hadoop mapreduce开发实践之输出数据压缩

Posted 2020-10-23

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1、hadoop 输出数据压缩

1.1、为什么要压缩？

输出数据较大时，使用hadoop提供的压缩机制对数据进行压缩，可以指定压缩的方式。减少网络传输带宽和存储的消耗；
可以对map的输出进行压缩（map输出到reduce输入的过程，可以shuffle过程中网络传输的数据量）
可以对reduce的输出结果进行压缩（最终保存到hdfs上的数据，主要是减少占用HDFS存储）

mapper和reduce程序都不需要更改，只需要在streaming程序运行中指定参数即可；

-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、执行程序

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

1.4、查看结果

$ 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