AWS Big Data Blog

Category: Amazon EMR

Visualize Big Data with Amazon QuickSight, Presto, and Apache Spark on Amazon EMR

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Last December, we introduced the Amazon Athena connector in Amazon QuickSight, in the Derive Insights from IoT in Minutes using AWS IoT, Amazon Kinesis Firehose, Amazon Athena, and Amazon QuickSight post. The […]

Build a Real-time Stream Processing Pipeline with Apache Flink on AWS

NOTE: As of November 2018, you can run Apache Flink programs with Amazon Kinesis Analytics for Java Applications in a fully managed environment. You can find further details in a new blog post on the AWS Big Data Blog and in this Github repository. ————————– September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. […]

Securely Analyze Data from Another AWS Account with EMRFS

Sometimes, data to be analyzed is spread across buckets owned by different accounts. In order to ensure data security, appropriate credentials management needs to be in place. This is especially true for large enterprises storing data in different Amazon S3 buckets for different departments. For example, a customer service department may need access to data […]

Harmonize, Search, and Analyze Loosely Coupled Datasets on AWS

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. You have come up with an exciting hypothesis, and now you are keen to find and analyze as much data as possible to prove (or refute) it. There are many datasets that might be applicable, but they have been created […]

Secure Amazon EMR with Encryption

In the last few years, there has been a rapid rise in enterprises adopting the Apache Hadoop ecosystem for critical workloads that process sensitive or highly confidential data. Due to the highly critical nature of the workloads, the enterprises implement certain organization/industry wide policies and certain regulatory or compliance policies. Such policy requirements are designed […]

Serving Real-Time Machine Learning Predictions on Amazon EMR

The typical progression for creating and using a trained model for recommendations falls into two general areas: training the model and hosting the model. Model training has become a well-known standard practice. We want to highlight one of many ways to host those recommendations (for example, see the Analyzing Genomics Data at Scale using R, […]

Respond to State Changes on Amazon EMR Clusters with Amazon CloudWatch Events

Jonathan Fritz is a Senior Product Manager for Amazon EMR Customers can take advantage of the Amazon EMR API to create and terminate EMR clusters, scale clusters using Auto Scaling or manual resizing, and submit and run Apache Spark, Apache Hive, or Apache Pig workloads. These decisions are often triggered from cluster state-related information. Previously, […]