SQL Server DBA: The worst days

In a recent blog post Steve Jones posed the question; what was the worst day in your career? Great idea by the way.

A couple of experiences that occurred early on in my DBA career sprung to mind. There was the rather nasty corruption of a critical but not highly available application database that happened mid-afternoon which led to a very manual and overnight full restore (legacy system means very legacy hardware).  

The subsequent post-restore checks were also quite lengthy meaning the entire recovery process concluded at around 5.30AM the next morning, which actually wasn't that far from my estimated ETA of a working system. Operationally the effects weren't too bad; transactions were captured using a separate system and then migrated into the restored database when it came back online. I'll never forget the post incident discussion either; no finger pointing, no blame whatsoever just a well done to all for having a successful recovery operation and a genuine interest in how we could further minimise any impact in future. 

Then there was the time the execution of an application patch with a slight (and undiscovered until then) code imperfection brought down an entire production server, that just happened to be attempting to process some rather critical financial workloads from various systems at the same time. In truth it was a completely freak event that had happened on a combination of very old systems that were considered flaky at best.

The systems were brought online quickly enough but tying together the results of the various processes that may or may not have worked took hours and hours of querying with lots of manual updates. It might sound terrible, but because of the coordinated effort between different teams and individuals it had actually taken a fraction of the time that it could have done and not only that, data was confirmed to be 100% accurate.  

Want another corruption tale? Why not. How about the time a system database on a 2005 instance went all corrupt rendering the instance completely useless? Of course it never happens to a system that nobody cares about, no, yet another critical system. The operational teams went to plan B very quickly but even better, a solution that avoided large restores was implemented quickly so the downtime, although handled well, was still significantly reduced.

Looking back there's plenty more, I think it's fair to say that disaster is a real occupational hazard for database professionals. And yet despite being labelled "worst days" I actually look back on them with a large degree of genuine fondness. 

You see disasters are always going to happen when databases are involved, it's a fact and how we deal with them at the time is equally as important as how we learn from these events. In each of these examples a recovery plan was in existence for both technical and operational viewpoints, as well as that everyone involved knew what was happening, what to do and critically not to add any additional pain to the situation but to arrive at the solution as quickly as possible.

Learning from these events meant asking the right questions and not taking a viewpoint of blame. How can we prevent this, how can we make a recovery process more robust and what can we implement technically and operationally to improve our response times and also critically, when can we schedule the next Disaster Recovery test? 

Worst days? In one sense most definitely yes. Nobody wants to be in the middle of a technical disaster that's going to take hours to resolve but a solid recovery plan, collaborative effort to a solution and an open forum to analyse and learn from the event makes these memories much less painful!

Reasons why DevOps implementations fail.

Over the last few years we have seen a monumental rise in the number of organisations adopting a DevOps working culture. This trend shows no signs of slowing down whatsoever and whilst many are now realising the benefits of these working practices many are also struggling with the adoption and in some cases it's either stopped completely or not even started.

There's a number of reasons of why this happens and I've seen some common causes, which is actually a good thing because we can recognise where these are occurring or even prevent them before they start to become a problem.

No clear direction.

It's very difficult to drive to a destination if you don't know where you're actually going (trust me on this, I've tried it). This is obviously very reasonable advice however many DevOps projects fail because of a lack of direction. It's actually a common issue with many buzzing trends, particularly in IT where organisations rush into a technology stack or movement just for the sake of doing it. Inevitably this often always leads to failure.

Organisations need to fully understand what a DevOps culture is, its objectives and its close relationships with their existing business processes and frameworks. A common misconception is people often viewing DevOps as a direct replacement for ITIL when in actual fact it's more of a cultural change built on top of ITIL principles. By fully understanding DevOps the benefits of adoption become much more viable and ultimately the path to it's success becomes much simpler.     

Adopting a silo approach to DevOps.

I often see individual teams being very successful in implementing components of DevOps practices only for other teams being behind in terms of adoption and/or understanding. The classic case is the Developer and DBA; the developer is pushing for much more frequent releases (a realised benefit of DevOps) but then the DBA, who perhaps isn't on board, is then trying their best to slow down all of these changes to their production databases. In the words of Bon Jovi, "we're half way there".

This lack of cohesion or a shared direction can result in a significant bottleneck and the DevOps practices start to creak a little. Then other unintended side effects start to creep in, such as blame and finger pointing (some of the things that a healthy DevOps culture seeks to eliminate) and then it can all start to fall apart. 

DevOps for databases is one particular area that is so heavily reliant on lots of people in different roles working together in a collaborative manner. An organisation must identify this and start to encourage teams to engage and build with each other in the early phases of a DevOps implementation, but organisations also have to be very careful in how they seek to develop this collaborative culture...

Forced collaboration.

I believe collaboration underpins the entire DevOps methodology so it makes perfect sense for organisations to work towards developing much closer working relationships between teams however organisations can also over-formalise things, even making the activity seem very process-driven which often leads to much less buy in from individuals, even entire teams.

This causes obvious problems, not least the silo approach mentioned in the previous point, so organisations have to find the balance on being almost relaxed in how they let relationships build and at the same time provide a certain degree of steer. This isn't as easy as it sounds and it is certainly reliant on strong leadership. In my experience successful implementations have been led by those that enable positive change rather than those who try to dictate it.

Rushing into new tools.

New tools are awesome, fact and in a DevOps ecosystem there are so many to pick and choose from that each bring new ways of doing things and [hopefully] improving productivity. The advantages are great, without a doubt but often tools can be implemented way too early without a focus on the underlying processes. This can significantly reduce the effectiveness of what a particular toolset/platform is trying to achieve; a release management tool for example won't improve a change/release process if the process is fundamentally flawed.

The most successful DevOps implementations focus on people and process first, leveraging the strengths and principles of existing frameworks and building strong collaborative working practices. New tools are going to be an important factor of a system designed with DevOps principles in mind but they need to be leveraged correctly and for the right reasons.


These are some of the common pitfalls that I've seen occur during DevOps implementations, many of which are deeply rooted in the working culture, not the technologies. There is undoubtedly so much to gain by adopting the principles and often it requires organisations to step back and observe their working practices first and spend time exploring the benefits of working with DevOps.

In my next post I'll cover how to address some of these issues and offer some insights into the benefits of building collaborative relationships between data professionals.

The DBA and the Data Platform

I've been consulting now for well over a year, it's been a fantastic experience so far; I've had the pleasure of meeting and working with some truly incredible people and it's also been amazing to be helping organisations get the most from their SQL Server platforms.

The last 12 months have been extremely interesting considering the current technical shift towards a seemingly endless list of new platforms and capabilities. For many organisations this shift has fundamentally changed how they do things (or going to do things) and many are going through their own journey of digital transformation understanding these new technologies and how to leverage them to improve their existing processes.

Right at the centre is data, nowadays considered to be a companies greatest asset, so how we use data or to be more exact how we extract more value from it is a frequent aim of these transformation projects. As a result the data professional roles within an organisation have changed too and many teams and individuals are having to broaden their technical skill set to design, deliver and support these new capabilities.

There is no truer example of this than the role of DBA but yet the question still remains on which direction(s) they should be focusing their future on? By that I mean development; which skills should they be learning, what certification, what products, platforms etc? It's easy to see why it's confusing; there are lots and lots of new technologies available to us but that also means there is no consistent path for administrators to set out on. 

It was easier in the not so distant past; the DBA role tended to come in two distinct flavours; development or operational, but now the line between the two has became far less apparent and in many cases non-existent. The DBA role has without question become much more rounded containing core elements from both "sides" but it goes beyond that. Modern approaches to database administration have reduced the footprint of the operational side of the role so a more DevOps orientated DBA is an essential part of the roadmap, for organisations and individuals alike.

This shared roadmap is actually an integral component of an evolving data platform. I've worked with many different organisations at different stages of development but a key component in each has always been a collaborative working practice between data professionals and I'd say the success of a platform depends on it. Over the past year I've worked alongside many different teams; architects, DBA's, developers, release analysts, change and testing specialists, when working together they all have a great influence of the effectiveness of a data solution. 

Whilst it's fair to say organisations should be encouraging this type of working practice it is very much dependent on individuals to pursue and implement it. For DBA's this means engaging with other teams much more frequently, understanding their skills and processes but also adding their own expertise and skill set to produce a much more co-operative function. 

It might not fully answer this common question of what next for DBA's, there's a lot of factors involved, not least your personal career aspirations but it does show how when looking for your next phase of self development the paths that you need to take could be very close to your current role. 

Your skills as a DBA will always be of paramount importance towards availability, security and performance, but by widening your technical scope by working much more closely with those around you not only improves you as an data professional but also the overall effectiveness your data platform. The starting point is to seek out these opportunities; start building relationships, start knowledge sharing and developing new ideas and different ways of working. 

In many ways the data platform is a reflection of the people tasked with shaping it. If we choose not to broaden ourselves, learn new ideas then at some point we come to a standstill, especially in this rapidly evolving technical landscape. If that happens a data platform stops growing, not in terms of data quantity but most certainly in terms of both capability and perhaps most critical of all, value. 

This puts a big emphasis on self-development but we've always had that, it's nothing new. The key is to seek out those opportunities, start close and work with teams that you will probably already have a working relationship with. As these relationships grow so does the collaborative skill set and as a result business processes improve and technical solutions get faster and more productive.

This also cuts down reactive measures, less time fire fighting means more time delivering enhancements and of course, more learning. Any learning process shouldn't have a cut off point, the more we broaden our horizons the more the effective we become and in turn, our products, our services and our platforms keep on evolving.

This is the true nature of a technical platform and we as data professionals play such an important part not just in the support or development of them but towards shaping their growth, effectiveness and their value. Perhaps the key to all of this is realising the value of our own development alongside it.   

VIEW SERVER STATE

Quick reference post on the VIEW SERVER STATE permission within SQL Server. This is a server level permission that once granted enables a login to view the results of Dynamic Management Objects.

I find that it's typically used for troubleshooting or performance tuning related activities and is a good alternative to the good old sysadmin role membership route, especially for external people.

To demonstrate what the permission allows I'll first create a new login on a test instance with the following command:

CREATE LOGIN SQLClarity WITH PASSWORD = 'SQLCl@r1ty' 

Now I've logged into Management Studio with the credentials I've created above. So let's try to select records from a DMV, in this case my instances cumulative wait statistics:

SELECT * FROM sys.dm_os_wait_stats

I get the following error:

Msg 300, Level 14, State 1, Line 1
VIEW SERVER STATE permission was denied on object 'server', database 'master'.
Msg 297, Level 16, State 1, Line 1

The user does not have permission to perform this action.

SQL Server has been quite specific on how to resolve the issue by stating that the VIEW SERVER STATE permission was denied. 

There are a couple of ways we can grant this permission, from the server properties > permissions window as in the image below. Remember that although the error message indicates the issue is on the master database it is a server level permission not a database one (such as view database state). 

Or we can use T-SQL syntax such as the following:

GRANT VIEW SERVER STATE TO SQLClarity

Now the results from the DMV are visible without error. 

This is a really useful way of restricting access for what could typically be viewed as an administrative task, however, one final word of caution though. This permission is applied at the server level and gives access to all of the Dynamic Management Objects and whilst in this particular case something like wait statistics might not be that sensitive the DMVs and DMFs do expose a lot of information so you have to bear this in mind when applying this level of permission.

Databases and DevOps

This is my post for T-SQL Tuesday #91 hosted this month by Grant Fritchey, the subject this time around is Databases and DevOps. For those who aren't aware what T-SQL Tuesday is it's essentially a monthly blog party where the host (Grant this time) will decide on a topic and fellow bloggers will write a related post on the subject; you can read more about it here.

My post is going to be rather high level (what's new I hear you say!) and that's because this is where I often see DevOps fail, people don't quite grasp the fundamental concepts and requirements to make it work, but to begin with, sing a long with me for a second: 

Now this is a story all about how

My life for flipped-turned upside down

And I'l like to take a minute

Just sit right there

and I'll tell you about how implementing DevOps sometimes fails. 

Okay, it doesn't rhyme, I stole the lyrics and I certainly can't rap (not without whisky anyway) but for some people the concept of DevOps does bring with it the idea of having their (working) life being flipped upside down. People get confused about what it all means and this can cause resistance, an unwillingness to look at what DevOps is trying to achieve and essentially hold on to their current way of working.

The main cause of this tends to be how people go about implementing DevOps. I've seen organisations sort of grasp at the concept, try to introduce it too quickly or even try to impose it and then, quite understandably it fails miserably each time. 

People (or indeed companies) tend to focus on the lower levels of DevOps or even try to get the benefits straight away, the "continuous this" and the "continuous that" when in actual fact they're not even starting at the right place, a case of crawl before you can walk if you like.

The phrase DevOps is the bringing together of two different terms; Development and Operations so to make a success of it we need to think along those exact same lines. That means we need to focus on two things; communication and collaboration.

Communication is easy right? After all everyone kind of talks to one another so what's the problem? Well look at the traditional relationship between Developer and the DBA (operations). Both have been working very different styles for many years now; developers are making constant changes, pushing out releases as often as possible whereas the DBA is trying to put the brakes on and keep the systems in a stable state. 

This often results in push backs and whilst they will certainly communicate, it might not necessarily be the right kind of communication and now we've got to try to get them to meet in the middle somehow and work in a very coupled fashion! 

Fundamentally what is needed is an understanding of each others role. For me this is the real starting point of DevOps and although in some cases this will mean the breaking down of walls in no way is it an impossible task. Introducing each others way of thinking without trying to abolish the existing mindset but rather have a purpose of helping one another is how this common approach should be formed, and taken advantage of. 

Side Note: I have noticed that this sounds a lot like couples therapy!? Is this the real meaning of DevOps - are we been healed somehow!?

Ultimately this mutual understanding results in much more solid foundation that can be used to then implement the lower levels of DevOps such as the different technical methodologies and tool sets.  

Some of the most successful DevOps cultures that I have seen are where teams contain developers that are ex database admins and vice versa - yeah it's true, people actually do this! In these cases people haven't just brought their technical skills over to a new team, they've brought their understanding of the other functions too and will often use that in a co-operative manner to find the best solution - essentially, isn't this what DevOps is all about?

Now I am not saying that anyone should start shuffling around their IT department because that's the last thing you want to be doing. You can't force or impose this concept, it needs to grow and to some degree let people find their own ways of understanding and working with one another. Whilst challenging yes, the process doesn't need to be threatening or overwhelming in any way and done correctly it won't feel like that. 

So to go back to the lyrics right at the beginning of this post, no it won't flip your life upside down we just all need to take a minute, sit right there, and learn from one another.

Installing SQL Server on Ubuntu 16.04.2

This article is going to show you how it to set up a Linux/SQL Server test environment which will consist of a virtual machine using the Ubuntu Operating System with the latest CTP release of SQL Server 2017 running on it. 

The plan to make SQL Server available on Linux was announced way back in March 2016 and with the recent announcement of the SQL Server 2017 (and subsequent CTP releases) things certainly appear to be right on track for SQL and Linux. 

It's worth adding that in recent weeks I have started to see organisations really take up the idea and have spoken to a few people who are creating their own test boxes and started to think about how to use this combination. Not only that, they've also started to ask for people with the right technical knowledge too so perhaps if you are a DBA who hasn't had a bit of exposure to Linux then now is probably the right time to start! All in all though, it's an encouraging sign for Microsoft.

Anyway, before we get going I'm going to be using VMWare Workstation 12 Player to create the Ubuntu virtual machine, you can download the software from this link and use VM's for non-commercial use.

To start off I need to download the Ubuntu Operating System ISO, which is available from here where you will find the following two download options:

I went for the 16.04.2 LTS version and once downloading and the following message was displayed, which I had great delight sharing with my open-source buddies (this one is for you Adrian).

Once the download has finished I can open up VMWare Player and select the Create a New Virtual Machine option as shown in the image below:

From here I can choose how the Operating System will be installed; from a DVD in my machine, from an ISO (what we will select) or I can install an OS later. Here we can see that I have browsed to the downloaded ISO file and the install process has recognised that it's the Ubuntu 16.04.2 OS.

After clicking next some user details are required:

Which actually tells me off as user names can only be lowercase apparently so I fixed that and carried on to the next part where I need to specify a name for my new Virtual Machine:

Clicking next takes me to the disk capacity screen, I left the options as default so used a 20Gb max disk size and left the split virtual disk into multiple files option selected:

After clicking next we move on to create the virtual machine however before we click Finish and proceed with the create/install process I need to make a slight modification to the configuration of my VM.

The system requirements for running SQL Server on Ubuntu 16.04.2 contains the following 

Note

You need at least 3.25GB of memory to run SQL Server on Linux. For other system requirements, see System requirements for SQL Server on Linux.

On the create VM window the Memory is currently set to 1024 MB so by clicking the Customize Hardware button I can change the allocated memory to 4GB (4096 MB) as in the screenshot below:

I can then click Close as there are no more hardware configurations that I need to make and now I can click Finish and the install process will start; if prompted to install VMware Tools for Linux then go ahead and Download and Install.

Pretty neat install screen, you just don't see enough purple these days!

Once installed the virtual machine will reboot and Ubuntu will start. I get presented with a login screen where I need to enter the username and password that I specified during the install process and now I am ready to go!

Ubuntu!

Now I was following the initial guide that is available here but ran into an error at the very beginning when trying to import the CPG keys, wasn't a biggie as it meant I just didnt have the curl tool so I just had to run the following command first:

sudo apt install curl

Before I could successfully run the curl command:

curl https://packages.microsoft.com/keys/microsoft.asc | sudo apt-key add -

This brought up a install progress type screen and because the Time Spent value was increasing I figured things were progressing...however after a few minutes I was given a connection refused error!!

A little bit of digging around soon led me to a solution, superuser mode which kind of reminded me of the run as administrator option in Windows a little bit.

To start superuser mode type the following:

sudo su

Then I was able to run the curl command once more for info here's a screenshot containing the connection error and the subsequent sudo su and completed curl command:

Now for the next step I need to register the mssql-server repository:

curl https://packages.microsoft.com/config/ubuntu/16.04/mssql-server.list |

sudo tee /etc/apt/sources.list.d/mssql-server.list

No errors, this is good and now I can also quit using superuser mode at this point:

exit

Now for the actual installation and to do this I need to run the following commands which will go ahead and install SQL Server:

sudo apt-get update sudo apt-get install -y mssql-server

Next step is to run the conf-setup to specify and confirm the administrator password for SQL Server:

sudo /opt/mssql/bin/mssql-conf setup

Success!

SQL Server is now installed but I can run a quick test to see if the service is running correctly by using the following command:

systemctl status mssql-server

Which brings up the following screen (with a reassuring green selection of text):

That's it, I now have a brand new test instance of Ubuntu with SQL Server running quite happily, for now at least! 

Installing Python and using the new command line T-SQL script generator

Earlier today two new command line tools were announced for SQL Server, one an experimental Linux tools DBFS which enables access to live DMVs without using a UI like SSMS and secondly a tool that enables script generation of objects within SQL rather like the Generate SQL Scripts option in SSMS.

In this post I'm going to run through the installation of the script generator tool and provide a very quick demo. The reason I'm going through this is because in order to install the tool we need to use something called PIP. PIP is a package management system that enables us install and use packages written in Python. Yeah, Python again! 

So if you haven't already installed Python, because it isn't available by default in Windows you'll need to get it from here:

https://www.python.org/downloads/

This will take you to the download screen and here you get two version options; 2.7.13 or 3.6.1, I went for the latter and there is a link that explains the differences between version 2 and version 3 of Python: https://wiki.python.org/moin/Python2orPython3

And this is the installation screen, before hitting the install option make sure the Add Python 3.6 to PATH is selected otherwise things won't be working as expected after install.

Nothing untoward in the actual installation and we get a successful message in a couple of minutes.

So now that Python is installed we need to install the mssql-scripter package and that is very straightforward and rather familiar to those using PowerShell I guess. We use the command: pip install mssql-scripter from a Windows command prompt ran as administrator.

The installation package goes and does its thing!

Again, after a couple of minutes we get a couple of done messages and returned to the command prompt, installation all good.

Once complete we can pass in a -h parameter to the mssql-scripter command and see a wide array of options that are available to us but in this demo I'll keep it simple and you can refer to the original link to see the different ways of using the tools.

To use the command I've typed out the following which will create a script (adventureworks.sql) in my working directory containing the DDL and DML commands for the objects in the AdventureWorks2014 database:

mssql-scripter -S localhost -d AdventureWorks2014  > ./adventureworks2014.sql

Worth noting that although mssql-scripter is brand new I am using this on a SQL Server 2014 instance. 

The script ran in just a few seconds which is very impressive and it produced the file as expected and whilst I'll not put the entire script content in this post here is a screenshot of the script opened inside SSMS.

Now I did work through some of the examples on the release article however I did run into unrecognized argument errors when using -schema-and-data which is shame as I did want to test that functionality. I'll await a comment back on that one and then perhaps run through some more scenarios of using the command.

Edit: I did parse the created script: 

Command(s) completed successfully.

Torn Pages and using DBCC PAGE

Today's post is about torn pages and using the undocumented DBCC PAGE command within SQL. Occasionally you might find you need to run this command and in this example it's because I have received an error message that looks a bit like this:

SQL Server detected a logical consistency-based I/O error: torn page (expected signature: 0xaaaaaaaa; actual signature: 0xa9aaaaaa). It occurred during a read of page (1:25756919) in database ID 9 at offset 0x000031209ee000 in file 'F:\DATA\ScratchDatabase.mdf'

This is an error that has been picked up on one of my test systems and indicates that SQL Server has detected a torn page, that is a page that has been incorrectly written by SQL Server and possibly indicates a problem in the IO subsystem.

The problem here is that whilst we know the database and the page where the error has occurred we don't know the specific table the page belongs and importantly what type of page is in error. The reason why the page type is important is because this will drastically impact our recovery process but the first thing we will do is check a system table to see if any other page errors have been reported:

SELECT * FROM msdb..suspect_pages

database_id	file_id	page_id	event_type	error_count	last_update_date
9	1	25756919	3	1	2017-01-29 08:24:05.760

Here we can see that only one row has been returned, the event_type refers to a torn page, here's the full type descriptions and a link for more information:

1 = An 823 error that causes a suspect page (such as a disk error) or an 824 error other than a bad checksum or a torn page (such as a bad page ID).

2 = Bad checksum.

3 = Torn page.

4 = Restored (page was restored after it was marked bad).

5 = Repaired (DBCC repaired the page).

7 = Deallocated by DBCC.

To identify the table in error we will use DBCC PAGE. This command takes a database id (or name), file id and page id and will return the actual page information back to the results window (we need to enable trace flag 3604 to do this though); for my example I would use the following command:

DBCC PAGE (9, 1, 25756919, 0)

This returns a lot of information to the results window (I can use the option WITH TABLERESULTS for a grid view) so I have removed a fair chunk of it and highlighted the two parts that I really need.

PAGE: (1:25756919)

 

PAGE HEADER:

Page @0x0000000728010000

m_pageId = (1:25756919)             m_headerVersion = 1                 m_type = 2

m_typeFlagBits = 0x0                m_level = 0                         m_flagBits = 0x104

m_objId (AllocUnitId.idObj) = 266296m_indexId (AllocUnitId.idInd) = 256

Metadata: AllocUnitId = 72057611489902592                               

Metadata: PartitionId = 72057607060652032                                Metadata: IndexId = 20

Metadata: ObjectId = 567673070      m_prevPage = (1:25756918)           m_nextPage = (1:38369560)

The first is Metadata: ObjectId = 567673070 which refers to the table that this page belongs to. The second is Metadata: IndexId = 20 which tells me as it isn't 0 (heap) or 1 (clustered index) that the page error is within a non-clustered index and I can use the following code to identify the actual index where the problem lies.

SELECT * FROM sys.indexes WHERE index_id = 20 AND object_id = 567673070

This returns the suspect index and to resolve we can very simply drop and recreate the index effectively reallocating the pages, suspect and all. This is potentially much quicker than performing a full restore and I have lost count of the times I have seen people resort to a full restore without checking the actual type of page corruption that they're attempting to resolve.


Another option here is that because we know the effected table we can run a DBCC CHECKTABLE command (rather than a DBCC CHECKDB on the entire database), passing in the full table name as a parameter; to get the name of the table we use our ObjectId again that was returned from DBCC PAGE with the following:

SELECT OBJECT_NAME (567673070)

This would return the table name that we can use to check the structure to see if our page issue has been resolved:

DBCC CHECKTABLE ('dbo.ETL_TestLoad) WITH NO_INFOMSGS

DBCC results for 'ETL_TestLoad'.
There are 341465 rows in 93513 pages for object "ETL_TestLoad".
DBCC execution completed. If DBCC printed error messages, contact your system administrator.

Using DBCC CHECKTABLE in this scenario may have proven that our torn page has been resolved but you should always, without question, perform a full database consistency check to look for further errors. In the event of IO issues this could easily return more and more page problems, maybe irrecoverable data page ones at that. Any page read/write errors must result in both a full consistency check and a check with the storage people to see if they can see any underlying issues.


For some further reading check out my post: How to consistency check large databases