I’m a data geek 🤓 In fact, I like data so much that I have made it my career! I work with Azure Data and the Microsoft Data Platform, focusing on Data Integration using Azure Data Factory (ADF), Azure Synapse Analytics, and SQL Server Integration Services (SSIS).
In this category, I write technical posts and guides, and share my experiences with certification exams. You can also find a few interviews with Azure and SQL Server experts!
Azure Data posts may cover topics like Azure Data Factory, Azure Synapse Analytics, Azure SQL Databases, and Azure Data Lake Storage. Microsoft Data Platform posts may cover topics like SQL Server, T-SQL, and SQL Server Management Studio (SSMS), and SQL Server Integration Services (SSIS).
T-SQL Tuesday #66 is hosted by me (yay, fun!) and is all about monitoring. We all monitor something while working with SQL Server, and there are so many topics to choose from. As a Data Warehouse developer I use Adam Machanic’s sp_WhoIsActive all the time, I look at the Integration Services Dashboard in SSMS to monitor SSIS package executions and I check the Job Activity Monitor for a quick overview of what’s currently running on our servers.
However, I decided to write about a custom Real Time Monitoring solution we use in my company (Storebrand) that my coworkers in Lithuania created. I couldn’t resist this opportunity to show one of our cool solutions that I get to use and to brag about how talented my coworkers are 👏🏻
Welcome to T-SQL Tuesday #66! My name is Cathrine Wilhelmsen (@cathrinew) and I’m very happy to be your host for the T-SQL Tuesday on May 12th, 2015. The topic of the month is monitoring.
Much Monitoring in the Month of May
We all monitor something while working with SQL Server: Maybe you’re a DBA who monitors database performance, an SSIS developer who monitors job and package execution, an application developer who monitors queries or a BI analyst who monitors report usage? Do you use T-SQL or PowerShell scripts? Have you created your own monitoring reports or applications? Have you invested in a complete monitoring solution from a vendor? What is monitored manually and what is automated with alerts? If a brand new SQL Server professional in your role asks you for advice, what do you say is the number one most important thing to monitor? Have you ever stayed awake for a week solving a problem that could have been avoided with proper monitoring? Did you implement a monitoring solution that saved your company?
Inserts, updates and deletes on large tables can be very slow and expensive, cause locking and blocking, and even fill up the transaction log. One of the main benefits of table partitioning is that you can speed up loading and archiving of data by using partition switching.
Partition switching moves entire partitions between tables almost instantly. It is extremely fast because it is a metadata-only operation that updates the location of the data, no data is physically moved. New data can be loaded to separate tables and then switched in, old data can be switched out to separate tables and then archived or purged. All data preparation and manipulation can be done in separate tables without affecting the partitioned table.
T-SQL Tuesday #65 is hosted by Mike Donnelly (@SQLMD). There is no specific topic to write about this month, Mike simply wants us to learn something new and then write a blog post to teach it to others. I want to share something that I only recently learned, something I wish I had known about years ago, something that became part of my toolbox as soon as I discovered it: the Numbers Table. It is so simple and solves so many problems that everyone should know about it 🤓
A Numbers Table (perhaps most known as a Tally Table, sometimes called an Auxiliary Table of Numbers and even referred to as the Swiss Army Knife of SQL Server) is a one-column helper table that contains the numbers 1, 2, 3, 4, 5 and so on all the way up to the-highest-number-you-could-possibly-need.
It can be used to replace slower loops and row-by-row operations with faster set-based operations, generate dates, split strings, find gaps in data sets, expand data sets, insert test data and probably hundreds of other things. There are so many great and detailed articles already published about this topic, so I will stick to the T-SQL Tuesday topic of “Teach Something New” and share the two most recent things I learned: different ways to create a numbers table, and different ways to quickly insert test data by using a numbers table.
There are many benefits of partitioning large tables. You can speed up loading and archiving of data, you can perform maintenance operations on individual partitions instead of the whole table, and you may be able to improve query performance. However, implementing table partitioning is not a trivial task and you need a good understanding of how it works to implement and use it correctly.
Being a business intelligence and data warehouse developer, not a DBA, it took me a while to understand table partitioning. I had to read a lot, get plenty of hands-on experience and make some mistakes along the way. (The illustration to the left is my Table Partitioning Cheat Sheet.) This post covers the basics of partitioned tables, partition columns, partition functions and partition schemes.