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  • MySql transfer / update (a bit specific)

    - by Jeff
    before posting I was digging whole site but didn't find help for my problem, so I hope someone will help... Facts: 30 Gb mysql database on remote server (about 20.000.000 rows) data are once weekly updated in local network (mysql) I need to transfer/replace local updated database with remote connection is about 2mb (real mb, not mbps) up/down Point is that I can't have 'down time' of remote mysql server. Until now I Tried: navicat data sync - Ok, but take about 3 days to finish dbForge - ok but need 5 days to finish mysql dump transfer to remote server and execution - about day, but a lot of downtime rsync folder with database /mysql/lib/MY_DATABASE - 4 hours, but after that I need to execute always 'repir on remote server' which takes about 2 hours, and a lot of down time mysql dump piped from cl to directly goto server - still now satisfied many problems I could give you more things that I tried... mysql replication - slow Anyase, what is best,best way to: refresh remote mysql on weekly level and in same time to have 0 sec down time nor huge server load If you have any idea please share

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  • Amazon EC2 as load balanced/failover solution

    - by sugiggs
    Hi All, I'm thinking of an idea but not sure the pros/cons of it. At the moment, we are hosting our website on a dedicated server. As a failover/load balanced solution, I'm thinking to use Amazon EC2+EBS. The files can be rsync and mysql can be setup as master-master replication When the load is high, I can up the machine, given sometime to "sync" and load balanced the traffic there. is it do-able? any link I can read more on this?

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  • Windows 2012 Master & Ubuntu Bind 9 Slave & SOA

    - by RecentCoin
    I'm kinda like the maid... I don't do Windows. But thanks to new things we're implementing, I'm now attempting replicating a single zone from our AD cluster. We had this working just fine but someone had to "adjust" it. That broke the replication completely. We've gotten that restarted but now a different DC is showing as the SOA. Does it matter which of the domain controllers is listed as the SOA? The contents of the zone file appear to be correct. Part of me says "Good enough. Leave it be." but the rest of me doesn't want a 3AM phone call. So does anyone know if it matters which DC is listed as the SOA?

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  • Is it possible to extend the Active Directory schema in a Windows 2003 DC (NOT R2) to support DFSR?

    - by JohannesH
    We're in the process of installing a brand new Windows Server 2008 Web cluster and we would like to synchronize some files between the servers. The problem is that the DC in the domain is an old Windows Server 2003 Standard (NOT R2) which apparently doesn't contain some extension to the AD schema. Is it possible to upgrade the schema without upgrading the DC servers to R2? When I try to create a Replication Group on the 2008 Server I get the following message: --------------------------- Error --------------------------- srv.XXXXXX.XX: The Active Directory Domain Services schema on domain controller activedc07.srv.XXXXXX.XX cannot be read. This error might be caused by a schema that has not been extended, or was extended improperly. See Help and Support Center for information about extending the Active Directory Domain Services schema. Schema version 30 is not supported. --------------------------- OK ---------------------------

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  • Is it possible to extend the ad schema in a Win2003 DC Server (NOT R2) to support DFSR?

    - by JohannesH
    we're in the process of installing a brand new Windows Server 2008 Web cluster and we would like to synchronize some files between the servers. The problem is that the DC in the domain is an old Windows Server 2003 Standard (NOT R2) which apparently doesn't contain some extension to the AD schema. Is it possible to upgrade the schema without upgrading the DC servers to R2? When I try to create a Replication Group on the 2008 Server I get the following message: --------------------------- Error --------------------------- srv.XXXXXX.XX: The Active Directory Domain Services schema on domain controller activedc07.srv.XXXXXX.XX cannot be read. This error might be caused by a schema that has not been extended, or was extended improperly. See Help and Support Center for information about extending the Active Directory Domain Services schema. Schema version 30 is not supported. --------------------------- OK ---------------------------

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  • TFS 2010 Basic Concepts

    - by jehan
    v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Here, I’m going to discuss some key Architectural changes and concepts that have taken place in TFS 2010 when compared to TFS 2008. In TFS 2010 Installation, First you need to do the Installation and then you have to configure the Installation Feature from the available features. This is bit similar to SharePoint Installation, where you will first do the Installation and then configure the SharePoint Farms. 1) Installation Features available in TFS2010: a) Basic: It is the most compact TFS installation possible. It will install and configure Source Control, Work Item tracking and Build Services only. (SharePoint and Reporting Integration will not be possible). b) Standard Single Server: This is suitable for Single Server deployment of TFS. It will install and configure Windows SharePoint Services for you and will use the default instance of SQL Server. c) Advanced: It is suitable, if you want use Remote Servers for SQL Server Databases, SharePoint Products and Technologies and SQL Server Reporting Services. d) Application Tier Only: If you want to configure high availability for Team Foundation Server in a Load Balanced Environment (NLB) or you want to move Team Foundation Server from one server to other or you want to restore TFS. e) Upgrade: If you want to upgrade from a prior version of TFS. Note: One more important thing to know here about  TFS 2010 Basic is that,  it can be installed on Client Operations Systems(Windows 7 and Windows Vista SP3), Where as  earlier you cannot Install previous version of TFS (2008 and 2005) on client OS. 2) Team Project Collections: Connect to TFS dialog box in TFS 2008:  In TFS 2008, the TFS Server contains a set of Team Projects and each project may or may not be independent of other projects and every checkin gets a ever increasing  changeset ID  irrespective of the team project in which it is checked in and the same applies to work items  also, who also gets unique Work Item Ids.The main problem with this approach was that there are certain things which were impossible to do; those were required as per the Application Development Process. a)      If something has gone wrong in one team project and now you want to restore it back to earlier state where it was working properly then it requires you to restore the Database of Team Foundation Server from the backup you have taken as per your Maintenance plans and because of this the other team projects may lose out on the work which is not backed up. b)       Your company had a merge with some other company and now you have two TFS servers. One TFS Server which you are working on and other TFS server which other company was working and now after the merge you want to integrate the team projects from two TFS servers into one, which is almost impossible to achieve in TFS 2008. Though you can create the Team Projects in one server manually (In Source Control) which you want to integrate from the other TFS Server, but will lose out on History of Change Sets and Work items and others which are very important. There were few more issues of this sort, which were difficult to resolve in TFS 2008. To resolve issues related to above kind of scenarios which were mainly related TFS Maintenance, Integration, migration and Security,  Microsoft has come up with Team Project Collections concept in TFS 2010.This concept is similar to SharePoint Site Collections and if you are familiar with SharePoint Architecture, then it will help you to understand TFS 2010 Architecture easily. Connect to TFS dialog box in TFS 2010: In above dialog box as you can see there are two Team Project Collections, each team project can contain any number of team projects as you can see on right side it shows the two Team Projects in Team Project Collection (Default Collection) which I have chosen. Note: You can connect to only one Team project Collection at a time using an instance of  TFS Team Explorer. How does it work? To introduce Team Project Collections, changes have been done in reorganization of TFS databases. TFS 2008 was composed of 5-7 databases partitioned by subsystem (each for Version Control, Work Item Tracking, Build, Integration, Project Management...) New TFS 2010 database architecture: TFS_Config: It’s the root database and it contains centralized TFS configuration data, including the list of all team projects exist in TFS server. TFS_Warehouse: The data warehouse contains all the reporting data of served by this server (farm). TFS_* : This contains individual team project collection data. This database contains all the operational data of team project collection regardless of subsystem.In additional to this, you will have databases for SharePoint and Report Server. 3) TFS Farms:  As TFS 2010 is more flexible to configure as multiple Application tiers and multiple Database tiers, so it will be more appropriate to call as TFS Farm if you going for multi server installation of TFS. NLB support for TFS application tiers – With TFS 2010: you can configure multiple TFS application tier machines to serve the same set of Team Project Collections. The primary purpose of NLB support is to enable a cleaner and more complete high availability than in TFS 2008. Even if any application tier in the farm fails then farm will automatically continue to work with hardly any indication to end users of a problem. SQL data tiers: With 2010 you can configure many SQL Servers. Each Database can be configured to be on any SQL Server because each Team Project Collection is an independent database. This feature can also be used to load balance databases across SQL Servers.These new capabilities will significantly change the way enterprises manage their TFS installations in the future. With Team Project Collections and TFS farms, you can create a single, arbitrarily large TFS installation. You can grow it incrementally by adding ATs and SQL Servers as needed.

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  • Basics of Join Predicate Pushdown in Oracle

    - by Maria Colgan
    Happy New Year to all of our readers! We hope you all had a great holiday season. We start the new year by continuing our series on Optimizer transformations. This time it is the turn of Predicate Pushdown. I would like to thank Rafi Ahmed for the content of this blog.Normally, a view cannot be joined with an index-based nested loop (i.e., index access) join, since a view, in contrast with a base table, does not have an index defined on it. A view can only be joined with other tables using three methods: hash, nested loop, and sort-merge joins. Introduction The join predicate pushdown (JPPD) transformation allows a view to be joined with index-based nested-loop join method, which may provide a more optimal alternative. In the join predicate pushdown transformation, the view remains a separate query block, but it contains the join predicate, which is pushed down from its containing query block into the view. The view thus becomes correlated and must be evaluated for each row of the outer query block. These pushed-down join predicates, once inside the view, open up new index access paths on the base tables inside the view; this allows the view to be joined with index-based nested-loop join method, thereby enabling the optimizer to select an efficient execution plan. The join predicate pushdown transformation is not always optimal. The join predicate pushed-down view becomes correlated and it must be evaluated for each outer row; if there is a large number of outer rows, the cost of evaluating the view multiple times may make the nested-loop join suboptimal, and therefore joining the view with hash or sort-merge join method may be more efficient. The decision whether to push down join predicates into a view is determined by evaluating the costs of the outer query with and without the join predicate pushdown transformation under Oracle's cost-based query transformation framework. The join predicate pushdown transformation applies to both non-mergeable views and mergeable views and to pre-defined and inline views as well as to views generated internally by the optimizer during various transformations. The following shows the types of views on which join predicate pushdown is currently supported. UNION ALL/UNION view Outer-joined view Anti-joined view Semi-joined view DISTINCT view GROUP-BY view Examples Consider query A, which has an outer-joined view V. The view cannot be merged, as it contains two tables, and the join between these two tables must be performed before the join between the view and the outer table T4. A: SELECT T4.unique1, V.unique3 FROM T_4K T4,            (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3) VWHERE T4.unique3 = V.hundred(+) AND       T4.ten = V.ten(+) AND       T4.thousand = 5; The following shows the non-default plan for query A generated by disabling join predicate pushdown. When query A undergoes join predicate pushdown, it yields query B. Note that query B is expressed in a non-standard SQL and shows an internal representation of the query. B: SELECT T4.unique1, V.unique3 FROM T_4K T4,           (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3             AND T4.unique3 = V.hundred(+)             AND T4.ten = V.ten(+)) V WHERE T4.thousand = 5; The execution plan for query B is shown below. In the execution plan BX, note the keyword 'VIEW PUSHED PREDICATE' indicates that the view has undergone the join predicate pushdown transformation. The join predicates (shown here in red) have been moved into the view V; these join predicates open up index access paths thereby enabling index-based nested-loop join of the view. With join predicate pushdown, the cost of query A has come down from 62 to 32.  As mentioned earlier, the join predicate pushdown transformation is cost-based, and a join predicate pushed-down plan is selected only when it reduces the overall cost. Consider another example of a query C, which contains a view with the UNION ALL set operator.C: SELECT R.unique1, V.unique3 FROM T_5K R,            (SELECT T1.unique3, T2.unique1+T1.unique1             FROM T_5K T1, T_10K T2             WHERE T1.unique1 = T2.unique1             UNION ALL             SELECT T1.unique3, T2.unique2             FROM G_4K T1, T_10K T2             WHERE T1.unique1 = T2.unique1) V WHERE R.unique3 = V.unique3 and R.thousand < 1; The execution plan of query C is shown below. In the above, 'VIEW UNION ALL PUSHED PREDICATE' indicates that the UNION ALL view has undergone the join predicate pushdown transformation. As can be seen, here the join predicate has been replicated and pushed inside every branch of the UNION ALL view. The join predicates (shown here in red) open up index access paths thereby enabling index-based nested loop join of the view. Consider query D as an example of join predicate pushdown into a distinct view. We have the following cardinalities of the tables involved in query D: Sales (1,016,271), Customers (50,000), and Costs (787,766).  D: SELECT C.cust_last_name, C.cust_city FROM customers C,            (SELECT DISTINCT S.cust_id             FROM sales S, costs CT             WHERE S.prod_id = CT.prod_id and CT.unit_price > 70) V WHERE C.cust_state_province = 'CA' and C.cust_id = V.cust_id; The execution plan of query D is shown below. As shown in XD, when query D undergoes join predicate pushdown transformation, the expensive DISTINCT operator is removed and the join is converted into a semi-join; this is possible, since all the SELECT list items of the view participate in an equi-join with the outer tables. Under similar conditions, when a group-by view undergoes join predicate pushdown transformation, the expensive group-by operator can also be removed. With the join predicate pushdown transformation, the elapsed time of query D came down from 63 seconds to 5 seconds. Since distinct and group-by views are mergeable views, the cost-based transformation framework also compares the cost of merging the view with that of join predicate pushdown in selecting the most optimal execution plan. Summary We have tried to illustrate the basic ideas behind join predicate pushdown on different types of views by showing example queries that are quite simple. Oracle can handle far more complex queries and other types of views not shown here in the examples. Again many thanks to Rafi Ahmed for the content of this blog post.

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  • MySQL Connect: What to Expect From the Wondrous Land of MySQL Cluster

    - by Mat Keep
    The MySQL Connect conference is only a couple of weeks away, with MySQL engineers, support teams, consultants and community aces busy putting the final touches to their talks. There will be many exciting new announcements and sharing of best practices at the conference, covering the range of MySQL technologies. MySQL Cluster will a big part of this, so I wanted to share some key sessions for those of you who plan on attending, as well as some resources for those who are not lucky enough to be able to make the trip, but who can't afford to miss the key news. Of course, this is no substitute to actually being there….and the good news is that registration is still open ;-) Roadmap: Whats New in MySQL Cluster Saturday 29th, 1300-1400, in Golden Gate room 5.                                                                                        Bernd Ocklin, director of MySQL Cluster development, and myself will be taking a look at what follows the latest MySQL Cluster 7.2 release. I don't want to give to much away - lets just say its not often you can add powerful new functionality to a product while at the same time making life radically simpler for its users. For those not making it to the Conference, a live webinar repeating the talk is scheduled for Thursday 25th October at 09.00 pacific time. Hold the date, registration will be open for that soon and published to our MySQL Webinars page Best Practices Getting Started with MySQL Cluster, Hands-On Lab Saturday 29th, 1600-1700, in Plaza Room A.                                                              Santo Leto, one of our lead MySQL Cluster support engineers, regularly works with users new to MySQL Cluster, assisting them in installation, configuration, scaling, etc. In this lab, Santo will share best-practices in getting started. Delivering Breakthrough Performance with MySQL Cluster Saturday 29th, 1730-1830, in Golden Gate room 5. Frazer Clement, lead MySQL Cluster software engineer, will demonstrate how to translate the awesome Cluster benchmarks (remember 1 BILLION UPDATEs per minute ?!) into real-world performance. You can also get some best practices from our new MySQL Cluster performance guide  MySQL Cluster BoF Saturday 29th, 1900-2000, room Golden Gate 5.                                                                                                           Come and get a demonstration of new tools for the installation and configuration of MySQL Cluster, and spend time with the engineering team discussing any questions or issues you may have. Developing High-Throughput Services with NoSQL APIs to InnoDB and MySQL Cluster Sunday 30th, 1145 - 1245, in Golden Gate room 7.   In this session, JD Duncan and Andrew Morgan will present how to get started with both Memcached and new NoSQL APIs. JD and I recently ran a webinar demonstrating how to build simple Twitter-like services with Memcached and MySQL Cluster. The replay is available for download.  Case Studies: MySQL Cluster @ El Chavo, Latin America’s #1 Facebook Game Sunday 30th, 1745 - 1845, in Golden Gate room 4.                             Playful Play deployed MySQL Cluster CGE to power their market leading social game. This session will discuss the challenges they faced, why they selected MySQL Cluster and their experiences to date. You can read more about Playful Play and MySQL Cluster here  A Journey into NoSQLand: MySQL’s NoSQL Implementation Sunday 30th, 1345 - 1445, in Golden Gate room 4.                                          Lig Turmelle, web DBA at Kaplan Professional and esteemed Oracle Ace, will discuss her experiences working with the NoSQL interfaces for both MySQL Cluster and InnoDB Evaluating MySQL HA Alternatives Saturday 29th, 1430-1530, room Golden Gate 5                                                                                   Henrik Ingo, former member of the MySQL sales engineering team, will provide an overview of various HA technologies for MySQL, starting with replication, progressing to InnoDB, Galera and MySQL Cluster What about the other stuff? Of course MySQL Connect has much, much more than MySQL Cluster. There will be lots on replication (which I'll blog about soon), MySQL 5.6, InnoDB, cloud, etc, etc. Take a look at the full Content Catalog to see more. If you are attending, I hope to see you at one of the Cluster sessions...and remember, registration is still open

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  • SQLAuthority News – Downloads Available for Microsoft SQL Server Compact 3.5

    - by pinaldave
    There are few downloads released for Microsoft SQL Server Compact 3.5. Here is quick lists of the same. Microsoft SQL Server Compact 3.5 Service Pack 2 for Windows Desktop SQL Server Compact 3.5 SP2 is an embedded database that allows developers to build robust applications for Windows desktops and mobile devices. The download contains the files for installing SQL Server Compact 3.5 SP2 and Synchronization Services for ADO.NET version 1.0 SP1 on Windows desktop. Microsoft SQL Server Compact 3.5 Service Pack 2 Server Tools SQL Server Compact 3.5 SP2 Server Tools Windows Installer (MSI) file installs replication components on the computer running the Internet Information Services (IIS) for synchronizing data with SQL Server 2005, SQL Server 2008 and SQL Server 2008 R2 November CTP. Microsoft SQL Server Compact 3.5 Service Pack 2 Books Online SQL Server Compact 3.5 is a small footprint in-process database engine that allows developers to build robust applications for Windows Desktops and Mobile Devices. This download contains the Books Online for the SP2 version of SQL Server Compact 3.5. Note: The brief description below the download link is taken from respective download page. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority News, T SQL, Technology

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  • Multi-tenant ASP.NET MVC - Views

    - by zowens
    Part I – Introduction Part II – Foundation Part III – Controllers   So far we have covered the basic premise of tenants and how they will be delegated. Now comes a big issue with multi-tenancy, the views. In some applications, you will not have to override views for each tenant. However, one of my requirements is to add extra views (and controller actions) along with overriding views from the core structure. This presents a bit of a problem in locating views for each tenant request. I have chosen quite an opinionated approach at the present but will coming back to the “views” issue in a later post. What’s the deal? The path I’ve chosen is to use precompiled Spark views. I really love Spark View Engine and was planning on using it in my project anyways. However, I ran across a really neat aspect of the source when I was having a look under the hood. There’s an easy way to hook in embedded views from your project. There are solutions that provide this, but they implement a special Virtual Path Provider. While I think this is a great solution, I would rather just have Spark take care of the view resolution. The magic actually happens during the compilation of the views into a bin-deployable DLL. After the views are compiled, the are simply pulled out of the views DLL. Each tenant has its own views DLL that just has “.Views” appended after the assembly name as a convention. The list of reasons for this approach are quite long. The primary motivation is performance. I’ve had quite a few performance issues in the past and I would like to increase my application’s performance in any way that I can. My customized build of Spark removes insignificant whitespace from the HTML output so I can some some bandwidth and load time without having to deal with whitespace removal at runtime.   How to setup Tenants for the Host In the source, I’ve provided a single tenant as a sample (Sample1). This will serve as a template for subsequent tenants in your application. The first step is to add a “PostBuildStep” installer into the project. I’ve defined one in the source that will eventually change as we focus more on the construction of dependency containers. The next step is to tell the project to run the installer and copy the DLL output to a folder in the host that will pick up as a tenant. Here’s the code that will achieve it (this belongs in Post-build event command line field in the Build Events tab of settings) %systemroot%\Microsoft.NET\Framework\v4.0.30319\installutil "$(TargetPath)" copy /Y "$(TargetDir)$(TargetName)*.dll" "$(SolutionDir)Web\Tenants\" copy /Y "$(TargetDir)$(TargetName)*.pdb" "$(SolutionDir)Web\Tenants\" The DLLs with a name starting with the target assembly name will be copied to the “Tenants” folder in the web project. This means something like MultiTenancy.Tenants.Sample1.dll and MultiTenancy.Tenants.Sample1.Views.dll will both be copied along with the debug symbols. This is probably the simplest way to go about this, but it is a tad inflexible. For example, what if you have dependencies? The preferred method would probably be to use IL Merge to merge your dependencies with your target DLL. This would have to be added in the build events. Another way to achieve that would be to simply bypass Visual Studio events and use MSBuild.   I also got a question about how I was setting up the controller factory. Here’s the basics on how I’m setting up tenants inside the host (Global.asax) protected void Application_Start() { RegisterRoutes(RouteTable.Routes); // create a container just to pull in tenants var topContainer = new Container(); topContainer.Configure(config => { config.Scan(scanner => { scanner.AssembliesFromPath(Path.Combine(Server.MapPath("~/"), "Tenants")); scanner.AddAllTypesOf<IApplicationTenant>(); }); }); // create selectors var tenantSelector = new DefaultTenantSelector(topContainer.GetAllInstances<IApplicationTenant>()); var containerSelector = new TenantContainerResolver(tenantSelector); // clear view engines, we don't want anything other than spark ViewEngines.Engines.Clear(); // set view engine ViewEngines.Engines.Add(new TenantViewEngine(tenantSelector)); // set controller factory ControllerBuilder.Current.SetControllerFactory(new ContainerControllerFactory(containerSelector)); } The code to setup the tenants isn’t actually that hard. I’m utilizing assembly scanners in StructureMap as a simple way to pull in DLLs that are not in the AppDomain. Remember that there is a dependency on the host in the tenants and a tenant cannot simply be referenced by a host because of circular dependencies.   Tenant View Engine TenantViewEngine is a simple delegator to the tenant’s specified view engine. You might have noticed that a tenant has to define a view engine. public interface IApplicationTenant { .... IViewEngine ViewEngine { get; } } The trick comes in specifying the view engine on the tenant side. Here’s some of the code that will pull views from the DLL. protected virtual IViewEngine DetermineViewEngine() { var factory = new SparkViewFactory(); var file = GetType().Assembly.CodeBase.Without("file:///").Replace(".dll", ".Views.dll").Replace('/', '\\'); var assembly = Assembly.LoadFile(file); factory.Engine.LoadBatchCompilation(assembly); return factory; } This code resides in an abstract Tenant where the fields are setup in the constructor. This method (inside the abstract class) will load the Views assembly and load the compilation into Spark’s “Descriptors” that will be used to determine views. There is some trickery on determining the file location… but it works just fine.   Up Next There’s just a few big things left such as StructureMap configuring controllers with a convention instead of specifying types directly with container construction and content resolution. I will also try to find a way to use the Web Forms View Engine in a multi-tenant way we achieved with the Spark View Engine without using a virtual path provider. I will probably not use the Web Forms View Engine personally, but I’m sure some people would prefer using WebForms because of the maturity of the engine. As always, I love to take questions by email or on twitter. Suggestions are always welcome as well! (Oh, and here’s another link to the source code).

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  • How many different servers are needed to keep a website running with no downtime? [closed]

    - by Mason Wheeler
    Machines go down. It's a fact of life. They may need to be rebooted for some reason, or they may have a hardware failure, or a power outage. So if I wanted to deploy a website with a server backed by a SQL database, putting the whole thing on one server wouldn't be good enough. It obviously needs at least two servers, so that if one goes down, the other can pick up the slack until the first comes back up. Of course, if I have the server software on two machines, either one of which could go down, I can't place the database on either of those two machines, because it could go down. So the database needs its own server. But that server can go down, so I need a backup database server and some sort of replication system to keep it in sync so the main can fail-over to it. So far, that's a bare minimum of 4 machines to keep one website running with a reasonable chance of no downtime. (Assuming no catastrophic events take place that take down both front-end servers at once or both DB servers at once, and no hacks, DDOS attacks, etc. Am I missing any other factors, or should I consider 4 servers to be the minimum for running a website with a goal of continuing operation without downtime even when a server goes down?

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  • SQL Contest – Win 10 Amazon Gift Cards worth (USD 200) and 10 NuoDB T-Shirts

    - by Pinal Dave
    This month, we have yet not run any contest so we will be running a very interesting contest with the help of good guys at NuoDB. NuoDB has just released version 2.0 and You can download NuoDB from here. NuoDB’s NewSQL distributed database is designed to be a single database that works across multiple servers, which can scale easily, and scale on demand. That’s one system that gives high connectivity but no latency, complexity or maintenance issues. MySQL works in some circumstances, but a period of growth isn’t one of them. So as a company moves forward, the MySQL database can’t keep pace. Data storage and data replication errors creep in. Soon the diaspora of the offices becomes a problem. Your telephone system isn’t just distributed, it is literally all over the place. You can read my detailed article about how Why VoIP Service Providers Should Think About NuoDB’s Geo Distribution. Here is the contest: Contest Part 1: NuoDB R2.0 delivered a long list of improvements and new features. List three of the major features of NuoDB 2.0. Here is the hint1, hint2, hint3. Contest Part 2: Download NuoDB using this link. Once you download NuoDB, leave a comment over here with the name of the platform and installer size. (For example Windows Platform Size abc.dd MB) Here is the what you can win! Giveaways 10 Amazon Gift Card (Each of USD 20 – total USD 200) 10 Amazingly looking NuoDB T-Shirts (For the first 10 downloads) Rules Participate before Oct 28, 2013. All the valid answers will be published after Oct 28, 2013 and winners will receive an email on Nov 1st, 2013. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: NuoDB

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  • Using SQL Source Control with Fortress or Vault &ndash; Part 2

    - by AjarnMark
    In Part 1, I started talking about using Red-Gate’s newest version of SQL Source Control and how I really like it as a viable method to source control your database development.  It looks like this is going to turn into a little series where I will explain how we have done things in the past, and how life is different with SQL Source Control.  I will also explain some of my philosophy and methodology around deployment with these tools.  But for now, let’s talk about some of the good and the bad of the tool itself. More Kudos and Features I mentioned previously how impressed I was with the responsiveness of Red-Gate’s team.  I have been having an ongoing email conversation with Gyorgy Pocsi, and as I have run into problems or requested things behave a little differently, it has not been more than a day or two before a new Build is ready for me to download and test.  Quite impressive! I’m sure much of the requests I put in were already in the plans, so I can’t really take credit for them, but throughout this conversation, Red-Gate has implemented several features that were not in the first Early Access version.  Those include: Honoring the Fortress configuration option to require Work Item (Bug) IDs on check-ins. Adding the check-in comment text as a comment to the Work Item. Adding the list of checked-in files, along with the Fortress links for automatic History and DIFF view Updating the status of a Work Item on check-in (e.g. setting the item to Complete or, in our case “Dev-Complete”) Support for the Fortress 2.0 API, and not just the Vault Pro 5.1 API.  (See later notes regarding support for Fortress 2.0). These were all features that I felt we really needed to have in-place before I could honestly consider converting my team to using SQL Source Control on a regular basis.  Now that I have those, my only excuse is not wanting to switch boats on the team mid-stream.  So when we wrap up our current release in a few weeks, we will make the jump.  In the meantime, I will continue to bang on it to make sure it is stable.  It passed one test for stability when I did a test load of one of our larger database schemas into Fortress with SQL Source Control.  That database has about 150 tables, 200 User-Defined Functions and nearly 900 Stored Procedures.  The initial load to source control went smoothly and took just a brief amount of time. Warnings Remember that this IS still in pre-release stage and while I have not had any problems after that first hiccup I wrote about last time, you still need to treat it with a healthy respect.  As I understand it, the RTM is targeted for February.  There are a couple more features that I hope make it into the final release version, but if not, they’ll probably be coming soon thereafter.  Those are: A Browse feature to let me lookup the Work Item ID instead of having to remember it or look back in my Item details.  This is just a matter of convenience. I normally have my Work Item list open anyway, so I can easily look it up, but hey, why not make it even easier. A multi-line comment area.  The current space for writing check-in comments is a single-line text box.  I would like to have a multi-line space as I sometimes write lengthy commentary.  But I recognize that it is a struggle to get most developers to put in more than the word “fixed” as their comment, so this meets the need of the majority as-is, and it’s not a show-stopper for us. Merge.  SQL Source Control currently does not have a Merge feature.  If two or more people make changes to the same database object, you will get a warning of the conflict and have to choose which one wins (and then manually edit to include the others’ changes).  I think it unlikely you will run into actual conflicts in Stored Procedures and Functions, but you might with Views or Tables.  This will be nice to have, but I’m not losing any sleep over it.  And I have multiple tools at my disposal to do merges manually, so really not a show-stopper for us. Automation has its limits.  As cool as this automation is, it has its limits and there are some changes that you will be better off scripting yourself.  For example, if you are refactoring table definitions, and want to change a column name, you can write that as a quick sp_rename command and preserve the data within that column.  But because this tool is looking just at a before and after picture, it cannot tell that you just renamed a column.  To the tool, it looks like you dropped one column and added another.  This is not a knock against Red-Gate.  All automated scripting tools have this issue, unless the are actively monitoring your every step to know exactly what you are doing.  This means that when you go to Deploy your changes, SQL Compare will script the change as a column drop and add, or will attempt to rebuild the entire table.  Unfortunately, neither of these approaches will preserve the existing data in that column the way an sp_rename will, and so you are better off scripting that change yourself.  Thankfully, SQL Compare will produce warnings about the potential loss of data before it does the actual synchronization and give you a chance to intercept the script and do it yourself. Also, please note that the current official word is that SQL Source Control supports Vault Professional 5.1 and later.  Vault Professional is the new name for what was previously known as Fortress.  (You can read about the name change on SourceGear’s site.)  The last version of Fortress was 2.x, and the API for Fortress 2.x is different from the API for Vault Pro.  At my company, we are currently running Fortress 2.0, with plans to upgrade to Vault Pro early next year.  Gyorgy was able to come up with a work-around for me to be able to use SQL Source Control with Fortress 2.0, even though it is not officially supported.  If you are using Fortress 2.0 and want to use SQL Source Control, be aware that this is not officially supported, but it is working for us, and you can probably get the work-around instructions from Red-Gate if you’re really, really nice to them. Upcoming Topics Some of the other topics I will likely cover in this series over the next few weeks are: How we used to do source control back in the old days (a few weeks ago) before SQL Source Control was available to Vault users What happens when you restore a database that is linked to source control Handling multiple development branches of source code Concurrent Development practices and handling Conflicts Deployment Tips and Best Practices A recap after using the tool for a while

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  • Add a Graphical User Interface (GUI) to the Microsoft Robocopy Command Line Tool

    - by Lori Kaufman
    Robocopy, or “Robust File Copy,” is a command line directory replication tool from Microsoft. It is available as part of Windows 7 and Vista as a standard feature, and was available as part of the Windows Server 2003 Resource Kit. NOTE: For Windows XP, you can obtain Robocopy by downloading the resource kit. Robocopy allows you to setup simple or advanced backup strategies. It provides such features as multi-threaded copying, mirroring or synchronization mode, automatic retry, and the ability to resume the copying process. If you are comfortable with using command line tools, you can run Robocopy directly on the command line using the command syntax and options. You can also download the command line reference and usage notes for Robocopy as a PDF file. If you are more comfortable using a graphical user interface, or GUI, rather than the command line, there are a couple of options for adding a GUI to the Robocopy command line tool, making it easier to use. Both tools, RoboMirror and RichCopy, are discussed below and links to download each tool are provided. How to Factory Reset Your Android Phone or Tablet When It Won’t Boot Our Geek Trivia App for Windows 8 is Now Available Everywhere How To Boot Your Android Phone or Tablet Into Safe Mode

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  • How to Setup an Active Directory Domain-Week 26

    - by OWScott
    Today's lesson covers how to create an Active Directory domain and join a member server to it. This week's topic takes a slightly different turn from the normally IIS related topics, but this is key video to help setup either a test or production environment that requires Active Directory. Part of being a web administrator is understanding the servers and how they interact with each other. This week’s lesson takes a different path than usual and covers how to create an Active Directory domain and how to join a member computer to that domain. In less than 13 minutes we complete the entire process, end to end. An understanding of Active Directory is useful, whether it’s simply to setup a test lab, or to learn more so that you can manage a production domain environment. This week starts a mini-series on web farms. Today’s lesson is on setting up a domain which is a necessary prerequisite for next week which will be on Distributed File System Replication (DFS-R), a useful technology for web farms. Upcoming lessons will cover shared configuration, Application Request Routing (ARR), and more. Additionally, this video introduces us to Vaasnet (www.vaasnet.com), a service that allows the web pro to gain immediate access to an entire lab environment for situations such as these. This is week 26 (the middle week!) of a 52 week series for the Web Pro. Past and future videos can be found here: http://dotnetslackers.com/projects/LearnIIS7/ You can find this week’s video here.

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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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  • SQL SERVER – 2014 CTP1 Available for Download – SQL SERVER 2014 Community Technology Preview 1

    - by Pinal Dave
    Microsoft announced that SQL Server 2014 CTP 1 available to download at TechEd Europe. You can download SQL Server 2014 CTP1 from here. Additionally, there is in depth documentation of the product in the Product Guide over here. In this blog post I have in depth discussed what are the salient features which I was looking forward in the new version. Always On supports now 8 secondaries instead of 4 Online Indexing at partition level – this is a good thing as now index rebuilding can be done at a partition level Statistics at the partition level – this will be a huge improvement in performance In-Memory OLTP works by providing in-application memory storage for the most often used tables in SQL Server. Columnstore Index can be updated – I just can’t wait for this feature (Columnstore Index) Resource Governor can control IO along with CPU and Memory Increase performance by extending SQL Server in-memory buffer pool to SSDs Backup to Azure Storage You can read about the new features of the SQL Server 2014 in the following links: What’s New (Database Engine) What’s New in Analysis Services and Business Intelligence What’s New (Integration Services) What’s New (Replication) What’s New (Reporting Services) Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Service Pack, SQL Tips and Tricks, T SQL, Technology Tagged: CTP

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  • LobsterPot Solutions in the USA

    - by Rob Farley
    We’re expanding! I’m thrilled to announce that Microsoft Gold Partner LobsterPot Solutions has started another branch appointing the amazing Ted Krueger (5-time SQL MVP awardee) as the US lead. Ted is well-known in the SQL Server world, having written books on indexing, consulting and on being a DBA (not to mention contributing chapters to both MVP Deep Dives books). He is an expert on replication and high availability, and strong in the Business Intelligence space – vast experience which is both broad and deep. Ted is based in the south east corner of Wisconsin, just north of Chicago. He has been a consultant for eons and has helped many clients with their projects and problems, taking the role as both technical lead and consulting lead. He is also tireless in supporting and developing the SQL Server community, presenting at conferences across America, and helping people through his blog, Twitter and more. Despite all this – it’s neither his technical excellence with SQL Server nor his consulting skill that made me want him to lead LobsterPot’s US venture. I wanted Ted because of his values. In the time I’ve known Ted, I’ve found his integrity to be excellent, and found him to be morally beyond reproach. This is the biggest priority I have when finding people to represent the LobsterPot brand. I have no qualms in recommending Ted’s character or work ethic. It’s not just my thoughts on him – all my trusted friends that know Ted agree about this. So last week, LobsterPot Solutions LLC was formed in the United States, and in a couple of weeks, we will be open for business! LobsterPot Solutions can be contacted via email at [email protected], on the web at either www.lobsterpot.com.au or www.lobsterpotsolutions.com, and on Twitter as @lobsterpot_au and @lobsterpot_us. Ted Kruger blogs at LessThanDot, and can also be found on Twitter and LinkedIn. This post is cross-posted from http://lobsterpotsolutions.com/lobsterpot-solutions-in-the-usa

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  • Combination of Operating Mode and Commit Strategy

    - by Kevin Yang
    If you want to populate a source into multiple targets, you may also want to ensure that every row from the source affects all targets uniformly (or separately). Let’s consider the Example Mapping below. If a row from SOURCE causes different changes in multiple targets (TARGET_1, TARGET_2 and TARGET_3), for example, it can be successfully inserted into TARGET_1 and TARGET_3, but failed to be inserted into TARGET_2, and the current Mapping Property TLO (target load order) is “TARGET_1 -> TARGET_2 -> TARGET_3”. What should Oracle Warehouse Builder do, in order to commit the appropriate data to all affected targets at the same time? If it doesn’t behave as you intended, the data could become inaccurate and possibly unusable.                                               Example Mapping In OWB, we can use Mapping Configuration Commit Strategies and Operating Modes together to achieve this kind of requirements. Below we will explore the combination of these two features and how they affect the results in the target tables Before going to the example, let’s review some of the terms we will be using (Details can be found in white paper Oracle® Warehouse Builder Data Modeling, ETL, and Data Quality Guide11g Release 2): Operating Modes: Set-Based Mode: Warehouse Builder generates a single SQL statement that processes all data and performs all operations. Row-Based Mode: Warehouse Builder generates statements that process data row by row. The select statement is in a SQL cursor. All subsequent statements are PL/SQL. Row-Based (Target Only) Mode: Warehouse Builder generates a cursor select statement and attempts to include as many operations as possible in the cursor. For each target, Warehouse Builder inserts each row into the target separately. Commit Strategies: Automatic: Warehouse Builder loads and then automatically commits data based on the mapping design. If the mapping has multiple targets, Warehouse Builder commits and rolls back each target separately and independently of other targets. Use the automatic commit when the consequences of multiple targets being loaded unequally are not great or are irrelevant. Automatic correlated: It is a specialized type of automatic commit that applies to PL/SQL mappings with multiple targets only. Warehouse Builder considers all targets collectively and commits or rolls back data uniformly across all targets. Use the correlated commit when it is important to ensure that every row in the source affects all affected targets uniformly. Manual: select manual commit control for PL/SQL mappings when you want to interject complex business logic, perform validations, or run other mappings before committing data. Combination of the commit strategy and operating mode To understand the effects of each combination of operating mode and commit strategy, I’ll illustrate using the following example Mapping. Firstly we insert 100 rows into the SOURCE table and make sure that the 99th row and 100th row have the same ID value. And then we create a unique key constraint on ID column for TARGET_2 table. So while running the example mapping, OWB tries to load all 100 rows to each of the targets. But the mapping should fail to load the 100th row to TARGET_2, because it will violate the unique key constraint of table TARGET_2. With different combinations of Commit Strategy and Operating Mode, here are the results ¦ Set-based/ Correlated Commit: Configuration of Example mapping:                                                     Result:                                                      What’s happening: A single error anywhere in the mapping triggers the rollback of all data. OWB encounters the error inserting into Target_2, it reports an error for the table and does not load the row. OWB rolls back all the rows inserted into Target_1 and does not attempt to load rows to Target_3. No rows are added to any of the target tables. ¦ Row-based/ Correlated Commit: Configuration of Example mapping:                                                   Result:                                                  What’s happening: OWB evaluates each row separately and loads it to all three targets. Loading continues in this way until OWB encounters an error loading row 100th to Target_2. OWB reports the error and does not load the row. It rolls back the row 100th previously inserted into Target_1 and does not attempt to load row 100 to Target_3. Then, if there are remaining rows, OWB will continue loading them, resuming with loading rows to Target_1. The mapping completes with 99 rows inserted into each target. ¦ Set-based/ Automatic Commit: Configuration of Example mapping: Result: What’s happening: When OWB encounters the error inserting into Target_2, it does not load any rows and reports an error for the table. It does, however, continue to insert rows into Target_3 and does not roll back the rows previously inserted into Target_1. The mapping completes with one error message for Target_2, no rows inserted into Target_2, and 100 rows inserted into Target_1 and Target_3 separately. ¦ Row-based/Automatic Commit: Configuration of Example mapping: Result: What’s happening: OWB evaluates each row separately for loading into the targets. Loading continues in this way until OWB encounters an error loading row 100 to Target_2 and reports the error. OWB does not roll back row 100th from Target_1, does insert it into Target_3. If there are remaining rows, it will continue to load them. The mapping completes with 99 rows inserted into Target_2 and 100 rows inserted into each of the other targets. Note: Automatic Correlated commit is not applicable for row-based (target only). If you design a mapping with the row-based (target only) and correlated commit combination, OWB runs the mapping but does not perform the correlated commit. In set-based mode, correlated commit may impact the size of your rollback segments. Space for rollback segments may be a concern when you merge data (insert/update or update/insert). Correlated commit operates transparently with PL/SQL bulk processing code. The correlated commit strategy is not available for mappings run in any mode that are configured for Partition Exchange Loading or that include a Queue, Match Merge, or Table Function operator. If you want to practice in your own environment, you can follow the steps: 1. Import the MDL file: commit_operating_mode.mdl 2. Fix the location for oracle module ORCL and deploy all tables under it. 3. Insert sample records into SOURCE table, using below plsql code: begin     for i in 1..99     loop         insert into source values(i, 'col_'||i);     end loop;     insert into source values(99, 'col_99'); end; 4. Configure MAPPING_1 to any combinations of operating mode and commit strategy you want to test. And make sure feature TLO of mapping is open. 5. Deploy Mapping “MAPPING_1”. 6. Run the mapping and check the result.

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  • Get Ready to Meet Oracle GoldenGate 11gR2 at OpenWorld

    - by Irem Radzik
      Oracle GoldenGate 11g Release 2 could not come at a better time. At Oracle OpenWorld 2012 we have a great set of sessions and demos for Oracle GoldenGate users: deep dives into the new features of Oracle GoldenGate 11gR2, as well as great customer presentations from Comcast, Bank of America, Turk Telekom, Ticketmaster, St. Jude Medical Center, and more. Here are 3 must-attend sessions for GoldenGate users and for those who want to get to know GoldenGate’s capabilities: Real-World Zero-Downtime Operations with Oracle GoldenGate: Customer Panel Oct 1st 1:45 PM Moscone West – 3005 Oracle GoldenGate 11g Release 2 New Features Oct 1st 3:15 PM Moscone West – 3005 Real-World Operational Reporting with Oracle GoldenGate: Customer Panel Oct 2nd 11:45 AM Moscone West - 3005 For a full list of GoldenGate and data integration sessions, please check out our Focus-On for Data Integration. Similar to last year, Hands-on-Labs will be available for those who want to experience the power of GoldenGate first hand. One of these instructor-led sessions provides “Deep Dive into Oracle GoldenGate” will be held on Thursday Oct 4th 11:15am at Marriott Marquis - Salon ½. I expect the spots will fill out fast in this session. Oracle GoldenGate Demos will be running Monday through Wednesday in Moscone South in both Oracle Database and Oracle Fusion Middleware sections of the Oracle demo grounds. We will be showcasing: Monitoring Oracle GoldenGate for End-to-End Visibility Oracle GoldenGate 11gR2 New Features Oracle GoldenGate 11gR2: Real-Time, Transactional Database Replication Oracle GoldenGate Veridata Oracle Maximum Availability Architecture If you are not able to attend OpenWorld, you should not miss this week’s live webcast introducing Oracle GoldenGate 11g Release 2. On Wednesday the webcast will present the new features of GoldenGate and attendees will have a long, live Q&A panel session with the PM team.  I also recommend checking out the resources for GoldenGate to download new white papers. The whole team is looking forward to sharing with you the latest and greatest features of GoldenGate at the launch webcast and at OpenWorld.

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  • How to archive data from a table to a local or remote database in SQL 2005 and SQL 2008

    - by simonsabin
    Often you have the need to archive data from a table. This leads to a number of challenges 1. How can you do it without impacting users 2. How can I make it transactionally consistent, i.e. the data I put in the archive is the data I remove from the main table 3. How can I get it to perform well Points 1 is very much tied to point 3. If it doesn't perform well then the delete of data is going to cause lots of locks and thus potentially blocking. For points 1 and 3 refer to my previous posts DELETE-TOP-x-rows-avoiding-a-table-scan and UPDATE-and-DELETE-TOP-and-ORDER-BY---Part2. In essence you need to be removing small chunks of data from your table and you want to do that avoiding a table scan. So that deals with the delete approach but archiving is about inserting that data somewhere else. Well in SQL 2008 they introduced a new feature INSERT over DML (Data Manipulation Language, i.e. SQL statements that change data), or composable DML. The ability to nest DML statements within themselves, so you can past the results of an insert to an update to a merge. I've mentioned this before here SQL-Server-2008---MERGE-and-optimistic-concurrency. This feature is currently limited to being able to consume the results of a DML statement in an INSERT statement. There are many restrictions which you can find here http://msdn.microsoft.com/en-us/library/ms177564.aspx look for the section "Inserting Data Returned From an OUTPUT Clause Into a Table" Even with the restrictions what we can do is consume the OUTPUT from a DELETE and INSERT the results into a table in another database. Note that in BOL it refers to not being able to use a remote table, remote means a table on another SQL instance. To show this working use this SQL to setup two databases foo and fooArchive create database foo go --create the source table fred in database foo select * into foo..fred from sys.objects go create database fooArchive go if object_id('fredarchive',DB_ID('fooArchive')) is null begin     select getdate() ArchiveDate,* into fooArchive..FredArchive from sys.objects where 1=2       end go And then we can use this simple statement to archive the data insert into fooArchive..FredArchive select getdate(),d.* from (delete top (1)         from foo..Fred         output deleted.*) d         go In this statement the delete can be any delete statement you wish so if you are deleting by ids or a range of values then you can do that. Refer to the DELETE-TOP-x-rows-avoiding-a-table-scan post to ensure that your delete is going to perform. The last thing you want to do is to perform 100 deletes each with 5000 records for each of those deletes to do a table scan. For a solution that works for SQL2005 or if you want to archive to a different server then you can use linked servers or SSIS. This example shows how to do it with linked servers. [ONARC-LAP03] is the source server. begin transaction insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*') d commit transaction and to prove the transactions work try, you should get the same number of records before and after. select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive   begin transaction insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*') d rollback transaction   select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive The transactions are very important with this solution. Look what happens when you don't have transactions and an error occurs   select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive   insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*                     raiserror (''Oh doo doo'',15,15)') d                     select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive Before running this think what the result would be. I got it wrong. What seems to happen is that the remote query is executed as a transaction, the error causes that to rollback. However the results have already been sent to the client and so get inserted into the

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  • Announcing Release of Oracle Solaris Cluster 4.1!

    - by user9159196
    Oct 26, 2012We are very happy to announce the release of  Oracle Solaris Cluster 4.1, providing High Availability (HA) and  Disaster Recovery (DR) capabilities for Oracle Solaris 11.1.  This is yet another proof of Oracle's continued investment in Oracle Solaris technologies such as Oracle Solaris Cluster. For this new release we have improved the Solaris Cluster integration within the Oracle environment. For example  we've created new agents such as PeopleSoft JobScheduler or added the support of the Oracle ZFS Storage Appliance replication in the Geo Edition module (to facilitate disaster recovery in multi-site configuration equipped with those types of storage.) We have also extended the Oracle Solaris Zone Cluster feature with support of Oracle Solaris 10 zone clusters and exclusive-IP to facilitate deployment of virtualized or cloud architecture.And there are many more new features to discover in this release. Stay tuned for more specific articles. In the mean time check out the What's new document or even better, download the latest version from  here.Also, join the Oracle Solaris 11 Online Event on November 7 where an entire session will be devoted to discussing Oracle Solaris Cluster 4.1. Our Oracle Solaris Cluster engineers will be on hand to respond to your questions. We look forward to your feedback and inputs! -Nancy Chow and Eve Kleinknecht 

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  • A Successful OTN MySQL Developer Day in Paris

    - by Bertrand Matthelié
    @font-face { font-family: "Arial"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; } On Wednesday this week Oracle held its first MySQL Developer Day in France. The room was packed with close to 100 people eager to learn more about MySQL. @font-face { font-family: "Arial"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; } We got great feedback from the attendees who could hear about the new MySQL Cluster 7.2 features, NoSQL Access to MySQL and MySQL Cluster, MySQL performance tuning in MySQL 5.5 and in MySQL 5.6…and more. Sessions included MySQL Essentials MySQL Replication and Scalability Developing MySQL Applications with Java and PHP MySQL Cluster Testing early releases of MySQL in a sandbox (by guest speaker and Oracle ACE Director for MySQL Giuseppe Maxia) MySQL Performance Tuning MySQL Enterprise Edition Management Tools Developing MySQL applications for ISVs & OEMs Thank you to all attendees for your active participation, and to all speakers for great and engaging presentations! More OTN MySQL Developer Days to come…stay tuned.

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  • SSIS: Deploying OLAP cubes using C# script tasks and AMO

    - by DrJohn
    As part of the continuing series on Building dynamic OLAP data marts on-the-fly, this blog entry will focus on how to automate the deployment of OLAP cubes using SQL Server Integration Services (SSIS) and Analysis Services Management Objects (AMO). OLAP cube deployment is usually done using the Analysis Services Deployment Wizard. However, this option was dismissed for a variety of reasons. Firstly, invoking external processes from SSIS is fraught with problems as (a) it is not always possible to ensure SSIS waits for the external program to terminate; (b) we cannot log the outcome properly and (c) it is not always possible to control the server's configuration to ensure the executable works correctly. Another reason for rejecting the Deployment Wizard is that it requires the 'answers' to be written into four XML files. These XML files record the three things we need to change: the name of the server, the name of the OLAP database and the connection string to the data mart. Although it would be reasonably straight forward to change the content of the XML files programmatically, this adds another set of complication and level of obscurity to the overall process. When I first investigated the possibility of using C# to deploy a cube, I was surprised to find that there are no other blog entries about the topic. I can only assume everyone else is happy with the Deployment Wizard! SSIS "forgets" assembly references If you build your script task from scratch, you will have to remember how to overcome one of the major annoyances of working with SSIS script tasks: the forgetful nature of SSIS when it comes to assembly references. Basically, you can go through the process of adding an assembly reference using the Add Reference dialog, but when you close the script window, SSIS "forgets" the assembly reference so the script will not compile. After repeating the operation several times, you will find that SSIS only remembers the assembly reference when you specifically press the Save All icon in the script window. This problem is not unique to the AMO assembly and has certainly been a "feature" since SQL Server 2005, so I am not amazed it is still present in SQL Server 2008 R2! Sample Package So let's take a look at the sample SSIS package I have provided which can be downloaded from here: DeployOlapCubeExample.zip  Below is a screenshot after a successful run. Connection Managers The package has three connection managers: AsDatabaseDefinitionFile is a file connection manager pointing to the .asdatabase file you wish to deploy. Note that this can be found in the bin directory of you OLAP database project once you have clicked the "Build" button in Visual Studio TargetOlapServerCS is an Analysis Services connection manager which identifies both the deployment server and the target database name. SourceDataMart is an OLEDB connection manager pointing to the data mart which is to act as the source of data for your cube. This will be used to replace the connection string found in your .asdatabase file Once you have configured the connection managers, the sample should run and deploy your OLAP database in a few seconds. Of course, in a production environment, these connection managers would be associated with package configurations or set at runtime. When you run the sample, you should see that the script logs its activity to the output screen (see screenshot above). If you configure logging for the package, then these messages will also appear in your SSIS logging. Sample Code Walkthrough Next let's walk through the code. The first step is to parse the connection string provided by the TargetOlapServerCS connection manager and obtain the name of both the target OLAP server and also the name of the OLAP database. Note that the target database does not have to exist to be referenced in an AS connection manager, so I am using this as a convenient way to define both properties. We now connect to the server and check for the existence of the OLAP database. If it exists, we drop the database so we can re-deploy. svr.Connect(olapServerName); if (svr.Connected) { // Drop the OLAP database if it already exists Database db = svr.Databases.FindByName(olapDatabaseName); if (db != null) { db.Drop(); } // rest of script } Next we start building the XMLA command that will actually perform the deployment. Basically this is a small chuck of XML which we need to wrap around the large .asdatabase file generated by the Visual Studio build process. // Start generating the main part of the XMLA command XmlDocument xmlaCommand = new XmlDocument(); xmlaCommand.LoadXml(string.Format("<Batch Transaction='false' xmlns='http://schemas.microsoft.com/analysisservices/2003/engine'><Alter AllowCreate='true' ObjectExpansion='ExpandFull'><Object><DatabaseID>{0}</DatabaseID></Object><ObjectDefinition/></Alter></Batch>", olapDatabaseName));  Next we need to merge two XML files which we can do by simply using setting the InnerXml property of the ObjectDefinition node as follows: // load OLAP Database definition from .asdatabase file identified by connection manager XmlDocument olapCubeDef = new XmlDocument(); olapCubeDef.Load(Dts.Connections["AsDatabaseDefinitionFile"].ConnectionString); // merge the two XML files by obtain a reference to the ObjectDefinition node oaRootNode.InnerXml = olapCubeDef.InnerXml;   One hurdle I had to overcome was removing detritus from the .asdabase file left by the Visual Studio build. Through an iterative process, I found I needed to remove several nodes as they caused the deployment to fail. The XMLA error message read "Cannot set read-only node: CreatedTimestamp" or similar. In comparing the XMLA generated with by the Deployment Wizard with that generated by my code, these read-only nodes were missing, so clearly I just needed to strip them out. This was easily achieved using XPath to find the relevant XML nodes, of which I show one example below: foreach (XmlNode node in rootNode.SelectNodes("//ns1:CreatedTimestamp", nsManager)) { node.ParentNode.RemoveChild(node); } Now we need to change the database name in both the ID and Name nodes using code such as: XmlNode databaseID = xmlaCommand.SelectSingleNode("//ns1:Database/ns1:ID", nsManager); if (databaseID != null) databaseID.InnerText = olapDatabaseName; Finally we need to change the connection string to point at the relevant data mart. Again this is easily achieved using XPath to search for the relevant nodes and then replace the content of the node with the new name or connection string. XmlNode connectionStringNode = xmlaCommand.SelectSingleNode("//ns1:DataSources/ns1:DataSource/ns1:ConnectionString", nsManager); if (connectionStringNode != null) { connectionStringNode.InnerText = Dts.Connections["SourceDataMart"].ConnectionString; } Finally we need to perform the deployment using the Execute XMLA command and check the returned XmlaResultCollection for errors before setting the Dts.TaskResult. XmlaResultCollection oResults = svr.Execute(xmlaCommand.InnerXml);  // check for errors during deployment foreach (Microsoft.AnalysisServices.XmlaResult oResult in oResults) { foreach (Microsoft.AnalysisServices.XmlaMessage oMessage in oResult.Messages) { if ((oMessage.GetType().Name == "XmlaError")) { FireError(oMessage.Description); HadError = true; } } } If you are not familiar with XML programming, all this may all seem a bit daunting, but perceiver as the sample code is pretty short. If you would like the script to process the OLAP database, simply uncomment the lines in the vicinity of Process method. Of course, you can extend the script to perform your own custom processing and to even synchronize the database to a front-end server. Personally, I like to keep the deployment and processing separate as the code can become overly complex for support staff.If you want to know more, come see my session at the forthcoming SQLBits conference.

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  • We Need More Migration!

    - by rickramsey
    source Eva Mendez says, "Oye chico, do you really want to keep your data in that tired legacy file system when it could be enjoying encryption, compression, deduplication, snapshots, remote replication and other benefits provided by ZFS in Oracle Solaris 11? It's really not that hard to cross over. If you know how." "I don't know how, me dices? Esta bien, papacito. Go to OTN. Take my word for it. They know how." <blushing> Aw shucks, Eva. Anything for you! </blushing> The Best Way to Migrate Data From Legacy File Systems to ZFS To migrate data from a legacy filesystem to ZFS in Oracle Solaris 11, you need to install the shadow-migration package and enable the shadowd service. Then follow the simple procedure described by Dominic Kay. How to Update to Oracle Solaris 11 Using the Image Packaging System Oracle Solaris 11.1 has been released. You can upgrade using either Oracle's official Solaris release repository or, if you have a support contract, the Support repository. Peter Dennis explains how. How to Migrate Oracle Database from Oracle Solaris 8 to Oracle Solaris 11 How to use the Oracle Solaris 8 P2V (physical to virtual) Archiver tool, which comes with Oracle Solaris Legacy Containers, to migrate a physical Oracle Solaris 8 system with Oracle Database and an Oracle Automatic Storage Management file system into an Oracle Solaris 8 branded zone inside an Oracle Solaris 10 guest domain on top of an Oracle Solaris 11 control domain. - Ricardo Website Newsletter Facebook Twitter

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