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  • Expanding list of databases in SQL Server 2008 Management Studio Takes Longer than SQL Server 2005

    - by Clever Human
    Is it just me, or does expanding the list of databases in SQL Server 2008 Management Studio take significantly more time than expanding the list of databases in SQL Server 2005 Management Studio? If it isn't just me, is there an explanation for this behavior? Whatever it is doing in the background that makes it take longer, can we turn that off? Is it configurable? I know, it seems trivial, but I am perpetually being surprised at how long this takes.

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  • Different databases using WCF dataservice

    - by espenk
    I have multiple SQL Server databases with the same schema. I would like to use one WCF data service (Rest service) to access the different databases. How can I accomplish this so the client can pass in the correct database name or connection string?

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  • Is anyone using KVM in production?

    - by Andy Shellam
    I've been trying to set up a pair of servers utilising KVM on Ubuntu 9.10 to host 8 virtual machines between them and ended up with various issues from the VMs freezing, to not powering on. I had one virtual server set up and running and was setting up a second, when any operation involving OpenSSL would cause the VM to lock up in a weird way - all network traffic would cease, it wouldn't process logins on the console, but it wasn't taking any CPU time off the host. The first virtual server was identical and worked perfectly. Another VM I tried to setup had installed Ubuntu fine then refused to reboot, throwing kernel exceptions to do with XFS. I've now installed Citrix XenServer 5.5 on both hosts, and am now setting up my third VM with absolutely no issues. I also had the same experience when I tried VMware, but I preferred Xen as it appears to give more features on the free license. My question is am I just unlucky with KVM, or is KVM as unstable as it appears? Are you using, or planning on using, KVM in production, and how successful have you been?

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  • ubuntu - Best way of repartitioning a (running) production server

    - by egarcia
    I've got an (externally hosted) production server running Ubuntu LTS. It serves webpages (rails) and has an svn repository accesible through Apache, and a PostgreSQL db. I've got ssh access to the server and root privileges. Most of the "interesting" stuff is located in /var/ : svn repositories are inside /var/svn, web pages under /var/www, etc. Yesterday I was curious about how much disk space had it left, so I did the following: $ df -h Filesystem Size Used Avail Use% Mounted on /dev/md1 950M 402M 500M 45% / varrun 990M 64K 990M 1% /var/run varlock 990M 0 990M 0% /var/lock udev 990M 76K 989M 1% /dev devshm 990M 0 990M 0% /dev/shm /dev/md5 4.7G 668M 4.1G 15% /usr /dev/md6 4.7G 1.4G 3.4G 29% /var /dev/md7 221G 28M 221G 1% /home none 990M 4.0K 990M 1% /tmp My 'var' partition, which holds most of the interesting part, is only 4.7G big. The /home/ partition, on the other hand, is 221G, but it is mostly unused. I should have checked the disk layout before starting installing stuff. Ideally I would need /var/ and /home/ to be "switched" - /home/ should be the one with 4.7G, and /var/ the one with 221G. Is there a way to solve this without having to reinstall the whole thing?

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  • Real benefits of tcp TIME-WAIT and implications in production environment

    - by user64204
    SOME THEORY I've been doing some reading on tcp TIME-WAIT (here and there) and what I read is that it's a value set to 2 x MSL (maximum segment life) which keeps a connection in the "connection table" for a while to guarantee that, "before your allowed to create a connection with the same tuple, all the packets belonging to previous incarnations of that tuple will be dead". Since segments received (apart from SYN under specific circumstances) while a connection is either in TIME-WAIT or no longer existing would be discarded, why not close the connection right away? Q1: Is it because there is less processing involved in dealing with segments from old connections and less processing to create a new connection on the same tuple when in TIME-WAIT (i.e. are there performance benefits)? If the above explanation doesn't stand, the only reason I see the TIME-WAIT being useful would be if a client sends a SYN for a connection before it sends remaining segments for an old connection on the same tuple in which case the receiver would re-open the connection but then get bad segments and and would have to terminate it. Q2: Is this analysis correct? Q3: Are there other benefits to using TIME-WAIT? SOME PRACTICE I've been looking at the munin graphs on a production server that I administrate. Here is one: As you can see there are more connections in TIME-WAIT than ESTABLISHED, around twice as many most of the time, on some occasions four times as many. Q4: Does this have an impact on performance? Q5: If so, is it wise/recommended to reduce the TIME-WAIT value (and what to)? Q6: Is this ratio of TIME-WAIT / ESTABLISHED connections normal? Could this be related to malicious connection attempts?

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  • Replication keeps popping up on SharePoint databases

    - by Ddono25
    My typical discovery scenario: We receive an alert that the transaction log is growing quickly. We are in Simple Recovery so I go to check it out. Log is already sized to 100GB and is at 80% capacity. I run the "Whats using my log files" script from SQL Server Central and see that Replication is enabled on the database. We do not set up replication, and I don't think Replication can be done on SharePoint content db's as Replication is not supported (requires PK on all tables). This has been occurring on random servers (about 5 so far, all within the past three weeks) and it only occurs on Content Databases. sp_removedbreplication does not always work in removing the Replication either. We have found that we need to run the sp_removedbreplication, change all db owners to SA and reset Recovery Mode to Simple to completely eradicate any vestiges of this bug. How would Replication be enabling itself? We have never set up Replication on these servers. There is no evidence of any type of Replication other than the 'log_reuse_wait_desc' from the DMV query and log growth. Any help on this ghost would be appreciated!

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  • Production monitoring for EC2 instances

    - by Janine
    I'm setting up my first production instance on EC2 and want to make sure I have all necessary monitoring in place. There are three different types of things I want to monitor: Is the instance running? EC2 instances can be terminated without warning if the underlying hardware fails, and as far as I know they aren't automatically restarted. So if not, start it back up. Is UNIX running properly? This is the usual stuff about CPU load, disk space, etc. Is the website responding? If not, restart it. I initially set up Nagios on a physical server outside the cloud, but it is really only helpful for item 2. It can tell me if the instance is gone or if the website is not responding, but as far as I can tell it can't execute any commands to fix the situation. My Googling on this subject has yielded a plethora of options - Cacti, Monit, God, Ganglia, and probably more I'm forgetting now. I don't have time to research them all. I am aware of Amazon's Cloudwatch but it doesn't seem to do anything that my Nagios installation doesn't already do. If you already have something like this in place, can you please share what has worked well for you?

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  • Fun with Aggregates

    - by Paul White
    There are interesting things to be learned from even the simplest queries.  For example, imagine you are given the task of writing a query to list AdventureWorks product names where the product has at least one entry in the transaction history table, but fewer than ten. One possible query to meet that specification is: SELECT p.Name FROM Production.Product AS p JOIN Production.TransactionHistory AS th ON p.ProductID = th.ProductID GROUP BY p.ProductID, p.Name HAVING COUNT_BIG(*) < 10; That query correctly returns 23 rows (execution plan and data sample shown below): The execution plan looks a bit different from the written form of the query: the base tables are accessed in reverse order, and the aggregation is performed before the join.  The general idea is to read all rows from the history table, compute the count of rows grouped by ProductID, merge join the results to the Product table on ProductID, and finally filter to only return rows where the count is less than ten. This ‘fully-optimized’ plan has an estimated cost of around 0.33 units.  The reason for the quote marks there is that this plan is not quite as optimal as it could be – surely it would make sense to push the Filter down past the join too?  To answer that, let’s look at some other ways to formulate this query.  This being SQL, there are any number of ways to write logically-equivalent query specifications, so we’ll just look at a couple of interesting ones.  The first query is an attempt to reverse-engineer T-SQL from the optimized query plan shown above.  It joins the result of pre-aggregating the history table to the Product table before filtering: SELECT p.Name FROM ( SELECT th.ProductID, cnt = COUNT_BIG(*) FROM Production.TransactionHistory AS th GROUP BY th.ProductID ) AS q1 JOIN Production.Product AS p ON p.ProductID = q1.ProductID WHERE q1.cnt < 10; Perhaps a little surprisingly, we get a slightly different execution plan: The results are the same (23 rows) but this time the Filter is pushed below the join!  The optimizer chooses nested loops for the join, because the cardinality estimate for rows passing the Filter is a bit low (estimate 1 versus 23 actual), though you can force a merge join with a hint and the Filter still appears below the join.  In yet another variation, the < 10 predicate can be ‘manually pushed’ by specifying it in a HAVING clause in the “q1” sub-query instead of in the WHERE clause as written above. The reason this predicate can be pushed past the join in this query form, but not in the original formulation is simply an optimizer limitation – it does make efforts (primarily during the simplification phase) to encourage logically-equivalent query specifications to produce the same execution plan, but the implementation is not completely comprehensive. Moving on to a second example, the following query specification results from phrasing the requirement as “list the products where there exists fewer than ten correlated rows in the history table”: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) < 10 ); Unfortunately, this query produces an incorrect result (86 rows): The problem is that it lists products with no history rows, though the reasons are interesting.  The COUNT_BIG(*) in the EXISTS clause is a scalar aggregate (meaning there is no GROUP BY clause) and scalar aggregates always produce a value, even when the input is an empty set.  In the case of the COUNT aggregate, the result of aggregating the empty set is zero (the other standard aggregates produce a NULL).  To make the point really clear, let’s look at product 709, which happens to be one for which no history rows exist: -- Scalar aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709;   -- Vector aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709 GROUP BY th.ProductID; The estimated execution plans for these two statements are almost identical: You might expect the Stream Aggregate to have a Group By for the second statement, but this is not the case.  The query includes an equality comparison to a constant value (709), so all qualified rows are guaranteed to have the same value for ProductID and the Group By is optimized away. In fact there are some minor differences between the two plans (the first is auto-parameterized and qualifies for trivial plan, whereas the second is not auto-parameterized and requires cost-based optimization), but there is nothing to indicate that one is a scalar aggregate and the other is a vector aggregate.  This is something I would like to see exposed in show plan so I suggested it on Connect.  Anyway, the results of running the two queries show the difference at runtime: The scalar aggregate (no GROUP BY) returns a result of zero, whereas the vector aggregate (with a GROUP BY clause) returns nothing at all.  Returning to our EXISTS query, we could ‘fix’ it by changing the HAVING clause to reject rows where the scalar aggregate returns zero: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) BETWEEN 1 AND 9 ); The query now returns the correct 23 rows: Unfortunately, the execution plan is less efficient now – it has an estimated cost of 0.78 compared to 0.33 for the earlier plans.  Let’s try adding a redundant GROUP BY instead of changing the HAVING clause: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY th.ProductID HAVING COUNT_BIG(*) < 10 ); Not only do we now get correct results (23 rows), this is the execution plan: I like to compare that plan to quantum physics: if you don’t find it shocking, you haven’t understood it properly :)  The simple addition of a redundant GROUP BY has resulted in the EXISTS form of the query being transformed into exactly the same optimal plan we found earlier.  What’s more, in SQL Server 2008 and later, we can replace the odd-looking GROUP BY with an explicit GROUP BY on the empty set: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ); I offer that as an alternative because some people find it more intuitive (and it perhaps has more geek value too).  Whichever way you prefer, it’s rather satisfying to note that the result of the sub-query does not exist for a particular correlated value where a vector aggregate is used (the scalar COUNT aggregate always returns a value, even if zero, so it always ‘EXISTS’ regardless which ProductID is logically being evaluated). The following query forms also produce the optimal plan and correct results, so long as a vector aggregate is used (you can probably find more equivalent query forms): WHERE Clause SELECT p.Name FROM Production.Product AS p WHERE ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) < 10; APPLY SELECT p.Name FROM Production.Product AS p CROSS APPLY ( SELECT NULL FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ) AS ca (dummy); FROM Clause SELECT q1.Name FROM ( SELECT p.Name, cnt = ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) FROM Production.Product AS p ) AS q1 WHERE q1.cnt < 10; This last example uses SUM(1) instead of COUNT and does not require a vector aggregate…you should be able to work out why :) SELECT q.Name FROM ( SELECT p.Name, cnt = ( SELECT SUM(1) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID ) FROM Production.Product AS p ) AS q WHERE q.cnt < 10; The semantics of SQL aggregates are rather odd in places.  It definitely pays to get to know the rules, and to be careful to check whether your queries are using scalar or vector aggregates.  As we have seen, query plans do not show in which ‘mode’ an aggregate is running and getting it wrong can cause poor performance, wrong results, or both. © 2012 Paul White Twitter: @SQL_Kiwi email: [email protected]

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  • Fun with Aggregates

    - by Paul White
    There are interesting things to be learned from even the simplest queries.  For example, imagine you are given the task of writing a query to list AdventureWorks product names where the product has at least one entry in the transaction history table, but fewer than ten. One possible query to meet that specification is: SELECT p.Name FROM Production.Product AS p JOIN Production.TransactionHistory AS th ON p.ProductID = th.ProductID GROUP BY p.ProductID, p.Name HAVING COUNT_BIG(*) < 10; That query correctly returns 23 rows (execution plan and data sample shown below): The execution plan looks a bit different from the written form of the query: the base tables are accessed in reverse order, and the aggregation is performed before the join.  The general idea is to read all rows from the history table, compute the count of rows grouped by ProductID, merge join the results to the Product table on ProductID, and finally filter to only return rows where the count is less than ten. This ‘fully-optimized’ plan has an estimated cost of around 0.33 units.  The reason for the quote marks there is that this plan is not quite as optimal as it could be – surely it would make sense to push the Filter down past the join too?  To answer that, let’s look at some other ways to formulate this query.  This being SQL, there are any number of ways to write logically-equivalent query specifications, so we’ll just look at a couple of interesting ones.  The first query is an attempt to reverse-engineer T-SQL from the optimized query plan shown above.  It joins the result of pre-aggregating the history table to the Product table before filtering: SELECT p.Name FROM ( SELECT th.ProductID, cnt = COUNT_BIG(*) FROM Production.TransactionHistory AS th GROUP BY th.ProductID ) AS q1 JOIN Production.Product AS p ON p.ProductID = q1.ProductID WHERE q1.cnt < 10; Perhaps a little surprisingly, we get a slightly different execution plan: The results are the same (23 rows) but this time the Filter is pushed below the join!  The optimizer chooses nested loops for the join, because the cardinality estimate for rows passing the Filter is a bit low (estimate 1 versus 23 actual), though you can force a merge join with a hint and the Filter still appears below the join.  In yet another variation, the < 10 predicate can be ‘manually pushed’ by specifying it in a HAVING clause in the “q1” sub-query instead of in the WHERE clause as written above. The reason this predicate can be pushed past the join in this query form, but not in the original formulation is simply an optimizer limitation – it does make efforts (primarily during the simplification phase) to encourage logically-equivalent query specifications to produce the same execution plan, but the implementation is not completely comprehensive. Moving on to a second example, the following query specification results from phrasing the requirement as “list the products where there exists fewer than ten correlated rows in the history table”: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) < 10 ); Unfortunately, this query produces an incorrect result (86 rows): The problem is that it lists products with no history rows, though the reasons are interesting.  The COUNT_BIG(*) in the EXISTS clause is a scalar aggregate (meaning there is no GROUP BY clause) and scalar aggregates always produce a value, even when the input is an empty set.  In the case of the COUNT aggregate, the result of aggregating the empty set is zero (the other standard aggregates produce a NULL).  To make the point really clear, let’s look at product 709, which happens to be one for which no history rows exist: -- Scalar aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709;   -- Vector aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709 GROUP BY th.ProductID; The estimated execution plans for these two statements are almost identical: You might expect the Stream Aggregate to have a Group By for the second statement, but this is not the case.  The query includes an equality comparison to a constant value (709), so all qualified rows are guaranteed to have the same value for ProductID and the Group By is optimized away. In fact there are some minor differences between the two plans (the first is auto-parameterized and qualifies for trivial plan, whereas the second is not auto-parameterized and requires cost-based optimization), but there is nothing to indicate that one is a scalar aggregate and the other is a vector aggregate.  This is something I would like to see exposed in show plan so I suggested it on Connect.  Anyway, the results of running the two queries show the difference at runtime: The scalar aggregate (no GROUP BY) returns a result of zero, whereas the vector aggregate (with a GROUP BY clause) returns nothing at all.  Returning to our EXISTS query, we could ‘fix’ it by changing the HAVING clause to reject rows where the scalar aggregate returns zero: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) BETWEEN 1 AND 9 ); The query now returns the correct 23 rows: Unfortunately, the execution plan is less efficient now – it has an estimated cost of 0.78 compared to 0.33 for the earlier plans.  Let’s try adding a redundant GROUP BY instead of changing the HAVING clause: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY th.ProductID HAVING COUNT_BIG(*) < 10 ); Not only do we now get correct results (23 rows), this is the execution plan: I like to compare that plan to quantum physics: if you don’t find it shocking, you haven’t understood it properly :)  The simple addition of a redundant GROUP BY has resulted in the EXISTS form of the query being transformed into exactly the same optimal plan we found earlier.  What’s more, in SQL Server 2008 and later, we can replace the odd-looking GROUP BY with an explicit GROUP BY on the empty set: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ); I offer that as an alternative because some people find it more intuitive (and it perhaps has more geek value too).  Whichever way you prefer, it’s rather satisfying to note that the result of the sub-query does not exist for a particular correlated value where a vector aggregate is used (the scalar COUNT aggregate always returns a value, even if zero, so it always ‘EXISTS’ regardless which ProductID is logically being evaluated). The following query forms also produce the optimal plan and correct results, so long as a vector aggregate is used (you can probably find more equivalent query forms): WHERE Clause SELECT p.Name FROM Production.Product AS p WHERE ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) < 10; APPLY SELECT p.Name FROM Production.Product AS p CROSS APPLY ( SELECT NULL FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ) AS ca (dummy); FROM Clause SELECT q1.Name FROM ( SELECT p.Name, cnt = ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) FROM Production.Product AS p ) AS q1 WHERE q1.cnt < 10; This last example uses SUM(1) instead of COUNT and does not require a vector aggregate…you should be able to work out why :) SELECT q.Name FROM ( SELECT p.Name, cnt = ( SELECT SUM(1) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID ) FROM Production.Product AS p ) AS q WHERE q.cnt < 10; The semantics of SQL aggregates are rather odd in places.  It definitely pays to get to know the rules, and to be careful to check whether your queries are using scalar or vector aggregates.  As we have seen, query plans do not show in which ‘mode’ an aggregate is running and getting it wrong can cause poor performance, wrong results, or both. © 2012 Paul White Twitter: @SQL_Kiwi email: [email protected]

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  • Node.js server crashes , Database operations halfway?

    - by Ranadeep
    I have a node.js app with mongodb backend going to production in a week and i have few doubts on how to handle app crashes and restart . Say i have a simple route /followUser in which i have 2 database operations /followUser ----->Update User1 Document.followers = User2 ----->Update User2 Document.followers = User1 ----->Some other mongodb(via mongoose)operation What happens if there is a server crash(due to power failure or maybe the remote mongodb server is down ) like this scenario : ----->Update User1 Document.followers = User2 SERVER CRASHED , FOREVER RESTARTS NODE What happens to these operations below ? The system is now in inconsistent state and i may have error everytime i ask for User2 followers ----->Update User2 Document.followers = User1 ----->Some other mongodb(via mongoose)operation Also please recommend good logging and restart/monitor modules for apps running in linux

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  • Is there an established or defined best practice for source control branching between development and production builds?

    - by Matthew Patrick Cashatt
    Thanks for looking. I struggled in how to phrase my question, so let me give an example in hopes of making more clear what I am after: I currently work on a dev team responsible for maintaining and adding features to a web application. We have a development server and we use source control (TFS). Each day everyone checks in their code and when the code (running on the dev server) passes our QA/QC program, it goes to production. Recently, however, we had a bug in production which required an immediate production fix. The problem was that several of us developers had code checked in that was not ready for production so we had to either quickly complete and QA the code, or roll back everything, undo pending changes, etc. In other words, it was a mess. This made me wonder: Is there an established design pattern that prevents this type of scenario. It seems like there must be some "textbook" answer to this, but I am unsure what that would be. Perhaps a development branch of the code and a "release-ready" or production branch of the code?

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  • What to do with database in dev/production phases of a website?

    - by TheLQ
    For a while now I've been keeping a website I'm developing in the standard dev/production phases. Its been pretty simple: Mercurial repo for dev, repo for production. Do work in dev, get approved, push to production. But now I'm trying to apply this process to a new website that has a database and am struggling on how to figure out a development strategy. What I didn't mention above is that I do all my work on my own repo, push it to dev, then later push it to production, so its 3 different servers. So how do I manage my database? The obvious solution of mysqldump every commit isn't going to happen, and a dump at the end of the day isn't all that helpful when you want to undo later one change that happened in the middle of the day. What is the best way to accomplish this?

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  • SSL Certificates, two-way authentication and loadbalancers

    - by 5arx
    We're looking to implement two-way authentication with client certificates for a privileged subset of our application users. The idea will be that if a certificate is detected the user will be asked for an additional password/PIN and that will be used to verify the certificate and user. Ordinary users will continue to authenticate themselves via the standard login mechanism. Our production environment (hosted by a well-known company) comprises load-balanced application servers and I'm unclear as to how this set-up will handle the certificates and I'm not certain if there are any pitfalls I should be aware of. I would very appreciate some thoughts, comments or real-world advice on the subject.

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  • Creating a Sharepoint Development Environment from an Existing Production Environment

    - by Starky
    I have very little experience using Sharepoint but a good amount using Visual Studio 2008, SQL Server 2005, Windows Server 2003 and IIS6. I need to create a development environment for a SharePoint 2007 system that will be used internally. The system is already deployed over two servers - one of the servers simply holds the database and everything else is on the other server. We are also using WSS 3.0. I have created a Virtual Machine with all the required software including a clean installation of SharePoint Server 2007 and I wish to use this single Virtual Machine as the development environment. Right now there are no custom assemblies being used on the production server as far as I am aware. There are 3 websites, one over port 80 for user accesss, one over a custom port for central administration, and one over another custom port. Not sure what the last one is for but my blank instance of Sharepoint on my Virtual Machine also has something similar. I attempted to use the STSADM tool to backup and restore these 3 sites from my production environment to my development environment and while the operations completed succesfully, the central administration site in my development environment acted strangely and I could not access port 80 - I did not seem to have correct credentials for it. I suspected that it would not have been so simple so could I please have advice on how to create my development environment so that I can use it to deploy updates to the production one.

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  • SQL Server slow in production environment

    - by Lieven Cardoen
    I have a weird problem in a customer's production environment. I can't give any details on the infrastructure, except that SQL server runs on a virtual server. The data, log and filestream file are on another storage server (data and filestream together and log on a separate server). In our local Test environment, there's one particular query that executes with these durations: first we clear the cache 300ms (First time it takes longer, but from then on it's cached.) 20ms 15ms 17ms In the customer's production environment, the SQL Server is more powerful, these are the durations (I didn't have the rights to clear the cache. Will try this tomorrow). 2500ms 2600ms 2400ms The servers in the customer's production environment are more powerful but they do have virtual servers (we don't). What could be the cause... Not enough memory? Fragmentation? Physical storage? How would you tackle this performance problem? EDIT: Some people have asked me if the data set is equal and it is. I restored their database on our environment. It's true that this was the first thing I looked at. (@Everyone: I added the edit because it will be the first thing that many will think off).

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  • What should every developer know about databases?

    - by Aaronaught
    Whether we like it or not, many if not most of us developers either regularly work with databases or may have to work with one someday. And considering the amount of misuse and abuse in the wild, and the volume of database-related questions that come up every day, it's fair to say that there are certain concepts that developers should know - even if they don't design or work with databases today. So: What are the important concepts that developers and other software professionals ought to know about databases? Guidelines for Responses: Keep your list short. One concept per answer is best. Be specific. "Data modelling" may be an important skill, but what does that mean precisely? Explain your rationale. Why is your concept important? Don't just say "use indexes." Don't fall into "best practices." Convince your audience to go learn more. Upvote answers you agree with. Read other people's answers first. One high-ranked answer is a more effective statement than two low-ranked ones. If you have more to add, either add a comment or reference the original. Don't downvote something just because it doesn't apply to you personally. We all work in different domains. The objective here is to provide direction for database novices to gain a well-founded, well-rounded understanding of database design and database-driven development, not to compete for the title of most-important.

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  • SVN marking file production ready

    - by dan.codes
    I am kind of new to SVN, I haven't used it in detail basically just checking out trunk and committing then exporting and deploying. I am working on a big project now with several developers and we are looking for the best deployment process. The one thing we are hung up on is the best way to tag, branch and so on. We are used to CVS where all you have to do is commit a file and tag it as production ready and if not that code will not get deployed. I see that SVN handles tagging differently then CVS. I figure I am looking at this and making it overly complex. It seems the only way to work on a project and commit files without it being in the production code is to do it in a branch and then merge those changes when you are ready for it to be deployed. I am assuming you could also be working on other code that should be deployed so you would have to be switching between working copies, because otherwise you are working on a branch that isn't getting mixed in with the trunk or production branch? This process seems overly complex and I was wondering if anyone could give me what you think is the best process for managing this.

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  • Can't see *all* databases in a remote SQL Server instance

    - by George
    Yesterday I posted a related question on StackOverflow. This problem involved not being able to see a SQL Server 2008 instance on another PC. I am not sure why adding the port number enabled me to see a SQL Server that I could not otherwise see, since the port number that I specified was, after all, the default port. Now I notice that I have another problem. While I can connect to the remote SQL 2008 Server instance, I cannot see all the databases in the instance. I am trying to connect to the 2008 instance from another PC using SQL Server 2008 Mgt Studio. I am connecting from a Windows 7 Ultimate PC to a Windows XP Pro PC. I suspect that my problem has something to do with not all database in the remote instance having the same version. For example, I "upgraded" a a SL 2005 database to 2008 by doing a backup frm 2005 and importing it into 2008. When I realized that this was not one of the database that I could see from my other PC, I noticed that the compatability level of the imported was still 2005, so I changed it to 2008. Still I could not see the database. I am sure that this is relevant: I just noticed that on my remote server, the sql node instance node, named "sql2008" says "version 10" when I am on the remote serfver, but when I connect to the sql2008 remote instance fron my local PC, the connection is shown locally as being a "SQL Servr version 8.0" instance. I suspect that locally, I am only being shown databases that are somehow in the remote 2008 instance but have not been upgraded. I guess I don't know what constitutes an upgraded database and I don not know who to connect to see all the databases, even if this requires multiple connections from the source PC.

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  • Determine whether app is communicating with APNS sandbox or production environment

    - by goldierox
    I have push notifications set up in my app. I'm trying to determine whether the device token I've received from APNS in the application:didRegisterForRemoteNotificationsWithDeviceToken: method came from the sandbox or development environment. If I can distinguish which environment initialized the token, I'll be able to tell my server to which environment to send the push notification. I've tried using the DEBUG macro to determine this, but I've seen some strange behavior with this and don't trust it to be 100% correct. #ifdef DEBUG BOOL isProd = YES; #else BOOL isProd = NO; #endif Ideally, I'd be able to examine the aps-environment entitlement (value is Development or Production) in code, but I'm not sure if this is even possible. What's the proper way to determine whether your app is communicating with the APNS sandbox or production environments? I'm assuming that the server needs to know this in the first place. Please correct me if this is assumption is incorrect. Edited: Apple's documentation on Provider Communication with APNS details the difference between communicating with the sandbox and production. However, the documentation doesn't give information on how to be consistent with registering the token (from the iOS client app) and communicating with the server.

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  • Accessing Oracle 6i and 9i/10g Databases using C#

    - by Mike M
    Hi all, I am making two build files using NAnt. The first aims to automatically compile Oracle 6i forms and reports and the second aims to compile Oracle 9i/10g forms and reports. Within the NAnt task is a C# script which prompts the developer for database credentials (username, password, database) in order to compile the forms and reports. I want to then run these credentials against the relevant database to ensure the credentials entered are correct and, if they are not, prompt the user to re-enter their credentials. My script currently looks as follows: class GetInput { public static void ScriptMain(Project project) { Console.Clear(); Console.WriteLine("==================================================================="); Console.WriteLine("Welcome to the Compile and Deploy Oracle Forms and Reports Facility"); Console.WriteLine("==================================================================="); Console.WriteLine(); Console.WriteLine("Please enter the acronym of the project to work on from the following list:"); Console.WriteLine(); Console.WriteLine("--------"); Console.WriteLine("- BCS"); Console.WriteLine("- COPEN"); Console.WriteLine("- FCDD"); Console.WriteLine("--------"); Console.WriteLine(); Console.Write("Selection: "); project.Properties["project.type"] = Console.ReadLine(); Console.WriteLine(); Console.Write("Please enter username: "); string username = Console.ReadLine(); project.Properties["username"] = username; string password = ReturnPassword(); project.Properties["password"] = password Console.WriteLine(); Console.Write("Please enter database: "); string database = Console.ReadLine(); project.Properties["database"] = database Console.WriteLine(); //Call method to verify user credentials Console.WriteLine(); Console.WriteLine("Compiling files..."; } public static string ReturnPassword() { Console.Write("Please enter password: "); string password = ""; ConsoleKeyInfo nextKey = Console.ReadKey(true); while (nextKey.Key != ConsoleKey.Enter) { if (nextKey.Key == ConsoleKey.Backspace) { if (password.Length > 0) { password = password.Substring(0, password.Length - 1); Console.Write(nextKey.KeyChar); Console.Write(" "); Console.Write(nextKey.KeyChar); } } else { password += nextKey.KeyChar; Console.Write("*"); } nextKey = Console.ReadKey(true); } return password; } } Having done a bit of research, I find that you can connect to Oracle databases using the System.Data.OracleClient namespace clicky. However, as mentioned in the link, Microsoft is discontinuing support for this so it is not a desireable solution. I have also fonud that Oracle provides its own classes for connecting to Oracle databases clicky. However, this only seems to support connecting to Oracle 9 or newer databases (clicky) so it is not feasible solution as I also need to connect to Oracle 6i databases. I could achieve this by calling a bat script from within the C# script, but I would much prefer to have a single build file for simplicity. Ideally, I would like to run a series of commands such as is contained in the following .bat script: rem -- Set Database SID -- set ORACLE_SID=%DBSID% sqlplus -s %nameofuser%/%password%@%dbsid% set cmdsep on set cmdsep '"'; --" set term on set echo off set heading off select '========================================' || CHR(10) || 'Have checked and found both Password and ' || chr(10) || 'Database Identifier are valid, continuing ...' || CHR(10) || '========================================' from dual; exit; This requires me to set the environment variable of ORACLE_SID and then run sqlplus in silent mode (-s) followed by a series of sql set commands (set x), the actual select statement and an exit command. Can I achieve this within a c# script without calling a bat script, or am I forced to call a bat script? Thanks in advance!

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  • Click Once Deployment Process and Issue Resolution

    - by Geordie
    Introduction We are adopting Click Once as a deployment standard for Thick .Net application clients.  The latest version of this tool has matured it to a point where it can be used in an enterprise environment.  This guide will identify how to use Click Once deployment and promote code trough the dev, test and production environments. Why Use Click Once over SCCM If we already use SCCM why add Click Once to the deployment options.  The advantages of Click Once are their ability to update the code in a single location and have the update flow automatically down to the user community.  There have been challenges in the past with getting configuration updates to download but these can now be achieved.  With SCCM you can do the same thing but it then needs to be packages and pushed out to users.  Each time a new user is added to an application, time needs to be spent by an administrator, to push out any required application packages.  With Click Once the user would go to a web link and the application and pre requisites will automatically get installed. New Deployment Steps Overview The deployment in an enterprise environment includes several steps as the solution moves through the development life cycle before being released into production.  To make mitigate risk during the release phase, it is important to ensure the solution is not deployed directly into production from the development tools.  Although this is the easiest path, it can introduce untested code into production and result in unexpected results. 1. Deploy the client application to a development web server using Visual Studio 2008 Click Once deployment tools.  Once potential production versions of the solution are being generated, ensure the production install URL is specified when deploying code from Visual Studio.  (For details see ‘Deploying Click Once Code from Visual Studio’) 2. xCopy the code to the test server.  Run the MageUI tool to update the URLs, signing and version numbers to match the test server. (For details see ‘Moving Click Once Code to a new Server without using Visual Studio’) 3. xCopy the code to the production server.  Run the MageUI tool to update the URLs, signing and version numbers to match the production server. The certificate used to sign the code should be provided by a certificate authority that will be trusted by the client machines.  Finally make sure the setup.exe contains the production install URL.  If not redeploy the solution from Visual Studio to the dev environment specifying the production install URL.  Then xcopy the install.exe file from dev to production.  (For details see ‘Moving Click Once Code to a new Server without using Visual Studio’) Detailed Deployment Steps Deploying Click Once Code From Visual Studio Open Visual Studio and create a new WinForms or WPF project.   In the solution explorer right click on the project and select ‘Publish’ in the context menu.   The ‘Publish Wizard’ will start.  Enter the development deployment path.  This could be a local directory or web site.  When first publishing the solution set this to a development web site and Visual basic will create a site with an install.htm page.  Click Next.  Select weather the application will be available both online and offline. Then click Finish. Once the initial deployment is completed, republish the solution this time mapping to the directory that holds the code that was just published.  This time the Publish Wizard contains and additional option.   The setup.exe file that is created has the install URL hardcoded in it.  It is this screen that allows you to specify the URL to use.  At some point a setup.exe file must be generated for production.  Enter the production URL and deploy the solution to the dev folder.  This file can then be saved for latter use in deployment to production.  During development this URL should be pointing to development site to avoid accidently installing the production application. Visual studio will publish the application to the desired location in the process it will create an anonymous ‘pfx’ certificate to sign the deployment configuration files.  A production certificate should be acquired in preparation for deployment to production.   Directory structure created by Visual Studio     Application files created by Visual Studio   Development web site (install.htm) created by Visual Studio Migrating Click Once Code to a new Server without using Visual Studio To migrate the Click Once application code to a new server, a tool called MageUI is needed to modify the .application and .manifest files.  The MageUI tool is usually located – ‘C:\Program Files\Microsoft SDKs\Windows\v6.0A\Bin’ folder or can be downloaded from the web. When deploying to a new environment copy all files in the project folder to the new server.  In this case the ‘ClickOnceSample’ folder and contents.  The old application versions can be deleted, in this case ‘ClickOnceSample_1_0_0_0’ and ‘ClickOnceSample_1_0_0_1’.  Open IIS Manager and create a virtual directory that points to the project folder.  Also make the publish.htm the default web page.   Run the ManeUI tool and then open the .application file in the root project folder (in this case in the ‘ClickOnceSample’ folder). Click on the Deployment Options in the left hand list and update the URL to the new server URL and save the changes.   When MageUI tries to save the file it will prompt for the file to be signed.   This step cannot be bypassed if you want the Click Once deployment to work from a web site.  The easiest solution to this for test is to use the auto generated certificate that Visual Studio created for the project.  This certificate can be found with the project source code.   To save time go to File>Preferences and configure the ‘Use default signing certificate’ fields.   Future deployments will only require application files to be transferred to the new server.  The only difference is then updating the .application file the ‘Version’ must be updated to match the new version and the ‘Application Reference’ has to be update to point to the new .manifest file.     Updating the Configuration File of a Click Once Deployment Package without using Visual Studio When an update to the configuration file is required, modifying the ClickOnceSample.exe.config.deploy file will not result in current users getting the new configurations.  We do not want to go back to Visual Studio and generate a new version as this might introduce unexpected code changes.  A new version of the application can be created by copying the folder (in this case ClickOnceSample_1_0_0_2) and pasting it into the application Files directory.  Rename the directory ‘ClickOnceSample_1_0_0_3’.  In the new folder open the configuration file in notepad and make the configuration changes. Run MageUI and open the manifest file in the newly copied directory (ClickOnceSample_1_0_0_3).   Edit the manifest version to reflect the newly copied files (in this case 1.0.0.3).  Then save the file.  Open the .application file in the root folder.  Again update the version to 1.0.0.3.  Since the file has not changed the Deployment Options/Start Location URL should still be correct.  The application Reference needs to be updated to point to the new versions .manifest file.  Save the file. Next time a user runs the application the new version of the configuration file will be down loaded.  It is worth noting that there are 2 different types of configuration parameter; application and user.  With Click Once deployment the difference is significant.  When an application is downloaded the configuration file is also brought down to the client machine.  The developer may have written code to update the user parameters in the application.  As a result each time a new version of the application is down loaded the user parameters are at risk of being overwritten.  With Click Once deployment the system knows if the user parameters are still the default values.  If they are they will be overwritten with the new default values in the configuration file.  If they have been updated by the user, they will not be overwritten. Settings configuration view in Visual Studio Production Deployment When deploying the code to production it is prudent to disable the development and test deployment sites.  This will allow errors such as incorrect URL to be quickly identified in the initial testing after deployment.  If the sites are active there is no way to know if the application was downloaded from the production deployment and not redirected to test or dev.   Troubleshooting Clicking the install button on the install.htm page fails. Error: URLDownloadToCacheFile failed with HRESULT '-2146697210' Error: An error occurred trying to download <file>   This is due to the setup.exe file pointing to the wrong location. ‘The setup.exe file that is created has the install URL hardcoded in it.  It is this screen that allows you to specify the URL to use.  At some point a setup.exe file must be generated for production.  Enter the production URL and deploy the solution to the dev folder.  This file can then be saved for latter use in deployment to production.  During development this URL should be pointing to development site to avoid accidently installing the production application.’

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  • PhpMyAdmin import/export - strange character encoding issues.

    - by John Hunt
    Hello, I'm migrating a site to a new host, and there are a couple of databases on there. There's no SSH access so I'm stuck with phpmyadmin. The issue is that certain characters (namely just whitespace) seems to being corrupt on the new site (same html, and apache doesn't seem to be messing with any encodings - you can see the strange characters have changed when I use less on my linux machine after downloading a table dump from both servers.) The issue isn't as bad if I import into the new database as utf-8 - whitespace characters only have one funny A type symbol instead of two. I've been trying various combinations of character encoding etc to no avail. Exporting from: phpMyAdmin 2.6.2 MySQL 4.1.20 MySQL connection collation: utf8_general_ci MySQL charset: UTF-8 Unicode (utf8) Collation on tables and their fields is: latin1_swedish_ci Importing to: phpMyAdmin - 2.11.9.2 MySQL client version: 5.0.45 MySQL charset: UTF-8 Unicode (utf8) MySQL connection collation: utf8_general_ci The import sql has this kind of thing in it: ENGINE=MyISAM DEFAULT CHARSET=latin1 AUTO_INCREMENT=192 ; I get the impression this is actually a bug or something with mysqldump as nothing seems to work.. does anyone have any insight into this? Cheers, John.

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