AWS Big Data Blog

Category: Advanced (300)

Enable Multi-AZ deployments for your Amazon Redshift data warehouse

November 2023: This post was reviewed and updated with the general availability of Multi-AZ deployments for provisioned RA3 clusters. Originally published on December 9th, 2022. Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical […]

Use Snowflake with Amazon MWAA to orchestrate data pipelines

This blog post is co-written with James Sun from Snowflake. Customers rely on data from different sources such as mobile applications, clickstream events from websites, historical data, and more to deduce meaningful patterns to optimize their products, services, and processes. With a data pipeline, which is a set of tasks used to automate the movement […]

Spark on AWS Lambda: An Apache Spark runtime for AWS Lambda

Spark on AWS Lambda (SoAL) is a framework that runs Apache Spark workloads on AWS Lambda. It’s designed for both batch and event-based workloads, handling data payload sizes from 10 KB to 400 MB. This post highlights the SoAL architecture, provides infrastructure as code (IaC), offers step-by-step instructions for setting up the SoAL framework in your AWS account, and outlines SoAL architectural patterns for enterprises.

Simplify Amazon Redshift monitoring using the new unified SYS views

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud, providing up to five times better price-performance than any other cloud data warehouse, with performance innovation out of the box at no additional cost to you. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to […]

Run Spark SQL on Amazon Athena Spark

At AWS re:Invent 2022, Amazon Athena launched support for Apache Spark. With this launch, Amazon Athena supports two open-source query engines: Apache Spark and Trino. Athena Spark allows you to build Apache Spark applications using a simplified notebook experience on the Athena console or through Athena APIs. Athena Spark notebooks support PySpark and notebook magics […]

SmugMug’s durable search pipelines for Amazon OpenSearch Service

SmugMug operates two very large online photo platforms, SmugMug and Flickr, enabling more than 100 million customers to safely store, search, share, and sell tens of billions of photos. Customers uploading and searching through decades of photos helped turn search into critical infrastructure, growing steadily since SmugMug first used Amazon CloudSearch in 2012, followed by […]

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Using Spark SQL to run Hive workloads provides not only the simplicity of SQL-like queries but also taps into the exceptional speed and performance provided by Spark. Spark SQL is an Apache Spark module for structured data processing. One […]

Unleash the power of Snapshot Management to take automated snapshots using Amazon OpenSearch Service

Snapshot Management helps you create point-in-time backups of your domain using OpenSearch Dashboards, including both data and configuration settings (for visualizations and dashboards). You can use these snapshots to restore your cluster to a specific state, recover from potential failures, and even clone environments for testing or development purposes. In this post, we share how to use Snapshot Management to take automated snapshots using OpenSearch Service.