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  • When creating a GUI wizard, should all pages/tabs be of the same size? [closed]

    - by Job
    I understand that some libraries would force me to, but my question is general. If I have a set of buttons at the bottom: Back, Next, Cancel?, (other?), then should their location ever change? If the answer is no, then what do I do about pages with little content? Do I stretch things? Place them in the lone upper left corner? According to Steve Krug, it does not make sense to add anything to GUI that does not need to be there. I understand that there are different approaches to wizards - some have tabs, others do not. Some tabs are lined horizontally at the top; others - vertically on the left. Some do not show pages/tabs, and are simply sequences of dialogs. This is probably a must when the wizard is "non-linear", e.g. some earlier choices can result in branching. Either way the problem is the same - sacrifice on the consistency of the "big picture" (outline of the page/tab + location of buttons), or the consistency of details (some tabs might be somewhat packed; others having very little content). A third choice, I suppose is putting extra effort in the content in order to make sure that organizing the content such that it is more or less evenly distributed from page to page. However, this can be difficult to do (say, when the very first tab contains only a choice of three things, and then branches off from there; there are probably other examples), and hard to maintain this balance if any of the content changes later. Can you recommend a good approach? A link to a relevant good blog post or a chapter of a book is also welcome. Let me know if you have questions.

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  • Acer Aspire AS5738PG Netbook review

    <b>Linux User and Developer:</b> "For a Linux developer interested in touch computing, the Acer 5738 represents an interesting option for developing touch-screen apps and working with eventual touch versions of Linux distros."

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  • Should developers do their own software releases (if there is a prod support team in place)?

    - by leora
    I know there are going to always be differences depending on the particular size, staff etc, but i wanted to get feedback in general around: In an environment where you have a production support team doing first line support and release management, is it better to simply have developers manage their own releases instead? In this case, its internal software at an insurance company but the question should be valid at any company, size, etc I think. Currently, we have our production team do releases but there is an argument that its inefficient and that if you allowed developers the ability to do it, they will focus more on making it simple and efficient and avoid basically passing on scripts, etc to run to another team. The counter argument is that if you don't have a check and balance, you could get a software team (or an individual) that doesn't a very hacky job about getting their software out there (making on the fly changes, not documenting the process, etc) and that by forcing the prod support team to do the actual release, it enforces consistency and proper checks and balances. I know this is not a black or white issue but I wanted to see what folks thought on this so the discipline and consistency is there but without the feeling that an inefficient process is in place.

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  • How to properly name record creation(insertion) datetime field ?

    - by alpav
    If I create a table with datetime default getdate() field that is intended to keep date&time of record insertion, which name is better to use for that field ? I like to use Created and I've seen people use DateCreated or CreateDate. Other possible candidates that I can think of are: CreatedDate, CreateTime, TimeCreated, CreateDateTime, DateTimeCreated, RecordCreated, Inserted, InsertedDate, ... From my point of view anything with Date inside name looks bad because it can be confused with date part in case if I have 2 fields: CreateDate,CreateTime, so I wonder if there are any specific recommendations/standards in that area based on real reasons, not just style, mood or consistency. Of course, if there are 100 existing tables and this is table 101 then I would use same naming convention as used in those 100 tables for the sake of consistency, but this question is about first table in first database in first server in first application.

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  • When do you learn from your mistakes?

    - by smayers81
    When are you supposed to learn from your mistakes in coding / design? Is it something you take with you to the next project or do you learn in the middle of your current one, sacrificing consistency for cleaner, more well-informed code? For example, my application can be distinctly demarcated down two lines of business -- say one side is for sales and the other is for marketing. Both are somewhat tied together, but as far as the team structure, use cases, developers, etc. the app consists of the Sales code and the Marketing Code. Now, say the Sales code went in first and while good-intentioned, made some bad mistakes. Should the Marketing Code follow suit and make the same mistakes for the sake of consistency or should Marketing architects and designers instead learn from the mistakes that Sales made and developer a cleaner codebase, even though Sales and Marketing are in the exact same system? Basically, do you learn from your mistakes while in a project or do you continue to pile crap on top of crap?

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  • Tool to write linear temporal logic from UML 2.0 sequence diagram

    - by user326180
    i am working on checking model consistency of software. to do this i need to write linear temporal logic for UML 2.0 sequence diagram. if any body have any other tool for the same please response as soon as possible. I will be very obliged to you. i have found charmy tool have plugin for the same. Does anybody have source code for charmy tool(CHecking ARchitectural Model consistencY). It is not available on their website. Thanks in advance.

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  • some examples for using specific searchalgorithm

    - by Robert
    I could understand the following search algorithms: Constraint Satisfaction with Arc Consistency, Uninformed search A* Search MinMax I would understand the definition and working principles of the above algorithm,but could you please give me some real world examples that the above algorithms will be suitable?My idea would be: For CSP with Arc Consistency,assign students to groups that each group must contain both technical and management students,and no 2 technical students in a same group. Uniformed Search: search for a file under UNIX directoy. A* Search: search a way (staring from home) to go to mulitple stores to buy things then get back home with minimum total travelling time. MinMax:Go or other Chess. Please correct me if I am wrong.

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  • PHP modifying and combining array

    - by Industrial
    Hi everyone, I have a bit of an array headache going on. The function does what I want, but since I am not yet to well acquainted with PHP:s array/looping functions, so thereby my question is if there's any part of this function that could be improved from a performance-wise perspective? I tried to be as complete as possible in my descriptions in each stage of the functions which shortly described prefixes all keys in an array, fill up eventual empty/non-valid keys with '' and removes the prefixes before returning the array: $var = myFunction ( array('key1', 'key2', 'key3', '111') ); function myFunction ($keys) { $prefix = 'prefix_'; $keyCount = count($keys); // Prefix each key and remove old keys for($i=0;$i<$keyCount; $i++){ $keys[] = $prefix.$keys[$i]; unset($keys[$i]); } // output: array('prefix_key1', 'prefix_key2', 'prefix_key3', '111) // Get all keys from memcached. Only returns valid keys $items = $this->memcache->get($keys); // output: array('prefix_key1' => 'value1', 'prefix_key2' => 'value2', 'prefix_key3'=>'value3) // note: key 111 was not found in memcache. // Fill upp eventual keys that are not valid/empty from memcache $return = $items + array_fill_keys($keys, ''); // output: array('prefix_key1' => 'value1', 'prefix_key2' => 'value2', 'prefix_key3'=>'value3, 'prefix_111' => '') // Remove the prefixes for each result before returning array to application foreach ($return as $k => $v) { $expl = explode($prefix, $k); $return[$expl[1]] = $v; unset($return[$k]); } // output: array('key1' => 'value1', 'key2' => 'value2', 'key3'=>'value3, '111' => '') return $return; } Thanks a lot!

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  • How (and if) to write a single-consumer queue using the task parallel library?

    - by Eric
    I've heard a bunch of podcasts recently about the TPL in .NET 4.0. Most of them describe background activities like downloading images or doing a computation, using tasks so that the work doesn't interfere with a GUI thread. Most of the code I work on has more of a multiple-producer / single-consumer flavor, where work items from multiple sources must be queued and then processed in order. One example would be logging, where log lines from multiple threads are sequentialized into a single queue for eventual writing to a file or database. All the records from any single source must remain in order, and records from the same moment in time should be "close" to each other in the eventual output. So multiple threads or tasks or whatever are all invoking a queuer: lock( _queue ) // or use a lock-free queue! { _queue.enqueue( some_work ); _queueSemaphore.Release(); } And a dedicated worker thread processes the queue: while( _queueSemaphore.WaitOne() ) { lock( _queue ) { some_work = _queue.dequeue(); } deal_with( some_work ); } It's always seemed reasonable to dedicate a worker thread for the consumer side of these tasks. Should I write future programs using some construct from the TPL instead? Which one? Why?

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  • Windows Azure VMs - New "Stopped" VM Options Provide Cost-effective Flexibility for On-Demand Workloads

    - by KeithMayer
    Originally posted on: http://geekswithblogs.net/KeithMayer/archive/2013/06/22/windows-azure-vms---new-stopped-vm-options-provide-cost-effective.aspxDidn’t make it to TechEd this year? Don’t worry!  This month, we’ll be releasing a new article series that highlights the Best of TechEd announcements and technical information for IT Pros.  Today’s article focuses on a new, much-heralded enhancement to Windows Azure Infrastructure Services to make it more cost-effective for spinning VMs up and down on-demand on the Windows Azure cloud platform. NEW! VMs that are shutdown from the Windows Azure Management Portal will no longer continue to accumulate compute charges while stopped! Previous to this enhancement being available, the Azure platform maintained fabric resource reservations for VMs, even in a shutdown state, to ensure consistent resource availability when starting those VMs in the future.  And, this meant that VMs had to be exported and completely deprovisioned when not in use to avoid compute charges. In this article, I'll provide more details on the scenarios that this enhancement best fits, and I'll also review the new options and considerations that we now have for performing safe shutdowns of Windows Azure VMs. Which scenarios does the new enhancement best fit? Being able to easily shutdown VMs from the Windows Azure Management Portal without continued compute charges is a great enhancement for certain cloud use cases, such as: On-demand dev/test/lab environments - Freely start and stop lab VMs so that they are only accumulating compute charges when being actively used.  "Bursting" load-balanced web applications - Provision a number of load-balanced VMs, but keep the minimum number of VMs running to support "normal" loads. Easily start-up the remaining VMs only when needed to support peak loads. Disaster Recovery - Start-up "cold" VMs when needed to recover from disaster scenarios. BUT ... there is a consideration to keep in mind when using the Windows Azure Management Portal to shutdown VMs: although performing a VM shutdown via the Windows Azure Management Portal causes that VM to no longer accumulate compute charges, it also deallocates the VM from fabric resources to which it was previously assigned.  These fabric resources include compute resources such as virtual CPU cores and memory, as well as network resources, such as IP addresses.  This means that when the VM is later started after being shutdown from the portal, the VM could be assigned a different IP address or placed on a different compute node within the fabric. In some cases, you may want to shutdown VMs using the old approach, where fabric resource assignments are maintained while the VM is in a shutdown state.  Specifically, you may wish to do this when temporarily shutting down or restarting a "7x24" VM as part of a maintenance activity.  Good news - you can still revert back to the old VM shutdown behavior when necessary by using the alternate VM shutdown approaches listed below.  Let's walk through each approach for performing a VM Shutdown action on Windows Azure so that we can understand the benefits and considerations of each... How many ways can I shutdown a VM? In Windows Azure Infrastructure Services, there's three general ways that can be used to safely shutdown VMs: Shutdown VM via Windows Azure Management Portal Shutdown Guest Operating System inside the VM Stop VM via Windows PowerShell using Windows Azure PowerShell Module Although each of these options performs a safe shutdown of the guest operation system and the VM itself, each option handles the VM shutdown end state differently. Shutdown VM via Windows Azure Management Portal When clicking the Shutdown button at the bottom of the Virtual Machines page in the Windows Azure Management Portal, the VM is safely shutdown and "deallocated" from fabric resources.  Shutdown button on Virtual Machines page in Windows Azure Management Portal  When the shutdown process completes, the VM will be shown on the Virtual Machines page with a "Stopped ( Deallocated )" status as shown in the figure below. Virtual Machine in a "Stopped (Deallocated)" Status "Deallocated" means that the VM configuration is no longer being actively associated with fabric resources, such as virtual CPUs, memory and networks. In this state, the VM will not continue to allocate compute charges, but since fabric resources are deallocated, the VM could receive a different internal IP address ( called "Dynamic IPs" or "DIPs" in Windows Azure ) the next time it is started.  TIP: If you are leveraging this shutdown option and consistency of DIPs is important to applications running inside your VMs, you should consider using virtual networks with your VMs.  Virtual networks permit you to assign a specific IP Address Space for use with VMs that are assigned to that virtual network.  As long as you start VMs in the same order in which they were originally provisioned, each VM should be reassigned the same DIP that it was previously using. What about consistency of External IP Addresses? Great question! External IP addresses ( called "Virtual IPs" or "VIPs" in Windows Azure ) are associated with the cloud service in which one or more Windows Azure VMs are running.  As long as at least 1 VM inside a cloud service remains in a "Running" state, the VIP assigned to a cloud service will be preserved.  If all VMs inside a cloud service are in a "Stopped ( Deallocated )" status, then the cloud service may receive a different VIP when VMs are next restarted. TIP: If consistency of VIPs is important for the cloud services in which you are running VMs, consider keeping one VM inside each cloud service in the alternate VM shutdown state listed below to preserve the VIP associated with the cloud service. Shutdown Guest Operating System inside the VM When performing a Guest OS shutdown or restart ( ie., a shutdown or restart operation initiated from the Guest OS running inside the VM ), the VM configuration will not be deallocated from fabric resources. In the figure below, the VM has been shutdown from within the Guest OS and is shown with a "Stopped" VM status rather than the "Stopped ( Deallocated )" VM status that was shown in the previous figure. Note that it may require a few minutes for the Windows Azure Management Portal to reflect that the VM is in a "Stopped" state in this scenario, because we are performing an OS shutdown inside the VM rather than through an Azure management endpoint. Virtual Machine in a "Stopped" Status VMs shown in a "Stopped" status will continue to accumulate compute charges, because fabric resources are still being reserved for these VMs.  However, this also means that DIPs and VIPs are preserved for VMs in this state, so you don't have to worry about VMs and cloud services getting different IP addresses when they are started in the future. Stop VM via Windows PowerShell In the latest version of the Windows Azure PowerShell Module, a new -StayProvisioned parameter has been added to the Stop-AzureVM cmdlet. This new parameter provides the flexibility to choose the VM configuration end result when stopping VMs using PowerShell: When running the Stop-AzureVM cmdlet without the -StayProvisioned parameter specified, the VM will be safely stopped and deallocated; that is, the VM will be left in a "Stopped ( Deallocated )" status just like the end result when a VM Shutdown operation is performed via the Windows Azure Management Portal.  When running the Stop-AzureVM cmdlet with the -StayProvisioned parameter specified, the VM will be safely stopped but fabric resource reservations will be preserved; that is the VM will be left in a "Stopped" status just like the end result when performing a Guest OS shutdown operation. So, with PowerShell, you can choose how Windows Azure should handle VM configuration and fabric resource reservations when stopping VMs on a case-by-case basis. TIP: It's important to note that the -StayProvisioned parameter is only available in the latest version of the Windows Azure PowerShell Module.  So, if you've previously downloaded this module, be sure to download and install the latest version to get this new functionality. Want to Learn More about Windows Azure Infrastructure Services? To learn more about Windows Azure Infrastructure Services, be sure to check-out these additional FREE resources: Become our next "Early Expert"! Complete the Early Experts "Cloud Quest" and build a multi-VM lab network in the cloud for FREE!  Build some cool scenarios! Check out our list of over 20+ Step-by-Step Lab Guides based on key scenarios that IT Pros are implementing on Windows Azure Infrastructure Services TODAY!  Looking forward to seeing you in the Cloud! - Keith Build Your Lab! Download Windows Server 2012 Don’t Have a Lab? Build Your Lab in the Cloud with Windows Azure Virtual Machines Want to Get Certified? Join our Windows Server 2012 "Early Experts" Study Group

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  • DBCC CHECKDB on VVLDB and latches (Or: My Pain is Your Gain)

    - by Argenis
      Does your CHECKDB hurt, Argenis? There is a classic blog series by Paul Randal [blog|twitter] called “CHECKDB From Every Angle” which is pretty much mandatory reading for anybody who’s even remotely considering going for the MCM certification, or its replacement (the Microsoft Certified Solutions Master: Data Platform – makes my fingers hurt just from typing it). Of particular interest is the post “Consistency Options for a VLDB” – on it, Paul provides solid, timeless advice (I use the word “timeless” because it was written in 2007, and it all applies today!) on how to perform checks on very large databases. Well, here I was trying to figure out how to make CHECKDB run faster on a restored copy of one of our databases, which happens to exceed 7TB in size. The whole thing was taking several days on multiple systems, regardless of the storage used – SAS, SATA or even SSD…and I actually didn’t pay much attention to how long it was taking, or even bothered to look at the reasons why - as long as it was finishing okay and found no consistency errors. Yes – I know. That was a huge mistake, as corruption found in a database several days after taking place could only allow for further spread of the corruption – and potentially large data loss. In the last two weeks I increased my attention towards this problem, as we noticed that CHECKDB was taking EVEN LONGER on brand new all-flash storage in the SAN! I couldn’t really explain it, and were almost ready to blame the storage vendor. The vendor told us that they could initially see the server driving decent I/O – around 450Mb/sec, and then it would settle at a very slow rate of 10Mb/sec or so. “Hum”, I thought – “CHECKDB is just not pushing the I/O subsystem hard enough”. Perfmon confirmed the vendor’s observations. Dreaded @BlobEater What was CHECKDB doing all the time while doing so little I/O? Eating Blobs. It turns out that CHECKDB was taking an extremely long time on one of our frankentables, which happens to be have 35 billion rows (yup, with a b) and sucks up several terabytes of space in the database. We do have a project ongoing to purge/split/partition this table, so it’s just a matter of time before we deal with it. But the reality today is that CHECKDB is coming to a screeching halt in performance when dealing with this particular table. Checking sys.dm_os_waiting_tasks and sys.dm_os_latch_stats showed that LATCH_EX (DBCC_OBJECT_METADATA) was by far the top wait type. I remembered hearing recently about that wait from another post that Paul Randal made, but that was related to computed-column indexes, and in fact, Paul himself reminded me of his article via twitter. But alas, our pathologic table had no non-clustered indexes on computed columns. I knew that latches are used by the database engine to do internal synchronization – but how could I help speed this up? After all, this is stuff that doesn’t have a lot of knobs to tweak. (There’s a fantastic level 500 talk by Bob Ward from Microsoft CSS [blog|twitter] called “Inside SQL Server Latches” given at PASS 2010 – and you can check it out here. DISCLAIMER: I assume no responsibility for any brain melting that might ensue from watching Bob’s talk!) Failed Hypotheses Earlier on this week I flew down to Palo Alto, CA, to visit our Headquarters – and after having a great time with my Monkey peers, I was relaxing on the plane back to Seattle watching a great talk by SQL Server MVP and fellow MCM Maciej Pilecki [twitter] called “Masterclass: A Day in the Life of a Database Transaction” where he discusses many different topics related to transaction management inside SQL Server. Very good stuff, and when I got home it was a little late – that slow DBCC CHECKDB that I had been dealing with was way in the back of my head. As I was looking at the problem at hand earlier on this week, I thought “How about I set the database to read-only?” I remembered one of the things Maciej had (jokingly) said in his talk: “if you don’t want locking and blocking, set the database to read-only” (or something to that effect, pardon my loose memory). I immediately killed the CHECKDB which had been running painfully for days, and set the database to read-only mode. Then I ran DBCC CHECKDB against it. It started going really fast (even a bit faster than before), and then throttled down again to around 10Mb/sec. All sorts of expletives went through my head at the time. Sure enough, the same latching scenario was present. Oh well. I even spent some time trying to figure out if NUMA was hurting performance. Folks on Twitter made suggestions in this regard (thanks, Lonny! [twitter]) …Eureka? This past Friday I was still scratching my head about the whole thing; I was ready to start profiling with XPERF to see if I could figure out which part of the engine was to blame and then get Microsoft to look at the evidence. After getting a bunch of good news I’ll blog about separately, I sat down for a figurative smack down with CHECKDB before the weekend. And then the light bulb went on. A sparse column. I thought that I couldn’t possibly be experiencing the same scenario that Paul blogged about back in March showing extreme latching with non-clustered indexes on computed columns. Did I even have a non-clustered index on my sparse column? As it turns out, I did. I had one filtered non-clustered index – with the sparse column as the index key (and only column). To prove that this was the problem, I went and setup a test. Yup, that'll do it The repro is very simple for this issue: I tested it on the latest public builds of SQL Server 2008 R2 SP2 (CU6) and SQL Server 2012 SP1 (CU4). First, create a test database and a test table, which only needs to contain a sparse column: CREATE DATABASE SparseColTest; GO USE SparseColTest; GO CREATE TABLE testTable (testCol smalldatetime SPARSE NULL); GO INSERT INTO testTable (testCol) VALUES (NULL); GO 1000000 That’s 1 million rows, and even though you’re inserting NULLs, that’s going to take a while. In my laptop, it took 3 minutes and 31 seconds. Next, we run DBCC CHECKDB against the database: DBCC CHECKDB('SparseColTest') WITH NO_INFOMSGS, ALL_ERRORMSGS; This runs extremely fast, as least on my test rig – 198 milliseconds. Now let’s create a filtered non-clustered index on the sparse column: CREATE NONCLUSTERED INDEX [badBadIndex] ON testTable (testCol) WHERE testCol IS NOT NULL; With the index in place now, let’s run DBCC CHECKDB one more time: DBCC CHECKDB('SparseColTest') WITH NO_INFOMSGS, ALL_ERRORMSGS; In my test system this statement completed in 11433 milliseconds. 11.43 full seconds. Quite the jump from 198 milliseconds. I went ahead and dropped the filtered non-clustered indexes on the restored copy of our production database, and ran CHECKDB against that. We went down from 7+ days to 19 hours and 20 minutes. Cue the “Argenis is not impressed” meme, please, Mr. LaRock. My pain is your gain, folks. Go check to see if you have any of such indexes – they’re likely causing your consistency checks to run very, very slow. Happy CHECKDBing, -Argenis ps: I plan to file a Connect item for this issue – I consider it a pretty serious bug in the engine. After all, filtered indexes were invented BECAUSE of the sparse column feature – and it makes a lot of sense to use them together. Watch this space and my twitter timeline for a link.

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  • Stairway to Transaction Log Management in SQL Server, Level 1: Transaction Log Overview

    The transaction log is used by SQL Server to maintain data consistency and integrity. If the database is not in Simple-recovery mode, it can also be used in an appropriate backup regime to restore the database to a point in time. The Future of SQL Server Monitoring "Being web-based, SQL Monitor enables you to check on your servers from almost any location" Jonathan Allen.Try SQL Monitor now.

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  • DBA Best Practices - A Blog Series: Episode 1 - Backups

    - by Argenis
      This blog post is part of the DBA Best Practices series, on which various topics of concern for daily database operations are discussed. Your feedback and comments are very much welcome, so please drop by the comments section and be sure to leave your thoughts on the subject. Morning Coffee When I was a DBA, the first thing I did when I sat down at my desk at work was checking that all backups had completed successfully. It really was more of a ritual, since I had a dual system in place to check for backup completion: 1) the scheduled agent jobs to back up the databases were set to alert the NOC in failure, and 2) I had a script run from a central server every so often to check for any backup failures. Why the redundancy, you might ask. Well, for one I was once bitten by the fact that database mail doesn't work 100% of the time. Potential causes for failure include issues on the SMTP box that relays your server email, firewall problems, DNS issues, etc. And so to be sure that my backups completed fine, I needed to rely on a mechanism other than having the servers do the taking - I needed to interrogate the servers and ask each one if an issue had occurred. This is why I had a script run every so often. Some of you might have monitoring tools in place like Microsoft System Center Operations Manager (SCOM) or similar 3rd party products that would track all these things for you. But at that moment, we had no resort but to write our own Powershell scripts to do it. Now it goes without saying that if you don't have backups in place, you might as well find another career. Your most sacred job as a DBA is to protect the data from a disaster, and only properly safeguarded backups can offer you peace of mind here. "But, we have a cluster...we don't need backups" Sadly I've heard this line more than I would have liked to. You need to understand that a cluster is comprised of shared storage, and that is precisely your single point of failure. A cluster will protect you from an issue at the Operating System level, and also under an outage of any SQL-related service or dependent devices. But it will most definitely NOT protect you against corruption, nor will it protect you against somebody deleting data from a table - accidentally or otherwise. Backup, fine. How often do I take a backup? The answer to this is something you will hear frequently when working with databases: it depends. What does it depend on? For one, you need to understand how much data your business is willing to lose. This is what's called Recovery Point Objective, or RPO. If you don't know how much data your business is willing to lose, you need to have an honest and realistic conversation about data loss expectations with your customers, internal or external. From my experience, their first answer to the question "how much data loss can you withstand?" will be "zero". In that case, you will need to explain how zero data loss is very difficult and very costly to achieve, even in today's computing environments. Do you want to go ahead and take full backups of all your databases every hour, or even every day? Probably not, because of the impact that taking a full backup can have on a system. That's what differential and transaction log backups are for. Have I answered the question of how often to take a backup? No, and I did that on purpose. You need to think about how much time you have to recover from any event that requires you to restore your databases. This is what's called Recovery Time Objective. Again, if you go ask your customer how long of an outage they can withstand, at first you will get a completely unrealistic number - and that will be your starting point for discussing a solution that is cost effective. The point that I'm trying to get across is that you need to have a plan. This plan needs to be practiced, and tested. Like a football playbook, you need to rehearse the moves you'll perform when the time comes. How often is up to you, and the objective is that you feel better about yourself and the steps you need to follow when emergency strikes. A backup is nothing more than an untested restore Backups are files. Files are prone to corruption. Put those two together and realize how you feel about those backups sitting on that network drive. When was the last time you restored any of those? Restoring your backups on another box - that, by the way, doesn't have to match the specs of your production server - will give you two things: 1) peace of mind, because now you know that your backups are good and 2) a place to offload your consistency checks with DBCC CHECKDB or any of the other DBCC commands like CHECKTABLE or CHECKCATALOG. This is a great strategy for VLDBs that cannot withstand the additional load created by the consistency checks. If you choose to offload your consistency checks to another server though, be sure to run DBCC CHECKDB WITH PHYSICALONLY on the production server, and if you're using SQL Server 2008 R2 SP1 CU4 and above, be sure to enable traceflags 2562 and/or 2549, which will speed up the PHYSICALONLY checks further - you can read more about this enhancement here. Back to the "How Often" question for a second. If you have the disk, and the network latency, and the system resources to do so, why not backup the transaction log often? As in, every 5 minutes, or even less than that? There's not much downside to doing it, as you will have to clear the log with a backup sooner than later, lest you risk running out space on your tlog, or even your drive. The one drawback to this approach is that you will have more files to deal with at restore time, and processing each file will add a bit of extra time to the entire process. But it might be worth that time knowing that you minimized the amount of data lost. Again, test your plan to make sure that it matches your particular needs. Where to back up to? Network share? Locally? SAN volume? This is another topic where everybody has a favorite choice. So, I'll stick to mentioning what I like to do and what I consider to be the best practice in this regard. I like to backup to a SAN volume, i.e., a drive that actually lives in the SAN, and can be easily attached to another server in a pinch, saving you valuable time - you wouldn't need to restore files on the network (slow) or pull out drives out a dead server (been there, done that, it’s also slow!). The key is to have a copy of those backup files made quickly, and, if at all possible, to a remote target on a different datacenter - or even the cloud. There are plenty of solutions out there that can help you put such a solution together. That right there is the first step towards a practical Disaster Recovery plan. But there's much more to DR, and that's material for a different blog post in this series.

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  • Oracle Magazine, July/August 2008

    Oracle Magazine July/August features articles on business intelligence, Linux, green technology, Oracle OpenWorld, Oracle Advanced Compression, Oracle Total Recall, managing files, using database advisors, Linux kernel, page template consistency, handling exceptions, client result cache, and much more.

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  • DBA Best Practices - A Blog Series: Episode 1 - Backups

    - by Argenis
      This blog post is part of the DBA Best Practices series, on which various topics of concern for daily database operations are discussed. Your feedback and comments are very much welcome, so please drop by the comments section and be sure to leave your thoughts on the subject. Morning Coffee When I was a DBA, the first thing I did when I sat down at my desk at work was checking that all backups have completed successfully. It really was more of a ritual, since I had a dual system in place to check for backup completion: 1) the scheduled agent jobs to back up the databases were set to alert the NOC in failure, and 2) I had a script run from a central server every so often to check for any backup failures. Why the redundancy, you might ask. Well, for one I was once bitten by the fact that database mail doesn't work 100% of the time. Potential causes for failure include issues on the SMTP box that relays your server email, firewall problems, DNS issues, etc. And so to be sure that my backups completed fine, I needed to rely on a mechanism other than having the servers do the taking - I needed to interrogate the servers and ask each one if an issue had occurred. This is why I had a script run every so often. Some of you might have monitoring tools in place like Microsoft System Center Operations Manager (SCOM) or similar 3rd party products that would track all these things for you. But at that moment, we had no resort but to write our own Powershell scripts to do it. Now it goes without saying that if you don't have backups in place, you might as well find another career. Your most sacred job as a DBA is to protect the data from a disaster, and only properly safeguarded backups can offer you peace of mind here. "But, we have a cluster...we don't need backups" Sadly I've heard this line more than I would have liked to. You need to understand that a cluster is comprised of shared storage, and that is precisely your single point of failure. A cluster will protect you from an issue at the Operating System level, and also under an outage of any SQL-related service or dependent devices. But it will most definitely NOT protect you against corruption, nor will it protect you against somebody deleting data from a table - accidentally or otherwise. Backup, fine. How often do I take a backup? The answer to this is something you will hear frequently when working with databases: it depends. What does it depend on? For one, you need to understand how much data your business is willing to lose. This is what's called Recovery Point Objective, or RPO. If you don't know how much data your business is willing to lose, you need to have an honest and realistic conversation about data loss expectations with your customers, internal or external. From my experience, their first answer to the question "how much data loss can you withstand?" will be "zero". In that case, you will need to explain how zero data loss is very difficult and very costly to achieve, even in today's computing environments. Do you want to go ahead and take full backups of all your databases every hour, or even every day? Probably not, because of the impact that taking a full backup can have on a system. That's what differential and transaction log backups are for. Have I answered the question of how often to take a backup? No, and I did that on purpose. You need to think about how much time you have to recover from any event that requires you to restore your databases. This is what's called Recovery Time Objective. Again, if you go ask your customer how long of an outage they can withstand, at first you will get a completely unrealistic number - and that will be your starting point for discussing a solution that is cost effective. The point that I'm trying to get across is that you need to have a plan. This plan needs to be practiced, and tested. Like a football playbook, you need to rehearse the moves you'll perform when the time comes. How often is up to you, and the objective is that you feel better about yourself and the steps you need to follow when emergency strikes. A backup is nothing more than an untested restore Backups are files. Files are prone to corruption. Put those two together and realize how you feel about those backups sitting on that network drive. When was the last time you restored any of those? Restoring your backups on another box - that, by the way, doesn't have to match the specs of your production server - will give you two things: 1) peace of mind, because now you know that your backups are good and 2) a place to offload your consistency checks with DBCC CHECKDB or any of the other DBCC commands like CHECKTABLE or CHECKCATALOG. This is a great strategy for VLDBs that cannot withstand the additional load created by the consistency checks. If you choose to offload your consistency checks to another server though, be sure to run DBCC CHECKDB WITH PHYSICALONLY on the production server, and if you're using SQL Server 2008 R2 SP1 CU4 and above, be sure to enable traceflags 2562 and/or 2549, which will speed up the PHYSICALONLY checks further - you can read more about this enhancement here. Back to the "How Often" question for a second. If you have the disk, and the network latency, and the system resources to do so, why not backup the transaction log often? As in, every 5 minutes, or even less than that? There's not much downside to doing it, as you will have to clear the log with a backup sooner than later, lest you risk running out space on your tlog, or even your drive. The one drawback to this approach is that you will have more files to deal with at restore time, and processing each file will add a bit of extra time to the entire process. But it might be worth that time knowing that you minimized the amount of data lost. Again, test your plan to make sure that it matches your particular needs. Where to back up to? Network share? Locally? SAN volume? This is another topic where everybody has a favorite choice. So, I'll stick to mentioning what I like to do and what I consider to be the best practice in this regard. I like to backup to a SAN volume, i.e., a drive that actually lives in the SAN, and can be easily attached to another server in a pinch, saving you valuable time - you wouldn't need to restore files on the network (slow) or pull out drives out a dead server (been there, done that, it’s also slow!). The key is to have a copy of those backup files made quickly, and, if at all possible, to a remote target on a different datacenter - or even the cloud. There are plenty of solutions out there that can help you put such a solution together. That right there is the first step towards a practical Disaster Recovery plan. But there's much more to DR, and that's material for a different blog post in this series.

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  • WEBCAST: Strategies for Managing the Oracle Database Lifecycle

    - by Scott McNeil
    Thursday November 110:00 a.m. PST / 1:00 p.m. EST Join us for a live Webcast and see how Oracle Enterprise Manager 12c makes database lifecycle management easier. You’ll learn how to: Simplify database configurations thanks to extensive automation for discovery and change detection Improve IT service levels with Oracle’s next-generation database patching and provisioning automation Ensure consistency and compliance with comprehensive database change management Register today. Stay Connected: Twitter | Facebook | YouTube | Linkedin | NewsletterDownload the Oracle Enterprise Manager Cloud Control12c Mobile app

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  • SQL Date Comparison

    - by Derek Dieter
    When comparing the datetime datatype in SQL Server, it is important to maintain consistency in order to gaurd against SQL interpreting a date differently than you intend. In at least one occasion I have seen someone specify a short format for a date, like (1/4/08) only to find that SQL interpreted the month as [...]

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  • Why are source control systems still mostly backed with files?

    - by Andy
    It seems that more source control systems still use files as the means of storing the version data. Vault and TFS use Sql Server as their data store, which I would think would be better for data consistency as well as speed. So why is it that SVN, I believe GIT, CVS, etc still use the file system as essentially a database, (I ask this question as we had our SVN server just corrupt itself during a normal commit) instead of using actual database software (MSSQL, Oracle, Postgre, etc)?

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  • Supercharge your CRM solution with Oracle Policy Automation

    Tune into this conversation with Davin Fifield, VP, Product Development for Oracle Policy Automation to learn how to rapidly deliver customer self-service for product selection, significantly lower training costs for rolling out new call center processes, and in general dramatically improve business agility, consistency and transparency of decision making within and beyond your CRM solution of choice.

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  • UML Receptions and AcceptEventActions

    - by Silli
    What shall be the relationship between the receptions of a class (was classifier before Aadaam correction) and the AcceptEventActions in the activity describing the behavior of its instances? I understand the former is related to signals reception of the type while the latter is related to runtime ReceiveSignalEvent events of the class instances (objects). But it is not totally clear to me how to express consistency among these constructs.

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  • SQL Server Reporting Services Advanced Charting

    SQL Server Reporting Services (SSRS) has evolved over the years to incorporate many new data visualization capabilities. In this article, Scott Murray illustrates how DBAs can use these tools to produce reports that include Indicators, Embedded Charts, Sparklins, and Chart overlays. Countless happy developers. One award-winning bundle.The SQL Developer Bundle can transform the way you and your team work, aiding collaboration, efficiency, and consistency. Download your free trial now.

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  • Why Does the SEO Process Take So Long? Expert SEO Speaks Out

    For the first 6 months, the SEO expert works on identifying the winning keywords, implementing on-page optimization and content strategies, and building diverse quality links back to the important keyword pages on your website. Most time consuming is the building of a solid Link Reputation by implementing a focused SEO Strategy which is in alignment with the "New Link Variables" like - Consistency, Relevancy, Diversity, Progression, Participation and Age of links. So first ask yourself, is your SEO strategy, the right SEO strategy for your website?

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  • Why does GtkCalendar counts months from 0?

    - by int_ua
    So I spent several hours in rage, figuring out why isn't my code writing to the /sys/class/rtc/rtc0/wakealarm correctly. The problem is that it doesn't return anything if the value is wrong. And finally I noticed this small 5 between the year and the day. Why isn't it counting days and years from zero for consistency? For comparison: QCalendarWidget counts month from 1 to 12 (docs) So GtkCalendar... F**k You!

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  • Error during installation of an SQL server Failover Cluster Instance

    A common issue I've run into while helping with SQL Server Failover Cluster (FCI) installations is the failure of the Network Name. In the following post I'll discuss a bit of background, the common root cause, and how to resolve it. Countless happy developers. One award-winning bundle.The SQL Developer Bundle can transform the way you and your team work, aiding collaboration, efficiency, and consistency. Download your free trial now.

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