Showing posts with label Howto. Show all posts
Showing posts with label Howto. Show all posts

## Friday, November 23, 2018

### Happy Fibonacci day, here is how to generate a Fibonacci sequence in SQL

Image by Jahobr - Own work, CC0, Link

Since today is Fibonacci day I decided to to a short post about how to do generate a Fibonacci sequence in T-SQL. But first let's take a look at what a Fibonacci sequence actually is.

In mathematics, the Fibonacci numbers are the numbers in the following integer sequence, called the Fibonacci sequence, and characterized by the fact that every number after the first two is the sum of the two preceding ones:

1, 1, 2, 3, 5, 8, 13, 21, 34, ...

Often, especially in modern usage, the sequence is extended by one more initial term:

0, 1, 1, 2, 3, 5, 8, 13, 21, 34, ...

November 23 is celebrated as Fibonacci day because when the date is written in the mm/dd format (11/23), the digits in the date form a Fibonacci sequence: 1,1,2,3.

So here is how you can generate a Fibonacci sequence in SQL, you can do it by using s recursive table expression.  Here is what it looks like if you wanted to generate the Fibonacci sequence to up to a value of 1 million

```;WITH Fibonacci (Prev, Next) as
(
SELECT 1, 1
UNION ALL
SELECT Next, Prev + Next
FROM Fibonacci
WHERE Next < 1000000
)
SELECT Prev as Fibonacci
FROM Fibonacci
WHERE Prev < 1000000```

That will generate a Fibonacci sequence that starts with 1, if you need a Fibonacci sequence that start with 0, all you have to do is replace the 1 to 0 in the first select statement
```
```
```;WITH Fibonacci (Prev, Next) as
(
SELECT 1, 1
UNION ALL
SELECT Next, Prev + Next
FROM Fibonacci
WHERE Next < 1000000
)
SELECT Prev as Fibonacci
FROM Fibonacci
WHERE Prev < 1000000
```

Here is what it looks like in SSMS

Happy Fibonacci day!!

I created the same for PostgreSQL, the only difference is that you need to add the keyword RECURSIVE in the CTE, here is that post  Happy Fibonacci day, here is how to generate a Fibonacci sequence in PostgreSQL

## Saturday, May 13, 2017

### All the Build 2017 data related sessions in 1 spot, SQL Server, CosmosDB, Azure SQL DB and more

Are you bored this weekend? No problem, I have got you covered, I have put together a page with all the data related sessions from the build 2017 conference. I have embedded the videos and also added links to the page at the channel 9 site. I have also added links to the presentations and source code if it was available.  I have arranged this in 4 categories:

SQL Server
Azure SQL DB
CosmosDB
The rest of the sessions

This way the sessions are not all intermingled

## SQL Server

Securing your app data with Microsoft SQL Server 2017
by Tommy Mullaney

Join us for an overview of strategy and best practices to build secure applications using SQL Server. SQL Server offers a versatile toolset of security capabilities, which enable you to protect sensitive data and meet stringent compliance requirements. You’ll leave with an understanding of how these capabilities fit together to protect your application as a whole, including the new security enhancements available in the latest version of SQL Server.

Evolving SQL workloads from software to SaaS: Data for devs immersion
by Tara Shankar Jana

In this modern era; applications must recover from user errors efficiently, must be optimized for transactional performance, provide real-time insights into app transactions, must be secure and complaint, and support seamless integration to cloud, hybrid scenarios and other data types/systems. These applications must also learn and adapt to deliver more powerful experiences using cloud-based data services, applications, and intelligence. In this session we use a scenario-based hands-on lab program (immersion), to offer you a cohesive and consistent experience to build modern on-premises/cloud based applications with intelligence. Build hack-free, high performance, scalable applications using Microsoft SQL Server, Microsoft ML and Azure data services.

Advanced SQL Server on Linux (Docker) via Entity Framework (EF)
by Tara Shankar Jana

It’s SQL Server as you already know it today, but it’s now native to Linux. It works with your data, your favorite tools, application frameworks (Entity Framework) and programming languages. In this session, we pull the code for an application running in cloud to a Linux-based machine. We test and enhance the application for performance (using EF, in-memory) and security against SQL vNext (Linux). Then we re-deploy the changes using DevOps to Azure with just a flip of d, show how the application works across platforms, on-premises, and in the cloud. Best part, all of it will be done in ten minutes.

SQL Unplugged
by Scott Klein, Rohan Kumar

In this Channel 9 Live session we'll discuss all things SQL

Serving AI with data: How to use R, Python, and machine learning with Microsoft SQL Server 2017
by Umachandar Jayachandran, Nellie Gustafsson

In this session, learn how to use R and Python to perform statistical and machine learning tasks in SQL Server 2017. Also, learn how to operationalize your R or Python scripts using the SQL Server integration.

Microsoft SQL Server 2017 in the modern datacenter: how to run on Linux, Docker, OpenShift, and Kubernetes
by Travis Wright, Tobias Ternstrom

With the on-premises data center evolving into a private cloud, the fast pace of innovation in public clouds, and the strong interest in container technology it begs the question: How do you run a database in this new environment? In this session we examine what it means that SQL Server is evolving to support both Windows and Linux, including running inside a container on both platforms. Should you run SQL Server inside a Docker container? How does it play with orchestration technologies like OpenShift and Kubernetes? The brief answer is that we believe SQL Server should be ubiquitous and run in our customers environment of choice. Come to the session to hear the long answer with a bunch of demos!

How to do Predictive Modelling using R and SQL Server ML Services
4 days ago  by Umachandar Jayachandran, Nellie Gustafsson

Learn how to use R scripts from T-SQL to perform training and scoring and leverage parallelism and streaming capabilities to get better performance.

Built-in machine learning in Microsoft SQL Server 2017 with Python
by Sumit Kumar

Machine learning services in SQL Server 2017 provides Python support for in-database machine learning, now. In this session we show the basics of how to run Python code in SQL Server. We then discuss how any app that can talk to SQL Server can get intelligence from machine learning models running in SQL Server. We showcase an app that uses a Python-based deep learning model built and deployed in SQL Server. The model leverages an open source deep learning framework running with SQL Server and utilizes GPU for boosting model training performance.

Modernize your database development lifecycle with SQL Server Data Tools in Visual Studio
2 days ago  by Tara Raj

Learn how SQL Server Data Tools (SSDT) turns Visual Studio into a powerful environment for database development. Easily build, debug, maintain, and refactor databases inside Visual Studio with a declarative model that spans all the phases of database development and easily enables continuous integration and deployment for your databases. Work offline with a database project, or work directly with a connected database instance in Azure SQL Database, Azure SQL Data Warehouse, and SQL Server running on Windows, Linux, or Docker, on-premises or in any cloud.

## Azure SQL DB

Get to the cloud faster with Azure SQLDB Managed Instance and Database Migration Service
by Lindsey Allen, Harini Gupta

A new, expanded Azure SQL Database offers fully-managed server instance with greater compatibility with SQL Server application features and more, and the ability to move hundreds of databases at once using the Database Migration Service. It provides security isolation with Azure Virtual Network, along with built-in HADR, built-in intelligent performance tuning, and intelligent security services that are already available in Azure SQL Database. To reduce the friction of transitioning your relational database estate to public cloud, expanded Azure SQL Database provides SQL Server application compatibility including commonly used cross database references using three-part names, CLR, SQL Agent, Transactional Replication, Change Data Capture, Service Broker, and a lot more. We showcase a five-step seamless migration experience from your on-premises SQL Server instances to expanded Azure SQL Database using the newly announced Azure Database Migration Service.

Migrating Oracle database to the Azure SQL DB with Database Migration Service
by Shamik Ghosh, Alexander Ivanov

In this virtual session, you learn how to assess, remediate and migrate the schema, data, and server artifacts from on-premises Oracle instances to Azure SQL DB. We walk you through an end-to-end experience using Azure data migration tools and services to help solve your database migration needs.

How to build global-scale applications with Microsoft Azure SQL Database
by Rohan Kumar, Bob Strudwick

Join us in this session to learn how to build a global-scale IoT application by walking through a sample application and real-world customer case study. Gain insight on building an IoT application on a fully managed Azure database as a service, with built-in intelligence for performance, cost and security, dynamic scaling and hassle-free HADR, and infrastructure maintenance. We show you how to use Azure SQL Database enterprise grade in-memory engines to handle high volume and high concurrent transactions; while running real-time analytics queries on the same database. New features are released in Azure SQL Database in fast cadence; we show you the new Graph processing in the context of an IoT scenario, Adaptive Query Processing, predictive analytics, and the first in market built-in homomorphic data encryption feature for securing data at rest and in motion. It will be a fun learning hour.

Design Patterns for SaaS applications on Azure SQL Database
by Julie Strauss, Bill Gibson

Experience the power of building multi-tenant SaaS applications on Azure SQL Database, Microsoft’s fully managed database as a service platform: Using a sample SaaS application, we walk through a series of SaaS-focused design and management patterns that have been distilled from work with a multitude of customers. Patterns spans from multi-tenant provisioning, schema management, performance monitoring and management to operational analytics. The code for the sample application, plus management scripts, ARM templates and tutorials, will be available for download in an easy-to-explore “SaaS-in-a-Box” package, enabling you to jump-start your own SaaS application.

## CosmosDB

CosmosDB
by Seth Juarez, Rimma Nehme

In this session we meet with Rimma Nehme and Seth Juarez to discuss some of the latest Build 2017 announcements around CosmosDB

Azure Cosmos DB: Build planet scale mobile apps in minutes
by Kirill Gavrylyuk

This session has no description, but the video is below

Azure Cosmos DB: API for MongoDB
by Andrew Hoh

Azure Cosmos DB (formerly known as Azure DocumentDB) natively supports multiple APIs; one of which is the API for MongoDB. Use existing code, applications, drivers, and tools to work with Azure Cosmos DB. Benefit from the fully managed and scalable Azure database, while continuing to use familiar skills and tools for MongoDB. Come and watch this video to learn about the feature and how to migrate to this cosmic-scale database, Azure Cosmos DB.

Azure Cosmos DB: NoSQL capabilities everyone should know about
by Aravind Ramachandran

Microsoft Azure provides a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development. As a schema-free NoSQL database, the service provides rich and familiar SQL query capabilities with consistent low latencies on JSON data - ensuring that 99% of your reads are served under 10 milliseconds and 99% of your writes are served under 15 milliseconds. These unique benefits make it a great fit for web, mobile, gaming, IoT, AI, and many other applications that need seamless scale and global replication. Come and learn about the NoSQL capabilities in Azure Cosmos DB that every developer should know about.

A lap around Azure HDInsight and Cosmos DB Open Source Analytics + NoSQL
by Andrew Liu, Raghav Mohan

Recently, we released the Spark Connector for our distributed NoSQL service – Azure Cosmos DB (formerly known as Azure DocumentDB). By connecting Apache Spark running on top Azure HDInsight to Azure Cosmos DB, you can accelerate your ability to solve fast-moving data science problems and machine learning. The Spark to Azure Cosmos DB connector efficiently exploits the native Cosmos DB managed indexes and enables updateable columns when performing analytics, push-down predicate filtering against fast-changing globally-distributed data, ranging from IoT, data science, and analytics scenarios. Come learn how you can perform blazing fast planet-scale data processing with Azure Cosmos DB and HDInsight.

## Data lakes, U-SQL, Azure DBMS  and the rest

How to get started with the new Azure DBMS for PostgreSQL.
by Eric Spear, Irakliy Khaburzaniya, Sunil Kamath

Join this session to learn about Microsoft’s latest announcement of managed PostgreSQL database on Azure. In this breakout, we will learn from two early adopting customers, how they've leveraged this latest database service to innovate faster. We will learn from their experience of using the managed PostgreSQL service, including migrating to the service, and discuss next steps in their application journey. We will walk through some of the key service features and discuss how you as a developer can migrate your existing applications or develop new applications that use this managed PostgreSQL in Azure. If you’re a developer with applications that use PostgreSQL today, whether on-premises or cloud, and want to learn about how this new managed service can help, this session is for you!

How to get started with the new Azure DBMS for MySQL.
by Gebi Liang, Jason M. Anderson, Matt Williams

Join this session to learn about Microsoft’s managed MySQL offering in Azure. We’ll walk through Microsoft’s strategy for supporting Open-Source database systems in Azure and what it means to you as a developer as you look to develop or deploy applications that use MySQL in Azure. An overview of the architecture of the service along with how Azure Database for MySQL is integrated with other Azure Services such as Web Apps will also be discussed and demo’d. If you’re a developer with applications using MySQL today, whether on-prem or already in Azure today, this session is for you!

How to serve AI with data: The future of the Microsoft Data Platform
by Joseph Sirosh, Alex Miller

The cloud is truly becoming the “brain” for our connected planet. You’re not just running algorithms in the cloud, rather you’re connecting that with data from sensors from around the world. By bringing data into the cloud, you can integrate all of the information, apply machine learning and AI on top of that, and deliver apps that are continuously learning and evolving in the cloud. Consequently, the devices and applications connected to cloud are learning and becoming increasingly intelligent. Please join us on a journey through the core new patterns that are emerging as we bring advanced intelligence, the cloud, IoT, and big data together.

How to run AI at Petabyte Scale with cognitive functions in the Azure Data Lake
by Wee Hyong Tok

In this session, learn how you can use Azure Data Lake (ADL) for doing Big Cognition on raw customer support data. Learn how you can use ADL to perform key phrase extraction, sentiment analysis, and how you can use R/Python scripts for support volume forecasting. In addition, learn how you can use federated queries in ADL with Azure SQL Database. Discover how you can pull all these insights into an Azure SQL Data Warehouse, and using Azure Analysis Services to enable interactive analysis of the processed data. Join us for this exciting session as we show how you can develop intelligent applications by using the insights derived from processing massive Petabyte-scale datasets.

Image processing at scale using U-SQL in Azure Data Lake
by Saveen Reddy

Making use of cognitive capabilities such as Image OCR or Sentiment Analysis of text is straightforward with small datasets of a few terabytes. But, at the scale of hundreds of terabytes or even a petabyte, you need a different approach to that can massively scale out *AND* be simple to build. Azure Data Lake offers a straightforward way of programming using .NET code against these massive Petabyte-scale datasets without the need to become a deep expert in distributed computing, big data technologies, or machine learning.Link to Build site:

Lift and shift any runtime into U-SQL for large scale processing
by Michael Rys

One of U-SQL’s major strengths is to scale out user code over your large data lake assets. This presentation first shows how we have used the U-SQL extensibility model to give you access to Python and R and then shows how to run Scala from within U-SQL.

There you have have a bunch of data related sessions for your viewing pleasure

## Monday, April 24, 2017

### How to shut down SQL Server

The question how to shutdown SQL Server came up at work last week, I figured it would be a nice topic for the newer DBAs and SQL Server programmers

Note: I assume SQL Server is not part of a clustered environment here, if your SQL Server instance is part of a cluster, then use the failover cluster manager instead!

There are a bunch of way to shut down SQL Server, here is how you can do it

Configuration Manager

To shut down SQL Server for the SQL Server Configuration Manager, navigate to your instance, right click and select Stop

SSMS Object Explorer

The process from SSMS is very similar to Configuration Manager, right click on the instance and select Stop

Shutdown command

From SSMS open a new query window and type shutdown or shutdown with nowait

Unless the WITHNOWAIT option is used, SHUTDOWN shuts down SQL Server by:

• Waiting for currently running Transact-SQL statements or stored procedures to finish. To display a list of all active processes and locks, run sp_who and sp_lock, respectively.
• Inserting a checkpoint in every database.

That seems kinda dangerous can someone pass that command to a proc by masking it?

```declare @d varchar(30)= reverse('tiawon htiw nwodtuhs')
exec(@d)
```

The SHUTDOWN statement cannot be executed within a transaction or by a stored procedure. Msg 0, Level 11, State 0, Line 3 A severe error occurred on the current command. The results, if any, should be discarded.

That is good to know  :-)

Command prompt

Open a command prompt as administrator and type net stop MSSQLSERVER

```Microsoft Windows [Version 10.0.14393]

C:\WINDOWS\system32>net stop MSSQLSERVER
The SQL Server (MSSQLSERVER) service is stopping.
The SQL Server (MSSQLSERVER) service was stopped successfully.

C:\WINDOWS\system32>net start MSSQLSERVER
The SQL Server (MSSQLSERVER) service is starting.
The SQL Server (MSSQLSERVER) service was started successfully.

C:\WINDOWS\system32>
```

To start SQL Server again, change net stop to net start

Below are a couple of more ways but you should really not be using those!!

Yes, you can kill SQL Server from task manager

You can use the plain old DOS command taskkill as well

That is one way of course but you might get a bunch of people yelling at you

Unplug the power to your server after making sure you have no UPS battery backup plugged in
Great way to test recovery... .. sarcasm people.....

Shutdown the data center
You laugh but this actually happened to me once, someone did some work and shut down the whole development part of the data canter. We had SQL Server 2000 running on NT 4, it was not restarted in 6 years (meaning wasn't patched either) It was an isolated box, internal ip, couldn't be reached from outside the dev network

There you have all the ways that you can use to shut down SQL Server

## Friday, December 09, 2016

### 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

GO
```

```USE [master]
GO
GO
GO
GO
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
GO
USE [Good]
GO
GO
```

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.

## Sunday, November 27, 2016

### 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
[--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]

[--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

## Saturday, November 26, 2016

### BULK INSERT with a file containing linefeeds gotcha

I blogged about this before but someone ran into this issue again at work so I thought it made sense to revisit this.

I prefer to use BULK INSERT or bcp as much as possible, this is especially true if all I need to do is dump the file into a table. If there is a need to do complex stuff,  I will use SQL Server Integration Services or Informatica. These days files are generated by all kinds of systems, these can be Windows, *nix, Mac, Raspberry Pis, IoT systems and many other systems.

If you get an error importing one of these files, your first course of action is to open one of these files in something like Notepad++ or Editplus.  Notepad++ and Editplus have more functionality and are many times faster than notepad. The nice thing about either of these is that you can see control characters.

See how you can see the linefeeds here? You cannot do that in notepad

So let's say you get a file where the row terminator is a linefeed, how would you specify that as a row terminator in BULK INSERT?

You can try n which stands for newline

```BULK INSERT SomeTable
FROM 'D:\JunkdrawImportMe.txt'
WITH (FIELDTERMINATOR = 't',
FIRSTROW =2,
ROWTERMINATOR = 'n')```

Nope, that doesn't work, you get 0 rows inserted

You can try r which stands for carriage return

```BULK INSERT SomeTable
FROM 'D:\JunkdrawImportMe.txt'
WITH (FIELDTERMINATOR = 't',
FIRSTROW =2,
ROWTERMINATOR = 'r')
```

Nope, that doesn't work either, you get 0 rows inserted

```BULK INSERT SomeTable
FROM 'D:\JunkdrawImportMe.txt'
WITH (FIELDTERMINATOR = 't',
FIRSTROW =2,
ROWTERMINATOR = 'l')
```

You get an error

Msg 4864, Level 16, State 1, Line 1
Bulk load data conversion error (type mismatch or invalid character for the specified codepage) for row 2, column 1 (SomeDate).

What about if you try a CHAR(10) which is a linefeed

```BULK INSERT SomeTable
FROM 'D:\JunkdrawImportMe.txt'
WITH (FIELDTERMINATOR = 't',
FIRSTROW =2,
ROWTERMINATOR = CHAR(10) )
```

You get this error

Msg 102, Level 15, State 1, Line 5
Incorrect syntax near 'CHAR'.

How about if you embed it by using Dynamic SQL

```DECLARE @cmd varchar(1000)
SET @cmd = 'BULK INSERT SomeTable
FROM ''D:\JunkdrawImportMe.txt''
WITH ( FIELDTERMINATOR = ''t'',
FIRSTROW =2,
ROWTERMINATOR = '''+CHAR(10)+''')'
EXEC(@cmd)
```

The dynamic SQL solution works, that was my original answer to this.

What about if we use the hex code for line feed 0x0a?

```BULK INSERT SomeTable
FROM 'D:\JunkdrawImportMe.txt'
WITH (FIELDTERMINATOR = 't',
FIRSTROW =2,
ROWTERMINATOR = '0x0a') --CHAR(10) or ‘l’ does not work
-- 0x0a is the hex code for linefeed CHAR(10)
```

Bingo, that works as well.  I actually prefer this, who wants to muck around with Dynamic SQL if there is an easier way....

That's all, keep this in mind next time you get a file with a linefeed and you are struggling importing that file

## Sunday, November 20, 2016

### How to read the errorlog on SQL Server installed on Linux

I finally installed SQL Server on Linux, while I was messing around with some queries, I noticed the following command fails with an error

The error is

Started executing query at Line 1
Msg 22004, Level 16, State 1, Line 0 Failed to open loopback connection. Please see event log for more information.
Msg 22004, Level 16, State 1, Line 0 Error log location not found.
Total execution time: 00:01:01.34

So how do you then look at the log on Linux? I don't have SSMS installed on the host machine where the Linux Virtual Machine lives. SQLCMD gives the same error. I don't know if it even works from SSMS from a windows box.

Edit: so it looks like it works from SSMS

To answer this question, the errorlog is stored in this location  /var/opt/mssql/log. You need to be a superuser to access this location

So in my case, I can just execute the following from a terminal in Ubuntu

sudo cat /var/opt/mssql/log/errorlog

And it looks like this

There you have it, this is how you can look at the error log

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

## Wednesday, March 02, 2016

### Easy running totals with windowing functions

Back in the pre SQL Server 2012 days, if you wanted to do a running count, you either had to run a subquery or you could use a variable. This was slow because for each row the query that did the sum would be executed. With the additions to the windowing functions in SQL Server 2012, this is now running much faster.

Let's take a look, first create the following table

```CREATE TABLE #test(Id tinyint,SomeDate date, Charge decimal(20,10))

insert #test
SELECT 1,'20120101',1000
UNION ALL
SELECT 1,'20120401',200
UNION ALL
SELECT 1,'20120501',300
UNION ALL
SELECT 1,'20120601',600
UNION ALL
SELECT 2,'20120101',100
UNION ALL
SELECT 2,'20130101',500
UNION ALL
SELECT 2,'20140101',-800
UNION ALL
SELECT 3,'20120101',100
```

let's check that data we just inserted into the temporary table

```SELECT * FROM #test
```

The output looks like this

```Id SomeDate Charge
1 2012-01-01 1000.0000000000
1 2012-04-01 200.0000000000
1 2012-05-01 300.0000000000
1 2012-06-01 600.0000000000
2 2012-01-01 100.0000000000
2 2013-01-01 500.0000000000
2 2014-01-01 -800.0000000000
3 2012-01-01 100.0000000000
```

What we want is the following

```id StartDate Enddate         Charge         RunningTotal
1 2012-01-01 2012-03-31 1000.0000000000 1000.0000000000
1 2012-04-01 2012-04-30 200.0000000000 1200.0000000000
1 2012-05-01 2012-05-31 300.0000000000 1500.0000000000
1 2012-06-01 9999-12-31 600.0000000000 2100.0000000000
2 2012-01-01 2012-12-31 100.0000000000 100.0000000000
2 2013-01-01 2013-12-31 500.0000000000 600.0000000000
2 2014-01-01 9999-12-31 -800.0000000000 -200.0000000000
3 2012-01-01 9999-12-31 100.0000000000 100.0000000000
```

For each row, we want to have the date that the row starts on and also the date when it end, we also want a running total as well. If there is no row after the current row for that id, we want the end date to be 9999-12-31.

So we will use a couple of functions. The first one is LEAD, LEAD accesses data from a subsequent row in the same result set without the use of a self-join. So the LEAD part looks like this

What we are doing is subtracting 1 from the date in the subsequent row (ateadd(dd,-1,SomeDate))
We are using 1 as the offset since we want to apply this to the next row. Finally if there is no subsequent row, we want to use the date 9999-12-31 instead of NULL

To do the running count, we will do the following

SUM(Charge) OVER (PARTITION BY id ORDER BY SomeDate
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)
AS RunningTotal

What this means in English is for each id ordered by date, sum up the charge values for the rows between the preceding rows and the current row. Here is what all that stuff means.

ROWS BETWEEN
Specifies the rows that make up the range to use as implied by

UNBOUNDED PRECEDING
Specifies that the window starts at the first row of the partition. UNBOUNDED PRECEDING can only be specified as window starting point.

CURRENT ROW
Specifies that the window starts or ends at the current row when used with ROWS or the current value when used with RANGE.
CURRENT ROW can be specified as both a starting and ending point.

And here is the query

```SELECT id, someDate as StartDate,
OVER (PARTITION BY id ORDER BY SomeDate) as Enddate,
Charge,
SUM(Charge) OVER (PARTITION BY id ORDER BY SomeDate
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)
AS RunningTotal
FROM #test
ORDER BY id, SomeDate
```

And running that query, gives us the running count as well as the dates

```id StartDate Enddate         Charge         RunningTotal
1 2012-01-01 2012-03-31 1000.0000000000 1000.0000000000
1 2012-04-01 2012-04-30 200.0000000000 1200.0000000000
1 2012-05-01 2012-05-31 300.0000000000 1500.0000000000
1 2012-06-01 9999-12-31 600.0000000000 2100.0000000000
2 2012-01-01 2011-12-31 100.0000000000 100.0000000000
2 2012-01-01 2011-13-31 500.0000000000 600.0000000000
2 2012-01-01 9999-12-31 -800.0000000000 -200.0000000000
3 2012-01-01 9999-12-31 100.0000000000 100.0000000000
```
That's all for this post...

## Tuesday, April 22, 2008

### How to rename a column in a SQL Server table without using the designer

If you have a table and you want to rename a column without using the designer, how can you do that?

First create this table

CREATE TABLE TestColumnChange(id int)
INSERT TestColumnChange VALUES(1)

SELECT * FROM TestColumnChange

As you can see the select statement returns id as the column name. you can use ALTER table ALTER Column to change the dataype of a column but not the name.

Here is what we will do, execute the statement below

EXEC sp_rename 'TestColumnChange.[id]', 'value', 'COLUMN'

Now do the select, you will see that the column name has changed

SELECT * FROM TestColumnChange

That is it, very simple

## Tuesday, July 31, 2007

### Cannot resolve collation conflict for equal to operation.

You set up your linked server, you write a query which joins two tables, you execute the query and the error message is this
Cannot resolve collation conflict for equal to operation

What does this mean? This mean that the collation on the two tables is different

Let's look at an example. Le's create two tables, onme with Traditional_Spanish_CI_AI collation and one with the default. The default collation for me is SQL_Latin1_General_CP1_CI_AS.

CREATE TABLE #Foo (SomeCol varchar(50) COLLATE Traditional_Spanish_CI_AI)
CREATE TABLE #Foo2 (SomeCol varchar(50))

INSERT #Foo VALUES ('AAA')
INSERT #Foo VALUES ('BBB')
INSERT #Foo VALUES ('CCC')
INSERT #Foo VALUES ('DDD')

INSERT #Foo2 VALUES ('AAA')
INSERT #Foo2 VALUES ('BBB')
INSERT #Foo2 VALUES ('CCC')
INSERT #Foo2 VALUES ('DDD')

Now run this query and you will get the error message

SELECT * FROM #Foo F1
JOIN #Foo2 f2 ON f1.SomeCol = f2.SomeCol

Server: Msg 446, Level 16, State 9, Line 1
Cannot resolve collation conflict for equal to operation.

SELECT * FROM #Foo F1
JOIN #Foo2 f2 ON f1.SomeCol = f2.SomeCol COLLATE Traditional_Spanish_CI_AI

That works, if you add COLLATE SQL_Latin1_General_CP1_CI_AS to #Foo SomeCol that will work also

SELECT * FROM #Foo F1
JOIN #Foo2 f2 ON f1.SomeCol COLLATE SQL_Latin1_General_CP1_CI_AS = f2.SomeCol

If you want to know what these collations mean then run the following query (yes that is not a typo it is indeed ::).

SELECT *
FROM ::fn_helpcollations()

case-insensitive,
accent-insensitive,
kanatype-insensitive,
width-insensitive

SQL_Latin1_General_CP1_CI_AS
Latin1-General,
case-insensitive,
accent-sensitive,
kanatype-insensitive,
width-insensitive for Unicode Data,
SQL Server Sort Order 52 on Code Page 1252 for non-Unicode Data

## Monday, December 12, 2005

### Fun With SQL Server Update Triggers

Below is some code that will show how to test for updated field values in an update trigger. As you can see the IF UPDATE (field) is true even when the values don’t change. Another thing to keep in mind is that if a value changes from NULL to something else and vice-versa, and you are comparing deleted and inserted tables without using COALESCE or ISNULL it won’t return those rows. Run the code below to see what I mean

CREATE TABLE TestTrigger (TestID INT identity,
name VARCHAR(20),
value DECIMAL(12,2) ,
CONSTRAINT chkPositiveValue CHECK (value > 0.00) )

INSERT INTO TestTrigger
SELECT 'SQL',500.23

CREATE TRIGGER trTest
ON TestTrigger
FOR UPDATE
AS

IF
@@ROWCOUNT =0
RETURN

IF UPDATE(value)
BEGIN
SELECT
'1', * FROM deleted d JOIN inserted i ON d.testid =i.testid
SELECT '2',* FROM deleted d JOIN inserted i ON d.testid =i.testid
AND i.value <> d.value
SELECT '3',* FROM deleted d JOIN inserted i ON d.testid =i.testid
AND COALESCE(i.value,-1) <> COALESCE(d.value,-1)
END
GO

--Let's update the value to 100
UPDATE TestTrigger SET value = 100 WHERE testid =1
--we get back all 3 rows

--Let's run the same statement
UPDATE TestTrigger SET value = 100 WHERE testid =1
--we get back the first row

--Let's really update
UPDATE TestTrigger SET value = 200 WHERE testid =1
--we get back all 3 rows

--Let's update with NULL
UPDATE TestTrigger SET value =NULL WHERE testid =1
--we get back rows 1 and 3, row 2 is not returned because it can't compare it

--Let's update with NULL again
UPDATE TestTrigger SET value =NULL WHERE testid =1
--we get back row 1

--Let's update with 300
UPDATE TestTrigger SET value =300 WHERE testid =1
--we get back rows 1 and 3, row 2 doesn't return because it can't compare NULL to 300

--Let's update with 500
UPDATE TestTrigger SET value =500 WHERE testid =1
--we get back all 3 rows