AWS Big Data Blog

Category: Analytics

Build a real-time streaming application using Apache Flink Python API with Amazon Kinesis Data Analytics

Amazon Kinesis Data Analytics is now expanding its Apache Flink offering by adding support for Python. This is exciting news for many of our customers who use Python as their primary language for application development. This new feature enables developers to build Apache Flink applications in Python using serverless Kinesis Data Analytics. With Kinesis Data […]

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Introducing Auto-Tune in Amazon ES

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Today we announced Auto-Tune in Amazon Elasticsearch Service (Amazon ES), an innovation undertaken to automatically optimize resources in Elasticsearch clusters to improve its performance and availability. Auto-Tune gives us a unique opportunity of applying our learnings from operating clusters at […]

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Build a serverless tracking pixel solution in AWS

Let’s describe the typical use case where a tracking pixel solution, also known as a web beacon, might help you: Analyzing web traffic is critical to understanding user behavior in order to improve their experience. Let’s think about a company—Example Company Hotels—that embeds a piece of HTML into a high-traffic, third-party website (example.HighTrafficWebsite.com) to have […]

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The following diagram shows the overall architecture to address our two challenges.

Extract multidimensional data from Microsoft SQL Server Analysis Services using AWS Glue

AWS Glue is fully managed service that makes it easier for you to extract, transform, and load (ETL) data for analytics. You can easily create ETL jobs to connect to backend data sources. There are several natively supported data sources, but what if you need to extract data from an unsupported data source? What if […]

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The following diagram shows our solution architecture.

Effective data lakes using AWS Lake Formation, Part 2: Creating a governed table for streaming data sources

We announced the preview of AWS Lake Formation transactions, row-level security, and acceleration at AWS re:Invent 2020. In Part 1 of this series, we explained how to set up a governed table and add objects to it. In this post, we expand on this example, and demonstrate how to ingest streaming data into governed tables using Lake Formation transactions. […]

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The following graph shows that the minimum throughput achieved with the persistent HFile

Amazon EMR 6.2.0 adds persistent HFile tracking to improve performance with HBase on Amazon S3

Apache HBase is an open-source, NoSQL database that you can use to achieve low latency random access to billions of rows. Starting with Amazon EMR 5.2.0, you can enable HBase on Amazon Simple Storage Service (Amazon S3). With HBase on Amazon S3, the HBase data files (HFiles) are written to Amazon S3, enabling data lake […]

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Best Western slashes analytics costs, improves operations worldwide using Amazon QuickSight

This is a guest blog post by Best Western Hotels and Resorts. In their own words, “Best Western Hotels & Resorts is an award-winning global network of hotels located in over 100 countries and territories that offers accommodations for all types of travelers.” With 18 brands and varied ownership structures across geographies, Best Western Hotel […]

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How 1Strategy simplified their spreadsheet ETL process using AWS Glue DataBrew

This is a guest blog post by Pat Reilly and Gary Houk at 1Strategy. In their own words, “1Strategy is an APN Premier Consulting Partner focusing exclusively on AWS solutions. 1Strategy consultants help businesses architect, migrate, and optimize their workloads on AWS, creating scalable, cost-effective, secure, and reliable solutions. 1Strategy holds the AWS DevOps, Migration, […]

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Automate dynamic mapping and renaming of column names in data files using AWS Glue: Part 2

In Part 1 of this two-part post, we looked at how we can create an AWS Glue ETL job that is agnostic enough to rename columns of a data file by mapping to column names of another file. The solution focused on using a single file that was populated in the AWS Glue Data Catalog […]

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Automate dynamic mapping and renaming of column names in data files using AWS Glue: Part 1

A common challenge ETL and big data developers face is working with data files that don’t have proper name header records. They’re tasked with renaming the columns of the data files appropriately so that downstream application and mappings for data load can work seamlessly. One example use case is while working with ORC files and […]

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