| | 1 | [[PageOutline]] |
| | 2 | |
| | 3 | ◢ <[wiki:TCCA140822/Lab5 實作五]> | <[wiki:TCCA140822 回課程大綱]> ▲ | <[wiki:TCCA140822/Lab7 實作七]> ◣ |
| | 4 | |
| | 5 | = 實作六 Lab 6 = |
| | 6 | |
| | 7 | {{{ |
| | 8 | #!html |
| | 9 | <div style="text-align: center;"><big style="font-weight: bold;"><big>在完全分散模式執行 MapReduce 基本運算<br/>Running MapReduce in Full Distributed Mode by Examples</big></big></div> |
| | 10 | }}} |
| | 11 | {{{ |
| | 12 | #!text |
| | 13 | 以下練習,請連線至 hadoop.3du.me 操作。底下的 userXX 等於您的用戶名稱。 |
| | 14 | }}} |
| | 15 | |
| | 16 | == Sample 1 : WordCount == |
| | 17 | |
| | 18 | * 如名稱,WordCount會對所有的字作字數統計,並且從a-z作排列[[BR]]WordCount example will count each word shown in documents and sorting from a to z. |
| | 19 | {{{ |
| | 20 | ~$ hadoop fs -put /opt/hadoop/conf lab5_input |
| | 21 | ~$ hadoop fs -rmr lab5_out2 ## 這行是預防上次有執行過這個範例的防呆步驟 |
| | 22 | ~$ hadoop jar hadoop-examples.jar wordcount lab5_input lab5_out2 |
| | 23 | }}} |
| | 24 | |
| | 25 | * 連線到 http://hadoop.3du.me:50030 查詢您剛剛提交的任務(Job)狀態 |
| | 26 | |
| | 27 | * 檢查輸出結果的方法同之前方法[[BR]]Let's check the computed result of '''wordcount''' from HDFS : |
| | 28 | {{{ |
| | 29 | $ hadoop fs -ls lab5_out2 |
| | 30 | $ hadoop fs -cat lab5_out2/part-r-00000 |
| | 31 | }}} |
| | 32 | * 結果如下[[BR]]You should see results like this: |
| | 33 | {{{ |
| | 34 | "". 4 |
| | 35 | "*" 9 |
| | 36 | "127.0.0.1" 3 |
| | 37 | "AS 2 |
| | 38 | "License"); 2 |
| | 39 | "_logs/history/" 1 |
| | 40 | "alice,bob 9 |
| | 41 | |
| | 42 | ( ... skip ... ) |
| | 43 | }}} |
| | 44 | |
| | 45 | == Sample 2: grep == |
| | 46 | |
| | 47 | * 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[[BR]]grep is a command to extract specific characters in documents. In hadoop examples, you can use this command to extract strings match the regular expression and count for matched strings. |
| | 48 | {{{ |
| | 49 | $ hadoop fs -ls lab5_input |
| | 50 | $ hadoop jar hadoop-examples.jar grep lab5_input lab5_out3 'dfs[a-z.]+' |
| | 51 | }}} |
| | 52 | * 運作的畫面如下:[[BR]]You should see procedure like this: |
| | 53 | {{{ |
| | 54 | 11/04/19 10:00:20 INFO mapred.FileInputFormat: Total input paths to process : 25 |
| | 55 | 11/04/19 10:00:20 INFO mapred.JobClient: Running job: job_201104120101_0645 |
| | 56 | 11/04/19 10:00:21 INFO mapred.JobClient: map 0% reduce 0% |
| | 57 | ( ... skip ... ) |
| | 58 | }}} |
| | 59 | * 接著查看結果[[BR]]Let's check the computed result of '''grep''' from HDFS : |
| | 60 | {{{ |
| | 61 | $ hadoop fs -ls lab5_out3 |
| | 62 | Found 2 items |
| | 63 | drwx------ - hXXXX supergroup 0 2011-04-19 10:00 /user/hXXXX/lab5_out1/_logs |
| | 64 | -rw-r--r-- 2 hXXXX supergroup 1146 2011-04-19 10:00 /user/hXXXX/lab5_out1/part-00000 |
| | 65 | $ hadoop fs -cat lab5_out3/part-00000 |
| | 66 | }}} |
| | 67 | * 結果如下[[BR]]You should see results like this: |
| | 68 | {{{ |
| | 69 | 4 dfs.permissions |
| | 70 | 4 dfs.replication |
| | 71 | 4 dfs.name.dir |
| | 72 | 3 dfs.namenode.decommission.interval. |
| | 73 | 3 dfs.namenode.decommission.nodes.per.interval |
| | 74 | 3 dfs. |
| | 75 | ( ... skip ... ) |
| | 76 | }}} |
| | 77 | |
| | 78 | == More Examples == |
| | 79 | |
| | 80 | 可執行的指令一覽表:[[BR]]Here is a list of hadoop examples : |
| | 81 | |
| | 82 | || aggregatewordcount || An Aggregate based map/reduce program that counts the words in the input files. || |
| | 83 | || aggregatewordhist || An Aggregate based map/reduce program that computes the histogram of the words in the input files. || |
| | 84 | || grep || A map/reduce program that counts the matches of a regex in the input. || |
| | 85 | || join || A job that effects a join over sorted, equally partitioned datasets || |
| | 86 | || multifilewc || A job that counts words from several files. || |
| | 87 | || pentomino || A map/reduce tile laying program to find solutions to pentomino problems. || |
| | 88 | || pi || A map/reduce program that estimates Pi using monte-carlo method. || |
| | 89 | || randomtextwriter || A map/reduce program that writes 10GB of random textual data per node. || |
| | 90 | || randomwriter || A map/reduce program that writes 10GB of random data per node. || |
| | 91 | || sleep || A job that sleeps at each map and reduce task. || |
| | 92 | || sort || A map/reduce program that sorts the data written by the random writer. || |
| | 93 | || sudoku || A sudoku solver. || |
| | 94 | || wordcount || A map/reduce program that counts the words in the input files. || |
| | 95 | |
| | 96 | You could find more detail at [http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/examples/package-summary.html org.apache.hadoop.examples] |