AWS Big Data Blog
Category: Serverless
Access Amazon Athena in your applications using the WebSocket API
In this post, we present a solution that can integrate with your front-end application to query data from Amazon S3 using an Athena synchronous API invocation. With this solution, you can add a layer of abstraction to your application on direct Athena API calls and promote the access using the WebSocket API developed with Amazon API Gateway. The query results are returned back to the application as Amazon S3 presigned URLs.
Achieve up to 27% better price-performance for Spark workloads with AWS Graviton2 on Amazon EMR Serverless
Amazon EMR Serverless is a serverless option in Amazon EMR that makes it simple to run applications using open-source analytics frameworks such as Apache Spark and Hive without configuring, managing, or scaling clusters. At AWS re:Invent 2022, we announced support for running serverless Spark and Hive workloads with AWS Graviton2 (Arm64) on Amazon EMR Serverless. […]
Amazon EMR Serverless supports larger worker sizes to run more compute and memory-intensive workloads
Amazon EMR Serverless allows you to run open-source big data frameworks such as Apache Spark and Apache Hive without managing clusters and servers. With EMR Serverless, you can run analytics workloads at any scale with automatic scaling that resizes resources in seconds to meet changing data volumes and processing requirements. EMR Serverless automatically scales resources up […]
Use fuzzy string matching to approximate duplicate records in Amazon Redshift
It’s common to ingest multiple data sources into Amazon Redshift to perform analytics. Often, each data source will have its own processes of creating and maintaining data, which can lead to data quality challenges within and across sources. One challenge you may face when performing analytics is the presence of imperfect duplicate records within the source data. This post presents one possible approach to addressing this challenge in an Amazon Redshift data warehouse using fuzzy matching.
How Amazon Devices scaled and optimized real-time demand and supply forecasts using serverless analytics
Every day, Amazon devices process and analyze billions of transactions from global shipping, inventory, capacity, supply, sales, marketing, producers, and customer service teams. This data is used in procuring devices’ inventory to meet Amazon customers’ demands. With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics […]
Serverless logging with Amazon OpenSearch Serverless and Amazon Kinesis Data Firehose
February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. In this post, you will learn how you can use Amazon Kinesis Data Firehose to build a log ingestion pipeline to send VPC flow logs to Amazon OpenSearch Serverless. First, you create […]
Amazon OpenSearch Serverless is now generally available!
We ended 2022 on a high note with the preview release of Amazon OpenSearch Serverless at re:Invent. Today, we are happy to announce the general availability of Amazon OpenSearch Serverless, the serverless option for Amazon OpenSearch Service that makes it easier to run search and analytics workloads without even having to think about infrastructure management. […]
Build a serverless analytics application with Amazon Redshift and Amazon API Gateway
Serverless applications are a modernized way to perform analytics among business departments and engineering teams. Business teams can gain meaningful insights by simplifying their reporting through web applications and distributing it to a broader audience. Use cases can include the following: Dashboarding – A webpage consisting of tables and charts where each component can offer […]
Add your own libraries and application dependencies to Spark and Hive on Amazon EMR Serverless with custom images
Amazon EMR Serverless allows you to run open-source big data frameworks such as Apache Spark and Apache Hive without managing clusters and servers. Many customers who run Spark and Hive applications want to add their own libraries and dependencies to the application runtime. For example, you may want to add popular open-source extensions to Spark, […]
Amazon EMR Serverless cost estimator
Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run applications using open-source big data analytics frameworks such as Apache Spark and Hive without configuring, managing, and scaling clusters or servers. You get all the features of the latest open-source frameworks with the performance-optimized […]