AWS Big Data Blog

Category: AWS Big Data

Build a modern analytics stack optimized for sharing and collaborating with Mode and Amazon Redshift

Leading technology companies, such as Netflix and Airbnb, are building on AWS to solve problems on the edge of the data ecosystem. While these companies show us what data and analytics make possible, the complexity and scale of their problems aren’t typical. Most of our challenges aren’t figuring out how to process billions of records […]

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Amazon QuickSight Announces General Availability of ML Insights

At re:Invent 2018, we announced the preview of ML Insights, a set of out-of-the-box machine learning and natural language features that provide Amazon QuickSight users with business insights beyond visualization. Today, we are announcing the general availability of ML Insights. As the volume of data that customers generate continues to grow every day, it’s becoming […]

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Best practices for running Apache Spark applications using Amazon EC2 Spot Instances with Amazon EMR

In this blog post, we are going to focus on cost-optimizing and efficiently running Spark applications on Amazon EMR by using Spot Instances. We recommend several best practices to increase the fault tolerance of your Spark applications and use Spot Instances. These work without compromising availability or having a large impact on performance or the length of your jobs.

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How to enable cross-account Amazon Redshift COPY and Redshift Spectrum query for AWS KMS–encrypted data in Amazon S3

This post shows a step-by-step walkthrough of how to set up a cross-account Amazon Redshift COPY and Spectrum query using a sample dataset in Amazon S3. The sample dataset is encrypted at rest using AWS KMS-managed keys (SSE-KMS). About AWS Key Management Service (AWS KMS) With AWS Key Management Service (AWS KMS), you can have […]

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Improve Apache Spark write performance on Apache Parquet formats with the EMRFS S3-optimized committer

The EMRFS S3-optimized committer is a new output committer available for use with Apache Spark jobs as of Amazon EMR 5.19.0. This committer improves performance when writing Apache Parquet files to Amazon S3 using the EMR File System (EMRFS). In this post, we run a performance benchmark to compare this new optimized committer with existing committer […]

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Visualize over 200 years of global climate data using Amazon Athena and Amazon QuickSight

Climate Change continues to have a profound effect on our quality of life. As a result, the investigation into sustainability is growing. Researchers in both the public and private sector are planning for the future by studying recorded climate history and using climate forecast models. To help explain these concepts, this post introduces the Global […]

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Create real-time clickstream sessions and run analytics with Amazon Kinesis Data Analytics, AWS Glue, and Amazon Athena

Clickstream events are small pieces of data that are generated continuously with high speed and volume. Often, clickstream events are generated by user actions, and it is useful to analyze them. For example, you can detect user behavior in a website or application by analyzing the sequence of clicks a user makes, the amount of […]

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Metadata classification, lineage, and discovery using Apache Atlas on Amazon EMR

With the ever-evolving and growing role of data in today’s world, data governance is an essential aspect of effective data management. Many organizations use a data lake as a single repository to store data that is in various formats and belongs to a business entity of the organization. The use of metadata, cataloging, and data […]

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Our data lake story: How Woot.com built a serverless data lake on AWS

In this post, we talk about designing a cloud-native data warehouse as a replacement for our legacy data warehouse built on a relational database. At the beginning of the design process, the simplest solution appeared to be a straightforward lift-and-shift migration from one relational database to another. However, we decided to step back and focus […]

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