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Day: May 30, 2023

Databricks SQL Performance Tuning

Published 2023-05-30 by Kevin Feasel

Katie Cummiskey provides some tips for us:

We previously discussed how to use Power BI on top of Databricks Lakehouse efficiently. However, the well-designed and efficient Lakehouse itself is the basement for overall performance and good user experience.  We will discuss recommendations for physical layout of Delta tables, data modeling, as well as recommendations for Databricks SQL Warehouses.

These tips and techniques proved to be efficient based on our field experience. We hope you will find them relevant for your Lakehouse implementations too.

Read on for these tips.

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First Look at Loading Data into Fabric

Published 2023-05-30 by Kevin Feasel

Reitse Eskens digs into Microsoft Fabric:

In my previous blog, I wrote about some first impression working with Fabric and mostly following the Lakehouse tutorial provided by Microsoft. Well structured as this one may be, the sizes are not like the sizes I’m seeing in the wild. So I decided to give Fabric a bit more of a challenge by letting it loose on my TPC-H dataset.

Click through for Reitse’s early analysis.

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Filling Gaps in T-SQL

Published 2023-05-30 by Kevin Feasel

Itzik Ben-Gan has a new challenge:

The task involves developing a stored procedure called GetBalances that accepts a parameter called @accountid representing an account ID. The stored procedure should return a result set with all existing dates and balances for the input account, but also gap-filled with the dates of the missing workdays between the existing minimum and maximum dates for the account, along with the last known balance up to that point. The result should be ordered by the date.

My first thought was last observation carried forward, which is now available in SQL Server 2022 (Itzik’s solution 2). I kind of thought of solution 3, though did not think through the mechanics of how it’d work and so I get no credit there.

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Plan Analysis of Graph Tables

Published 2023-05-30 by Kevin Feasel

Hugo Kornelis is back and looking at graphs:

SQL Graph is the name for a set of features, introduced in SQL Server 2017 and extended in SQL Server 2019, that bring graph database functionality into SQL Server. See here for the full documentation as provided by Microsoft. In this first post about SQL Graph, I’ll look at what execution plans reveal about the internal structure of graph tables. I’ll then use that knowledge in later parts, where I’ll discuss more advanced queries on graph tables.

Click through for the primer.

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