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aws.amazon.com /2 weeks ago

Introducing AWS Glue 6.0 for faster and more cost-effective data integration

AWS Glue 6.0 is now available, lowering AWS Glue pricing by 30%, adding an AWS optimized build of Apache Spark 4.1, and introducing Apache Iceberg V3 capabilities suitable for ente...

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aws.amazon.com /1 month ago

Automate creating AWS Glue Data Catalog views with AWS SDK for data mesh use case

This post shows you how to use the Catalog objects API CreateTable() to programmatically create ATHENA and SPARK dialects using cross-account IAM definer roles, and how to add the...

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aws.amazon.com /2 weeks ago

Upgrade AWS Glue jobs to Glue 6.0 with AI-powered Spark upgrades

Walk through upgrading a PySpark ETL job from AWS Glue 5.1 to AWS Glue 6.0 using the generative AI upgrades for Apache Spark. The upgrade analysis automatically detects incompatibi...

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aws.amazon.com /1 week ago

Build a real-time event pipeline with Spark Real-Time Mode on AWS Glue 6.0

With AWS Glue 6.0, you can build real-time, near-real-time, and batch data pipelines on a single platform. Using a financial market-risk example, learn how to flag high-risk trades...

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dev.to /2 weeks ago

Building a Modern Data Lakehouse on AWS: S3, Iceberg, Glue, Athena, and Lake Formation

The data lakehouse has become the default architecture for analytics on AWS in 2026. It combines the best of both worlds: the low-cost, schema-flexible storage of a data lake (S3)...

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dzone.com /1 month ago

AWS Glue ETL Design Principles for Production PySpark Pipelines

AWS Glue makes it easy to get a PySpark pipeline running quickly. It is significantly harder to build one that stays maintainable as logic grows, performs reliably at scale, and do...

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aws.amazon.com /6 days ago

Query Amazon S3 Tables from Amazon EMR Trino using the Iceberg REST endpoint

Learn how to query Amazon S3 Tables from Trino on Amazon EMR using the Apache Iceberg REST catalog endpoint. This post shows how to deploy the integration with AWS CloudFormation,...

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aws.amazon.com /2 weeks ago

Agentic Data Operations Platform (ADOP): Data engineering into hours

The Agentic Data Operations Platform (ADOP) is a reference architecture on Amazon Bedrock that uses specialized AI agents to automate the full Bronze-to-Silver-to-Gold data pipelin...

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aws.amazon.com /1 week ago

Build with geospatial and variant types in Iceberg v3 on AWS Glue 6.0

AWS Glue 6.0 with Apache Spark 4.1 adds support for Apache Iceberg v3: native geospatial types, nanosecond-precision timestamps, the VARIANT type, and DEFAULT column values. This p...

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aws.amazon.com /1 month ago

Lowering AWS KMS decrypt API costs in EMR Spark jobs

Processing encrypted data in Amazon S3 with Amazon EMR and Apache Spark can drive up AWS KMS decrypt API costs as the number of objects grows. This post shows three techniques to r...

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aws.amazon.com /1 month ago

Zero Copy access to Apache Iceberg tables in Amazon S3 from Salesforce Data 360 using the Iceberg REST endpoint from AWS...

In this post, we demonstrate how AWS and Salesforce customers can access their enterprise data lakes on AWS from Salesforce Data 360 using zero-copy file federation.

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aws.amazon.com /2 weeks ago

Enable cross-cloud analytics with Amazon S3 Tables and Google BigQuery, Part 1: IAM-based access control

Your Google BigQuery users need to query data that lives in Amazon S3 Tables on AWS without copying it across clouds. This post shows how to connect BigQuery to Amazon S3 Tables th...

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aws.amazon.com /1 week ago

Accelerate Apache Spark debugging on Amazon EMR with AWS DevOps Agent

Extend AWS DevOps Agent to investigate Apache Spark failures on Amazon EMR. This post shows how to register the Apache Spark Troubleshooting Agent for Amazon EMR as a custom MCP ca...

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aws.amazon.com /1 month ago

High-performance Remote Shuffle Service on Amazon EMR with Apache Celeborn

In this post, we show how Apache Celeborn resolves this trade-off for Amazon EMR on EKS and Amazon EMR on EC2, improving job reliability while unlocking additional cost savings.

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aws.amazon.com /1 month ago

Multi-cloud lakehouse architecture on AWS for Agentic AI, Part 1: Architecture and best practices

This post focuses on explaining the architecture approach to build the open lakehouse architecture on AWS, unifying the metadata catalog across providers for the AI agents to acces...

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aws.amazon.com /1 month ago

Announcing the Agentic Catalog Experience in Amazon Quick

Amazon Quick introduces the Agentic Catalog Experience, an AI-powered workflow for data curators to discover upstream catalog assets in natural language and auto-create Datasets an...

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aws.amazon.com /1 month ago

Govern Amazon Redshift Data Warehouses Data Across Accounts using Amazon SageMaker Unified Studio

In this post, we show you how to use Amazon SageMaker Unified Studio to implement cross-account data sharing in Amazon Redshift using data mesh principles. We demonstrate how to bu...

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awstip.com /4 weeks ago

Beyond EC2 and S3: 15 AWS AI and Machine Learning Services Every Cloud & DevOps Engineer Should…

When people begin learning AWS, they usually focus on services like EC2, S3, IAM, VPC, RDS, Lambda, CloudFormation, and ECS. These are the…Continue reading on AWS Tip »

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aws.amazon.com /1 week ago

How Boomi Scribe streamlines documentation using AWS

Boomi Scribe is an AI-powered agent on AWS that automatically generates documentation for enterprise integration workflows. Learn how Boomi uses Amazon Bedrock, Amazon SageMaker AI...

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aws.amazon.com /1 week ago

Razor Group’s journey to a modern data lakehouse on AWS

Razor Group, one of Europe's leading ecommerce aggregators managing 250+ brands, migrated from always-on Amazon Redshift clusters to an open lakehouse on Apache Iceberg, Amazon S3...

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aws.amazon.com /1 month ago

Automate Spark Scala migration to 4.x with AWS Spark Upgrade Agent

Learn how to automate Apache Spark 3.x to 4.0 Scala migration on Amazon EMR using the AWS Spark Upgrade Agent. This post covers API deprecations, behavioral changes, build configur...

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aws.amazon.com /2 weeks ago

Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 1: Setting up your Snowflake...

Healthcare, retail, and life sciences teams store large volumes of operational data in Snowflake, but turning it into predictions is hard. In Part 1 of this series, you set up your...

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aws.amazon.com /6 days ago

Building medallion architecture with Iceberg materialized views in Amazon SageMaker

With Apache Iceberg materialized views in Amazon SageMaker, you can build a Bronze, Silver, and Gold medallion architecture as three SQL statements. This declarative approach folds...

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aws.amazon.com /1 month ago

Scaling fine-grained access control for enterprise lakehouse using SageMaker Unified Studio and AWS Lake Formation

As enterprise lakehouses grow to thousands of tables across business domains and regions, fine-grained access control becomes a governance bottleneck. This post shows how to combin...

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