AWS Big Data Blog

In this post, I discuss an alternate solution; namely, running separate CPU and GPU clusters, and driving the end-to-end modeling process from Apache Spark.

Lots to see on the Big Data Blog in June! Please take a look at the summaries below for something that catches your interest. Use Sqoop to Transfer Data from Amazon EMR to Amazon RDS Customers commonly process and transform vast amounts of data with EMR and then transfer and store summaries or aggregates of […]

In this post, I will show you how to transfer data using Apache Sqoop, which is a tool designed to transfer data between Hadoop and relational databases. Support for Apache Sqoop is available in Amazon EMR releases 4.4.0 and later.

This post shows you how you can use Spark Streaming to process data coming from Amazon Kinesis streams, build some graphs using Zeppelin, and then store the Zeppelin notebook in Amazon S3.

Amazon EMR has added Apache Tez version 0.8.3 as a supported application in release 4.7.0. Tez is an extensible framework for building batch and interactive data processing applications on top of Hadoop YARN.

Asmita Barve-Karandikar is an SDE with DynamoDB Customers often want to process streams on an Amazon DynamoDB table with a significant number of partitions or with a high throughput. AWS Lambda and the DynamoDB Streams Kinesis Adapter are two ways to consume DynamoDB streams in a scalable way. While Lambda lets you run your application […]

Mike Grimes is an SDE with Amazon EMR As a developer or data scientist, you rarely want to run a single serial job on an Apache Spark cluster. More often, to gain insight from your data you need to process it in multiple, possibly tiered steps, and then move the data into another format and […]

Tony Gibbs is a Solutions Architect with AWS (Update: This blog post has been translated into Japanese) When it comes to choosing a SQL-based database in AWS, there are many options. Sometimes it can be difficult to know which one to choose. For example, when would you use Amazon Aurora instead of Amazon RDS PostgreSQL […]

With today’s launch of Amazon EMR release 4.7, you can now create clusters with Apache Phoenix 4.7.0 for low-latency SQL and OLTP workloads. Phoenix uses Apache HBase as its backing store (HBase 1.2.1 is included on Amazon EMR release 4.7.0), using HBase scan operations and coprocessors for fast performance. Additionally, you can map Phoenix tables […]

Ben Snively is a Solutions Architect with AWS With big data, you deal with many different formats and large volumes of data. SQL-style queries have been around for nearly four decades. Many systems support SQL-style syntax on top of the data layers, and the Hadoop/Spark ecosystem is no exception. This allows companies to try new […]