AWS Big Data Blog

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 […]

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 […]

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 […]

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.

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 […]

In this blog post, we discuss the impact of Amazon Elastic Block Store (Amazon EBS) volume IOPS and throughput limits on Amazon OpenSearch Service domain and how to prevent/mitigate throughput throttling situation.

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.

This blog post presents an architecture solution that allows customers to extract key insights from Amazon S3 access logs at scale. We will partition and format the server access logs with Amazon Web Services (AWS) Glue, a serverless data integration service, to generate a catalog for access logs and create dashboards for insights.

Amazon’s serverless Apache Kafka offering, Amazon Managed Streaming for Apache Kafka (Amazon MSK) Serverless, is attracting a lot of interest. It’s appreciated for its user-friendly approach, ability to scale automatically, and cost-saving benefits over other Kafka solutions. However, a hurdle encountered by many users is the requirement of MSK Serverless to use AWS Identity and Access Management (IAM) access control. At the time of writing, the Amazon MSK library for IAM is exclusive to Kafka libraries in Java, creating a challenge for users of other programming languages. In this post, we aim to address this issue and present how you can use Amazon API Gateway and AWS Lambda to navigate around this obstacle.

In this post, we show how you can implement a suffix-based search. OpenSearch is an open-source RESTful search engine built on top of the Apache Lucene library. OpenSearch full-text search is fast, can give the result of complex queries within a fraction of a second. With OpenSearch, you can convert unstructured text into structured text using different text analyzers, tokenizers, and filters to improve search. OpenSearch uses a default analyzer, called the standard analyzer, which works well for most use cases out of the box. But for some use cases, it may not work best, and you need to use a specific analyzer.