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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.

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.

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Question of the Day

Creating a JSON Document III

I have this data in a table called dbo.NFLTeams

TeamID  TeamName       City             YearEstablished
------  --------       ----             ---------------
1       Cowboys        Dallas           1960
2       Eagles         Philadelphia     1933
3       Packers        Green Bay        1919
4       Chiefs         Kansas City      1960
5       49ers          San Francisco    1946
6       Broncos        Denver           1960
7       Seahawks       Seattle          1976
8       Patriots       New England      1960
If I run this code, how many rows are returned?
SELECT TOP 2 
  json_objectagg('Team' : TeamName)
FROM dbo.NFLTeams;

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