hadoop mapreduce開發實踐之輸出數據壓縮

1、hadoop 輸出數據壓縮

1.1、爲什麼要壓縮？

• 輸出數據較大時，使用hadoop提供的壓縮機制對數據進行壓縮，可以指定壓縮的方式。減少網絡傳輸帶寬和存儲的消耗；
• 可以對map的輸出進行壓縮（map輸出到reduce輸入的過程，可以shuffle過程中網絡傳輸的數據量）
• 可以對reduce的輸出結果進行壓縮（最終保存到hdfs上的數據，主要是減少佔用HDFS存儲）

mapper和reduce程序都不需要更改，只需要在streaming程序運行中指定參數即可；

-jobconf  "mapred.compress.map.output=true" \
-jobconf  "mapred.map.output.compression.codec=org.apache.hadoop.io.compress.GzipCodec" \
-jobconf  "mapred.output.compress=true" \
-jobconf  "mapred.output.compression.codec=org.apache.hadoop.io.compress.GzipCodec" \

1.2、 run_streaming程序

#!/bin/bash

HADOOP_CMD="/home/hadoop/app/hadoop/hadoop-2.6.0-cdh5.13.0/bin/hadoop"
STREAM_JAR_PATH="/home/hadoop/app/hadoop/hadoop-2.6.0-cdh5.13.0/share/hadoop/tools/lib/hadoop-streaming-2.6.0-cdh5.13.0.jar"

INPUT_FILE_PATH="/input/The_Man_of_Property"
OUTPUT_FILE_PATH="/output/wordcount/CacheArchiveCompressFile"

$HADOOP_CMD fs -rmr -skipTrash $OUTPUT_FILE_PATH

$HADOOP_CMD jar $STREAM_JAR_PATH \
                -input $INPUT_FILE_PATH \
                -output $OUTPUT_FILE_PATH \
                -jobconf "mapred.job.name=wordcount_wordwhite_cacheArchivefile_demo" \
                -jobconf  "mapred.compress.map.output=true" \
                -jobconf  "mapred.map.output.compression.codec=org.apache.hadoop.io.compress.GzipCodec" \
                -jobconf  "mapred.output.compress=true" \
                -jobconf  "mapred.output.compression.codec=org.apache.hadoop.io.compress.GzipCodec" \
                -mapper "python mapper.py WHF.gz" \
                -reducer "python reducer.py" \
                -cacheArchive "hdfs://localhost:9000/input/cachefile/wordwhite.tar.gz#WHF.gz" \
                -file "./mapper.py" \
                -file "./reducer.py"

1.3、 執行程序

$ chmod +x run_streaming_compress.sh
$ ./run_streaming_compress.sh
... 中間輸出省略 ...
18/02/02 10:51:50 INFO streaming.StreamJob: Output directory: /output/wordcount/CacheArchiveCompressFile

1.4、 查看結果

$ hadoop fs -ls /output/wordcount/CacheArchiveCompressFile
Found 2 items
-rw-r--r--   1 hadoop supergroup          0 2018-02-02 10:51 /output/wordcount/CacheArchiveCompressFile/_SUCCESS
-rw-r--r--   1 hadoop supergroup         81 2018-02-02 10:51 /output/wordcount/CacheArchiveCompressFile/part-00000.gz
$ hadoop fs -get /output/wordcount/CacheArchiveCompressFile/part-00000.gz ./
$ gunzip part-00000.gz 
$ cat part-00000 
and 2573
had 1526
have    350
in  1694
or  253
the 5144
this    412
to  2782

2、hadoop streaming 語法參考

• http://blog.51cto.com/balich/2065419