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Day: March 31, 2023

Join Operations in BigQuery

Published 2023-03-31 by Kevin Feasel

Rathish Kumar joins a few tables together:

SQL joins are used to combine columns from multiple tables to get desired result set. In a typical Relational model we use normalized tables, each table represents an entity (example: employee, department, etc) and its relationships and when we need to get data from more than one tables, for example employee name and employee department, we use joins to combine employee name column from employee table, department name column from department table based on employee number key column, which is available on both the tables.

Similarly, typical data warehouse setup follows Star or Snowflake schema consisting of a primary fact table and satellite dimension tables. Fact tables represents events (example: orders table in a ecommerce business) and dimension table represents attributes and slowly changing information (example: customer, product tables).

The syntax is rather similar to most database engines, though there are a few physical join operators which differ from typical relational database management systems. Also, I’ll take this moment to say thank you to Rathish for not using Venn diagrams to show joins and instead using a proper technique.

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Tracking Change Events in Snowflake

Published 2023-03-31 by Kevin Feasel

Kevin Wilkie shows off an interesting window function:

Notice that it has the OVER operator, you can order the data, and even partition the data as needed (Not seen in this example)!

But, as usual with Snowflake, there are even more functions we can work with! Sometimes, you just need to know when items are changed. Enter the CONDITIONAL_CHANGE_EVENT windowing function!

Click through for an example of how CONDITIONAL_CHANGE_EVENT() works.

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Finding Columnstore Index Storage and Memory Allocations

Published 2023-03-31 by Kevin Feasel

Jose Manuel Jurado Diaz has a few scripts for us:

Today, we got a new question how much is the size used by a columnstore index table at storage level and memory usage.

TSQL to obtain the total number of rows, size per schema, table and index.

Using the view sys.column_store_row_groups (Transact-SQL) – SQL Server | Microsoft Learn we could see the total number of rows and space usage at storage level.

Click through for that script, as well as a few more to learn how much space and memory that columnstore index is taking.

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Storing the Basis of Calculations, Not Results

Published 2023-03-31 by Kevin Feasel

Vladimir Khorikov hits on a topic of particular interest:

On the front-end, the duration is represented as 1h 47m. But how should we store it in our database? What data type should we use?

We could keep the duration as a 1h 47m string, just as we render it on the screen, but what if we later decide to change the string format? We might need to display it as 1:47 or 107 minutes instead. Do we then parse all the existing strings and convert them into a new format?

I like the thrust of this article. Two things I think people forget about in data modeling are ledgers and events, instead trying to store the results of these. Ledgers and events can be slower—though there are things we can do to pre-calculate more user-friendly results and speed up the process—but they provide you auditability, flexibility in how you want to calculate and display the information, and the ability to correct errors over time.

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SQL Alerts on Potential Attacks

Published 2023-03-31 by Kevin Feasel

David Fowler keeps his head on a swivel:

But let’s be honest, the above attacks are just going to be opportunistic hackers probably using an automated tool to hunt out open servers and try to exploit them, a bit like the guy walking down the road and trying all the car doors in the hope that someone will have left their unlocked. It someone’s specifically targeting your servers, the chances are that they’ll be a bit more sophisticated.

This is where things get a little more troublesome and where SQL doesn’t really give us any tools to help.

But there are warning signs that we can look out for and these can be certain error messages in the logs. There are three in particular that I see as red flags that something amiss may be going on.

Click through for those three warning signs and how you an create SQL Server alerts upon logging these messages. The errors aren’t guaranteed to be an attacker, though in reading them, I’d expect a high signal to noise ratio on them.

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