Process more files than ever and use Parquet with Azure Data Lake Analytics

In a recent release, Azure Data Lake Analytics (ADLA) takes the capability to process large amounts of files of many different formats to the next level. This blog post is showing you an end to end walk-through of generating many Parquet files from a rowset, and process them at scale with ADLA as well as…

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Get started with U-SQL: It’s easy!

Azure Data Lake Analytics combines declarative and imperative concepts in the form of a new language called U-SQL. The idea of learning a new language is daunting. Don’t worry!  U-SQL is easy to learn. You can learn the vast majority of the language in a single day. If you are familiar with SQL or languages…

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Use AU Analyzer for faster, lower cost Data Lake Analytics

Do you use Data Lake Analytics and wonder how many Analytics Units your jobs should have been assigned? Do you want to see if your job could consume a little less time or money? The recently-announced AU Analyzer tool can help you today! See our recent announcement of the AU Analyzer, available in both Visual…

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Azure Data Lake Command-line Quickstart using Azure Cloud Shell

Have you been using Azure Data Lake Analytics mainly from the Azure Portal or Visual Studio interfaces? Do you want to use Data Lake Analytics programmatically without installing anything? Do you want to get started with Azure PowerShell, but you’re on a Mac or Linux machine? Here’s how to get started with Azure PowerShell or…

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Organize your pipeline and recurring jobs easily with Data Lake Analytics (part 2)

Identify performance problems and reduce failed jobs with pipeline and recurring job information In part 1, we showed you how to tag and explore your pipeline and recurring jobs: Tag jobs with the new pipeline and recurring job metadata using Azure PowerShell Explore pipeline and recurring jobs using Azure Portal and Azure PowerShell In this…


Organize your pipeline and recurring jobs easily with Data Lake Analytics (part 1)

 Tagging and exploring pipeline and recurring jobs with metadata In a previous blog post, we introduced how managing/monitoring pipeline and recurring jobs is made easier with new concepts we added to Data Lake Analytics. Let’s take a deeper look at how to leverage this new capability. This is part 1 of a 2-part series. In…


Azure Data Lake Analytics and U-SQL Summer 2017 Updates: Introducing GZip on OUTPUT, Catalog Views, Major updates to Cognitive Libraries, Tool support to create your EXTRACT statement and much more!

Hello Azure Data Lake and U-SQL fans and followers. It has been a while since we release the release notes for all the cool features we released over the summer and listing all the pending deprecation items and breaking changes. The summer break is finally over, so without further ado, here are the Summer 2017…

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Azure Data Lake U-SQL April 25 2017 Updates: Introducing Packages, UNPIVOT INCLUDE NULLS, fast file set preview flag, R extension returns dataframes, exporting your cluster database with sample data to your local run and more!

We have concluded the rollout of our April 2017 refresh to all the regions today. Here are the April 2017 Updates for Azure Data Lake U-SQL and Developer Tooling! The main items are the release of the package feature that allows you to bundle assembly reference statements, variable declarations into a shareable package and reduce…

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