A Fine Slice Of SQL Server
I will leave the finer points of the problems with MERGE statements to the Michaels and Aarons of the SQL Server world.
This is just a… But why? post about them, because I’m honestly a bit puzzled by this missing implementation detail.
Read on to see what has Erik wishing could be true.
Comments closedJoe Celko defends the honor of the check constraint:
The problem is that newer SQL programmers (and even some more experienced ones) don’t take advantage of these constraints. Consider this slight rewrite of an actual posting on an SQL forum. In the original, the poster thought that identifiers should be integers and that ISO–11179 naming rules do not apply, so I cleaned it up a little, but this will make my point.
Click through to learn more about check constraints.
Comments closedCary Huang digs into Postgres:
I wrote another blog to briefly explain the responsibility of each query processing stage. You can find it here. In this blog. There is one that focuses primarily on the planner module that you can find here. In this blog, we will focus on the executor part of the query processing, which is the entry point to “communicate” with other PostgreSQL internal modules to collect the correct data for the query.
In fact, executor may not be the best term to describe this stage. In the PostgreSQL source code, it is actually “packaged” in another object called “portal”. Often, and it has 2 potential paths to take, the “executor” path, or the “process utility” path. Very often, we just call this stage as “executor” rather than “portal”, because executor handles most of the DML query types that involve SELECT, INSERT, UPDATE, DELETE…etc and it has to process them according to the query plan created by the “planner” module.
Read on to learn more about the portal and its two component parts.
Comments closedMarco Russo provides an option:
DAX is not like M when it comes to data manipulation, and it is not supposed to do that. However, if you need something in DAX similar to Table.FromList in M, this blog post is for you.
If you have a list of values in a string in DAX and you want to obtain a table with one row for each item in the list, you can do the following:
Definitely an example of “There’s a better way to do this than to use DAX” but sometimes you’re stuck, I suppose.
Comments closedJosephine Bush continues a series on modern data warehousing:
In today’s data-driven world, having the right tools to manage and process large datasets is crucial. That’s where Azure Data Lake Storage (ADLS) and Azure Data Factory (ADF) come in handy, making it easier than ever to store and transform your data. In this post, I’ll show you how to set up ADLS to store your Parquet files and configure ADF to manage your data flows efficiently.
Read on for an overview of both technologies.
Comments closedTom Zika performs an experiment:
In SQL Server, using the
KILLcommand to terminate a session results in an entry being logged in the error log.
This raises the question: Does theALTER INDEX REBUILDcommand with theWAIT_AT_LOW_PRIORITYoption also log its actions in the error log?
Tom does violate Betteridge’s Law of Headlines, but you should read the post regardless.
2 CommentsSteven Sanderson has me wondering who Greg is and why he gets an expression of his own:
If you’ve ever worked with text data in R, you know how important it is to have powerful tools for pattern matching. One such tool is the
gregexpr()function. This function is incredibly useful when you need to find all occurrences of a pattern within a string. Today, we’ll go into howgregexpr()works, explore its syntax, and go through several examples to make things clear.
Read on to learn more about the global regular expression function and how it works.
Comments closedSandeep Pawar has a script for us:
Sharing a function I have been using to get all the Fabric tenant settings and the description of each setting.
Read on for a quick note and the Python function that does the job.
Comments closedEduardo Pivaral does some work:
Healthy code should not include passwords, keys, or secrets in the source code. Sometimes, developers hard-code sensitive information while testing new features but forget to remove it afterward.
How can we validate code without including sensitive information so we can take action before we publish or share code?
Click through for a couple of options. If you do have GitHub Advanced Security (part of GitHub Enterprise Cloud), you can also create a custom pattern for secret scanning that can include passwords, database connection strings, and the like.
Comments closedSemab Tariq takes us through a pair of replication options:
In the world of database replication, choosing between synchronous and asynchronous methods can have a big impact on how reliable, consistent, and fast your data is.
This blog dives into what these methods are, how they work, and when you might want to use one over the other. Whether you’re trying to keep your data super safe or just want it to move quickly, we’ll break down everything you need to know about synchronous and asynchronous replication in PostgreSQL.
Read on for a quick overview of streaming replication and the differences between asynchronous and synchronous options.
Comments closed