A Fine Slice Of SQL Server
Steven Sanderson smooshes strings together:
String concatenation is a fundamental operation in data manipulation and cleaning. If you are working in R, mastering string concatenation will significantly enhance your data processing capabilities. This blog post will cover different ways to concatenate strings using base R, the
stringr,stringi, andgluepackages. Let’s go!
Read on for examples using paste(), paste0(), str_c(), stri_c(), and glue().
Kevin Wilkie does a bit of analysis:
Now that we know so much about getting data from Snowflake using the query history, we should be able to get all kinds of data that will be helpful for us. In the next few queries, I want to provide some queries I use that should make your Snowflake usage a bit more useful.
Click through for those queries.
Comments closedThe short story: SQL Server 2022 finally saw some growth this quarter! Two years after the release, 1 in 10 SQL Servers is finally running the latest version.
The long story: ever wonder how fast people are adopting new versions of SQL Server, or what’s “normal” out there for SQL Server adoption rates? Let’s find out in the summer 2024 version of our SQL ConstantCare® population report.
As always, this is my reminder that we’re looking at a particular sample of the SQL Server population—users of Brent’s service—and will likely have some skew. That said, even within the context of this population, it is interesting to see these trends over time, and Brent covers that in the post.
Comments closedWhen you’re designing the back end of a database, people will have all sorts of ideas.
Normalization, partitioning, referential integrity, and, usually, trying to figure out what to do when you have more than one client.
If your application is user-focused (like Stack Overflow), you don’t have to struggle too much with the idea of isolation. But when your application is geared more towards supporting multiple entities that have one or more users, things change. Sort of like how Stack Overflow manages all the other Stack Network sites.
Were you to ask me which model I prefer, it would be every tenant getting their own database. Your other options are:
- Everyone all mixed in together like gen-pop
- Using separate schemas inside a single database
Definitely read what Erik has to say. My prior job was a hybrid multi-tenant environment: for the main transactional database, there were several dozen SQL Server instances. Each instance had anywhere from one to a few dozen copies of the transactional database, and each database hosted one or more customers’ data. There’s not a lot of tooling out there to support that kind of strategy, so we had to build a lot of it in-house. But that said, it did work out reasonably well without having hundreds or thousands of databases on a single instance.
Comments closedSemab Tariq uses a Postgres extension:
The file_fdw (Foreign Data Wrapper) is a PostgreSQL extension that lets you access data stored in flat files, like CSV files, as if they were regular tables in your PostgreSQL database. This is useful for integrating external data sources without needing to import the data directly into your database.
file_fdw is a contrib module, meaning it’s an additional feature included with PostgreSQL but not part of its core functionality. Contrib modules provide extra capabilities and enhancements beyond the core database system.
At first, I was going to write that the mechanism looks a lot like PolyBase in SQL Server. But in actuality, it’s more like a hybrid of PolyBase and OPENROWSET, as there’s no definition of external data sources or file formats, but there is the creation of an external (“foreign”) table.
Kendra Little warns us not to let a person named General Failure run your military:
This post demonstrates two related bugs with plan forcing in Query Store which increase the likelihood of slower query execution and application timeouts in SQL Server environments.
These bugs are most likely to impact you if:
- You use the Automatic Plan Correction feature in SQL Server, which automatically forces query plans.
- Anyone manually forces query plans with Query Store.
- You have slow storage, which can increase your likelihood of having longer compilation times.
The General Purpose tier of Azure SQL Managed Instance and Azure SQL Database feature both slow storage and Automatic Plan Correction enabled by default. So, weirdly enough, your risks of suffering from this problem are high if you are an Azure SQL customer.
In the words of the great John Madden, that’s a heckuva bug.
Comments closed