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Day: October 17, 2022

Thoughts on Current 2022

Markos Sfikas, et al, recap the Current 2022 conference:

Throughout the conference, the theme of Batch vs. Streaming was apparent. Discussions covered how they can be unified, how batch processing’s performance can / must be improved for real-time applications, and more. There was even a dedicated panel discussion with Adi Polak, Amy Chen, Eric Sammer and Tyler Akidau discussing the state of streaming adoption today, and debating if streaming will ever fully replace batch. You can view some interesting points from the panel discussion in the Twitter thread from Robin Moffatt.

Click through for the full recap.

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General Purpose Tier Azure SQL DB Performance

Reitse Eskens continues a series on comparing tiers of Azure SQL Database:

In my previous blog, I wrote about the serverless tier, the one that can go to sleep if you’re not using it for more than one hour (minimum). That tier is cheaper as long as you’re not running it for more than 25% of the time. If you need more time, go provisioned.
Another difference between serverless and provisioned is that the provisioned one gets a set number of cores whereas the serverless one has a minimum and a maximum number of cores. So this time, the blog is about the provisioned tier where you choose a fixed number of CPU’s with a fixed monthly cost.

Click through for the analysis. I’ll reiterate here that I really hope Reitse has some graphics at the end (or at least tables) which sort of lay out where the boundaries between tiers are and what the performance and cost profiles look like between them.

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Running Jobs in Azure SQL Database

Etienne Lopes gets a job:

In SQL Server, many automated tasks are implemented via SQL Server Agent jobs. If you’re used to it, you may get a bit sad when you learn that SQL Server Agent is not present in Azure SQL Database. However if those automated tasks rely on T-SQL then they can still be easily implemented in Azure SQL Databases using elastic jobs that provide the ability to run T-SQL scripts on a schedule or on-demand

Read on to see how they work.

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MySQL Backups via mysqldump

Lukas Vileikis begins a series on MySQL backups with the classic option:

mysqldump is one of the most popular database backup tools in the MySQL world.

The tool is prevalent partly because it’s very basic and quite powerful – mysqldump database backup tool is command line-based, very simple and very straightforward to use. As far as MySQL or its flavors (MariaDB and Percona Server) are concerned, this command line-based tool is one of the top choices for junior and senior database engineers across the world alike.

Click through to see how it works.

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Date Ranges and Merge Interval

Daniel Hutmacher notes a performance killer:

In my last post, I found that DATEDIFF, DATEADD and the other date functions in SQL Server are not as datatype agnostic as the documentation would have you believe. Those functions would perform an implicit datatype conversion to either datetimeoffset or datetime (!), which would noticeably affect the CPU time of a query.

Well, today I was building a query on an indexed date range, and the execution plan contained a Merge Interval operator. Turns out, this operator brings a few unexpected surprises to your query performance. The good news is, it’s a relatively simple fix.

Click through for an example and some information on a fix. Hugo Kornelis also adds some good insights in the comments.

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