Connecting to SQL Server when your default database is not available

One of our database on the development went in suspect mode today. This database was the default for a bunch of logins.  These people could not login now. Someone needed to use a different database but he couldn’t login because the database that was in suspect mode was the default database for the login he was using.

I told this person to click on the Options button in the connection dialog and specify another database. I guess there was an misunderstanding because this person couldn’t get it to work. This means it is time for a blog post.

Let's take a look how this all works

Here is a script that will create 2 databases

CREATE DATABASE Good
GO
 
CREATE DATABASE OopsBad
GO

Now create a new login named TestLogin with a password of Test. We are also adding the login we just created to the OopsBad database and we will make the login part of the db_owner role

USE [master]
GO
CREATE LOGIN [TestLogin] WITH PASSWORD=N'Test', DEFAULT_DATABASE=[OopsBad]
USE [OopsBad]
GO
CREATE USER [TestLogin] FOR LOGIN [TestLogin]
GO
USE [OopsBad]
GO
ALTER ROLE [db_owner] ADD MEMBER [TestLogin]
GO

Add the login we just created to the Good database as well and make the login part of the db_owner role

USE [Good]
GO
CREATE USER [TestLogin] FOR LOGIN [TestLogin]
GO
USE [Good]
GO
ALTER ROLE [db_owner] ADD MEMBER [TestLogin]
GO

Make sure that you can login with the TestLogin account

Now that you know that you can login with the TestLogin account, use another account and put the OopsBad database in offline mode

Take the database online

ALTER DATABASE OopsBad SET OFFLINE

Now if you try to login with the TestLogin account, you will see the following error

Here is what you need to do, on the connect to server window, click on the Options button

One the next screen, click on the Connection Properties tab, do not click on  Browse server... from the drop down.  If you click that you might have to wait for a long time

Instead just type in the database name, in our case the database name is Good

Click on Connect and you should be in....  That's it, pretty simple, you just have to know where to find it.

Interesting SQL related links for the week of Dec 09, 2016

Here are some interesting articles I read and tweeted about this past week, I think you will like these as well. If you are bored this weekend, some of these might be good for you to read


Transaction Commit latency acceleration using Storage Class Memory in Windows Server 2016/SQL Server 2016 SP1

SQL Server 2016 SP1 adds a significant new performance feature, the ability to accelerate transaction commit times (latency) by up to 2-4X, when employing Storage Class Memory (NVDIMM-N nonvolatile storage). This scenario is also referred to as “persistent log buffer” as explained below.

This enhancement is especially valuable for workloads which require high frequency, low latency update transactions. These app patterns are common in the finance/trading industry as well as online betting and some process control applications.

SQLskills holiday gift to you: all 2015 Insider videos

As we all wind down for the 2016 holiday season, we want to give the SQL Server community a holiday gift to say ‘thank you’ for all your support during 2016, and what better gift than more free content?!

As many of you know, I publish a bi-weekly newsletter to more than 13,500 subscribers that contains an editorial on a SQL Server topic, a demo video, and a book review of my most recently completed book. We’re making all the 2015 demo videos available so everyone can watch them – 25 videos in all, mostly in WMV format. I did the same thing the last few years for the 2014 videos, 2013 videos, 2012 videos, and 2011 videos.

Developers Choice: Query progress – anytime, anywhere

One of the most important actions when a performance issue hits, is to get precise understanding on the workload that’s executing and how resource usage is being driven. The actual execution plan is an invaluable tool for this purpose.

Query completion is a prerequisite for the availability of an actual query plan, but with LQS (Live Query Statistics), you can already get information about in-flight query executions (see this blog post), which is especially useful for long running queries, and queries that run indefinitely and never finish.

To look at in-flight query executions, the query execution statistics profile infrastructure must be enabled on demand.

Get All of the Freebies for “End-to-End Troubleshooting Checklist for Microsoft SQL Server”

One of my most enduring and popular presentations is called End-to-End Troubleshooting Checklist for Microsoft SQL Server”. In this presentation, I take you through my six-step checklist from detection of a performance issue on SQL Server through identification of the root cause to remediation and finally post-mortem steps to ensure the problem is prevented (or at least detected immediately) in the future.

Over the years, I’ve had many inquiries about the slides, T-SQL scripts, and additional troubleshooting information. I’m happy to report that I’ve finally collated all of the associated content from that presentation!

Selective XML Indexes: Not Bad At All

So what is a Selective XML index? It’s an index! For XML! Where you pick the parts of the XML to index. Other XML indexes are rather all or nothing, and can end up being pretty huge, depending on the size of your documents. I think they’re at least size of data, if I recall correctly. Let’s take a look at some examples.

sp_WhatsupQueryStore

The sp_WhatsupQueryStore Stored Procedure is a Microsoft SQL Server Stored Procedure that retrieves all kinds of information from the Query Store. By running the script on this website the sp_WhatsupQueryStore Stored Procedure gets installed in the "master" database of your SQL Server Instance.

After installation you can run the Stored Procedure as follows:

EXEC sp_WhatsupQueryStore @dbname, @timewindow, @topqueries, @return_store_config, @return_forced_plans, @return_top_duration, @return_top_cpu, @return_top_log_read, @return_top_log_write, @return_top_phys_read

Clustered Columnstore Index in Azure SQL Database

Columnstore index is the preferred technology to run analytics queries in Azure SQL Databases. We recently announced general availability if In-Memory technologies for all Premium databases. Similar to In-Memory OLTP, the columnstore index technology is available in premium databases.

The columnstore technology is available in two flavors; clustered columnstore index (CCI) for DataMart analytics workloads and nonclustered columnstore index (NCCI) to run analytics queries on operational (i.e. OLTP) workload. Please refer to NCCI vs CCI for the differences between these two flavors of columnstore indexes. The columnstore index can speed up the performance of analytics queries up to 100x while significantly reducing the storage footprint. The data compression achieved depends on the schema and the data, but we see around 10x data compression on average when compared to rowstore with no compression. This blog will focus on Analytic workloads using CCI but cover NCCI in a future blog.

When Did SQL Server Last Update That Statistic? How Much Has Been Modified Since? And What Columns are in the Stat?

Whether I’m working as a DBA, a consultant, a teacher, or just answering questions in my inbox, I always end up needing a script to inspect statistics one way or another.

Here are some freshly written scripts for a classic DBA question: what’s going on in my stats?

SQL Server + Java: What’s new

Java continues to be one of the most widely used programming languages for a variety of application scenarios and industries. The Microsoft JDBC Driver for SQL Server is used to connect Java applications to SQL Server, whether SQL Server is hosted in the cloud or on-premises, or provided as a platform-as-a-service.

With the release of SQL Server v.Next public preview on Linux and Windows, the ability to connect to SQL Server on Linux, Windows, Docker or macOS (via Docker) makes cross-platform support for all connectors, including the JDBC driver, even more important. To enable Java developers to use the newest SQL Server features, we have been updating the JDBC driver with client-side support for new features, including Always Encrypted and Azure Active Directory Authentication.

Microsoft R Server 9.0 now available

Microsoft R Server 9.0, Microsoft's R distribution with added big-data, in-database, and integration capabilities, was released today and is now available for download to MSDN subscribers. This latest release is built on Microsoft R Open 3.3.2, and adds new machine-learning capabilities, new ways to integrate R into applications, and additional big-data support for Spark 2.0.

This release includes a brand new R package for machine learning: MicrosoftML. This package provides state-of-the-art, fast and scalable machine learning algorithms for common data science tasks including featurization, classification and regression. Some of the functions provided include:

• Fast linear and logistic model functions based on the Stochastic Dual Coordinate Ascent method;
• Fast Forests, a random forest and quantile regression forest implementation based on FastRank, an efficient implementation of the MART gradient boosting algorithm;
• A neural network algorithm with support for custom, multilayer network topologies and GPU acceleration;
• One-class anomaly detection based on support vector machines.

You can learn more about MicrosoftML at this live webinar on Wednesday, December 14.

Released: Public Preview for Microsoft Azure SQL Database Management Pack (6.7.11.0)

We are working on significantly updating the Management Pack for Azure SQL Database.

This release will bring support for Elastics Pools and Azure AD Authentication among other new features. We are also working on handling monitoring of larger number of databases. We are expecting to improve the scale by the time we RTM. Here are some numbers to give you an idea for this public preview:

Improve query performance on memory optimized tables with Temporal using new index creation enhancement in SP1

With the introduction of the Temporal feature in SQL 2016 and Azure SQL Database, there is an ability to time travel through the state of data as it was at any given point of time. Alongside In-Memory OLTP, Temporal on memory optimized tables allows you to harness the speed of In-Memory OLTP, and gives you the same ability to track history and audit every change made to a record. Temporal added to memory optimized tables also allows you to maintain a “smaller” memory optimized tables and thereby a smaller memory footprint by deleting data that isn’t “hot” anymore from the current memory optimized table, which in turn moves it to the history table without having an external archival process to do that.

When memory optimized and temporal tables are combined, an internal memory optimized table is created in addition to the history table, as depicted in the diagram below. Data is flushed asynchronously from the internal in-memory History table to the disk based history table. The flush interval  isn’t currently configurable. Data is flushed when the internal table reaches 8% of the memory consumed by the current table, OR you can flush it manually by executing the procedure sys.sp_xtp_flush_temporal_history. The internal memory optimized table is created with the same column definitions as the current in-memory table, but with a single index.

Extended per-operator level performance stats for Query Processing

As requested by the community to complete the per-operator information, starting with SQL Server 2016 SP1 we are now exposing memory grant per grant iterator (such as Sorts and Hash Matches). These give you added insight into memory grants, and how overall memory usage is driven throughout execution.

In the October release of SSMS we exposed per-operator stats directly in the Properties window for each operator, but the memory grant properties are not there yet. These will be added to the properties window in an upcoming release of SSMS

Interesting SQL related links for the week of Dec 02, 2016

Here are some interesting articles I read and tweeted about this past week, I think you will like these as well. If you are bored this weekend, some of these might be good for you to read



Microsoft is putting reprogrammable chips into millions of servers

All the Internet giants, including Microsoft, now supplement their CPUs with graphics processing units, chips designed to render images for games and other highly visual applications. When these companies train their neural networks to, for example, recognize faces in photos—feeding in millions and millions of pictures—GPUs handle much of the calculation. 

Some giants like Microsoft are also using alternative silicon to execute their neural networks after training. And even though it’s crazily expensive to custom-build chips, Google has gone so far as to design its own processor for executing neural nets, the tensor processing unit.

Developers choice: Programmatically identify LPIM and IFI privileges in SQL Server

Lock Pages in Memory and Instant File Initialization privileges are couple of configuration settings which every DBA, SQL Server consultant or enthusiast have it in their checklist to ensure they see a predictable performance for their SQL Server instance. While Lock Pages in Memory privilege information is logged in SQL Error log, Instant File initialization information was first introduced in SQL Errorlog starting SQL Server 2016 RTM and later added to SQL Server 2014 with SP2.

When you are managing, administering or monitoring large deployment of SQL Servers, it is still cumbersome to programmatically query SQL Error log to check if these permissions are enabled for the SQL Server service account. With SQL Server 2016 SP1, we have added new columns in the DMV which now makes it easy to develop scripts to programmatically query and report whether Lock Pages in Memory and instant file initialization privileges are enabled on a given instance of SQL Server.

Introducing Batch Mode Adaptive Memory Grant Feedback

SQL Server uses memory to store in-transit rows for hash join and sort operations. When a query execution plan is compiled for a statement, SQL Server estimates both the minimum required memory needed for execution and the ideal memory grant size needed to have all rows in memory. This memory grant size is based on the estimated number of rows for the operator and the associated average row size. If the cardinality estimates are inaccurate, performance can suffer:

• For cardinality under-estimates, the memory grant can end up being too small and the rows then spill to disk, causing significant performance degradation compared to a fully memory-resident equivalent.
• For cardinality over-estimates, the memory grant can be too large and the memory goes to waste. Concurrency can be impacted because the query may wait in a queue until enough memory becomes available, even though the query only ends up using a small portion of the granted memory.

SQL Server on Linux: High availability and security

With SQL Server on Linux, Microsoft brings SQL Server’s core relational database engine to the growing enterprise Linux ecosystem. Both High Availability and Disaster Recovery (HADR) and security are aspects of SQL Server that are critically important for enterprises. This article highlights the HADR and security solutions for SQL Server on Linux that are available today, as well as the roadmap for what’s coming soon.

Using SQL Tools with SQL Server on Linux

Today, developers can use SQL Server in a variety of environments including on-premises, in datacenters, in virtual machines, in clouds such as Azure, AWS and Google, and also as a Platform as a Service (PaaS) offering with Azure SQL Database and Azure SQL Data Warehouse.

We recently announced SQL Server v.Next CTP1 on Linux and Windows, which brings the power of SQL Server to both Windows — and for the first time ever — Linux. Developers can now create applications with SQL Server on Linux, Windows, Docker, or macOS (via Docker) and then deploy to Linux, Windows, or Docker, on-premises or in the cloud.

As part of this announcement, we have released new SQL tools and also updated existing SQL tools. Developers can use these tools to connect to and work with SQL running anywhere, including SQL Server on Linux, Windows or Docker.

Reading 7 Things I Learned About Aurora at AWS re:Invent 2016

Richie and I attended the AWS re:Invent conference in Vegas last week. Here’s some of my favorite takeaways about Amazon Aurora, their homegrown relational database with MySQL compatibility.

Changing the SQL Server port on Linux

Today, I decided to see how I can change the port SQL Server is listening on



To see what port SQL Server is listening on, you can use the netstat command, here is what the output looks like when I run netstat -tulpn | grep sqlservr

I used grep to limit the output to lines that contain sqlservr only

Next, to change the port that SQL Server is listening on to 3000, I ran the following command

sudo /opt/mssql/bin/mssql-conf set tcpport 3000

I restarted SQL Server bu running the command systemctl restart mssql-server

Then I ran  netstat -tulpn | grep sqlservr again and as you can see the output now has 3000 as the port number

Now I tried using sqlcmd, I ran the following sqlcmd -S localhost -U SA

I got an timeout error

Finally I ran the sqlcmd command again but I added port number 3000, like this
sqlcmd -S localhost,3000 -U SA

As you can see, this worked and I could connect to SQL Server listening on port 3000 when supplying that to the sqlcmd command

How do we reset SQL Server back to the default port?
To reset SQL Server back to use the default port, run the command below

/opt/mssql/bin/mssql-conf unset tcpport

Here is a screenshot of running netstat, resetting the port, restarting SQL Server and running netstat again

You want to learn a little more?

We used tulpn as options in our netstat command. So what do all these options do?

[-t] 

tcp

[-u] 

udp

[-l]

Show only listening sockets

[-p]

Show the PID (process identifier) and name of the program to which each socket belongs.

[-n] 

Show numerical addresses instead of trying to determine symbolic host, port or user names.

On a Linux system to get help for a command, use man, this will bring up the user manual for that command

So if you run man netstat, you will see the following (I only pasted 1 page here, there are more)

man netstat

--------------------------

NETSTAT(8)                 Linux Programmer's Manual                NETSTAT(8)

NAME

       netstat  - Print network connections, routing tables, interface statis‐

       tics, masquerade connections, and multicast memberships

SYNOPSIS

       netstat  [address_family_options]  [--tcp|-t]   [--udp|-u]   [--raw|-w]

       [--listening|-l]     [--all|-a]     [--numeric|-n]    [--numeric-hosts]

       [--numeric-ports]           [--numeric-users]           [--symbolic|-N]

       [--extend|-e[--extend|-e]]  [--timers|-o] [--program|-p] [--verbose|-v]

       [--continuous|-c]

       netstat              {--route|-r}              [address_family_options]

       [--extend|-e[--extend|-e]]         [--verbose|-v]        [--numeric|-n]

       [--numeric-hosts] [--numeric-ports] [--numeric-users] [--continuous|-c]

       netstat {--interfaces|-i} [--all|-a] [--extend|-e[--extend|-e]] [--ver‐

       bose|-v]  [--program|-p]  [--numeric|-n]  [--numeric-hosts] [--numeric-

       ports] [--numeric-users] [--continuous|-c]

       netstat      {--groups|-g}       [--numeric|-n]       [--numeric-hosts]

       [--numeric-ports] [--numeric-users] [--continuous|-c]

 Manual page netstat(8) line 1/348 15% (press h for help or q to quit)


To see all my SQL Server on Linux posts, click here: SQL Server on Linux