Version 5 (modified by jazz, 12 years ago) (diff) |
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◢ <實作九> | <回課程大綱> ▲ | <實作十一> ◣
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實作十 Lab10
HDFS、MapReduce 與 Hadoop Streaming 觀念驗證
Running Hadoop Streaming with HDFS and MapReduce
Running Hadoop Streaming with HDFS and MapReduce
準備輸入資料集 Input Dataset
- 首先準備輸入,包含兩部份:(1) 供 Velvet 計算的 *.fa 檔案,這裡為了方便示範起見,採用 test_long.fa 當範本,並複製 99 份不同檔名,當輸入 (2) 供 Mapper 運算的輸入檔案(內含 HDFS 的檔名路徑)
~$ cp /usr/share/doc/velvet-example/examples/data/test_long.fa.gz . ~$ gunzip test_long.fa.gz ~$ for ((i=1;i<100;i++)); do hadoop fs -put test_long.fa input-$i.fa; done ~$ for ((i=1;i<20;i++)); do echo /user/$(whoami)/input-$i.fa; done > split-01.txt ~$ for ((i=20;i<40;i++)); do echo /user/$(whoami)/input-$i.fa; done > split-02.txt ~$ for ((i=40;i<60;i++)); do echo /user/$(whoami)/input-$i.fa; done > split-03.txt ~$ for ((i=60;i<80;i++)); do echo /user/$(whoami)/input-$i.fa; done > split-04.txt ~$ for ((i=80;i<100;i++)); do echo /user/$(whoami)/input-$i.fa; done > split-05.txt ~$ hadoop fs -mkdir lab10_input ~$ hadoop fs -put split-0* lab10_input
- 檢查輸入檔案
~$ hadoop fs -ls ~$ hadoop fs -ls lab10_input
觀察 Hadoop Streaming 執行身份與工作目錄
- 撰寫 testmapper.sh
#!/bin/bash id="h998" mkdir -p /tmp/$id host=`hostname` pwd=`pwd` uid=`whoami` while read line; do input=$line filename=`basename $input` echo "$uid@$host:$pwd> hadoop fs -get $input /tmp/$id/$filename" echo "$uid@$host:$pwd> velveth output-$filename 17 -fasta -short /tmp/$id/$filename" echo "$uid@$host:$pwd> hadoop fs -put output-$filename ." done rm -rf /tmp/$id
- 接著,讓我們在本地端先驗證一下 testmapper.sh 的運作
~$ head -n 2 split-01.txt > split-00.txt ~$ cat > testmapper.sh << EOF #!/bin/bash id="`whoami`" mkdir -p /tmp/\$id host=\`hostname\` pwd=\`pwd\` uid=\`whoami\` while read line; do input=\$line filename=\`basename \$input\` echo "\$uid@\$host:\$pwd> hadoop fs -get \$input /tmp/\$id/\$filename" echo "\$uid@\$host:\$pwd> velveth output-\$filename 17 -fasta -short /tmp/\$id/\$filename" echo "\$uid@\$host:\$pwd> hadoop fs -put output-\$filename ." done rm -rf /tmp/\$id EOF ~$ chmod a+x testmapper.sh ~$ cat sample-00.txt | ./testmapper.sh h998@hadoop:/home/h998> hadoop fs -get /user/h998/input-1.fa /tmp/h998/input-1.fa h998@hadoop:/home/h998> velveth output-input-1.fa 17 -fasta -short /tmp/h998/input-1.fa h998@hadoop:/home/h998> hadoop fs -put output-input-1.fa . h998@hadoop:/home/h998> hadoop fs -get /user/h998/input-2.fa /tmp/h998/input-2.fa
- 讓我們用 Hadoop Streaming 的方式來執行 testmapper.sh
~$ hadoop jar hadoop-streaming.jar -input lab10_input -output lab10_out1 -mapper testmapper.sh -file testmapper.sh
- 觀察 lab10_out1 的結果,看與本機執行有何不同呢?
~$ hadoop fs -cat /user/$(whoami)/lab10_out1/part-00000 | head hadoop@hadoop104:/var/lib/hadoop/cache/hadoop/mapred/local/taskTracker/jobcache/job_201106041247_1820/attempt_201106041247_1820_m_000002_0/work> hadoop fs -get /user/h998/input-60.fa /tmp/h998/input-60.fa hadoop@hadoop104:/var/lib/hadoop/cache/hadoop/mapred/local/taskTracker/jobcache/job_201106041247_1820/attempt_201106041247_1820_m_000002_0/work> hadoop fs -get /user/h998/input-61.fa /tmp/h998/input-61.fa hadoop@hadoop104:/var/lib/hadoop/cache/hadoop/mapred/local/taskTracker/jobcache/job_201106041247_1820/attempt_201106041247_1820_m_000002_0/work> hadoop fs -get /user/h998/input-62.fa /tmp/h998/input-62.fa
實作透過 Hadoop Streaming 執行 99 組 velvet 運算
- 撰寫 mapper.sh
#!/bin/bash id="h998" mkdir -p /tmp/$id host=`hostname` pwd=`pwd` uid=`whoami` while read line; do input=$line filename=`basename $input` echo "$uid@$host> hadoop fs -get $input /tmp/$id/$filename" hadoop fs -get $input /tmp/$id/$filename echo "$uid@$host> velveth output-$filename 17 -fasta -short /tmp/$id/$filename" velveth output-$filename 17 -fasta -short /tmp/$id/$filename echo "$uid@$host> hadoop fs -put output-$filename /user/$id/." hadoop fs -put output-$filename /user/$id/. hadoop fs -chown $id /user/$id/output-$filename done rm -rf /tmp/$id
- 於本機測試 mapper.sh
~$ cat > mapper.sh << EOF #!/bin/bash id="`whoami`" mkdir -p /tmp/\$id host=\`hostname\` pwd=\`pwd\` uid=\`whoami\` while read line; do input=\$line filename=\`basename \$input\` echo "\$uid@\$host> hadoop fs -get \$input /tmp/\$id/\$filename" hadoop fs -get \$input /tmp/\$id/\$filename echo "\$uid@\$host> velveth output-\$filename 17 -fasta -short /tmp/\$id/\$filename" velveth output-\$filename 17 -fasta -short /tmp/\$id/\$filename echo "\$uid@\$host> hadoop fs -put output-\$filename /user/\$id/." hadoop fs -put output-\$filename /user/\$id/. hadoop fs -chown \$id /user/\$id/output-\$filename done rm -rf /tmp/\$id EOF ~$ chmod a+x mapper.sh ~$ cat sample-00.txt | ./mapper.sh ~$ hadoop fs -rmr output-* ~$ rm -rf output-sample-*
- 接著用 hadoop streaming 來執行
~$ hadoop jar hadoop-streaming.jar -input lab10_input -output lab10_out2 -mapper mapper.sh -file mapper.sh