This session dives into the world of on-demand Apache Spark on Google Cloud. We explore its native integration with BigQuery, its new capabilities and the benefits of using Spark for AI and machine learning (ML) workloads. We’ll discuss why Spark is a good choice for large-scale data processing, distributed training, and distributed inferencing. We’ll learn from Trivago about how they leveraged the Spark and BigQuery together to simplify their AI and ML workflows.

This session explores new features of Serverless Spark and its integration with BigQuery. Discover how to harness the strengths of BigQuery with generative AI and open-source tools for flexible, powerful data processing and AI model development. With Spark in BigQuery, you'll benefit from:

Rapid Spark development in BigQuery's secure, scalable environment Flexible data processing: Choose local execution, Spark, or BigQuery *Streamlined Spark workflows with BigQuery's workflow orchestration

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