AWS Big Data Blog

Category: Analytics

Introducing enhanced support for tagging, cross-account access, and network security in AWS Glue interactive sessions

AWS Glue interactive sessions allow you to run interactive AWS Glue workloads on demand, which enables rapid development by issuing blocks of code on a cluster and getting prompt results. This technology is enabled by the use of notebook IDEs, such as the AWS Glue Studio notebook, Amazon SageMaker Studio, or your own Jupyter notebooks. […]

Externalize Amazon MSK Connect configurations with Terraform

Managing configurations for Amazon MSK Connect, a feature of Amazon Managed Streaming for Apache Kafka (Amazon MSK), can become challenging, especially as the number of topics and configurations grows. In this post, we address this complexity by using Terraform to optimize the configuration of the Kafka topic to Amazon S3 Sink connector. By adopting this […]

How Chime Financial uses AWS to build a serverless stream analytics platform and defeat fraudsters

This is a guest post by Khandu Shinde, Staff Software Engineer and Edward Paget, Senior Software Engineering at Chime Financial. Chime is a financial technology company founded on the premise that basic banking services should be helpful, easy, and free. Chime partners with national banks to design member first financial products. This creates a more […]

Explore real-world use cases for Amazon CodeWhisperer powered by AWS Glue Studio notebooks

Many customers are interested in boosting productivity in their software development lifecycle by using generative AI. Recently, AWS announced the general availability of Amazon CodeWhisperer, an AI coding companion that uses foundational models under the hood to improve software developer productivity. With Amazon CodeWhisperer, you can quickly accept the top suggestion, view more suggestions, or […]

Optimize checkpointing in your Amazon Managed Service for Apache Flink applications with buffer debloating and unaligned checkpoints – Part 2

February 2024: This post was reviewed and updated for accuracy. This post is a continuation of a two-part series. In the first part, we delved into Apache Flink‘s internal mechanisms for checkpointing, in-flight data buffering, and handling backpressure. We covered these concepts in order to understand how buffer debloating and unaligned checkpoints allow us to […]

Optimize checkpointing in your Amazon Managed Service for Apache Flink applications with buffer debloating and unaligned checkpoints – Part 1

This post is the first of a two-part series regarding checkpointing mechanisms and in-flight data buffering. In this first part, we explain some of the fundamental Apache Flink internals and cover the buffer debloating feature. In the second part, we focus on unaligned checkpoints. Apache Flink is an open-source distributed engine for stateful processing over […]

Operational Data Processing Framework for Modern Data Architectures

Simplify operational data processing in data lakes using AWS Glue and Apache Hudi

AWS has invested in native service integration with Apache Hudi and published technical contents to enable you to use Apache Hudi with AWS Glue (for example, refer to Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 1: Getting Started). In AWS ProServe-led customer engagements, the use cases we work on usually come with technical complexity and scalability requirements. In this post, we discuss a common use case in relation to operational data processing and the solution we built using Apache Hudi and AWS Glue.

Securely process near-real-time data from Amazon MSK Serverless using an AWS Glue streaming ETL job with IAM authentication

Streaming data has become an indispensable resource for organizations worldwide because it offers real-time insights that are crucial for data analytics. The escalating velocity and magnitude of collected data has created a demand for real-time analytics. This data originates from diverse sources, including social media, sensors, logs, and clickstreams, among others. With streaming data, organizations […]

Capacity Management and Amazon EMR Managed Scaling improvements for Amazon EMR on EC2 clusters

In 2022, we told you about the new enhancements we made in Amazon EMR Managed Scaling, which helped improve cluster utilization as well as reduced cluster costs. In 2023, we are happy to report that the Amazon EMR team has been hard at work. We worked backward from customer requirements and launched multiple new features to enhance your Amazon EMR on EC2 clusters capacity management and scaling experience. Let’s dive deeper and discuss the new Amazon EMR on EC2 features in detail.