Category: Learning Levels

Spark jobs running on Amazon EMR on EKS generate logs that are very useful in identifying issues with Spark processes and also as a way to see Spark outputs. You can access these logs from a variety of sources. On the Amazon EMR virtual cluster console, you can access logs from the Spark History UI. […]

August 2023: This post was reviewed and updated for accuracy. AWS Glue supports native integration with Apache Hudi, Delta Lake, and Apache Iceberg. Refer to Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 2: AWS Glue Studio Visual Editor to learn more. Cloud data lakes […]

Jan 2024: This post was reviewed and updated for accuracy. Modern data architectures encourage the integration of data lakes, data warehouses, and purpose-built data stores, enabling unified governance and easy data movement. With a modern data architecture on AWS, you can store data in a data lake and use a ring of purpose-built data services […]

Amazon Managed Grafana recently announced a new data source plugin for Amazon Redshift, enabling you to query, visualize, and alert on your Amazon Redshift data from Amazon Managed Grafana workspaces. With the new Amazon Redshift data source, you can now create dashboards and alerts in your Amazon Managed Grafana workspaces to analyze your structured and […]

June 2023: This post was reviewed and updated for accuracy. AWS Glue has become a popular option for integrating data from disparate data sources due to its ability to integrate large volumes of data using distributed data processing frameworks. Many customers use AWS Glue to build data lakes and data warehouses. Data engineers who prefer […]

Amazon EMR on Amazon EKS is a deployment option offered by Amazon EMR that enables you to run Apache Spark applications on Amazon Elastic Kubernetes Service (Amazon EKS) in a cost-effective manner. It uses the EMR runtime for Apache Spark to increase performance so that your jobs run faster and cost less. In our benchmark […]

October 2024: This post has been updated along with Interactive Sessions support for AWS Glue Auto scaling. June 2023: This post was reviewed and updated for accuracy. Data created in the cloud is growing fast in recent days, so scalability is a key factor in distributed data processing. Many customers benefit from the scalability of […]

June 2024: This post was reviewed for accuracy and updated to cover Apache Iceberg. June 2023: This post was reviewed and updated for accuracy. Customers are increasingly building data lakes to store data at massive scale in the cloud. It’s common to use distributed computing engines, cloud-native databases, and data warehouses when you want to […]

September 2025: This post was reviewed for accuracy. AWS Glue Schema Registry now supports Protocol buffers (protobuf) schemas in addition to JSON and Avro schemas. This allows application teams to use protobuf schemas to govern the evolution of streaming data and centrally control data quality from data streams to data lake. AWS Glue Schema Registry […]

June 2023: This post was reviewed and updated for accuracy. Amazon Redshift is a fast, petabyte-scale cloud data warehouse delivering the best price–performance. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Data analysts and database developers want to use this data to train […]