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  • Getting Started with Prism (aka Composite Application Guidance for WPF and Silverlight)

    - by dotneteer
    Overview Prism is a framework from the Microsoft Patterns and Practice team that allow you to create WPF and Silverlight in a modular way. It is especially valuable for larger projects in which a large number of developers can develop in parallel. Prism achieves its goal by supplying several services: · Dependency Injection (DI) and Inversion of control (IoC): By using DI, Prism takes away the responsibility of instantiating and managing the life time of dependency objects from individual components to a container. Prism relies on containers to discover, manage and compose large number of objects. By varying the configuration, the container can also inject mock objects for unit testing. Out of the box, Prism supports Unity and MEF as container although it is possible to use other containers by subclassing the Bootstrapper class. · Modularity and Region: Prism supplies the framework to split application into modules from the application shell. Each module is a library project that contains both UI and code and is responsible to initialize itself when loaded by the shell. Each window can be further divided into regions. A region is a user control with associated model. · Model, view and view-model (MVVM) pattern: Prism promotes the user MVVM. The use of DI container makes it much easier to inject model into view. WPF already has excellent data binding and commanding mechanism. To be productive with Prism, it is important to understand WPF data binding and commanding well. · Event-aggregation: Prism promotes loosely coupled components. Prism discourages for components from different modules to communicate each other, thus leading to dependency. Instead, Prism supplies an event-aggregation mechanism that allows components to publish and subscribe events without knowing each other. Architecture In the following, I will go into a little more detail on the services provided by Prism. Bootstrapper In a typical WPF application, application start-up is controls by App.xaml and its code behind. The main window of the application is typically specified in the App.xaml file. In a Prism application, we start a bootstrapper in the App class and delegate the duty of main window to the bootstrapper. The bootstrapper will start a dependency-injection container so all future object instantiations are managed by the container. Out of box, Prism provides the UnityBootstrapper and MefUnityBootstrapper abstract classes. All application needs to either provide a concrete implementation of one of these bootstrappers, or alternatively, subclass the Bootstrapper class with another DI container. A concrete bootstrapper class must implement the CreateShell method. Its responsibility is to resolve and create the Shell object through the DI container to serve as the main window for the application. The other important method to override is ConfigureModuleCatalog. The bootstrapper can register modules for the application. In a more advance scenario, an application does not have to know all its modules at compile time. Modules can be discovered at run time. Readers to refer to one of the Open Modularity Quick Starts for more information. Modules Once modules are registered with or discovered by Prism, they are instantiated by the DI container and their Initialize method is called. The DI container can inject into a module a region registry that implements IRegionViewRegistry interface. The module, in its Initialize method, can then call RegisterViewWithRegion method of the registry to register its regions. Regions Regions, once registered, are managed by the RegionManager. The shell can then load regions either through the RegionManager.RegionName attached property or dynamically through code. When a view is created by the region manager, the DI container can inject view model and other services into the view. The view then has a reference to the view model through which it can interact with backend services. Service locator Although it is possible to inject services into dependent classes through a DI container, an alternative way is to use the ServiceLocator to retrieve a service on demard. Prism supplies a service locator implementation and it is possible to get an instance of the service by calling: ServiceLocator.Current.GetInstance<IServiceType>() Event aggregator Prism supplies an IEventAggregator interface and implementation that can be injected into any class that needs to communicate with each other in a loosely-coupled fashion. The event aggregator uses a publisher/subscriber model. A class can publishes an event by calling eventAggregator.GetEvent<EventType>().Publish(parameter) to raise an event. Other classes can subscribe the event by calling eventAggregator.GetEvent<EventType>().Subscribe(EventHandler, other options). Getting started The easiest way to get started with Prism is to go through the Prism Hands-On labs and look at the Hello World QuickStart. The Hello World QuickStart shows how bootstrapper, modules and region works. Next, I would recommend you to look at the Stock Trader Reference Implementation. It is a more in depth example that resemble we want to set up an application. Several other QuickStarts cover individual Prism services. Some scenarios, such as dynamic module discovery, are more advanced. Apart from the official prism document, you can get an overview by reading Glen Block’s MSDN Magazine article. I have found the best free training material is from the Boise Code Camp. To be effective with Prism, it is important to understands key concepts of WPF well first, such as the DependencyProperty system, data binding, resource, theme and ICommand. It is also important to know your DI container of choice well. I will try to explorer these subjects in depth in the future. Testimony Recently, I worked on a desktop WPF application using Prism. I had a wonderful experience with Prism. The Prism is flexible enough even in the presence of third party controls such as Telerik WPF controls. We have never encountered any significant obstacle.

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  • Improved Database Threat Management with Oracle Audit Vault and ArcSight ESM

    - by roxana.bradescu
    Data represents one of the most valuable assets in any organization, making databases the primary target of today's attacks. It is important that organizations adopt a database security defense-in-depth approach that includes data encryption and masking, access control for privileged users and applications, activity monitoring and auditing. With Oracle Audit Vault, organizations can reliably monitor database activity enterprise-wide and alert on any security policy exceptions. The new integration between Oracle Audit Vault and ArcSight Enterprise Security Manager, allows organizations to take advantage of enterprise-wide, real-time event aggregation, correlation and response to attacks against their databases. Join us for this live SANS Tool Talk event to learn more about this new joint solution and real-world attack scenarios that can now be quickly detected and thwarted.

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  • Content Query Web Part and the Yes/No Field

    - by Bil Simser
    The Content Query Web Part (CQWP) is a pretty powerful beast. It allows you to do multiple site queries and aggregate the results. This is great for rolling up content and doing some summary type reporting. Here’s a trick to remember about Yes/No fields and using the CQWP. If you’re building a news style site and want to aggregate say all the announcements that people tag a certain way, up onto the home page this might be a solution. First we need to allow a way for users of all our sites to mark an announcement for inclusion on our Intranet Home Page. We’ll do this by just modifying the Announcement Content type and adding a Yes/No field to it. There are alternate ways of doing this like building a new Announcement type or stapling a feature to all sites to add our column but this is pretty low impact and only affects our current site collection so let’s go with it for now, okay? You can berate me in the comments about the proper way I should have done this part. Go to the Site Settings for the Site Collection and click on Site Content Types under the Galleries. This takes you to the gallery for this site and all subsites. Scroll down until you see the List Content Types and click on Announcements. Now we’re modifying the Announcement content type which affects all those announcement lists that are created by default if you’re building sites using the Team Site template (or creating a new Announcements list on any site for that matter). Click on Add from new site column under the Column list. This will allow us to create a new Yes/No field that users will see in Announcement items. This field will allow the user to flag the announcement for inclusion on the home page. Feel free to modify the fields as you see fit for your environment, this is just an example. Now that we’ve added the column to our Announcements Content type we can go into any site that has an announcement list, modify that announcement and flag it to be included on our home page. See the new Featured column? That was the result of modifying our Announcements Content Type on this site collection. Now we can move onto the dirty part, displaying it in a CQWP on the home page. And here is where the fun begins (and the head scratching should end). On our home page we want to drop a Content Query Web Part and aggregate any Announcement that’s been flagged as Featured by the users (we could also add the filter to handle Expires so we don’t show old content so go ahead and do that if you want). First add a CQWP to the page then modify the settings for the web part. In the first section, Query, we want the List Type to be set to Announcements and the Content type to be Announcement so set your options like this: Click Apply and you’ll see the results display all Announcements from any site in the site collection. I have five team sites created each with a unique announcement added to them. Now comes the filtering. We don’t want to include every announcement, only ones users flag using that Featured column we added. At first blush you might scroll down to the Additional Filters part of the Query options and set the Featured column to be equal to Yes: This seems correct doesn’t it? After all, the column is a Yes/No column and looking at an announcement in the site, it displays the field as Yes or No: However after applying the filter you get this result: (I have the announcements from Team Site 1 and Team Site 4 flagged as Featured) Huh? It’s BACKWARDS! Let’s confirm that. Go back in and change the Additional Filters section from Yes to No and hit Apply and you get this: Wait a minute? Shouldn’t I see Team Site 1 and 4 if the logic is backwards? Why am I seeing the same thing as before. What gives… For whatever reason, unknown to me, a Yes/No field (even though it displays as such) really uses 1 and 0 behind the scenes. Yeah, someone was stuck on using integer values for booleans when they wrote SharePoint (probably after a long night of white boarding ways to mess with developers heads) and came up with this. The solution is pretty simple but not very discoverable. Set the filter to include your flagged items like so: And it will filter the items marked as Featured correctly giving you this result: This kind of solution could also be extended and enhanced. Here are a few suggestions and ideas: Modify the ItemStyle.xsl file to add a new style for this aggregation which would include the first few paragraphs of the body (or perhaps add another field to the Content type called Excerpt or Summary and display that instead) Add an Image column to the Announcement Content type to include a Picture field and display it in the summary Add a Category choice field (Employee News, Current Events, Headlines, etc.) and add multiple CQWPs to the home page filtering each one on a different category I know some may find this topic old and dusty but I didn’t see a lot out there specifically on filtering the Yes/No fields and the whole 1/0 trick was a little wonky, so I figured a few pictures would help walk through overcoming yet another SharePoint weirdness. With a little work and some creative juices you can easily us the power of aggregation and the CQWP to build a news site from content on your team sites.

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  • UML class diagram - can aggregated object be part of two aggregated classes?

    - by user970696
    Some sources say that aggregation means that the class owns the object and shares reference. Lets assume an example where a company class holds a list of cars but departments of that company has list of cars used by them. class Department { list<Car> listOfCars; } class Company { list<Car> listOfCars; //initialization of the list } So in UML class diagram, I would do it like this. But I assume this is not allowed because it would imply that both company and department own the objects.. [COMPANY]<>------[CAR] [DEPARTMENT]<>---| //imagine this goes up to the car class

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  • How did craigspro license Craigslist content? [closed]

    - by Joshua Frank
    There's an app called craigspro that provides a much better interface to Craigslist on mobile devices. They claim that the app is Officially Licensed by Craigslist, but I thought Craigslist never licensed their content, and the only thing I can find on the subject in the terms of use is this: Any copying, aggregation, display, distribution, performance or derivative use of craigslist or any content posted on craigslist whether done directly or through intermediaries (including but not limited to by means of spiders, robots, crawlers, scrapers, framing, iframes or RSS feeds) is prohibited. As a limited exception, general purpose Internet search engines and noncommercial public archives will be entitled to access craigslist without individual written agreements executed with CL that specifically authorize an exception to this prohibition if ... Does anyone know how do get a "written agreement" with Craigslist, and roughly what their terms would be? Do they charge a fee, or just check that you're not evil? I'll try next with Craigslist directly, but I'd like to get a sense of the landscape before stumbling in.

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  • Cloud Integration White Paper - Now Available

    - by Bruce Tierney
    Interested in expanding your existing application infrastructure to integrate with cloud applications?  Download the new Oracle White Paper "Cloud Integration - A Comprehensive Solution" to learn not just about connectivity but the other key aspects of successful cloud integration. The paper includes three technical examples of cloud integration with Oracle Fusion Applications, Saleforce, and Workday and follows with the importance of taking a comprehensive approach to also include service aggregation, service virtualization, cloud security considerations and the benefit of maintaining a unified approach to monitoring and management despite an increasingly distributed hybrid infrastructure. To keep the integration architecture from being defined "accidentally" as new business units subscribe to additional cloud vendors outside the participation of IT, a discussion on the "Accidental SOA Cloud Architecture" is included: As shown in the table of contents below, the white paper provides a combination of high-level awareness about key considerations as well as a technical deep dive of the steps needed for cloud integration connectivity: Hope you find the White Paper valuable.  Please download from the following link

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  • Now Available:Oracle Utilities Customer Self Service Version 2.1

    - by Roxana Babiciu
    The Oracle Utilities Global Business Unit is pleased to announce the general availability of Oracle Utilities Customer Self Service 2.1. It is ready for customers and partners to download and install via the Oracle Software Delivery Cloud. Key Features & Benefits: Oracle Utilities Customer Self Service 2.1 includes several new capabilities and enhancements including significantly improved Commercial Account Management and Advanced Notification Management using a new Oracle Utilities Notification Center module (licensed separately). These include the following: Advanced Notification Management Online Issues and Forms Management • Budget Management and Billing for Billed Budgets Prepaid User Dashboard Enhanced Usage Details Web Presentment Start/Stop/Transfer Service Automation Payment Arrangement Automation Account Sets Management for Large Commercial Customers Multiple Account Usage Data Aggregation, Comparison, and Data Download Multiple Account Financial History Mobile Outage Maps More information can be found on OPN

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  • Data architecture for event log metrics?

    - by elliot42
    My service has a large ongoing number of user events, and we would like to do things like "count occurrence of event type T since date D." We are trying to make two basic decisions: What to store? Storing every event vs. only storing aggregates (Event log style) log every event and count them later, vs. (Time-series style) store a single aggregated "count of event E for date D" for every day Where to store the data In a relational database (particularly MySQL) In a non-relational (NoSQL) database In flat log files (collected centrally over the network via syslog-ng) What is standard practice / where can I read more about comparing the different types of systems? Additional details: The total event stream is large, potentially hundreds of thousands of entries per day But our current need is only to count certain types of events within it We don't necessarily need real-time access to the raw data or aggregation results IMHO, "log all events to files, crawl them at a later time to filter and aggregate the stream" is a pretty standard UNIX Way, but my Rails-y compatriots seem to think that nothing is real unless it's in MySQL.

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  • Building an instance system.

    - by Kyle C
    I am looking into how to design an instance system for the game I am working on. I have always wondered how these are created in games like World of Warcraft, where instances == dungeons/raids/etc). Areas that are separated from players other than those in your group, but have specific logic to them. Specifically how can you reuse your existing code base and not have a bunch of checks everywhere ? if (isInstance) do x; else do y; I don't know if this will make too much of a difference on any answers, but we're using a pretty classic "Object as pure aggregation" component system for our entities.

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  • Many ui panels needs interaction with same object

    - by user877329
    I am developing a tool for simulating systems like the Gray-Scott model (That is systems where spatial distribution depends on time). The actual model is loaded from a DLL or shared object and the simulation is performed by a Simulation object. There are at least two situations when the simulation needs to be destroyed: The user loads a new model The user changes the size of the domain To make sure nothing goes wrong, the current Model, Simulation, and rendering Thread are all managed by an ApplicationState object. But the two cases above are initiated from two different UI objects. Is it then ok to distribute a reference to the ApplicationState object to all panels that need to access at least one method on the ApplicationState object? Another solution would be to use aggregation so that the panel from which the user chooses model knows the simulation parameter panel. Also, the ApplicationState class seems somewhat clumsy, so I would like to have something else

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  • Using Subjects to Deploy Queries Dynamically

    - by Roman Schindlauer
    In the previous blog posting, we showed how to construct and deploy query fragments to a StreamInsight server, and how to re-use them later. In today’s posting we’ll integrate this pattern into a method of dynamically composing a new query with an existing one. The construct that enables this scenario in StreamInsight V2.1 is a Subject. A Subject lets me create a junction element in an existing query that I can tap into while the query is running. To set this up as an end-to-end example, let’s first define a stream simulator as our data source: var generator = myApp.DefineObservable(     (TimeSpan t) => Observable.Interval(t).Select(_ => new SourcePayload())); This ‘generator’ produces a new instance of SourcePayload with a period of t (system time) as an IObservable. SourcePayload happens to have a property of type double as its payload data. Let’s also define a sink for our example—an IObserver of double values that writes to the console: var console = myApp.DefineObserver(     (string label) => Observer.Create<double>(e => Console.WriteLine("{0}: {1}", label, e)))     .Deploy("ConsoleSink"); The observer takes a string as parameter which is used as a label on the console, so that we can distinguish the output of different sink instances. Note that we also deploy this observer, so that we can retrieve it later from the server from a different process. Remember how we defined the aggregation as an IQStreamable function in the previous article? We will use that as well: var avg = myApp     .DefineStreamable((IQStreamable<SourcePayload> s, TimeSpan w) =>         from win in s.TumblingWindow(w)         select win.Avg(e => e.Value))     .Deploy("AverageQuery"); Then we define the Subject, which acts as an observable sequence as well as an observer. Thus, we can feed a single source into the Subject and have multiple consumers—that can come and go at runtime—on the other side: var subject = myApp.CreateSubject("Subject", () => new Subject<SourcePayload>()); Subject are always deployed automatically. Their name is used to retrieve them from a (potentially) different process (see below). Note that the Subject as we defined it here doesn’t know anything about temporal streams. It is merely a sequence of SourcePayloads, without any notion of StreamInsight point events or CTIs. So in order to compose a temporal query on top of the Subject, we need to 'promote' the sequence of SourcePayloads into an IQStreamable of point events, including CTIs: var stream = subject.ToPointStreamable(     e => PointEvent.CreateInsert<SourcePayload>(e.Timestamp, e),     AdvanceTimeSettings.StrictlyIncreasingStartTime); In a later posting we will show how to use Subjects that have more awareness of time and can be used as a junction between QStreamables instead of IQbservables. Having turned the Subject into a temporal stream, we can now define the aggregate on this stream. We will use the IQStreamable entity avg that we defined above: var longAverages = avg(stream, TimeSpan.FromSeconds(5)); In order to run the query, we need to bind it to a sink, and bind the subject to the source: var standardQuery = longAverages     .Bind(console("5sec average"))     .With(generator(TimeSpan.FromMilliseconds(300)).Bind(subject)); Lastly, we start the process: standardQuery.Run("StandardProcess"); Now we have a simple query running end-to-end, producing results. What follows next is the crucial part of tapping into the Subject and adding another query that runs in parallel, using the same query definition (the “AverageQuery”) but with a different window length. We are assuming that we connected to the same StreamInsight server from a different process or even client, and thus have to retrieve the previously deployed entities through their names: // simulate the addition of a 'fast' query from a separate server connection, // by retrieving the aggregation query fragment // (instead of simply using the 'avg' object) var averageQuery = myApp     .GetStreamable<IQStreamable<SourcePayload>, TimeSpan, double>("AverageQuery"); // retrieve the input sequence as a subject var inputSequence = myApp     .GetSubject<SourcePayload, SourcePayload>("Subject"); // retrieve the registered sink var sink = myApp.GetObserver<string, double>("ConsoleSink"); // turn the sequence into a temporal stream var stream2 = inputSequence.ToPointStreamable(     e => PointEvent.CreateInsert<SourcePayload>(e.Timestamp, e),     AdvanceTimeSettings.StrictlyIncreasingStartTime); // apply the query, now with a different window length var shortAverages = averageQuery(stream2, TimeSpan.FromSeconds(1)); // bind new sink to query and run it var fastQuery = shortAverages     .Bind(sink("1sec average"))     .Run("FastProcess"); The attached solution demonstrates the sample end-to-end. Regards, The StreamInsight Team

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  • Concatenation of fields in different rows

    - by spender
    I'm stuck on an aggregation problem that I can't get to the bottom of. I have some data which is best summarized as follows id |phraseId|seqNum|word ========================= 1 |1 |1 |hello 2 |1 |2 |world 3 |2 |1 |black 4 |2 |2 |and 5 |2 |3 |white I'd like a query that gives back the following data: phraseId|completePhrase ======================== 1 |hello world 2 |black and white Anyone?

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  • Django: Group by?

    - by Mark
    I'm looking for something like the following: previous_invoices = Invoice.objects.filter(is_open=False).order_by('-created').group_by('user') (group_by() doesn't exist) This would find the most recently closed invoice for each user. This aggregation API seems to let you do stuff like this for counts and sums, but I don't need a count or sum or anything, I actually want the invoice objects!

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  • How to formulate a SQL Server indexed view that aggregates distinct values?

    - by Jeremy Lew
    I have a schema that includes tables like the following (pseudo schema): TABLE ItemCollection { ItemCollectionId ...etc... } TABLE Item { ItemId, ItemCollectionId, ContributorId } I need to aggregate the number of distinct contributors per ItemCollectionId. This is possible with a query like: SELECT ItemCollectionId, COUNT(DISTINCT ContributorId) FROM Item GROUP BY ItemCollectionId I further want to pre-calculate this aggregation using an indexed (materialized) view. The DISTINCT prevents an index being placed on this view. Is there any way to reformulate this which will not violate SQL Server's indexed view constraints?

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  • MongoDB: What's the point of using MapReduce without parallelism?

    - by netvope
    Quoting http://www.mongodb.org/display/DOCS/MapReduce#MapReduce-Parallelism As of right now, MapReduce jobs on a single mongod process are single threaded Without parallelism, what are the benefits of MapReduce compared to simpler or more traditional methods for queries and data aggregation? To avoid confusion: the question is NOT "what are the benefits of document-oriented DB over traditional relational DB"

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  • Can a sql server aggregate udf be passed in multiple parameters?

    - by Burg
    I am trying to write an aggregate udf for using Sql Server 2008 and C# 3.5 that implodes an aggregation of data. The kind of syntax I am looking for is: SELECT [dbo].[Implode]([Id], ',') FROM [dbo].[Table] GROUP BY [ForeignID] where the second parameter is the delimiter for the aggregate function. And example return value would be something like: 1,4,56 Is there a way to have multiple parameters in an aggregate udf?

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  • Possible to distribute or parallel process a sequential program?

    - by damigu
    In C++, I've written a mathematical program (for diffusion limited aggregation) where each new point calculated is dependent on all of the preceding points. Is it possible to have such a program work in a parallel or distributed manner to increase computing speed? If so, what type of modifications to the code would I need to look into?

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  • What free space thresholds/limits are advisable for 640 GB and 2 TB hard disk drives with ZEVO ZFS on OS X?

    - by Graham Perrin
    Assuming that free space advice for ZEVO will not differ from advice for other modern implementations of ZFS … Question Please, what percentages or amounts of free space are advisable for hard disk drives of the following sizes? 640 GB 2 TB Thoughts A standard answer for modern implementations of ZFS might be "no more than 96 percent full". However if apply that to (say) a single-disk 640 GB dataset where some of the files most commonly used (by VirtualBox) are larger than 15 GB each, then I guess that blocks for those files will become sub optimally spread across the platters with around 26 GB free. I read that in most cases, fragmentation and defragmentation should not be a concern with ZFS. Sill, I like the mental picture of most fragments of a large .vdi in reasonably close proximity to each other. (Do features of ZFS make that wish for proximity too old-fashioned?) Side note: there might arise the question of how to optimise performance after a threshold is 'broken'. If it arises, I'll keep it separate. Background On a 640 GB StoreJet Transcend (product ID 0x2329) in the past I probably went beyond an advisable threshold. Currently the largest file is around 17 GB –  – and I doubt that any .vdi or other file on this disk will grow beyond 40 GB. (Ignore the purple masses, those are bundles of 8 MB band files.) Without HFS Plus: the thresholds of twenty, ten and five percent that I associate with Mobile Time Machine file system need not apply. I currently use ZEVO Community Edition 1.1.1 with Mountain Lion, OS X 10.8.2, but I'd like answers to be not too version-specific. References, chronological order ZFS Block Allocation (Jeff Bonwick's Blog) (2006-11-04) Space Maps (Jeff Bonwick's Blog) (2007-09-13) Doubling Exchange Performance (Bizarre ! Vous avez dit Bizarre ?) (2010-03-11) … So to solve this problem, what went in 2010/Q1 software release is multifold. The most important thing is: we increased the threshold at which we switched from 'first fit' (go fast) to 'best fit' (pack tight) from 70% full to 96% full. With TB drives, each slab is at least 5GB and 4% is still 200MB plenty of space and no need to do anything radical before that. This gave us the biggest bang. Second, instead of trying to reuse the same primary slabs until it failed an allocation we decided to stop giving the primary slab this preferential threatment as soon as the biggest allocation that could be satisfied by a slab was down to 128K (metaslab_df_alloc_threshold). At that point we were ready to switch to another slab that had more free space. We also decided to reduce the SMO bonus. Before, a slab that was 50% empty was preferred over slabs that had never been used. In order to foster more write aggregation, we reduced the threshold to 33% empty. This means that a random write workload now spread to more slabs where each one will have larger amount of free space leading to more write aggregation. Finally we also saw that slab loading was contributing to lower performance and implemented a slab prefetch mechanism to reduce down time associated with that operation. The conjunction of all these changes lead to 50% improved OLTP and 70% reduced variability from run to run … OLTP Improvements in Sun Storage 7000 2010.Q1 (Performance Profiles) (2010-03-11) Alasdair on Everything » ZFS runs really slowly when free disk usage goes above 80% (2010-07-18) where commentary includes: … OpenSolaris has changed this in onnv revision 11146 … [CFT] Improved ZFS metaslab code (faster write speed) (2010-08-22)

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  • Layer 2 topology discovery

    - by pegah s
    I have been given a network (it is a LAN) comprised of switches and I need to discover the topology of that. (There may be Link Aggregation Groups (LAGs) in the network as well.) I have done a lot of search on layer 2 topology discovery and I have seen many articles talking about using SNMP MIBs or LLDP (I do not know which one is better or more practical, but all devices in my network support SNMP). But my problem is that I cannot find "the software to install and run" to actually see the topology map. I would really appreciate if someone could send me the website where I can download the code and use it. I have also found a lot of tools available online such as OpenNMS, Nagios, The Dude, LANsurveyor, SNMPwalk, and many more... But I cannot figure out which one is the best to pick. To summarize: what is the easiest simplest way to discover the layer 2 network topology?

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  • Hyper-V networking....still not sure which way to go??

    - by CZhale
    We have our Hyper-V server up and running (Windows 2008 ENT SP2) and started to create some of our VMs. The server has 4 total nics. 2 onboard Broadcom 1gb nic cards and a pci dual port Intel Pro cards 1gb. Right now, I have setup 1 broadcom nic to be the hyper-v host nic, and setup the other broadcom nic for the VMs. We are not using the Intel Nics....should we be thinking about teaming?Link Aggregation?? I just want to achieve the best possible setup for the network, but have read many things for and against teaming the nics?? Thoughts?

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  • Postfix - searching emails (logstash, greylog or other solution)

    - by Yarik Dot
    We are currently having ~100 servers and all of them are using remote syslog, so we have aggregated all logs on one server. The most questioned problem from our support team is: Has an email from .... to ... been delivered? I'd like to give to our support team access to some logging tool and some guide for searching in logs. What would you have recommended me? Or, do you know any other alternatives to test? The problem of grepping logs is that there is not sender and recipient address on one line. So I supposed, there might by some aggregation by email id.

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  • Parallelism in .NET – Part 7, Some Differences between PLINQ and LINQ to Objects

    - by Reed
    In my previous post on Declarative Data Parallelism, I mentioned that PLINQ extends LINQ to Objects to support parallel operations.  Although nearly all of the same operations are supported, there are some differences between PLINQ and LINQ to Objects.  By introducing Parallelism to our declarative model, we add some extra complexity.  This, in turn, adds some extra requirements that must be addressed. In order to illustrate the main differences, and why they exist, let’s begin by discussing some differences in how the two technologies operate, and look at the underlying types involved in LINQ to Objects and PLINQ . LINQ to Objects is mainly built upon a single class: Enumerable.  The Enumerable class is a static class that defines a large set of extension methods, nearly all of which work upon an IEnumerable<T>.  Many of these methods return a new IEnumerable<T>, allowing the methods to be chained together into a fluent style interface.  This is what allows us to write statements that chain together, and lead to the nice declarative programming model of LINQ: double min = collection .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Other LINQ variants work in a similar fashion.  For example, most data-oriented LINQ providers are built upon an implementation of IQueryable<T>, which allows the database provider to turn a LINQ statement into an underlying SQL query, to be performed directly on the remote database. PLINQ is similar, but instead of being built upon the Enumerable class, most of PLINQ is built upon a new static class: ParallelEnumerable.  When using PLINQ, you typically begin with any collection which implements IEnumerable<T>, and convert it to a new type using an extension method defined on ParallelEnumerable: AsParallel().  This method takes any IEnumerable<T>, and converts it into a ParallelQuery<T>, the core class for PLINQ.  There is a similar ParallelQuery class for working with non-generic IEnumerable implementations. This brings us to our first subtle, but important difference between PLINQ and LINQ – PLINQ always works upon specific types, which must be explicitly created. Typically, the type you’ll use with PLINQ is ParallelQuery<T>, but it can sometimes be a ParallelQuery or an OrderedParallelQuery<T>.  Instead of dealing with an interface, implemented by an unknown class, we’re dealing with a specific class type.  This works seamlessly from a usage standpoint – ParallelQuery<T> implements IEnumerable<T>, so you can always “switch back” to an IEnumerable<T>.  The difference only arises at the beginning of our parallelization.  When we’re using LINQ, and we want to process a normal collection via PLINQ, we need to explicitly convert the collection into a ParallelQuery<T> by calling AsParallel().  There is an important consideration here – AsParallel() does not need to be called on your specific collection, but rather any IEnumerable<T>.  This allows you to place it anywhere in the chain of methods involved in a LINQ statement, not just at the beginning.  This can be useful if you have an operation which will not parallelize well or is not thread safe.  For example, the following is perfectly valid, and similar to our previous examples: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); However, if SomeOperation() is not thread safe, we could just as easily do: double min = collection .Select(item => item.SomeOperation()) .AsParallel() .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); In this case, we’re using standard LINQ to Objects for the Select(…) method, then converting the results of that map routine to a ParallelQuery<T>, and processing our filter (the Where method) and our aggregation (the Min method) in parallel. PLINQ also provides us with a way to convert a ParallelQuery<T> back into a standard IEnumerable<T>, forcing sequential processing via standard LINQ to Objects.  If SomeOperation() was thread-safe, but PerformComputation() was not thread-safe, we would need to handle this by using the AsEnumerable() method: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .AsEnumerable() .Min(item => item.PerformComputation()); Here, we’re converting our collection into a ParallelQuery<T>, doing our map operation (the Select(…) method) and our filtering in parallel, then converting the collection back into a standard IEnumerable<T>, which causes our aggregation via Min() to be performed sequentially. This could also be written as two statements, as well, which would allow us to use the language integrated syntax for the first portion: var tempCollection = from item in collection.AsParallel() let e = item.SomeOperation() where (e.SomeProperty > 6 && e.SomeProperty < 24) select e; double min = tempCollection.AsEnumerable().Min(item => item.PerformComputation()); This allows us to use the standard LINQ style language integrated query syntax, but control whether it’s performed in parallel or serial by adding AsParallel() and AsEnumerable() appropriately. The second important difference between PLINQ and LINQ deals with order preservation.  PLINQ, by default, does not preserve the order of of source collection. This is by design.  In order to process a collection in parallel, the system needs to naturally deal with multiple elements at the same time.  Maintaining the original ordering of the sequence adds overhead, which is, in many cases, unnecessary.  Therefore, by default, the system is allowed to completely change the order of your sequence during processing.  If you are doing a standard query operation, this is usually not an issue.  However, there are times when keeping a specific ordering in place is important.  If this is required, you can explicitly request the ordering be preserved throughout all operations done on a ParallelQuery<T> by using the AsOrdered() extension method.  This will cause our sequence ordering to be preserved. For example, suppose we wanted to take a collection, perform an expensive operation which converts it to a new type, and display the first 100 elements.  In LINQ to Objects, our code might look something like: // Using IEnumerable<SourceClass> collection IEnumerable<ResultClass> results = collection .Select(e => e.CreateResult()) .Take(100); If we just converted this to a parallel query naively, like so: IEnumerable<ResultClass> results = collection .AsParallel() .Select(e => e.CreateResult()) .Take(100); We could very easily get a very different, and non-reproducable, set of results, since the ordering of elements in the input collection is not preserved.  To get the same results as our original query, we need to use: IEnumerable<ResultClass> results = collection .AsParallel() .AsOrdered() .Select(e => e.CreateResult()) .Take(100); This requests that PLINQ process our sequence in a way that verifies that our resulting collection is ordered as if it were processed serially.  This will cause our query to run slower, since there is overhead involved in maintaining the ordering.  However, in this case, it is required, since the ordering is required for correctness. PLINQ is incredibly useful.  It allows us to easily take nearly any LINQ to Objects query and run it in parallel, using the same methods and syntax we’ve used previously.  There are some important differences in operation that must be considered, however – it is not a free pass to parallelize everything.  When using PLINQ in order to parallelize your routines declaratively, the same guideline I mentioned before still applies: Parallelization is something that should be handled with care and forethought, added by design, and not just introduced casually.

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  • OWB 11gR2 - Early Arriving Facts

    - by Dawei Sun
    A common challenge when building ETL components for a data warehouse is how to handle early arriving facts. OWB 11gR2 introduced a new feature to address this for dimensional objects entitled Orphan Management. An orphan record is one that does not have a corresponding existing parent record. Orphan management automates the process of handling source rows that do not meet the requirements necessary to form a valid dimension or cube record. In this article, a simple example will be provided to show you how to use Orphan Management in OWB. We first import a sample MDL file that contains all the objects we need. Then we take some time to examine all the objects. After that, we prepare the source data, deploy the target table and dimension/cube loading map. Finally, we run the loading maps, and check the data in target dimension/cube tables. OK, let’s start… 1. Import MDL file and examine sample project First, download zip file from here, which includes a MDL file and three source data files. Then we open OWB design center, import orphan_management.mdl by using the menu File->Import->Warehouse Builder Metadata. Now we have several objects in BI_DEMO project as below: Mapping LOAD_CHANNELS_OM: The mapping for dimension loading. Mapping LOAD_SALES_OM: The mapping for cube loading. Dimension CHANNELS_OM: The dimension that contains channels data. Cube SALES_OM: The cube that contains sales data. Table CHANNELS_OM: The star implementation table of dimension CHANNELS_OM. Table SALES_OM: The star implementation table of cube SALES_OM. Table SRC_CHANNELS: The source table of channels data, that will be loaded into dimension CHANNELS_OM. Table SRC_ORDERS and SRC_ORDER_ITEMS: The source tables of sales data that will be loaded into cube SALES_OM. Sequence CLASS_OM_DIM_SEQ: The sequence used for loading dimension CHANNELS_OM. Dimension CHANNELS_OM This dimension has a hierarchy with three levels: TOTAL, CLASS and CHANNEL. Each level has three attributes: ID (surrogate key), NAME and SOURCE_ID (business key). It has a standard star implementation. The orphan management policy and the default parent setting are shown in the following screenshots: The orphan management policy options that you can set for loading are: Reject Orphan: The record is not inserted. Default Parent: You can specify a default parent record. This default record is used as the parent record for any record that does not have an existing parent record. If the default parent record does not exist, Warehouse Builder creates the default parent record. You specify the attribute values of the default parent record at the time of defining the dimensional object. If any ancestor of the default parent does not exist, Warehouse Builder also creates this record. No Maintenance: This is the default behavior. Warehouse Builder does not actively detect, reject, or fix orphan records. While removing data from a dimension, you can select one of the following orphan management policies: Reject Removal: Warehouse Builder does not allow you to delete the record if it has existing child records. No Maintenance: This is the default behavior. Warehouse Builder does not actively detect, reject, or fix orphan records. (More details are at http://download.oracle.com/docs/cd/E11882_01/owb.112/e10935/dim_objects.htm#insertedID1) Cube SALES_OM This cube is references to dimension CHANNELS_OM. It has three measures: AMOUNT, QUANTITY and COST. The orphan management policy setting are shown as following screenshot: The orphan management policy options that you can set for loading are: No Maintenance: Warehouse Builder does not actively detect, reject, or fix orphan rows. Default Dimension Record: Warehouse Builder assigns a default dimension record for any row that has an invalid or null dimension key value. Use the Settings button to define the default parent row. Reject Orphan: Warehouse Builder does not insert the row if it does not have an existing dimension record. (More details are at http://download.oracle.com/docs/cd/E11882_01/owb.112/e10935/dim_objects.htm#BABEACDG) Mapping LOAD_CHANNELS_OM This mapping loads source data from table SRC_CHANNELS to dimension CHANNELS_OM. The operator CHANNELS_IN is bound to table SRC_CHANNELS; CHANNELS_OUT is bound to dimension CHANNELS_OM. The TOTALS operator is used for generating a constant value for the top level in the dimension. The CLASS_FILTER operator is used to filter out the “invalid” class name, so then we can see what will happen when those channel records with an “invalid” parent are loading into dimension. Some properties of the dimension operator in this mapping are important to orphan management. See the screenshot below: Create Default Level Records: If YES, then default level records will be created. This property must be set to YES for dimensions and cubes if one of their orphan management policies is “Default Parent” or “Default Dimension Record”. This property is set to NO by default, so the user may need to set this to YES manually. LOAD policy for INVALID keys/ LOAD policy for NULL keys: These two properties have the same meaning as in the dimension editor. The values are set to the same as the dimension value when user drops the dimension into the mapping. The user does not need to modify these properties. Record Error Rows: If YES, error rows will be inserted into error table when loading the dimension. REMOVE Orphan Policy: This property is used when removing data from a dimension. Since the dimension loading type is set to LOAD in this example, this property is disabled. Mapping LOAD_SALES_OM This mapping loads source data from table SRC_ORDERS and SRC_ORDER_ITEMS to cube SALES_OM. This mapping seems a little bit complicated, but operators in the red rectangle are used to filter out and generate the records with “invalid” or “null” dimension keys. Some properties of the cube operator in a mapping are important to orphan management. See the screenshot below: Enable Source Aggregation: Should be checked in this example. If the default dimension record orphan policy is set for the cube operator, then it is recommended that source aggregation also be enabled. Otherwise, the orphan management processing may produce multiple fact rows with the same default dimension references, which will cause an “unstable rowset” execution error in the database, since the dimension refs are used as update match attributes for updating the fact table. LOAD policy for INVALID keys/ LOAD policy for NULL keys: These two properties have the same meaning as in the cube editor. The values are set to the same as in the cube editor when the user drops the cube into the mapping. The user does not need to modify these properties. Record Error Rows: If YES, error rows will be inserted into error table when loading the cube. 2. Deploy objects and mappings We now can deploy the objects. First, make sure location SALES_WH_LOCAL has been correctly configured. Then open Control Center Manager by using the menu Tools->Control Center Manager. Expand BI_DEMO->SALES_WH_LOCAL, click SALES_WH node on the project tree. We can see the following objects: Deploy all the objects in the following order: Sequence CLASS_OM_DIM_SEQ Table CHANNELS_OM, SALES_OM, SRC_CHANNELS, SRC_ORDERS, SRC_ORDER_ITEMS Dimension CHANNELS_OM Cube SALES_OM Mapping LOAD_CHANNELS_OM, LOAD_SALES_OM Note that we deployed source tables as well. Normally, we import source table from database instead of deploying them to target schema. However, in this example, we designed the source tables in OWB and deployed them to database for the purpose of this demonstration. 3. Prepare and examine source data Before running the mappings, we need to populate and examine the source data first. Run SRC_CHANNELS.sql, SRC_ORDERS.sql and SRC_ORDER_ITEMS.sql as target user. Then we check the data in these three tables. Table SRC_CHANNELS SQL> select rownum, id, class, name from src_channels; Records 1~5 are correct; they should be loaded into dimension without error. Records 6,7 and 8 have null parents; they should be loaded into dimension with a default parent value, and should be inserted into error table at the same time. Records 9, 10 and 11 have “invalid” parents; they should be rejected by dimension, and inserted into error table. Table SRC_ORDERS and SRC_ORDER_ITEMS SQL> select rownum, a.id, a.channel, b.amount, b.quantity, b.cost from src_orders a, src_order_items b where a.id = b.order_id; Record 178 has null dimension reference; it should be loaded into cube with a default dimension reference, and should be inserted into error table at the same time. Record 179 has “invalid” dimension reference; it should be rejected by cube, and inserted into error table. Other records should be aggregated and loaded into cube correctly. 4. Run the mappings and examine the target data In the Control Center Manager, expand BI_DEMO-> SALES_WH_LOCAL-> SALES_WH-> Mappings, right click on LOAD_CHANNELS_OM node, click Start. Use the same way to run mapping LOAD_SALES_OM. When they successfully finished, we can check the data in target tables. Table CHANNELS_OM SQL> select rownum, total_id, total_name, total_source_id, class_id,class_name, class_source_id, channel_id, channel_name,channel_source_id from channels_om order by abs(dimension_key); Records 1,2 and 3 are the default dimension records for the three levels. Records 8, 10 and 15 are the loaded records that originally have null parents. We see their parents name (class_name) is set to DEF_CLASS_NAME. Those records whose CHANNEL_NAME are Special_4, Special_5 and Special_6 are not loaded to this table because of the invalid parent. Error Table CHANNELS_OM_ERR SQL> select rownum, class_source_id, channel_id, channel_name,channel_source_id, err$$$_error_reason from channels_om_err order by channel_name; We can see all the record with null parent or invalid parent are inserted into this error table. Error reason is “Default parent used for record” for the first three records, and “No parent found for record” for the last three. Table SALES_OM SQL> select a.*, b.channel_name from sales_om a, channels_om b where a.channels=b.channel_id; We can see the order record with null channel_name has been loaded into target table with a default channel_name. The one with “invalid” channel_name are not loaded. Error Table SALES_OM_ERR SQL> select a.amount, a.cost, a.quantity, a.channels, b.channel_name, a.err$$$_error_reason from sales_om_err a, channels_om b where a.channels=b.channel_id(+); We can see the order records with null or invalid channel_name are inserted into error table. If the dimension reference column is null, the error reason is “Default dimension record used for fact”. If it is invalid, the error reason is “Dimension record not found for fact”. Summary In summary, this article illustrated the Orphan Management feature in OWB 11gR2. Automated orphan management policies improve ETL developer and administrator productivity by addressing an important cause of cube and dimension load failures, without requiring developers to explicitly build logic to handle these orphan rows.

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  • Elastic versus Distributed in caching.

    - by Mike Reys
    Until now, I hadn't heard about Elastic Caching yet. Today I read Mike Gualtieri's Blog entry. I immediately thought about Oracle Coherence and got a little scare throughout the reading. Elastic Caching is the next step after Distributed Caching. As we've always positioned Coherence as a Distributed Cache, I thought for a brief instance that Oracle had missed a new trend/technology. But then I started reading the characteristics of an Elastic Cache. Forrester definition: Software infrastructure that provides application developers with data caching services that are distributed across two or more server nodes that consistently perform as volumes grow can be scaled without downtime provide a range of fault-tolerance levels Hey wait a minute, doesn't Coherence fullfill all these requirements? Oh yes, I think it does! The next defintion in the article is about Elastic Application Platforms. This is mainly more of the same with the addition of code execution. Now there is analytics functionality in Oracle Coherence. The analytics capability provides data-centric functions like distributed aggregation, searching and sorting. Coherence also provides continuous querying and event-handling. I think that when it comes to providing an Elastic Application Platform (as in the Forrester definition), Oracle is close, nearly there. And what's more, as Elastic Platform is the next big thing towards the big C word, Oracle Coherence makes you cloud-ready ;-) There you go! Find more info on Oracle Coherence here.

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