使用ls命令作为shell脚本的输入

gmol1639 于 2021-06-02 发布在 Hadoop

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我的文件在hadoop文件系统中；我需要运行Phoenix批量导入每一个。现在我的shell脚本是这样的：
测试.sh：

HADOOP_CLASSPATH=/usr/lib/hbase/lib/hbase-protocol-1.1.2.jar:/etc/hbase/conf hadoop jar  /usr/lib/phoenix/lib/phoenix/phoenix-1.2.0-client.jar org.apache.phoenix.mapreduce.CsvBulkLoadTool --table NETWORK_HEALTH --input $1

输出 hdfs dfs -ls /tmp/hbase-temp/tmp 是：

-rw-r--r--   2 root hadoop  405003334 2016-04-06 15:28 /tmp/hbase-temp/tmp/nodeHealth20160210-20160211.txt
-rw-r--r--   2 root hadoop 1373330318 2016-04-06 15:28 /tmp/hbase-temp/tmp/nodeHealth20160211-20160212.txt
-rw-r--r--   2 root hadoop 1303613420 2016-04-06 15:28 /tmp/hbase-temp/tmp/nodeHealth20160212-20160213.txt
-rw-r--r--   2 root hadoop 1239413840 2016-04-06 15:28 /tmp/hbase-temp/tmp/nodeHealth20160214-20160215.txt
-rw-r--r--   2 root hadoop 1342998954 2016-04-06 15:28 /tmp/hbase-temp/tmp/nodeHealth20160215-20160216.txt
-rw-r--r--   2 root hadoop 1248737317 2016-04-06 15:29 /tmp/hbase-temp/tmp/nodeHealth20160216-20160217.txt
-rw-r--r--   2 root hadoop 1146305115 2016-04-06 15:29 /tmp/hbase-temp/tmp/nodeHealth20160217-20160218.txt
-rw-r--r--   2 root hadoop 1357281689 2016-04-06 15:29 /tmp/hbase-temp/tmp/nodeHealth20160218-20160219.txt
-rw-r--r--   2 root hadoop 1113842508 2016-04-06 15:29 /tmp/hbase-temp/tmp/nodeHealth20160219-20160220.txt
-rw-r--r--   2 root hadoop 1193977572 2016-04-06 15:29 /tmp/hbase-temp/tmp/nodeHealth20160220-20160221.txt
-rw-r--r--   2 root hadoop 1005786711 2016-04-06 15:30 /tmp/hbase-temp/tmp/nodeHealth20160221-20160222.txt
-rw-r--r--   2 root hadoop 1159168545 2016-04-06 15:30 /tmp/hbase-temp/tmp/nodeHealth20160222-20160223.txt
-rw-r--r--   2 root hadoop 1163804889 2016-04-06 15:30 /tmp/hbase-temp/tmp/nodeHealth20160223-20160224.txt
-rw-r--r--   2 root hadoop 1048950098 2016-04-06 15:30 /tmp/hbase-temp/tmp/nodeHealth20160224-20160225.txt
-rw-r--r--   2 root hadoop 1251527803 2016-04-06 15:30 /tmp/hbase-temp/tmp/nodeHealth20160225-20160226.txt
-rw-r--r--   2 root hadoop 1288661897 2016-04-06 15:31 /tmp/hbase-temp/tmp/nodeHealth20160226-20160227.txt
-rw-r--r--   2 root hadoop 1226833581 2016-04-06 15:31 /tmp/hbase-temp/tmp/nodeHealth20160227-20160228.txt
-rw-r--r--   2 root hadoop 1245110612 2016-04-06 15:31 /tmp/hbase-temp/tmp/nodeHealth20160228-20160229.txt
-rw-r--r--   2 root hadoop 1321007542 2016-04-06 15:31 /tmp/hbase-temp/tmp/nodeHealth20160229-20160230.txt
-rw-r--r--   2 root hadoop 1301010760 2016-04-06 15:31 /tmp/hbase-temp/tmp/nodeHealth20160301-20160302.txt
-rw-r--r--   2 root hadoop 1121192190 2016-04-06 15:32 /tmp/hbase-temp/tmp/nodeHealth20160302-20160303.txt
-rw-r--r--   2 root hadoop 1296388727 2016-04-06 15:32 /tmp/hbase-temp/tmp/nodeHealth20160303-20160304.txt
-rw-r--r--   2 root hadoop 1280975648 2016-04-06 15:32 /tmp/hbase-temp/tmp/nodeHealth20160304-20160305.txt
-rw-r--r--   2 root hadoop 1264795738 2016-04-06 15:32 /tmp/hbase-temp/tmp/nodeHealth20160305-20160306.txt
-rw-r--r--   2 root hadoop 1248570281 2016-04-06 15:32 /tmp/hbase-temp/tmp/nodeHealth20160306-20160307.txt
-rw-r--r--   2 root hadoop 1335704328 2016-04-06 15:33 /tmp/hbase-temp/tmp/nodeHealth20160307-20160308.txt
-rw-r--r--   2 root hadoop 1246153114 2016-04-06 15:33 /tmp/hbase-temp/tmp/nodeHealth20160308-20160309.txt
-rw-r--r--   2 root hadoop 1251409839 2016-04-06 15:33 /tmp/hbase-temp/tmp/nodeHealth20160309-20160310.txt
-rw-r--r--   2 root hadoop 1120439077 2016-04-06 15:33 /tmp/hbase-temp/tmp/nodeHealth20160310-20160311.txt
-rw-r--r--   2 root hadoop 1151595336 2016-04-06 15:33 /tmp/hbase-temp/tmp/nodeHealth20160311-20160312.txt
-rw-r--r--   2 root hadoop 1304537932 2016-04-06 15:34 /tmp/hbase-temp/tmp/nodeHealth20160312-20160313.txt
-rw-r--r--   2 root hadoop 1065020972 2016-04-06 15:34 /tmp/hbase-temp/tmp/nodeHealth20160313-20160314.txt
-rw-r--r--   2 root hadoop 1237905144 2016-04-06 15:34 /tmp/hbase-temp/tmp/nodeHealth20160314-20160315.txt
-rw-r--r--   2 root hadoop 1038185956 2016-04-06 15:34 /tmp/hbase-temp/tmp/nodeHealth20160315-20160316.txt
-rw-r--r--   2 root hadoop 1216670016 2016-04-06 15:35 /tmp/hbase-temp/tmp/nodeHealth20160316-20160317.txt
-rw-r--r--   2 root hadoop 1139180542 2016-04-06 15:35 /tmp/hbase-temp/tmp/nodeHealth20160317-20160318.txt
-rw-r--r--   2 root hadoop 1052672363 2016-04-06 15:35 /tmp/hbase-temp/tmp/nodeHealth20160318-20160319.txt
-rw-r--r--   2 root hadoop  892045686 2016-04-06 15:35 /tmp/hbase-temp/tmp/nodeHealth20160319-20160320.txt

当我在下面运行命令时，它只对第一行起作用：
hdfs dfs-ls/tmp/hbase temp/tmp | awk'{print$8}'| xargs sh test.sh
如何修复它为ls输出中的每个文件运行test.sh？

hadoop linux shell bash awk

来源：https://stackoverflow.com/questions/36463236/use-ls-command-as-input-for-shell-script

2条答案

按热度按时间

kadbb4591#

添加 -n 1 听从你的命令

hdfs dfs -ls /tmp/hbase-temp/tmp | awk '{print $8}' | xargs -n 1 sh test.sh

以下是手册页文档：

-n number
         Set the maximum number of arguments taken from standard input for each invocation of utility.  An invocation of utility will use less than number standard input arguments if the number of bytes accu-
         mulated (see the -s option) exceeds the specified size or there are fewer than number arguments remaining for the last invocation of utility.  The current default value for number is 5000.

我有 echo $1 在我的test.sh文件和input.txt中的3个样本行中。试验结果为：

$awk '{print $8}' input.txt |xargs  -n1 sh test.sh                                                                                                                                 Wed  6 Apr 16:31:14 2016
/tmp/hbase-temp/tmp/nodeHealth20160210-20160211.txt
/tmp/hbase-temp/tmp/nodeHealth20160211-20160212.txt
/tmp/hbase-temp/tmp/nodeHealth20160212-20160213.txt

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62o28rlo2#

您可以使用进程替换：

while read -r _ _ _ _ _ _ _ var8 _; do
   bash ./test.sh "$var8"
done < <(hdfs dfs -ls /tmp/hbase-temp/tmp)

如果你必须使用 xargs 然后使用 -I 选项：

hdfs dfs -ls /tmp/hbase-temp/tmp | awk '{print $8}' | xargs -I {} sh test.sh '{}'`

赞(0）回复(0）举报 2021-06-02

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使用ls命令作为shell脚本的输入

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