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Best Practices for Running Spark with Scylla

Eyal Gutkind, Head of Solution Architects, ScyllaDB

Spark and Scylla deployments are a common theme. Executing analytics workloads on transactional data provide insights to the business team. ETL workloads using Spark and Scylla are common too. We cover different workloads we have seen in practice and how we helped optimize both Spark and Scylla deployments to support a smooth and efficient workflow. Best practices we discuss include correctly sizing the Spark and Scylla nodes, tuning partitions sizes, setting connectors concurrency and Spark retry policies. In addition, we will cover ways to use Spark and Scylla in migrations from different data models.

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