AWS Big Data Blog

Register now for the fifth annual AWS re:Invent, the largest gathering of the global cloud computing community. Join us in Las Vegas for opportunities to connect, collaborate, and learn about AWS solutions. There will be many opportunities for developers and data scientists working in big data to sharpen their skills and learn what’s coming next […]

NOTE: Amazon Redshift now supports creating an automatic snapshot schedule using the snapshot scheduler. For more information, please review this “What’s New” post. ———————————- Ian Meyers is a Solutions Architecture Senior Manager with AWS Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all your data […]

This is a guest post by Takumi Sakamoto, a software engineer at SmartNews. SmartNews in their own words: “SmartNews is a machine learning-based news discovery app that delivers the very best stories on the Web for more than 18 million users worldwide.” Data processing is one of the key technologies for SmartNews. Every team’s workload […]

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 […]