Articles

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Scala and Apache Spark in Tandem as a Next-Generation ETL Framework

Scala and Apache Spark might seem an unlikely medium for implementing an ETL process, but there are reasons for considering it as an alternative. After all, many Big Data solutions are ideally suited to the preparation of data for input into a relational database, and Scala is a well thought-out and expressive language. Krzysztof Stanaszek describes some of the advantages and disadvantages of a scala-based approach to implementing and testing an ETL solution.

2017-06-12

4,658 reads

External Article

How to partition data in Tabular SSAS

Partitioning data is a standard SQL Server administration practice. Partitions enable independent administration of different slices of data. When a SQL Server Analysis Services (SSAS) tabular data model is developed and processed, data is read from the source system and loaded into the tabular data model configured in In-Memory processing mode. Every time the model is processed, the entire data set may not require re-processing. Only certain slices of data containing changes may require re-processing which can be achieved by partitioning data into logical slices. In this post, Siddharth Mehta looks at how to partition tables in Tabular SSAS.

2017-06-08

2,832 reads

External Article

Comparing SSIS Catalog Contents Using DBFit Framework

When you are doing the rapid deployment of an updated SSIS project, there are a number of things you have to check to make sure that the deployment will be successful. These will include such settings as the values in environment variables, Package parameters and project parameters. The DbFit test framework turns out to be ideal for the purpose of doing final checks as part of a deployment process, as Nat Sundar demonstrates.

2017-06-07

3,586 reads

Blogs

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Fun with JSON

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Creating JSON II

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Engineer Lessons

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Question of the Day

Creating JSON II

On SQL Server 2025, what happens when I run this code:

SELECT JSON_OBJECTAGG( N'City':N'Denver' RETURNING JSON)
GO

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