Stairway to U-SQL Level 16: The Azure Data Lake Catalog
Delve behind the scenes and learn about the catalog used to manage Azure Data Lakes.
2020-04-08
2,694 reads
Big Data
Azure Data Lake Analytics using U-SQL Queries
This article will help with gaining confidence and familiarity with Microsoft Azure's Data Lake Analytics offering to process large datasets quickly while demonstrating the potential and capabilities of U-SQL to aggregate and process big data files.
2019-02-20
2,259 reads
2018-10-22
51 reads
Modern Data Warehouse Design Pattern – Part II
Join Anoop Kumar as he discusses two modern design patterns to handle Advanced Analytics on big data, and Real time analytics.
2018-10-02
3,526 reads
Stairway to U-SQL Level 20: Querying External Data with U-SQL
Did you know you can query SQL Server data with U-SQL? It's true! Find out how in this latest stairway step.
2018-03-14
1,656 reads
Distributed Computing Principles and SQL-on-Hadoop Systems
A look at SQL-On-Hadoop systems like PolyBase, Hive, Spark SQL in the context Distributed Computing Principles and new Big Data system design approach like the Lambda Architecture.
2019-09-06 (first published: 2017-10-26)
5,463 reads
Stairway to U-SQL Level 18: Populating a Data Lake with PowerShell
Learn how PowerShell can be used to manage files and folders in your Data Lake.
2021-01-06 (first published: 2017-10-04)
1,739 reads
Stairway to U-SQL Level 17: Executing U-SQL Jobs with PowerShell
Automate your Data Lake with PowerShell! Learn how PowerShell can be used to execute U-SQL scripts, as well as a few other little tricks.
2017-09-20
1,049 reads
Stairway to U-SQL Level 12: SQL.ARRAY and CROSS APPLY EXPLODE
U-SQL introduces two new data types - SQL.ARRAY and SQL.MAP. Here, we look at what we can do with SQL.ARRAY and the CROSS APPLY EXPLODE expression.
2017-01-11
2,584 reads
Why Would I Ever Need to Partition My Big ‘Raw’ Data?
Whether you are running an RDBMS, or a Big Data system, it is important to consider your data-partitioning strategy. As the volume of data grows, so it becomes increasingly important to match the way you partition your data to the way it is queried, to allow 'pruning' optimisation. When you have huge imports of data to consider, it can get complicated. Bartosz explains how to get things right; not perfect but wisely.
2016-11-22
3,345 reads
Blogs
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