core

Qualification and Profiling tools

The Qualification tool is used to look at a set of applications to determine if the RAPIDS Accelerator for Apache Spark might be a good fit for those applications.

The Profiling tool generates information which can be used for debugging and profiling applications. Information such as Spark version, executor information, properties and so on. This runs on either CPU or GPU generated event logs.

Please refer to Qualification tool documentation and Profiling tool documentation for more details on how to use the tools.

Build

We use Maven for the build. Simply run as below command:

mvn clean package

After a successful build, the jar of 'rapids-4-spark-tools_2.12-*-SNAPSHOT.jar' will be in 'target/' directory.
This will build the plugin for a single version of Spark. By default, this is Apache Spark 3.5.0.

For development purpose, you may need to run the tests against different spark versions. To run the tests against a specific Spark version, you can use the -Dbuildver=XXX command line option.
For instance to build Spark 3.5.1 you would use:

mvn -Dbuildver=351 clean package

Run mvn help:all-profiles to list supported Spark versions.

Running tests

The unit tests are run by default when building unless they are explicitly skipped by specifying -DskipTests.

To run an individual test the -Dsuites option can be specified:

mvn test -Dsuites=com.nvidia.spark.rapids.tool.qualification.QualificationSuite

Setting up an Integrated Development Environment

Before proceeding with importing spark-rapids-tools into IDEA or switching to a different Spark release profile, execute the install phase with the corresponding buildver, e.g. for Spark 3.5.0:

Manual Maven Install for a target Spark build

 mvn clean install -Dbuildver=350 -Dmaven.scaladoc.skip -DskipTests

Importing the project

To start working with the project in IDEA is as easy as importing the project as a Maven project. Select the profile used in the mvn command above, e.g. spark350 for Spark 3.5.0.

The tools project follows the same coding style guidelines as the Apache Spark project. For IntelliJ IDEA users, an example idea-code-style-settings.xml is available in the scripts subdirectory of the root project folder.