Amazon SageMaker now supports Amazon Athena for Apache Spark, bringing a new notebook experience and fast serverless Spark experience together within a unified workspace. Now, data engineers, analysts, and data scientists can easily query data, run Python code, develop jobs, train models, visualize data, and work with AI from one place, with no infrastructure to manage and second-level billing.
Athena for Apache Spark scales in seconds to support any workload, from interactive queries to petabyte-scale jobs. Athena for Apache Spark now runs on Spark 3.5.6, the same high-performance Spark engine available across AWS, optimized for open table formats including Apache Iceberg and Delta Lake. It brings you new debugging features, real-time monitoring in the Spark UI, and secure interactive cluster communication through Spark Connect. As you use these capabilities to work with your data, Athena for Spark now enforces table-level access controls defined in AWS Lake Formation.
Athena for Apache Spark is now available with Amazon SageMaker notebooks in US East (Ohio), US East (N. Virginia), US West (Oregon), Europe (Ireland), Europe (Frankfurt), Asia Pacific (Mumbai), Asia Pacific (Tokyo), Asia Pacific (Singapore), and Asia Pacific (Sydney). To learn more, visit Apache Spark engine version 3.5, read the AWS News Blog or visit Amazon SageMaker documentation. Visit the Getting Started guide to try it from Amazon SageMaker notebooks.
Categories: marketing:marchitecture/analytics,general:products/amazon-sagemaker
Source: Amazon Web Services
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