We have a series of views in our organization’s application database. The views definitions are all static queries that consist of few or many condition clauses.
When the application first started with the initial data, the views operated normally, but after a while, after a period where data volume increased, the application’s performance time, through the views usage, degraded.
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Filtered indexes are well documented, as they have been around in SQL Server for almost six years now. Despite their longevity and usefulness, discussions of them tend to be very simple overviews using simple queries and not digging too deeply into more precise costs and benefits. This article is inspired by a production problem that cropped up recently involving a filtered index that illustrated that general knowledge of their function was not as complete as it should have been.
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In a previous chapter, we learned how to use the Tuning Advisor to analyze queries and receive recommendations about indexes, partitions and statistics. In this new chapter, we will learn how to use the command line tool called DTA. The DTA is the command line of the Tuning Advisor.
The DTA is a very powerful tool that can be used to automate some tuning tasks. It can be used combined with the SQL Agent, SSIS, or customized and external tools like programs made in C# or Java.
In this article, we will show how to use this tool.
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This article is a continuation of a guide where we are checking all the available backup preferences for a database contained in an Availability Group.
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The indexes in many cases are great solutions to solve performance problems. For some problems, they are magical and very cheap solutions. In this chapter, we will show a demo of the SQL Server Tuning Advisor, which is a tool that comes with the SQL Server Installation. We will also use the SQL Server Profiler to generate the information for the Tuning Advisor.
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Since the AlwaysOn Availabiliy Groups feature was introduced, we got new options to make the backups strategy more complete, but also more complex. Taking an advantage of secondary replicas, we can offload both, the FULL and even the Transaction Log backups from the Primary Replica to the Secondary, leaving the Primary replica dedicated to serve the production application.
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The Query Store is a new feature in SQL Server 2016 that will greatly improve the process of performance tuning! The biggest limit of the query plan cache and the dynamic management views that relates to it is that it is very temporary. Queries are only accessible for as long as they are in cache, and as a result there is no way to travel back in time to determine what happened at 9am yesterday, or why performance worsened over a week-long period.
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CXPACKET is one of the famous wait types that database administrators are experiencing. Before moving into the details of the CXPACKET wait type, first, let us discuss the waits in SQL Server in brief.
SQL Server is a mini operating system. When SQL Server is executing any task and if for any reason it has to wait for resources to execute the task, it will wait in a list until it gets the relevant resources. This list is called the Waiter list or suspended list. This is not a queue as whenever that task is ready with required resources it will move to the runnable queue which means that it is ready to execute whenever the processor is free to execute. Depending on the type of wait, there are more than 200 wait types. CXPACKET, WRITELOG, ASYNC_NETWORK_IO are the most common wait types. This is a very brief discussion about waits. For any case where this is not clear, it will be better to get more details from other sources as this article is not intended to discuss waits in detail.
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Along with the release of SQL server 2016 CTP 3 now comes the preview of a brand new feature for on premise databases – the Query Store. This feature enables performance monitoring and troubleshooting through the log of executed queries.
This blogpost will cover the following aspects of the Query Store feature:
Here we are with the last part of this series of articles! In this article we are going to see two curiosities:
So, let’s start!
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In continuation to the Availability Groups series, here you have another curiosity coming to make your job easier and help you to provide a solution to your customers 🙂
This time we will be talking about listeners. Basically, we will be talking about the limitation of one listener per Availability Group. If you never tested / tried this, this is what happens when you already have a listener in the Availability Group, and try to create another one:
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In continuation to the previous article, where we talked about what happens when I add a readable secondary and why there are different options to control connections to the AG, it’s time to continue and demystify more curiosities about the beloved Availability Groups!
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In this new chapter, we will show how to use the Microsoft Portal to monitor the Virtual Machines with SQL Server Installed. We will show how to do it with the current Portal and the New Microsoft Azure Portal. We will check how to monitor performance, watch the logs, review the settings and change them. Read more »
With the release of SQL Server 2016 also comes a great new feature to get a live view of the current execution plan for an active query.
This blogpost will cover the aspects of this new feature including:
We all love Availability Groups! Since its introduction in the SQL Server 2012, some things changed. In the beginning it was seen as “just a replacement for the database mirroring”, but when we discovered that this would support readable secondary’s, the possibility of having a listener and get rid of the shared storage – even being based on a Failover Cluster – we saw that Availability Groups is a special feature. Read more »
In earlier chapters, I show you how to create your Virtual Machine in Azure using Power Shell.
In this new chapter, I will show you how to get information about your VM machine already created. We will use PowerShell cmdlet commands to retrieve the information.
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In-memory OLTP is a revolutionary tool introduced on SQL Server 2014. On SQL Server 2016 this will be even better, with a broader surface of supported tools. Check this article to know the news.
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We have already configured our Availability Group, now we need to make it flexible and accessible. It’s time to check on how to create a listener in order to make a single access point for you AG!
In continuation to our previous article, we are going to pass to another phase of this setup, as we already have our database in sync and safe, or highly available, depending of the chosen mode/architecture.
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In continuation to the part 1, on how to setup a SQL Server Availability Groups, let’s now check how to create the Availability Group itself and put the databases in sync.
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In this article we are going to explore how to configure an Availability Group between a clustered instance and a standalone instance, showing, step-by-step, how to setup a possible Disaster Recovery environment.
Introduced on SQL Server 2012, the Availability Groups brought the expectation to be an improved version of the database mirroring, which will be discontinued soon. The AlwaysOn Availability Groups was improved on SQL Server 2014, giving the capability of have more replicas, better troubleshooting possibilities and improving its availability. Comparing the Availability Groups with the database mirroring, in a very high level, we gained the possibility of have a listener to dynamically redirect the connection to the current active instance and also the capability of distribute the read workload between readable replicas. However, only the primary replica is able to write.
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Modeling for the xVelocity/Vertipaq engine is a completely different beast than modeling for your trusty multi-dimensional SSAS cubes.
In-memory = blazingly fast; At least that’s what you would think.
As Tabular models gain popularity with business users and developers alike, we’re starting to see that this isn’t always the case.
We’re going to take a look at some of the common errors and mistakes and how to avoid them.
And since the PowerPivot engine is the same – you will learn how to tune your PowerPivot-based Excel workbooks as well.
In sequence of the first article of the In-Memory OLTP Series that explained the main pillars, database creation and a briefly overview of the checkpoint files, now we will take a look into the table creation and data types allowed in the In-Memory OLTP feature in SQL Server 2014.
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When creating a hash index in a memory optimized table we need to define a value for the bucket count. Think twice before set a random value, you may pay the price later… On this article we will explain the effects of a bad defined bucket count and how to monitor it.
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In our last get together I mentioned that oft times SQL Server reports are created due to a dire business need to be used once and never again. Further, some reports that we believe are not often used could be “top of the pops” unbeknown to us. A guess as to a number of times a report is used per month, in addition to the statistics behind each report should not be guesswork, but rather monitored actively to ensure that frequently used reports are both efficient and effective. Further, those reports that are either not used or have not been run in quite some time, should perhaps be removed in order to keep the server clean and not cluttered.
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In sequence of the first article about the server memory importance, we will check another In-Memory OLTP key point: The Checkpoint files. Check what wrong can happen, and how to avoid this!
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