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Scaling Data Analytics Workloads on Databricks
Imagine an organization with thousands of users who want to run data analytics workloads. These users shouldn’t have to worry about provisioning instances from a cloud provider, deploying a runtime processing engine, scaling resources based on utilization, or ensuring their data is secure. Nor should the organization’s system administrators.
In this talk we will highlight some of the exciting problems we’re working on at Databricks in order to meet the demands of organizations that are analyzing data at scale. In particular, data engineers attending this session will walk away with learning how we:
Manage a typical query lifetime through the Databricks software stack
Dynamically allocate resources to satisfy the elastic demands of a single cluster
Isolate the data and the generated state within a large organization with multiple clusters