A Fine Slice Of SQL Server
Recently, I had to export some query results to CSV and Excel. One of the columns was extremely large query text which was defined as NVARCHAR(MAX). Here are some of the issues I faced with this request and how I over came them.
SSIS or the Import/Export wizard is fine. This is also a good use case for bcp or writing your own query using dbatools and outputting the results to file.
Comments closedJeremy Schneider performs some tests:
This is a follow‑up to the last article: Run Jepsen against CloudNativePG to see sync replication prevent data loss. In that post, we set up a Jepsen lab to make data loss visible when synchronous replication was disabled — and to show that enabling synchronous replication prevents it under crash‑induced failovers.
Since then, I’ve been trying to make data loss happen more reliably in the “async” configuration so students can observe it on their own hardware and in the cloud. Along the way, I learned that losing data on purpose is trickier than I expected.
Click through to learn more. Jepsen has been the gold standard in testing distributed database systems for data loss.
Comments closedTesting is an important step when developing code in R or any other language. If you are a Python user, you can consider reading our previous blogs in pytest. Writing tests helps us make sure that the code is working as expected. In the R ecosystem, the testthat package is one of the most used frameworks. In this blog we will explore some of the main properties of
{testthat}highlighting some of the most useful functions with some examples.
Read on to see how it works. This isn’t a mocking library, but rather an assertions-based testing library. And near the end, Aida includes an extra library that helps with plot testing.
Comments closedMike Robbins continues a series on Markdown:
Technical writers often need to embed code in their articles, whether snippets, configurations, commands, or examples. When presented clearly, code in your articles reinforces understanding and helps readers follow along more easily. When presented poorly, it creates confusion and frustration. This article demonstrates how to use inline code and code blocks effectively in Markdown, ensuring your code is readable, maintainable, and helpful to your audience.
This is, fortunately, a bit of Markdown that is very consistent across platforms.
Comments closedRebecca Lewis explains an issue with memory grant feedback in SQL Server:
Before SQL Server runs a query, it estimates how much memory it needs for sorting and joining. But what if it gets it wrong?
- Too little memory → Spills to tempdb (slow)
- Too much memory → Starves other queries
SQL Server 2017+ tries to fix bad estimates based on previous calls with ‘Memory Grant Feedback’. Kinda like: ‘Last time I gave you 2GB but you only used 50MB. Next time I’m giving you less.’
This is great in theory, though Rebecca shows a case in which the end result might not be great.
Comments closedThe main purpose of SLRUs is to track metadata about Postgres transactions.
SLRUs are a general mechanism used by multiple types. Like a lot of things in Postgres, the SLRU system is extensible which means extensions can create new types.
The “least recently used” aspect might be recognizable from cache systems. LRU refers to how the oldest items are evicted from the cache when it’s full, and newer items take their place. This is because the cache has a fixed amount of space (measured in 8KB pages) and thus can only store a fixed amount of items.
Read on to learn more about these two concepts and how things have changed in Postgres 17.
Comments closedAaron Merrill announces a new preview feature:
Introducing the Secure tab in the OneLake catalog—your central place to understand and manage access across Fabric items. From a single view, you can workspace roles with the View users experience and inspect or modify role OneLake security roles with View security roles. The Secure tab brings a streamlined view for governance teams and workspace owners to quickly validate permissions and tighten least‑privilege access.
Click through to see how it looks.
Comments closedErik Darling digs into Windows Performance Recorder. This is definitely a more advanced tool for analysis, and Erik focuses on call stack time for two given queries. Windows Performance Recorder isn’t something I’ve really used before, though Erik’s demo does show some of the power of the tool.
Comments closedHans-Jürgen Schönig wants the output:
PostgreSQL 18 offers a couple of new features such as asynchronous I/O (aio), improvements around indexing, and a lot more. However, there is one feature that has really caught my attention. While it might go unnoticed by many users, it is really powerful and, to me, somehow represents everything I like about PostgreSQL.
The improvement I want to focus on today is related to the way the “RETURNING-clause” works in PostgreSQL 18.
This behavior is very much like the OUTPUT clause in T-SQL. Though it appears that OLD and NEW are not themselves pseudotables like SQL Server’s INSERTED and DELETED, as there is an example that includes old and new columns together in the same row.
Temidayo Omoniyi provides an introduction to GitHub Actions workflows:
In today’s fast-paced development cycles, the demand to ship high-quality code quickly is more important than ever before. However, several tedious, labor-intensive, and prone to mistakes procedures that stand between producing code and releasing it to consumers frequently slow down teams.
Every Developer faces these common issues:
- Repetitive Checks: Before each push, unit tests, linters, and build scripts are manually executed.
- Inconsistent Environments: Code that passes locally in one environment but fails in another is known as the “it works on my machine” dilemma.
- High-Stakes Deployments: Deploying code by following a meticulous, manual checklist in which even one mistake could result in downtime.
- Slow Comments Loops: The review process is prolonged when you wait for a coworker to pull your branch, run tests, and provide comments on a pull request.
I like GitHub Actions workflows a lot. Once you’ve put together a workflow or two, it’s pretty easy to see what’s going on. On top of that, there is a huge amount of functionality and an enormous number of third-party templates to extend it even further.
Comments closed