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  • How are Reads Distributed in a Workload

    - by Bill Graziano
    People have uploaded nearly one millions rows of trace data to TraceTune.  That’s enough data to start to look at the results in aggregate.  The first thing I want to look at is logical reads.  This is the easiest metric to identify and fix. When you upload a trace, I rank each statement based on the total number of logical reads.  I also calculate each statement’s percentage of the total logical reads.  I do the same thing for CPU, duration and logical writes.  When you view a statement you can see all the details like this: This single statement consumed 61.4% of the total logical reads on the system while we were tracing it.  I also wanted to see the distribution of reads across statements.  That graph looks like this: On average, the highest ranked statement consumed just under 50% of the reads on the system.  When I tune a system, I’m usually starting in one of two modes: this “piece” is slow or the whole system is slow.  If a given piece (screen, report, query, etc.) is slow you can usually find the specific statements behind it and tune it.  You can make that individual piece faster but you may not affect the whole system. When you’re trying to speed up an entire server you need to identity those queries that are using the most disk resources in aggregate.  Fixing those will make them faster and it will leave more disk throughput for the rest of the queries. Here are some of the things I’ve learned querying this data: The highest ranked query averages just under 50% of the total reads on the system. The top 3 ranked queries average 73% of the total reads on the system. The top 10 ranked queries average 91% of the total reads on the system. Remember these are averages across all the traces that have been uploaded.  And I’m guessing that people mainly upload traces where there are performance problems so your mileage may vary. I also learned that slow queries aren’t the problem.  Before I wrote ClearTrace I used to identify queries by filtering on high logical reads using Profiler.  That picked out individual queries but those rarely ran often enough to put a large load on the system. If you look at the execution count by rank you’d see that the highest ranked queries also have the highest execution counts.  The graph would look very similar to the one above but flatter.  These queries don’t look that bad individually but run so often that they hog the disk capacity. The take away from all this is that you really should be tuning the top 10 queries if you want to make your system faster.  Tuning individually slow queries will help those specific queries but won’t have much impact on the system as a whole.

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  • Scrum Board for a distributed team

    - by Falcon
    I am looking for recommendations on a digital Scrum Board which can be shared over the internet. I imagine something like a big tablet on which you can draw and which remote users can access, too. I dislike Scrum software because I think one major benefit of a Scrum Board is its physical presence. It should be hard to ignore. The best solution would be two big tablets on which you can draw and which can be synchronized. Has anyone got product recommendations for something like this? Or would you rather use a software? Kind regards, Falcon

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  • Headaches using distributed version control for traditional teams?

    - by J Cooper
    Though I use and like DVCS for my personal projects, and can totally see how it makes managing contributions to your project from others easier (e.g. your typical Github scenario), it seems like for a "traditional" team there could be some problems over the centralized approach employed by solutions like TFS, Perforce, etc. (By "traditional" I mean a team of developers in an office working on one project that no one person "owns", with potentially everyone touching the same code.) A couple of these problems I've foreseen on my own, but please chime in with other considerations. In a traditional system, when you try to check your change in to the server, if someone else has previously checked in a conflicting change then you are forced to merge before you can check yours in. In the DVCS model, each developer checks in their changes locally and at some point pushes to some other repo. That repo then has a branch of that file that 2 people changed. It seems that now someone must be put in charge of dealing with that situation. A designated person on the team might not have sufficient knowledge of the entire codebase to be able to handle merging all conflicts. So now an extra step has been added where someone has to approach one of those developers, tell him to pull and do the merge and then push again (or you have to build an infrastructure that automates that task). Furthermore, since DVCS tends to make working locally so convenient, it is probable that developers could accumulate a few changes in their local repos before pushing, making such conflicts more common and more complicated. Obviously if everyone on the team only works on different areas of the code, this isn't an issue. But I'm curious about the case where everyone is working on the same code. It seems like the centralized model forces conflicts to be dealt with quickly and frequently, minimizing the need to do large, painful merges or have anyone "police" the main repo. So for those of you who do use a DVCS with your team in your office, how do you handle such cases? Do you find your daily (or more likely, weekly) workflow affected negatively? Are there any other considerations I should be aware of before recommending a DVCS at my workplace?

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  • Is there a Distributed SAN/Storage System out there?

    - by Joel Coel
    Like many other places, we ask our users not to save files to their local machines. Instead, we encourage that they be put on a file server so that others (with appropriate permissions) can use them and that the files are backed up properly. The result of this is that most users have large hard drives that are sitting mainly empty. It's 2010 now. Surely there is a system out there that lets you turn that empty space into a virtual SAN or document library? What I envision is a client program that is pushed out to users' PCs that coordinates with a central server. The server looks to users just like a normal file server, but instead of keeping entire file contents it merely keeps a record of where those files can be found among various user PCs. It then coordinates with the right clients to serve up file requests. The client software would be able to respond to such requests directly, as well as be smart enough to cache recent files locally. For redundancy the server could make sure files are copied to multiple PCs, perhaps allowing you to define groups in different locations so that an instance of the entire repository lives in each group to protect against a disaster in one building taking down everything else. Obviously you wouldn't point your database server here, but for simpler things I see several advantages: Files can often be transferred from a nearer machine. Disk space grows automatically as your company does. Should ultimately be cheaper, as you don't need to keep a separate set of disks I can see a few downsides as well: Occasional degradation of user pc performance, if the machine has to serve or accept a large file transfer during a busy period. Writes have to be propogated around the network several times (though I suspect this isn't really much of a problem, as reading happens in most places more than writing) Still need a way to send a complete copy of the data offsite occasionally, and this would make it very hard to do differentials Think of this like a cloud storage system that lives entirely within your corporate LAN and makes use of your existing user equipment. Our old main file server is due for retirement in about 2 years, and I'm looking into replacing it with a small SAN. I'm thinking something like this would be a better fit. As a school, we have a couple computer labs I can leave running that would be perfect for adding a little extra redundancy to the system. Unfortunately, the closest thing I can find is Dienst, and it's just a paper that dates back to 1994. Am I just using the wrong buzzwords in my searches, or does this really not exist? If not, is there a big downside that I'm missing?

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  • What does transactions per seconds for a load balancer mean

    - by Anurag
    I was looking at the product matrix of webmux 592G(load balancer). It says maximum connections per sec = 2.8M Maximum number of transactions = 100,000 What does the above numbers mean. Does above means that load balancer can have 2.8M connections open but only 100K of them will be active per seconds. Also incase any one has used webmux 592G do you guys know in practice how many connections it can have open and what qps it can serve

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  • Long-running transactions structured approach

    - by disown
    I'm looking for a structured approach to long-running (hours or more) transactions. As mentioned here, these type of interactions are usually handled by optimistic locking and manual merge strategies. It would be very handy to have some more structured approach to this type of problem using standard transactions. Various long-running interactions such as user registration, order confirmation etc. all have transaction-like semantics, and it is both error-prone and tedious to invent your own fragile manual roll-back and/or time-out/clean-up strategies. Taking a RDBMS as an example, I realize that it would be a major performance cost associated with keeping all the transactions open. As an alternative, I could imagine having a database supporting two isolation levels/strategies simultaneously, one for short-running and one for long-running conversations. Long-running conversations could then for instance have more strict limitations on data access to facilitate them taking more time (read-only semantics on some data, optimistic locking semantics etc). Are there any solutions which could do something similar?

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  • Entities groups in transactions

    - by Joel
    In the context of "Keys and Entity Groups" article by google: http://code.google.com/appengine/docs/python/datastore/transactions.html 1) "Only use entity groups when they are needed for transactions" 2) "Every entity belongs to an entity group, a set of one or more entities that can be manipulated in a single transaction." It seems like entity groups exist only for the use of transactions, i.e. making one transaction possible between all entities in a group. My question is then why are there parent-child relations between entities and not just a simple declaration of entities to be in a single group (that is defining A,B,C to be in the same group as opposed to defining relations between them "A (parent of) B, B (parent of C)"). What is the benefit from using parent-child relation model when the only purpose is for entities to be in the same group to make transaction possible? Thanks Joel

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  • Can I do transactions and locks in CouchDB?

    - by damian
    I need to do transactions (begin, commit or rollback), locks (select for update). How can I do it in a document model db? Edit: The case is this: I want to run an auctions site. And I think how to direct purchase as well. In a direct purchase I have to decrement the quantity field in the item record, but only if the quantity is greater than zero. That is why I need locks and transactions. I don't know how to address that without locks and/or transactions. Can I solve this with CouchDB?

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  • DBTransactions between stateless calls using GUIDs

    - by Marty Trenouth
    I'm looking to add transactional support to my DB engine and providing to Abstract Transaction Handling down to passing in Guids with the DB Action Command. The DB engine would run similar to: private static Database DB; public static Dictionary<Guid,DBTransaction> Transactions = new ...() public static void DoDBAction(string cmdstring,List<Parameter> parameters,Guid TransactionGuid) { DBCommand cmd = BuildCommand(cmdstring,parameters); if(Transactions.ContainsKey(TransactionGuid)) cmd.Transaction = Transactions[TransactionGuid]; DB.ExecuteScalar(cmd); } public static BuildCommand(string cmd, List<Parameter> parameters) { // Create DB command from EntLib Database and assign parameters } public static Guid BeginTransaction() { // creates new Transaction adding it to "Transactions" and opens a new connection } public static Guid Commit(Guid g) { // Commits Transaction and removes it from "Transactions" and closes connection } public static Guid Rollback(Guid g) { // Rolls back Transaction and removes it from "Transactions" and closes connection } The Calling system would run similar to: Guid g try { g = DBEngine.BeginTransaction() DBEngine.DoDBAction(cmdstring1, parameters,g) // do some other stuff DBEngine.DoDBAction(cmdstring2, parameters2,g) // sit here and wait for a response from other item DBEngine.DoDBAction(cmdstring3, parameters3,g) DBEngine.Commit(g) } catch(Exception){ DBEngine.Rollback(g);} Does this interfere with .NET connection pooling (other than a connection be accidently left open)? Will EntLib keep the connection open until the commit or rollback?

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  • Pros and cons of distributed revision control systems?

    - by Ludwig Weinzierl
    What are the advantages and disadvantages of distributed revision control systems? If you have any experience with distributed systems like Git, Mercurial, Plastic SCM, etc. please share your experience. Tell us what worked well and where problems arose. I'm particularly interested to hear about the use of distributed systems in traditional, commercial, non-open source projects but answers about other uses are also welcome.

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  • Spring, iBatis, MySQL - how to manage transactions?

    - by Enrique
    Hello I'm building a web application with spring ibatis and mysql. I'm going to use mysql stored procedures and I will call them with ibatis. My question is about how to manage the transactions. Should I manage the transactions inside the stored procedures or with spring/ibatis or with both?

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  • Using pivot tables to group transactions

    - by andreas
    I have my bank account statement and what I would like to do is group the descriptions of the transactions together with their debit or credit and sum their total. I could then see that, e.g., for ebay.com my total debit was $2000, etc. Description Debit Credit A 1 B 1 A 1 B 1 C 1 D 1 A 1 What I want to do is use a pivot table Description Debit Credit A 3 B 2 C 1 D 1 I am no able to do that, as I can't group the description and have additional debit and credit columns -- I get them all in rows with blanks.

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  • Memory management with Objective-C Distributed Objects: my temporary instances live forever!

    - by jkp
    I'm playing with Objective-C Distributed Objects and I'm having some problems understanding how memory management works under the system. The example given below illustrates my problem: Protocol.h #import <Foundation/Foundation.h> @protocol DOServer - (byref id)createTarget; @end Server.m #import <Foundation/Foundation.h> #import "Protocol.h" @interface DOTarget : NSObject @end @interface DOServer : NSObject < DOServer > @end @implementation DOTarget - (id)init { if ((self = [super init])) { NSLog(@"Target created"); } return self; } - (void)dealloc { NSLog(@"Target destroyed"); [super dealloc]; } @end @implementation DOServer - (byref id)createTarget { return [[[DOTarget alloc] init] autorelease]; } @end int main() { NSAutoreleasePool *pool = [[NSAutoreleasePool alloc] init]; DOServer *server = [[DOServer alloc] init]; NSConnection *connection = [[NSConnection new] autorelease]; [connection setRootObject:server]; if ([connection registerName:@"test-server"] == NO) { NSLog(@"Failed to vend server object"); } else [[NSRunLoop currentRunLoop] run]; [pool drain]; return 0; } Client.m #import <Foundation/Foundation.h> #import "Protocol.h" int main() { unsigned i = 0; for (; i < 3; i ++) { NSAutoreleasePool *pool = [[NSAutoreleasePool alloc] init]; id server = [NSConnection rootProxyForConnectionWithRegisteredName:@"test-server" host:nil]; [server setProtocolForProxy:@protocol(DOServer)]; NSLog(@"Created target: %@", [server createTarget]); [[NSRunLoop currentRunLoop] runUntilDate:[NSDate dateWithTimeIntervalSinceNow:1.0]]; [pool drain]; } return 0; } The issue is that any remote objects created by the root proxy are not released when their proxy counterparts in the client go out of scope. According to the documentation: When an object’s remote proxy is deallocated, a message is sent back to the receiver to notify it that the local object is no longer shared over the connection. I would therefore expect that as each DOTarget goes out of scope (each time around the loop) it's remote counterpart would be dellocated, since there is no other reference to it being held on the remote side of the connection. In reality this does not happen: the temporary objects are only deallocate when the client application quits, or more accurately, when the connection is invalidated. I can force the temporary objects on the remote side to be deallocated by explicitly invalidating the NSConnection object I'm using each time around the loop and creating a new one but somehow this just feels wrong. Is this the correct behaviour from DO? Should all temporary objects live as long as the connection that created them? Are connections therefore to be treated as temporary objects which should be opened and closed with each series of requests against the server? Any insights would be appreciated.

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  • NHibernate transactions randomly not rolled back

    - by cbp
    I have a suite of integration tests that run inside transactions. Sometimes it seems that NHibernate transactions are not being correctly rolled back. I can't work out what causes this. Here is a slightly simplified overview of the base class that these integration test fixtures run with: public class IntegrationTestFixture { private TransactionScope _transactionScope; private ConnectionScope _connectionScope; [TestFixtureSetUp] public virtual void TestFixtureSetUp() { var session = NHibernateSessionManager.SessionFactory.OpenSession(); CallSessionContext.Bind(session); _connectionScope = new ConnectionScope(); _transactionScope = new TransactionScope(); } [TestFixtureTearDown] public virtual void TestFixtureTearDown() { _transactionScope.Dispose(); _connectionScope.Dispose(); var session = CurrentSessionContext.Unbind(SessionFactory); session.Close(); session.Dispose(); } } A call to the TransactionScope's commit method is never made, therefore how is it possible that data still ends up in the database?

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  • hibernate transaction safety (with, without JBoss)

    - by Andy Nuss
    Hi, I am currently using just Hibernate and tomcat (no JBoss), and have hibernate transactions which I'm not clear on what transaction safety level I'm actually using, especially for those which read and get values and then update them). Thus I might be getting dirty reads? So I'm going to start having to study my transactions that require non-dirty reads, and make sure that (1) hibernate controls the transaction safety level of those transactions properly, and (2) be able to still have those transactions where dirty reads are ok. Do I need to install Hibernate with JBoss to control transaction safety levels? If so, what's the easiest way to do this without dramatically changing my application to use the J2EE apis, as I am currently using the basic Hibernate apis. Or better, can I get JTA control with Hibernate without using JBoss? Andy

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  • Better understanding of my SQL transactions

    - by Slew Poke
    I just realized that my application was needlessly making 50+ database calls per user request due to some hidden coding -- hidden in the sense that between LINQ, persistence frameworks and events it just so turned out that a huge number of calls were being made without me being aware. Is there a recommended way to analyze individual transactions going to my SQL 2008 database, preferably with some integration to my Visual Studio 2010 environment? I want to be able to 'spy' on individual transactions being made, but only for certain pieces of my code, and without making serious changes to either the code or database.

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  • How to avoid StaleObjectStateException when transaction updates thousands of entities?

    - by ThinkFloyd
    We are using Hibernate 3.6.0.Final with JPA 2 and Spring 3.0.5 for a large scale enterprise application running on tomcat 7 and MySQL 5.5. Most of the transactions in application, lives for less than a second and update 5-10 entities but in some use cases we need to update more than 10-20K entities in single transaction, which takes few minutes and hence more than 70% of times such transaction fails with StaleObjectStateException because some of those entities got updated by some other transaction. We generally maintain version column in all tables and in case of StaleObjectStateException we generally retry but since these longs transactions are anyways very long so if we keep on retrying then also I am not very sure that we'll be able to escape StaleObjectStateException. Also lot of activities keep updating these entities in busy hours so we cannot go with pessimistic approach because it can potentially halt many activities in system. Please suggest how to fix such long transaction issue because we cannot spawn thousands of independent and small transactions because we cannot afford messed up data in case of some failed & some successful transactions.

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  • Setting a time limit for a transaction in MySQL/InnoDB

    - by Trevor Burnham
    This sprang from this related question, where I wanted to know how to force two transactions to occur sequentially in a trivial case (where both are operating on only a single row). I got an answer—use SELECT ... FOR UPDATE as the first line of both transactions—but this leads to a problem: If the first transaction is never committed or rolled back, then the second transaction will be blocked indefinitely. The innodb_lock_wait_timeout variable sets the number of seconds after which the client trying to make the second transaction would be told "Sorry, try again"... but as far as I can tell, they'd be trying again until the next server reboot. So: Surely there must be a way to force a ROLLBACK if a transaction is taking forever? Must I resort to using a daemon to kill such transactions, and if so, what would such a daemon look like? If a connection is killed by wait_timeout or interactive_timeout mid-transaction, is the transaction rolled back? Is there a way to test this from the console? Clarification: innodb_lock_wait_timeout sets the number of seconds that a transaction will wait for a lock to be released before giving up; what I want is a way of forcing a lock to be released. Update: Here's a simple example that demonstrates why innodb_lock_wait_timeout is not sufficient to ensure that the second transaction is not blocked by the first: START TRANSACTION; SELECT SLEEP(55); COMMIT; With the default setting of innodb_lock_wait_timeout = 50, this transaction completes without errors after 55 seconds. And if you add an UPDATE before the SLEEP line, then initiate a second transaction from another client that tries to SELECT ... FOR UPDATE the same row, it's the second transaction that times out, not the one that fell asleep. What I'm looking for is a way to force an end to this transaction's restful slumber.

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  • MSDTC - Communication with the underlying transaction manager has failed (Firewall open, MSDTC network access on)

    - by SocialAddict
    I'm having problems with my ASP.NET web forms system. It worked on our test server but now we are putting it live one of the servers is within a DMZ and the SQL server is outside of that (on our network still though - although a different subnet) I have open up the firewall completely between these two boxes to see if that was the issue and it still gives the error message "Communication with the underlying transaction manager has failed" whenever we try and use the "TransactionScope". We can access the data for retrieval it's just transactions that break it. We have also used msdtc ping to test the connection and with the amendments on the firewall that pings successfully, but the same error occurs! How do i resolve this error? Any help would be great as we have a system to go live today. Panic :) Edit: I have created a more straightforward test page with a transaction as below and this works fine. Could a nested transaction cause this kind of error and if so why would this only cause an issue when using a live box in a dmz with a firewall? AuditRepository auditRepository = new AuditRepository(); try { using (TransactionScope scope = new TransactionScope()) { auditRepository.Add(DateTime.Now, 1, "TEST-TRANSACTIONS#1", 1); auditRepository.Save(); auditRepository.Add(DateTime.Now, 1, "TEST-TRANSACTIONS#2", 1); auditRepository.Save(); scope.Complete(); } } catch (Exception ex) { Response.Write("Test Error For Transaction: " + ex.Message + "<br />" + ex.StackTrace); }

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  • Ruby: Widely Distributed?

    - by Yar
    While I know it's not part of the Posix standard, but how widely distributed is Ruby on Linux, Unix and other *nix's? I ask because I loathe sh and use Ruby whenever I can on Ubuntu and OSX, but I don't want to get too locked in to 'strange' solutions.

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  • faking NAT with a VMware distributed switch across multiple hosts

    - by romant
    Have a VM that will act as the router, and will be connected to both networks (NAT + 'real'). I spread the distributed switch across the hosts, although any VM that is not on the same physical host as the router/dhcpd simply doesn't get an IP. So its obviously my dvSwitch config. Has anyone achieved a NAT solution using a dvSwitch before that they could share?! Thanks.

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