Are you wondering about the different implementations of T-SQL UNPIVOT transformations?  If so, there is no need to panic since you’re not alone. Fortunately, this is something you can get done within the shortest time possible provided you understand what is expected of you.  Luckily, we are here to offer a helping hand.  In this post, we will take you through the different implementations of the T-SQL UNPIVOT transformations you ought to know. Read on and find out more.

 

UNION ALL

Initially, SQL server did not offer an efficient way of converting columns into rows. For this reason, most users would rather opt for multiple reading from the same table using a different set of columns united through the UNION ALL statements. Unfortunately, this practice has a weakness of multiple data reading.  This mostly happens since UNION ALL will scan the rows once for every subquery. Eventually, it decreases the efficiency of the query execution.

 

UNPIVOT

One of the fastest routes you can take when looking forward to converting columns into rows is using the UNPIVOT SQL operator. This function was introduced in SQL server way back in 2005. However, you need to be fully aware of what is expected of you in order to have an easy ride. The good news is you can leverage the internet thus getting every piece of information you might need.

Dynamic SQL

We can never conclude without talking about the Dynamic SQL. When using this function, you can easily create a general-purpose query for any table on the condition that columns not part of the primary key have a compatible data-type between them. Nevertheless, this method is not that fast considering the automation generation of the UNPIVOT query needs and additional reading from the system views and rows.

Final Thoughts

These are just but some of the different implementations of T-SQL UNPIVOT transformations you need to know about. Be sure to understand what they entail if you’re to stand the chance of getting the most from them. It is then that you’re destined to have an easy ride.

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