A Fine Slice Of SQL Server
Today, we announced the general availability of SQL Server 2022, the most Azure-enabled release of SQL Server yet, with continued innovation across performance, security, and availability. This marks the latest milestone in the more than 30-year history of SQL Server.
Click through for the high-level overview of what’s in SQL Server 2022 and grab a copy to mess around with.
Comments closedAdam Zegelin takes us through full-text search options in PostgreSQL:
Full-text Search is a PostgreSQL® feature that facilitates the indexing of natural language text documents, and in the identification of indexed documents that match a given query. Matching documents can be sorted based on their relevance to the query, and document excerpts can be generated with the matching terms highlighted. A set of SQL data types, operators, and functions are provided to assist with the indexing, querying, and ranking of documents.
PostgreSQL uses the term document to mean any fragment of natural language text— essentially, strings containing human-readable words separated by whitespace and punctuation. Documents are often stored as text columns but can also be generated dynamically—such as by concatenating multiple columns together (even from multiple tables).
Click through for the tutorial.
Comments closedDanica Fine and Nikoleta Verbeck troubleshoot another common Apache Kafka issue:
It can be easy to go about life without thinking about them, but requests are an important part of Kafka; they form the basis of how clients (both producers and consumers) interact with data as it moves into and out of Kafka topics, and, in certain cases, too many requests can have a negative impact on your brokers. To understand how requests can affect the brokers, it’s important to be familiar with what happens under the hood when a request is made.
Read on to see how the process works under the covers, what kinds of metrics you can use to determine how well things are going, and what might be going wrong if you see certain symptoms.
Comments closedJana Sattainathan doesn’t have time to click-and-repeat:
This is something I had to do today. In this blog post, I am going to show you how you can disable or remove indexes matching certain name criteria or other condition(s) across multiple servers and databases in various tables. Usually, this is a very painful process if done by hand but with the fantastic work done by the dbatools team, it becomes quite easy.
Read on for the Powershell script.
Comments closedBrendan Tierney takes apart a phrase:
In the IT industry we hear the term “legacy” being using, but that does it mean? It can mean a lot of different things and it really depends on the person who is saying it, their context, what they want to portray and their intended meaning. In a lot of cases people seem to use it without knowing the meaning or the impact it can have. This can result in negative impact and not in the way the person intended.
Before looking at some (and there can be lots) possible meanings, lets have a look at what one person said recently.
Read on for a thoughtful reply to some marketing madness.
Comments closedGilbert Quevauvilliers gets the last word:
Power query can be so powerful and once again it came to my rescue.
I had a requirement where I wanted to append some text to the end of each of the column names in my table.
To do this I did the following below.
Click through for the solution.
Comments closedChris Webb reminds us that Power BI incremental refresh can lead to some fragmentation:
A lot of people are building large datasets in Power BI Premium nowadays, and if you’re building a large dataset you’re very likely to be using Power BI’s incremental refresh functionality with your fact tables or manually creating and refreshing partitions in them. If so, you should occasionally do a special kind of refresh to shrink the dictionaries on your fact tables.
Read on for a test of the most extreme scenario, though even less extreme versions can be bad.
Comments closedMatt Eland shows off the apply() function in Pandas:
Pandas is a wonderful library for manipulating tabular data with Python. Out of the box Pandas offers many ways of adding, removing, and updating columns and rows, but sometimes you need a bit more power.
In this article we’ll explore the
applyfunction and show how it can be used to run an operation against every row (or column) in your DataFrame – and why you might want to do that.
Read on to see how it works and what additional benefit it provides.
Comments closedSudhir Raparia doesn’t have time to wait:
Database Backup & Restore capabilities are crucial for ensuring Business continuity and Disaster recovery. Restore database operation is usually done in critical situations like hardware failure, application errors, ransomware attacks, accidental deletion of database etc., to restore a production database to latest known stable state. In such critical situations users would want to track the progress of restore operation accurately so that they can plan for subsequent actions and/or alternatives.
Currently in Azure SQL DB, you can view the database restore progress either using Portal or using T-SQL as follows:
Click through for information on that DMV, as well as a recent change to it in Azure SQL DB (though not yet Azure SQL Managed Instance).
Comments closedRobert Sheldon burns it all down:
In the last few articles in this series, you learned about three important data manipulation language (DML) statements: SELECT, INSERT, and UPDATE. The statements make it possible to retrieve, add, and modify data in a MySQL database. Another DML statement that is just as important is DELETE, which lets you remove one or more rows from a table, including temporary tables. In this article, I focus exclusively on the DELETE statement to help round out our discussion on the core DML statements in MySQL. Overall, the DELETE statement is fairly basic, but one that’s no less necessary to have in your arsenal of DML tools.
Read on to see how the DELETE statement works and the minor differences from SQL Server.