse & |
| | 108 | }}} |
| | 109 | |
| | 110 | 一開始會出現問你要將工作目錄放在哪裡:在這我們用預設值 |
| | 111 | |
| | 112 | |
| | 113 | [[Image(wiki:waue/2009/0617:2-1.png)]] |
| | 114 | ------- |
| | 115 | |
| | 116 | '''PS: 之後的說明則是在eclipse 上的介面操作''' |
| | 117 | |
| | 118 | ------- |
| | 119 | |
| | 120 | == 2.3 選擇視野 == |
| | 121 | |
| | 122 | || window -> || open pers.. -> || other.. -> || map/reduce|| |
| | 123 | |
| | 124 | [[Image(wiki:waue/2009/0617:win-open-other.png)]] |
| | 125 | |
| | 126 | ------- |
| | 127 | |
| | 128 | 設定要用 Map/Reduce 的視野 |
| | 129 | |
| | 130 | |
| | 131 | [[Image(wiki:waue/2009/0617:2-2.png)]] |
| | 132 | |
| | 133 | --------- |
| | 134 | |
| | 135 | 使用 Map/Reduce 的視野後的介面呈現 |
| | 136 | |
| | 137 | |
| | 138 | [[Image(wiki:waue/2009/0617:2-3.png)]] |
| | 139 | |
| | 140 | -------- |
| | 141 | |
| | 142 | == 2.4 建立專案 == |
| | 143 | |
| | 144 | || file -> || new -> || project -> || Map/Reduce -> || Map/Reduce Project -> || next || |
| | 145 | [[Image(wiki:waue/2009/0617:file-new-project.png)]] |
| | 146 | |
| | 147 | -------- |
| | 148 | |
| | 149 | 建立mapreduce專案(1) |
| | 150 | |
| | 151 | [[Image(wiki:waue/2009/0617:2-4.png)]] |
| | 152 | |
| | 153 | ----------- |
| | 154 | |
| | 155 | 建立mapreduce專案的(2) |
| | 156 | {{{ |
| | 157 | #!sh |
| | 158 | project name-> 輸入 : icas (隨意) |
| | 159 | use default hadoop -> Configur Hadoop install... -> 輸入: "/opt/hadoop" -> ok |
| | 160 | Finish |
| | 161 | }}} |
| | 162 | |
| | 163 | [[Image(wiki:waue/2009/0617:2-4-2.png)]] |
| | 164 | |
| | 165 | |
| | 166 | -------------- |
| | 167 | |
| | 168 | == 2.5 設定專案 == |
| | 169 | |
| | 170 | 由於剛剛建立了icas這個專案,因此eclipse已經建立了新的專案,出現在左邊視窗,右鍵點選該資料夾,並選properties |
| | 171 | |
| | 172 | -------------- |
| | 173 | |
| | 174 | Step1. 右鍵點選project的properties做細部設定 |
| | 175 | |
| | 176 | [[Image(wiki:waue/2009/0617:2-5.png)]] |
| | 177 | |
| | 178 | ---------- |
| | 179 | |
| | 180 | Step2. 進入專案的細部設定頁 |
| | 181 | |
| | 182 | hadoop的javadoc的設定(1) |
| | 183 | |
| | 184 | |
| | 185 | [[Image(wiki:waue/2009/0617:2-5-1.png)]] |
| | 186 | |
| | 187 | * java Build Path -> Libraries -> hadoop0.18.3-ant.jar |
| | 188 | * java Build Path -> Libraries -> hadoop0.18.3-core.jar |
| | 189 | * java Build Path -> Libraries -> hadoop0.18.3-tools.jar |
| | 190 | * 以 hadoop0.18.3-core.jar 的設定內容如下,其他依此類推 |
| | 191 | |
| | 192 | {{{ |
| | 193 | #!sh |
| | 194 | source ...-> 輸入:/opt/hadoop/src/core |
| | 195 | javadoc ...-> 輸入:file:/opt/hadoop/docs/api/ |
| | 196 | }}} |
| | 197 | |
| | 198 | ------------ |
| | 199 | Step3. hadoop的javadoc的設定完後(2) |
| | 200 | [[Image(wiki:waue/2009/0617:2-5-2.png)]] |
| | 201 | |
| | 202 | ------------ |
| | 203 | Step4. java本身的javadoc的設定(3) |
| | 204 | |
| | 205 | * javadoc location -> 輸入:file:/usr/lib/jvm/java-6-sun/docs/api/ |
| | 206 | |
| | 207 | [[Image(wiki:waue/2009/0617:2-5-3.png)]] |
| | 208 | |
| | 209 | ----- |
| | 210 | 設定完後回到eclipse 主視窗 |
| | 211 | |
| | 212 | |
| | 213 | == 2.6 連接hadoop server == |
| | 214 | |
| | 215 | -------- |
| | 216 | Step1. 視窗右下角黃色大象圖示"Map/Reduce Locations tag" -> 點選齒輪右邊的藍色大象圖示: |
| | 217 | [[Image(wiki:waue/2009/0617:2-6.png)]] |
| | 218 | |
| | 219 | ------------- |
| | 220 | Step2. 進行eclipse 與 hadoop 間的設定(2) |
| | 221 | [[Image(wiki:waue/2009/0617:2-6-1.png)]] |
| | 222 | |
| | 223 | {{{ |
| | 224 | #!sh |
| | 225 | Location Name -> 輸入:hadoop (隨意) |
| | 226 | Map/Reduce Master |
| | 227 | -> Host-> 輸入:localhost |
| | 228 | -> Port-> 輸入:9001 |
| | 229 | DFS Master |
| | 230 | -> Host-> 輸入:9000 |
| | 231 | Finish |
| | 232 | }}} |
| | 233 | ---------------- |
| | 234 | |
| | 235 | 設定完後,可以看到下方多了一隻藍色大象,左方展開資料夾也可以秀出在hdfs內的檔案結構 |
| | 236 | [[Image(wiki:waue/2009/0617:2-6-2.png)]] |
| | 237 | ------------- |
| | 238 | |
| | 239 | = 三、 撰寫範例程式 = |
| | 240 | |
| | 241 | * 之前在eclipse上已經開了個專案icas,因此這個目錄在: |
| | 242 | * /home/hadooper/workspace/icas |
| | 243 | * 在這個目錄內有兩個資料夾: |
| | 244 | * src : 用來裝程式原始碼 |
| | 245 | * bin : 用來裝編譯後的class檔 |
| | 246 | * 如此一來原始碼和編譯檔就不會混在一起,對之後產生jar檔會很有幫助 |
| | 247 | * 在這我們編輯一個範例程式 : WordCount |
| | 248 | |
| | 249 | == 3.1 mapper.java == |
| | 250 | |
| | 251 | 1. new |
| | 252 | |
| | 253 | || File -> || new -> || mapper || |
| | 254 | [[Image(wiki:waue/2009/0617:file-new-mapper.png)]] |
| | 255 | |
| | 256 | ----------- |
| | 257 | |
| | 258 | 2. create |
| | 259 | |
| | 260 | [[Image(wiki:waue/2009/0617:3-1.png)]] |
| | 261 | {{{ |
| | 262 | #!sh |
| | 263 | source folder-> 輸入: icas/src |
| | 264 | Package : Sample |
| | 265 | Name -> : mapper |
| | 266 | }}} |
| | 267 | ---------- |
| | 268 | |
| | 269 | 3. modify |
| | 270 | |
| | 271 | {{{ |
| | 272 | #!java |
| | 273 | package Sample; |
| | 274 | |
| | 275 | import java.io.IOException; |
| | 276 | import java.util.StringTokenizer; |
| | 277 | |
| | 278 | import org.apache.hadoop.io.IntWritable; |
| | 279 | import org.apache.hadoop.io.LongWritable; |
| | 280 | import org.apache.hadoop.io.Text; |
| | 281 | import org.apache.hadoop.mapred.MapReduceBase; |
| | 282 | import org.apache.hadoop.mapred.Mapper; |
| | 283 | import org.apache.hadoop.mapred.OutputCollector; |
| | 284 | import org.apache.hadoop.mapred.Reporter; |
| | 285 | |
| | 286 | public class mapper extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable> { |
| | 287 | private final static IntWritable one = new IntWritable(1); |
| | 288 | private Text word = new Text(); |
| | 289 | |
| | 290 | public void map(LongWritable key, Text value, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException { |
| | 291 | String line = value.toString(); |
| | 292 | StringTokenizer tokenizer = new StringTokenizer(line); |
| | 293 | while (tokenizer.hasMoreTokens()) { |
| | 294 | word.set(tokenizer.nextToken()); |
| | 295 | output.collect(word, one); |
| | 296 | } |
| | 297 | } |
| | 298 | } |
| | 299 | |
| | 300 | }}} |
| | 301 | |
| | 302 | 建立mapper.java後,貼入程式碼 |
| | 303 | [[Image(wiki:waue/2009/0617:3-2.png)]] |
| | 304 | |
| | 305 | ------------ |
| | 306 | |
| | 307 | == 3.2 reducer.java == |
| | 308 | |
| | 309 | 1. new |
| | 310 | |
| | 311 | * File -> new -> reducer |
| | 312 | [[Image(wiki:waue/2009/0617:file-new-reducer.png)]] |
| | 313 | |
| | 314 | ------- |
| | 315 | 2. create |
| | 316 | [[Image(wiki:waue/2009/0617:3-3.png)]] |
| | 317 | |
| | 318 | {{{ |
| | 319 | #!sh |
| | 320 | source folder-> 輸入: icas/src |
| | 321 | Package : Sample |
| | 322 | Name -> : reducer |
| | 323 | }}} |
| | 324 | |
| | 325 | ----------- |
| | 326 | |
| | 327 | 3. modify |
| | 328 | |
| | 329 | {{{ |
| | 330 | #!java |
| | 331 | package Sample; |
| | 332 | |
| | 333 | import java.io.IOException; |
| | 334 | import java.util.Iterator; |
| | 335 | |
| | 336 | import org.apache.hadoop.io.IntWritable; |
| | 337 | import org.apache.hadoop.io.Text; |
| | 338 | import org.apache.hadoop.mapred.MapReduceBase; |
| | 339 | import org.apache.hadoop.mapred.OutputCollector; |
| | 340 | import org.apache.hadoop.mapred.Reducer; |
| | 341 | import org.apache.hadoop.mapred.Reporter; |
| | 342 | |
| | 343 | public class reducer extends MapReduceBase implements Reducer<Text, IntWritable, Text, IntWritable> { |
| | 344 | public void reduce(Text key, Iterator<IntWritable> values, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException { |
| | 345 | int sum = 0; |
| | 346 | while (values.hasNext()) { |
| | 347 | sum += values.next().get(); |
| | 348 | } |
| | 349 | output.collect(key, new IntWritable(sum)); |
| | 350 | } |
| | 351 | } |
| | 352 | }}} |
| | 353 | |
| | 354 | * File -> new -> Map/Reduce Driver |
| | 355 | [[Image(wiki:waue/2009/0617:file-new-mr-driver.png)]] |
| | 356 | ---------- |
| | 357 | |
| | 358 | == 3.3 WordCount.java (main function) == |
| | 359 | |
| | 360 | 1. new |
| | 361 | |
| | 362 | 建立WordCount.java,此檔用來驅動mapper 與 reducer,因此選擇 Map/Reduce Driver |
| | 363 | |
| | 364 | |
| | 365 | [[Image(wiki:waue/2009/0617:3-4.png)]] |
| | 366 | ------------ |
| | 367 | |
| | 368 | 2. create |
| | 369 | |
| | 370 | {{{ |
| | 371 | #!sh |
| | 372 | source folder-> 輸入: icas/src |
| | 373 | Package : Sample |
| | 374 | Name -> : WordCount.java |
| | 375 | }}} |
| | 376 | |
| | 377 | ------- |
| | 378 | 3. modify |
| | 379 | |
| | 380 | {{{ |
| | 381 | #!java |
| | 382 | package Sample; |
| | 383 | import org.apache.hadoop.fs.Path; |
| | 384 | import org.apache.hadoop.io.IntWritable; |
| | 385 | import org.apache.hadoop.io.Text; |
| | 386 | import org.apache.hadoop.mapred.FileInputFormat; |
| | 387 | import org.apache.hadoop.mapred.FileOutputFormat; |
| | 388 | import org.apache.hadoop.mapred.JobClient; |
| | 389 | import org.apache.hadoop.mapred.JobConf; |
| | 390 | import org.apache.hadoop.mapred.TextInputFormat; |
| | 391 | import org.apache.hadoop.mapred.TextOutputFormat; |
| | 392 | |
| | 393 | public class WordCount { |
| | 394 | |
| | 395 | public static void main(String[] args) throws Exception { |
| | 396 | JobConf conf = new JobConf(WordCount.class); |
| | 397 | conf.setJobName("wordcount"); |
| | 398 | |
| | 399 | conf.setOutputKeyClass(Text.class); |
| | 400 | conf.setOutputValueClass(IntWritable.class); |
| | 401 | |
| | 402 | conf.setMapperClass(mapper.class); |
| | 403 | conf.setCombinerClass(reducer.class); |
| | 404 | conf.setReducerClass(reducer.class); |
| | 405 | |
| | 406 | conf.setInputFormat(TextInputFormat.class); |
| | 407 | conf.setOutputFormat(TextOutputFormat.class); |
| | 408 | |
| | 409 | FileInputFormat.setInputPaths(conf, new Path("/user/hadooper/input")); |
| | 410 | FileOutputFormat.setOutputPath(conf, new Path("lab5_out2")); |
| | 411 | |
| | 412 | JobClient.runJob(conf); |
| | 413 | } |
| | 414 | } |
| | 415 | }}} |
| | 416 | |
| | 417 | 三個檔完成後並存檔後,整個程式建立完成 |
| | 418 | [[Image(wiki:waue/2009/0617:3-5.png)]] |
| | 419 | |
| | 420 | ------- |
| | 421 | |
| | 422 | * 三個檔都存檔後,可以看到icas專案下的src,bin都有檔案產生,我們用指令來check |
| | 423 | |
| | 424 | {{{ |
| | 425 | $ cd workspace/icas |
| | 426 | $ ls src/Sample/ |
| | 427 | mapper.java reducer.java WordCount.java |
| | 428 | $ ls bin/Sample/ |
| | 429 | mapper.class reducer.class WordCount.class |
| | 430 | }}} |
| | 431 | |
| | 432 | = 四、測試範例程式 = |
| | 433 | |
| | 434 | 在此提供兩種方法來run我們從eclipse 上編譯出的code。 |
| | 435 | |
| | 436 | 方法一是直接在eclipse上用圖形介面操作,參閱 4.1 在eclipse上操作 |
| | 437 | |
| | 438 | 方法二是產生jar檔後搭配自動編譯程式Makefile,參閱4.2 |
| | 439 | |
| | 440 | |
| | 441 | == 4.1 法一:在eclipse上操作 == |
| | 442 | |
| | 443 | * 右鍵點選專案資料夾:icas -> run as -> run on Hadoop |
| | 444 | |
| | 445 | [[Image(wiki:waue/2009/0617:run-on-hadoop.png)]] |
| | 446 | |
| | 447 | |
| | 448 | |