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Month: January 2022

Profiling Python Code

Adrian Tam shows how you can test the performance of calls in Python:

Profiling is a technique to figure out how time is spent in a program. With this statistics, we can find the “hot spot” of a program and think about ways of improvement. Sometimes, hot spot in unexpected location may hint a bug in the program as well.

In this tutorial, we will see how we can use the profiling facility in Python. Specifically, you will see

– How we can compare small code fragments using timeit module

– How we can profile the entire program using cProfile module

– How we can invoke a profiler inside an existing program

– What the profiler cannot do

Read on for those techniques.

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Finding your SQL Server Product Key

I share a tale of woe:

I was working on an upgrade recently, trying to move from SQL Server 2016 to SQL Server 2019. I wanted to perform an upgrade in-place on an Azure VM, but needed to get the product key. There are a few places where you can find Powershell functions to get this product key, with Ryan @ Ryadel’s post being the most well-known. That method covers versions from SQL Server 2005 through 2014 (if you follow the notes in the blog post), but breaks on 2016.

Click through for a script which works for SQL Server 2016 and later.

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Static versus Dynamic Partitioning in Hive

The Hadoop in Real World team explains the difference between two partitioning strategies:

The difference between static and dynamic partitioning only exists when the partition is being created based on how the partitions are added to the table. Once the partitions are created, the tables won’t have any difference like static and dynamic partitions. All partitions are treated and one and the same.

Click through for the difference.

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Improving Managed Instance Load Performance

Niko Neugebauer provides some tips on improving data load performance when using SQL Managed Instances in the General Purpose tier:

In this blog post we shall consider some of the strategies for improving data loading performance in Azure SQL Managed Instance. These strategies apply to the repeatable ETL processes, meaning that if there a problem, data loading process can be repeated without loss of any bit of data or its consistency. Of course, these strategies do require a prepared design for the possibility of the repetition, but this is a basic requirement for any data loading process.

There are many great ways of ensuring high performance data loading and this blog post does not pretend to be exhaustive an ultimate resource, but it will provide a couple of known paths that can drastically improve the performance of the Log Throughput in Azure SQL MI.

Click through for some tips, including some which make sense on-prem and a couple which are specific to platform-as-a-service offerings.

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The Benefits of Indirect Checkpoints

Aaron Bertrand explains why it’s probably a good idea to enable indirect checkpoints:

At Stack Overflow, the upgrade to SQL Server 2019 was not as smooth as expected. It introduced long recovery times and high CPU on a secondary, during synchronization activity after failover, patching, and network connectivity testing. This symptom wasn’t present during similar activities and workloads under SQL Server 2017.

Aaron points out that if you have databased created in older versions of SQL Server, enabling indirect checkpoints can provide a performance boost to certain activities around log writing., including backup times.

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Wide Non-Clustered Indexes as Kinda-Sorta Clustered Indexes

Grant Fritchey gets our hopes up:

Everyone knows that you only get a single clustered index, right? Wouldn’t it be great though if you could have two clustered indexes?

Well, you can. Sort of. Let’s talk about it.

Click through to see what Grant means. This is a thing that I’ve done occasionally, though much more often, I’ve ripped it out because Database Tuning Advisor suggested it and a credulous user took DTA at its word.

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The Power BI Icon Map Custom Visual

Alice Drummond shows off a custom visual in Power BI:

Working across the environmental industry – it’s fair to say that pretty much ALL of DiscoverEI’s Power BI reports have a map! And if you thought that MapBox was good, well you’re going to LOVE the Icon Map custom visual in Power BI – which allows you to display interactive polygons, points, lines and of course – icons, all in the one visual…plus so much more!

We’ve been using the Icon Map custom visual in Power BI for the last couple of years and it’s safe to say that it is hands down our favourite mapping visual for Power BI! This visual is created for free for the community by James Dales. James is always making updates and enhancements to the visual so the best place to get the latest version and some helpful instructions and tips on how to use it is from his dedicated website: https://icon-map.com/index.html. And while you’re there remember to shout James a coffee or 10 to say thanks for creating such a fantastic mapping visual

Click through for a few examples of the visual and be sure to check it out in the link above.

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CORRESPONDING and ANSI SQL

Lukas Eder looks at a rarely-implemented keyword in SQL:

I recently stumbled upon a standard SQL feature that was implemented, to my surprise, in HSQLDB. The keyword is CORRESPONDING, and it can be used with all set operations, including UNIONINTERSECT, and EXCEPT.

Click through to see what it does. Be sure to check out the comments, where Joe Celko pops in to provide some additional historical context to explain why you won’t find this keyword in many implementations of the standard..

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Configuring a Debezium Connector for Event Hub Streaming

Niels Berglund continues a series:

This series came about as I in the post How to Use Kafka Client with Azure Event Hubs, somewhat foolishly said:

An interesting point here is that it is not only your Kafka applications that can publish to Event Hubs but any application that uses Kafka Client 1.0+, like Kafka Connect connectors!

I wrote the above without testing it myself, so when I was called out on it, I started researching (read “Googling”) to see if it was possible. The result of the “Googling” didn’t give a 100% answer, so I decided to try it out, and this series is the result.

In the first post, – as mentioned – we configured Kafka Connect to connect into Event Hubs. In this post, we look at configuring the Debezium connector.

Click through and enjoy the fruits of Berglund’s Folly—which, as far as it goes, I’d still rate Seward’s Folly higher but this one’s pretty good too.

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