run-tpcds-benchmark

To run the TPC-DS benchmark, you can invoke the skill to automate execution and compare Apache Spark and Quanton on Kubernetes. It interactively collects configurations, provides live progress updates, and generates a performance comparison report.

Interactive configuration for TPC-DS benchmarks works by asking you for input parameters like scale factor and executor setup. The skill uses these inputs to configure Apache Spark and Quanton before executing the benchmark on your Kubernetes cluster.

Yes, you need kubectl and minikube to benchmark Quanton against Apache Spark. These dependencies are required to provision the Kubernetes environment and interact with the necessary Spark and Quanton APIs for test execution.

You can get live progress updates while running TPC-DS benchmark tests. The skill keeps you informed about the benchmark progress in real-time as it interacts with Kubernetes, Spark, and Quanton APIs to execute the workload.

The best way to analyze Apache Spark vs Quanton performance results is by using the skill's automated results analysis. It generates and presents a comparison of the TPC-DS benchmark results in an easily understandable format after execution completes.

Using Kubernetes for TPC-DS benchmarking provides a standardized environment to fairly compare Apache Spark and Quanton. The skill leverages Kubernetes APIs to orchestrate the benchmark, ensuring consistent executor configuration and scalable test execution.