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Kartik Panjabi

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Articles

Introducing AWS Glue 5.1 for Apache Spark | Amazon Web Services

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By Chiho Sugimoto, Kartik Panjabi, Peter Manastyrny, Noritaka Sekiyama
| Amazon Web Services
AWS Glue is a serverless, scalable data integration service that makes it simple to discover, prepare, move, and integrate data from multiple sources. AWS recently announced Glue 5.1, a new version of AWS Glue that accelerates data integration workloads in AWS. AWS Glue 5.1 upgrades the Spark engines to Apache Spark 3.5.6, giving you newer Spark release along with the newer dependent libraries so you can develop, run, and scale your data integration workloads and get insights faster.
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Introducing MCP Server for Apache Spark History Server for AI-powered debugging and optimization | Amazon Web Services

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By Andrew Kim, Mohit Saxena, Kartik Panjabi, Manabu McCloskey
| Amazon Web Services
Organizations running Apache Spark workloads, whether on Amazon EMR, AWS Glue, Amazon Elastic Kubernetes Service (Amazon EKS), or self-managed clusters, invest countless engineering hours in performance troubleshooting and optimization.
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Enforce table level access control on data lake tables using AWS Glue 5.0 with AWS Lake Formation | Amazon Web Services

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By Layth Yassin, Matt Su, Noritaka Sekiyama, Kartik Panjabi
| Amazon Web Services
AWS Glue 5.0 now supports Full-Table Access (FTA) control in Apache Spark based on your policies defined in AWS Lake Formation. This new feature enables read and write operations from your AWS Glue 5.0 Spark jobs on Lake Formation registered tables when the job role has full table access. This level of control is ideal for use cases that need to comply with security regulations at the table level.
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