Compiling the tools jar

See instructions here: https://github.com/NVIDIA/spark-rapids-tools/tree/main/core#build

If any input is a S3 file path or directory path, 2 extra steps are needed to access S3 in Spark:

1. Download the matched jars based on the Hadoop version:

   • hadoop-aws-<version>.jar

   • aws-java-sdk-<version>.jar

2. Take Hadoop 2.7.4 for example, we can download and include below jars in the ‘–jars’ option to spark-shell or spark-submit: hadoop-aws-2.7.4.jar and aws-java-sdk-1.7.4.jar

3. In $SPARK_HOME/conf, create hdfs-site.xml with below AWS S3 keys inside:

            

            
<?xml version="1.0"?>
<configuration>
<property>
  <name>fs.s3a.access.key</name>
  <value>xxx</value>
</property>
<property>
  <name>fs.s3a.secret.key</name>
  <value>xxx</value>
</property>
</configuration>
        

Please refer to this doc on more options about integrating hadoop-aws module with S3.