Run Apache Spark SQL workloads on Azure Cobalt 100 Arm64 using Gluten and Velox for accelerated analytics
Introduction
Understand Azure Cobalt 100 and Apache Spark with Gluten and Velox
Create an Azure Cobalt 100 Arm64 virtual machine
Deploy Apache Spark SQL with Gluten and Velox on Arm64
Run TPC-DS Benchmark on Spark with Gluten and Velox on Arm64
Next Steps

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About this Learning Path

Skill level:  Advanced
Reading time:  2 hrs
Last updated:  04 May 2026
Skill level:
  Advanced
Reading time:
  2 hrs
Last updated:
  04 May 2026
Author:Pareena Verma, Arm
Arm IP:Neoverse
Tags: Performance and Architecture Microsoft Azure Linux Apache Spark Hadoop Hive Gluten Velox
Author:
  • Pareena Verma, Arm
Arm IP:
Neoverse
Tags:
Performance and Architecture Microsoft Azure Linux Apache Spark Hadoop Hive Gluten Velox

Who is this for?

This is an advanced topic for data engineers, platform engineers, and developers who want to build and optimize high-performance Spark SQL workloads using native execution engines on Arm-based cloud environments.

What will you learn?

Upon completion of this Learning Path, you will be able to:

  • Install and configure Hadoop, Spark, and Hive on Azure Cobalt 100 Arm64 virtual machines
  • Build and integrate Gluten with the Velox backend for native query execution
  • Configure Spark SQL for columnar and vectorized execution
  • Generate and load TPC-DS datasets for benchmarking
  • Run Spark SQL workloads and compare performance between vanilla Spark and Gluten with Velox

Prerequisites

Before starting, you will need the following:

  • A Microsoft Azure account with access to Cobalt 100 based instances (Dpsv6)
  • Basic understanding of distributed systems and Apache Spark
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