spark-rapids/user-guide/24.02/partials/tools-setup-onprem-with-hdfs.html

No more steps required to run the tools on on-prmises environment including standalone/local machines.

The tools CLI depends on Python implementation of PyArrow which relies on some environment variables to bind with HDFS:

• HADOOP_HOME: the root of your installed Hadoop distribution. Often has “lib/native/libhdfs.so”.

• JAVA_HOME: the location of your Java SDK installation.

• ARROW_LIBHDFS_DIR (optional): explicit location of “libhdfs.so” if it is installed somewhere other than $HADOOP_HOME/lib/native.

• Add the Hadoop jars to your CLASSPATH.

  Linux

  export CLASSPATH=`$HADOOP_HOME/bin/hadoop classpath --glob`
  

  Windows

  %HADOOP_HOME%/bin/hadoop classpath --glob > %CLASSPATH%
  

For more information on HDFS requirements, refer to the PyArrow HDFS documentation