# Getting started with Apache Spark on Google Axion C4A (Arm Neoverse-V2)

## In this learning path

- [Introduction](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark-on-gcp/)
- [Getting started with Apache Spark on Google Axion C4A (Arm Neoverse-V2)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark-on-gcp/background/)
- [How to create a Google Axion C4A Arm virtual machine on GCP](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark-on-gcp/instance/)
- [How to deploy Apache Spark on Google Axion C4A Arm virtual machines](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark-on-gcp/spark-deployment/)
- [Apache Spark baseline testing on Google Axion C4A Arm VM](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark-on-gcp/baseline/)
- [Apache Spark performance benchmarks on Arm64 and x86_64 in Google Cloud](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark-on-gcp/benchmarking/)
- [Next Steps](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark-on-gcp/_next-steps/)

## Google Axion C4A Arm instances in Google Cloud
Google Axion C4A is a family of Arm-based virtual machines built on Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high-performance and energy-efficient computing, these virtual machines offer strong performance for modern cloud workloads such as CI/CD pipelines, microservices, media processing, and general-purpose applications.

The C4A series provides a cost-effective alternative to x86 virtual machines while leveraging the scalability and performance benefits of the Arm architecture in Google Cloud.

To learn more about Google Axion, refer to the [Introducing Google Axion Processors, our new Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu) blog.

## Apache Spark for big data processing on Arm
Apache Spark is an open-source, distributed computing system designed for fast and general-purpose big data processing.

It provides high-level APIs in Java, Scala, Python, and R, and supports in-memory computation for increased performance.

Spark is widely used for large-scale data analytics, machine learning, and real-time data processing. Learn more from the [Apache Spark official website](https://spark.apache.org/) and its [detailed official documentation](https://spark.apache.org/docs/latest/).