经过很多错误的转折后，我发现，至少在弹性映射上减少了Hadoop的实现，Pig似乎忽略了CLASSPATH环境变量.相反，我发现我可以使用HADOOP_CLASSPATH变量来控制类路径.

After quite a few wrong turns, I found that, at least on the elastic map reduce implementation of Hadoop, Pig seems to ignore the CLASSPATH environment variable. I found instead that I could control the class path using the HADOOP_CLASSPATH variable instead.

一旦我意识到这一点，就可以很容易地设置要使用Python UDFS的内容:

Once I made that realization, it was fairly easy to get things setup to use Python UDFS:

• 安装Jython
  • sudo apt-get install jython -y -qq
  • Install Jython
    • sudo apt-get install jython -y -qq
    • export HADOOP_CLASSPATH=/usr/share/java/jython.jar:/usr/share/maven-repo/org/antlr/antlr-runtime/3.2/antlr-runtime-3.2.jar
      • jython.jar确保Hadoop可以找到PyException类
      • antlr-runtime-3.2.jar确保Hadoop可以找到CharStream类
      • sudo mkdir /usr/share/java/cachedir/
      • sudo chmod a+rw /usr/share/java/cachedir
      • sudo mkdir /usr/share/java/cachedir/
      • sudo chmod a+rw /usr/share/java/cachedir

      我应该指出，这似乎与我在寻找解决此问题的方法时发现的其他建议直接矛盾:

      I should point out that this seems to directly contradict other advice I found while searching for solutions to this problem:

      • 设置CLASSPATH和PIG_CLASSPATH环境变量似乎没有任何作用.
      • 包含UDF的.py文件不需要包含在HADOOP_CLASSPATH环境变量中.
      • Pig register语句中使用的.py文件的路径可以是相对的，也可以是绝对的，这似乎无关紧要.
      • Setting the CLASSPATH and PIG_CLASSPATH environment variables doesn't seem to do anything.
      • The .py file containing the UDF does not need to be included in the HADOOP_CLASSPATH environment variable.
      • The path to the .py file used in the Pig register statement may be relative or absolute, it doesn't seem to matter.