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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.

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How to Start Big Data with Apache Spark

It is worth getting familiar with Apache Spark because it a fast and general engine for large-scale data processing and you can use you existing SQL skills to get going with analysis of the type and volume of semi-structured data that would be awkward for a relational database. With an IDE such as Databricks you can very quickly get hands-on experience with an interesting technology.

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Question of the Day

RegEx Functions IV

I have this data in a table in a SQL Server 2025 database: 

EmailAddressID EmailAddress
7              dylan0@ADVENTURE-WORKS.COM
8              Diane1@ADVENTURE-WORKS.COM
If I run this query, which row(s) are returned? 
SELECT top 10
 *
 FROM person.EmailAddress
 WHERE REGEXP_LIKE(EmailAddress, '^D', 'i')
 AND BusinessEntityID IN (7,8)

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