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  • System.Data.SQLite

    - by csharp-source.net
    System.Data.SQLite is an enhanced version of the original SQLite database engine. It is a complete drop-in replacement for the original sqlite3.dll (you can even rename it to sqlite3.dll). It has no linker dependency on the .NET runtime so it can be distributed independently of .NET, yet embedded in the binary is a complete ADO.NET 2.0 provider for full managed development.

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  • Kleo Bare Metal Backups review

    <b>Linux User and Developer:</b> "Kleo Bare Metal Backups is a freely distributed product from Carroll-Net, Inc (http://carroll.net), a company that has been in the business of protecting and retrieving data for over 15 years. This experience shows in the design of the software."

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  • Integrating Coherence & Java EE 6 Applications using ActiveCache

    - by Ricardo Ferreira
    OK, so you are a developer and are starting a new Java EE 6 application using the most wonderful features of the Java EE platform like Enterprise JavaBeans, JavaServer Faces, CDI, JPA e another cool stuff technologies. And your architecture need to hold piece of data into distributed caches to improve application's performance, scalability and reliability? If this is your current facing scenario, maybe you should look closely in the solutions provided by Oracle WebLogic Server. Oracle had integrated WebLogic Server and its champion data caching technology called Oracle Coherence. This seamless integration between this two products provides a comprehensive environment to develop applications without the complexity of extra Java code to manage cache as a dependency, since Oracle provides an DI ("Dependency Injection") mechanism for Coherence, the same DI mechanism available in standard Java EE applications. This feature is called ActiveCache. In this article, I will show you how to configure ActiveCache in WebLogic and at your Java EE application. Configuring WebLogic to manage Coherence Before you start changing your application to use Coherence, you need to configure your Coherence distributed cache. The good news is, you can manage all this stuff without writing a single line of code of XML or even Java. This configuration can be done entirely in the WebLogic administration console. The first thing to do is the setup of a Coherence cluster. A Coherence cluster is a set of Coherence JVMs configured to form one single view of the cache. This means that you can insert or remove members of the cluster without the client application (the application that generates or consume data from the cache) knows about the changes. This concept allows your solution to scale-out without changing the application server JVMs. You can growth your application only in the data grid layer. To start the configuration, you need to configure an machine that points to the server in which you want to execute the Coherence JVMs. WebLogic Server allows you to do this very easily using the Administration Console. In this example, I will call the machine as "coherence-server". Remember that in order to the machine concept works, you need to ensure that the NodeManager are being executed in the target server that the machine points to. The NodeManager executable can be found in <WLS_HOME>/server/bin/startNodeManager.sh. The next thing to do is to configure a Coherence cluster. In the WebLogic administration console, go to Environment > Coherence Clusters and click in "New". Call this Coherence cluster of "my-coherence-cluster". Click in next. Specify a valid cluster address and port. The Coherence members will communicate with each other through this address and port. Our Coherence cluster are now configured. Now it is time to configure the Coherence members and add them to this cluster. In the WebLogic administration console, go to Environment > Coherence Servers and click in "New". In the field "Name" set to "coh-server-1". In the field "Machine", associate this Coherence server to the machine "coherence-server". In the field "Cluster", associate this Coherence server to the cluster named "my-coherence-cluster". Click in "Finish". Start the Coherence server using the "Control" tab of WebLogic administration console. This will instruct WebLogic to start a new JVM of Coherence in the target machine that should join the pre-defined Coherence cluster. Configuring your Java EE Application to Access Coherence Now lets pass to the funny part of the configuration. The first thing to do is to inform your Java EE application which Coherence cluster to join. Oracle had updated WebLogic server deployment descriptors so you will not have to change your code or the containers deployment descriptors like application.xml, ejb-jar.xml or web.xml. In this example, I will show you how to enable DI ("Dependency Injection") to a Coherence cache from a Servlet 3.0 component. In the WEB-INF/weblogic.xml deployment descriptor, put the following metadata information: <?xml version="1.0" encoding="UTF-8"?> <wls:weblogic-web-app xmlns:wls="http://xmlns.oracle.com/weblogic/weblogic-web-app" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://java.sun.com/xml/ns/javaee http://java.sun.com/xml/ns/javaee/web-app_2_5.xsd http://xmlns.oracle.com/weblogic/weblogic-web-app http://xmlns.oracle.com/weblogic/weblogic-web-app/1.4/weblogic-web-app.xsd"> <wls:context-root>myWebApp</wls:context-root> <wls:coherence-cluster-ref> <wls:coherence-cluster-name>my-coherence-cluster</wls:coherence-cluster-name> </wls:coherence-cluster-ref> </wls:weblogic-web-app> As you can see, using the "coherence-cluster-name" tag, we are informing our Java EE application that it should join the "my-coherence-cluster" when it loads in the web container. Without this information, the application will not be able to access the predefined Coherence cluster. It will form its own Coherence cluster without any members. So never forget to put this information. Now put the coherence.jar and active-cache-1.0.jar dependencies at your WEB-INF/lib application classpath. You need to deploy this dependencies so ActiveCache can automatically take care of the Coherence cluster join phase. This dependencies can be found in the following locations: - <WLS_HOME>/common/deployable-libraries/active-cache-1.0.jar - <COHERENCE_HOME>/lib/coherence.jar Finally, you need to write down the access code to the Coherence cache at your Servlet. In the following example, we have a Servlet 3.0 component that access a Coherence cache named "transactions" and prints into the browser output the content (the ammount property) of one specific transaction. package com.oracle.coherence.demo.activecache; import java.io.IOException; import javax.annotation.Resource; import javax.servlet.ServletException; import javax.servlet.annotation.WebServlet; import javax.servlet.http.HttpServlet; import javax.servlet.http.HttpServletRequest; import javax.servlet.http.HttpServletResponse; import com.tangosol.net.NamedCache; @WebServlet("/demo/specificTransaction") public class TransactionServletExample extends HttpServlet { @Resource(mappedName = "transactions") NamedCache transactions; protected void doGet(HttpServletRequest request, HttpServletResponse response) throws ServletException, IOException { int transId = Integer.parseInt(request.getParameter("transId")); Transaction transaction = (Transaction) transactions.get(transId); response.getWriter().println("<center>" + transaction.getAmmount() + "</center>"); } } Thats it! No more configuration is necessary and you have all set to start producing and getting data to/from Coherence. As you can see in the example code, the Coherence cache are treated as a normal dependency in the Java EE container. The magic happens behind the scenes when the ActiveCache allows your application to join the defined Coherence cluster. The most interesting thing about this approach is, no matter which type of Coherence cache your are using (Distributed, Partitioned, Replicated, WAN-Remote) for the client application, it is just a simple attribute member of com.tangosol.net.NamedCache type. And its all managed by the Java EE container as an dependency. This means that if you inject the same dependency (the Coherence cache named "transactions") in another Java EE component (JSF managed-bean, Stateless EJB) the cache will be the same. Cool isn't it? Thanks to the CDI technology, we can extend the same support for non-Java EE standards components like simple POJOs. This means that you are not forced to only use Servlets, EJBs or JSF in order to inject Coherence caches. You can do the same approach for regular POJOs created for you and managed by lightweight containers like Spring or Seam.

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  • Easy remote communication without WCF

    - by Ralf Westphal
    If you´ve read my previous posts about why I deem WCF more of a problem than a solution and how I think we should switch to asynchronous only communication in distributed application, you might be wondering, how this could be done in an easy way. Since a truely simple example to get started with WCF still is drawing quite some traffic to this blog, let me pick up on that and show you, how to accomplish the same but much easier with an async communication API. For simplicities sake let me put all...(read more)

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  • Recap: Oracle Fusion Middleware Strategies Driving Business Innovation

    - by Harish Gaur
    Hasan Rizvi, Executive Vice President of Oracle Fusion Middleware & Java took the stage on Tuesday to discuss how Oracle Fusion Middleware helps enable business innovation. Through a series of product demos and customer showcases, Hassan demonstrated how Oracle Fusion Middleware is a complete platform to harness the latest technological innovations (cloud, mobile, social and Fast Data) throughout the application lifecycle. Fig 1: Oracle Fusion Middleware is the foundation of business innovation This Session included 4 demonstrations to illustrate these strategies: 1. Build and deploy native mobile applications using Oracle ADF Mobile 2. Empower business user to model processes, design user interface and have rich mobile experience for process interaction using Oracle BPM Suite PS6. 3. Create collaborative user experience and integrate social sign-on using Oracle WebCenter Portal, Oracle WebCenter Content, Oracle Social Network & Oracle Identity Management 11g R2 4. Deploy and manage business applications on Oracle Exalogic Nike, LA Department of Water & Power and Nintendo joined Hasan on stage to share how their organizations are leveraging Oracle Fusion Middleware to enable business innovation. Managing Performance in the Wrld of Social and Mobile How do you provide predictable scalability and performance for an application that monitors active lifestyle of 8 million users on a daily basis? Nike’s answer is Oracle Coherence, a component of Oracle Fusion Middleware and Oracle Exadata. Fig 2: Oracle Coherence enabled data grid improves performance of Nike+ Digital Sports Platform Nicole Otto, Sr. Director of Consumer Digital Technology discussed the vision of the Nike+ platform, a platform which represents a shift for NIKE from a  "product"  to  a "product +" experience.  There are currently nearly 8 million users in the Nike+ system who are using digitally-enabled Nike+ devices.  Once data from the Nike+ device is transmitted to Nike+ application, users access the Nike+ website or via the Nike mobile applicatoin, seeing metrics around their daily active lifestyle and even engage in socially compelling experiences to compare, compete or collaborate their data with their friends. Nike expects the number of users to grow significantly this year which will drive an explosion of data and potential new experiences. To deal with this challenge, Nike envisioned building a shared platform that would drive a consumer-centric model for the company. Nike built this new platform using Oracle Coherence and Oracle Exadata. Using Coherence, Nike built a data grid tier as a distributed cache, thereby provide low-latency access to most recent and relevant data to consumers. Nicole discussed how Nike+ Digital Sports Platform is unique in the way that it utilizes the Coherence Grid.  Nike takes advantage of Coherence as a traditional cache using both cache-aside and cache-through patterns.  This new tier has enabled Nike to create a horizontally scalable distributed event-driven processing architecture. Current data grid volume is approximately 150,000 request per minute with about 40 million objects at any given time on the grid. Improving Customer Experience Across Multiple Channels Customer experience is on top of every CIO's mind. Customer Experience needs to be consistent and secure across multiple devices consumers may use.  This is the challenge Matt Lampe, CIO of Los Angeles Department of Water & Power (LADWP) was faced with. Despite being the largest utilities company in the country, LADWP had been relying on a 38 year old customer information system for serving its customers. Their prior system  had been unable to keep up with growing customer demands. Last year, LADWP embarked on a journey to improve customer experience for 1.6million LA DWP customers using Oracle WebCenter platform. Figure 3: Multi channel & Multi lingual LADWP.com built using Oracle WebCenter & Oracle Identity Management platform Matt shed light on his efforts to drive customer self-service across 3 dimensions – new website, new IVR platform and new bill payment service. LADWP has built a new portal to increase customer self-service while reducing the transactions via IVR. LADWP's website is powered Oracle WebCenter Portal and is accessible by desktop and mobile devices. By leveraging Oracle WebCenter, LADWP eliminated the need to build, format, and maintain individual mobile applications or websites for different devices. Their entire content is managed using Oracle WebCenter Content and secured using Oracle Identity Management. This new portal automated their paper based processes to web based workflows for customers. This includes automation of Self Service implemented through My Account -  like Bill Pay, Payment History, Bill History and Usage Analysis. LADWP's solution went live in April 2012. Matt indicated that LADWP's Self-Service Portal has greatly improved customer satisfaction.  In a JD Power Associates website satisfaction survey, results indicate rankings have climbed by 25+ points, marking a remarkable increase in user experience. Bolstering Performance and Simplifying Manageability of Business Applications Ingvar Petursson, Senior Vice Preisdent of IT at Nintendo America joined Hasan on-stage to discuss their choice of Exalogic. Nintendo had significant new requirements coming their way for business systems, both internal and external, in the years to come, especially with new products like the WiiU on the horizon this holiday season. Nintendo needed a platform that could give them performance, availability and ease of management as they deploy business systems. Ingvar selected Engineered Systems for two reasons: 1. High performance  2. Ease of management Figure 4: Nintendo relies on Oracle Exalogic to run ATG eCommerce, Oracle e-Business Suite and several business applications Nintendo made a decision to run their business applications (ATG eCommerce, E-Business Suite) and several Fusion Middleware components on the Exalogic platform. What impressed Ingvar was the "stress” testing results during evaluation. Oracle Exalogic could handle their 3-year load estimates for many functions, which was better than Nintendo expected without any hardware expansion. Faster Processing of Big Data Middleware plays an increasingly important role in Big Data. Last year, we announced at OpenWorld the introduction of Oracle Data Integrator for Hadoop and Oracle Loader for Hadoop which helps in the ability to move, transform, load data to and from Big Data Appliance to Exadata.  This year, we’ve added new capabilities to find, filter, and focus data using Oracle Event Processing. This product can natively integrate with Big Data Appliance or runs standalone. Hasan briefly discussed how NTT Docomo, largest mobile operator in Japan, leverages Oracle Event Processing & Oracle Coherence to process mobile data (from 13 million smartphone users) at a speed of 700K events per second before feeding it Hadoop for distributed processing of big data. Figure 5: Mobile traffic data processing at NTT Docomo with Oracle Event Processing & Oracle Coherence    

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  • Nagios: Central Monitoring

    <b>Begin Linux:</b> "This is part two of a three part series on distributed monitoring. You can usehttp://newsadmin.linuxtoday.com/ passive service and host checks to allow non-central Nagios servers to collect data from a network of machines and then transfer that information to a central Nagios server."

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  • How to include an apache library with my opensource code?

    - by OscarRyz
    I have this opensource code with MIT license that uses an Apache 2.0 licensed library. I want to include this in my project, so it can be built right away. In the point 4 of that license explains how to redistribute it: excerpt: 4 . Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: You must give any other recipients of the Work or Derivative Works a copy of this License; and You must cause any modified files to carry prominent notices stating that You changed the files; and You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. I'm not creating a derivative work ( I plan to provide it as it is ). I don't have a NOTICE file, just my my own LICENSE.txt file. Question: Where should I put something along the lines: "This project uses Xyz library distributed under Apache2.0 ..."? What's recommented? Should I provide the apache license file too? Or would be enough if I just say "Find the license online here...http://www.apache.org/licenses/LICENSE-2.0.html" I hope someone who has done this in the past may shed some light on the matter.

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  • Can one draw a cube using different method/drawing mode?

    - by den-javamaniac
    Hi. I've just started learning gamedev (in particular android EGL based) and have ran over a code from Pro Android Games 2 that looks as follows: /* * Copyright (C) 2007 Google Inc. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package opengl.scenes.cubes; import java.nio.ByteBuffer; import java.nio.ByteOrder; import java.nio.IntBuffer; import javax.microedition.khronos.opengles.GL10; public class Cube { public Cube(){ int one = 0x10000; int vertices[] = { -one, -one, -one, one, -one, -one, one, one, -one, -one, one, -one, -one, -one, one, one, -one, one, one, one, one, -one, one, one, }; int colors[] = { 0, 0, 0, one, one, 0, 0, one, one, one, 0, one, 0, one, 0, one, 0, 0, one, one, one, 0, one, one, one, one, one, one, 0, one, one, one, }; byte indices[] = { 0, 4, 5, 0, 5, 1, 1, 5, 6, 1, 6, 2, 2, 6, 7, 2, 7, 3, 3, 7, 4, 3, 4, 0, 4, 7, 6, 4, 6, 5, 3, 0, 1, 3, 1, 2 }; // Buffers to be passed to gl*Pointer() functions // must be direct, i.e., they must be placed on the // native heap where the garbage collector cannot vbb.asIntBuffer() // move them. // // Buffers with multi-byte datatypes (e.g., short, int, float) // must have their byte order set to native order ByteBuffer vbb = ByteBuffer.allocateDirect(vertices.length*4); vbb.order(ByteOrder.nativeOrder()); mVertexBuffer = vbb.asIntBuffer(); mVertexBuffer.put(vertices); mVertexBuffer.position(0); ByteBuffer cbb = ByteBuffer.allocateDirect(colors.length*4); cbb.order(ByteOrder.nativeOrder()); mColorBuffer = cbb.asIntBuffer(); mColorBuffer.put(colors); mColorBuffer.position(0); mIndexBuffer = ByteBuffer.allocateDirect(indices.length); mIndexBuffer.put(indices); mIndexBuffer.position(0); } public void draw(GL10 gl) { gl.glFrontFace(GL10.GL_CW); gl.glVertexPointer(3, GL10.GL_FIXED, 0, mVertexBuffer); gl.glColorPointer(4, GL10.GL_FIXED, 0, mColorBuffer); gl.glDrawElements(GL10.GL_TRIANGLES, 36, GL10.GL_UNSIGNED_BYTE, mIndexBuffer); } private IntBuffer mVertexBuffer; private IntBuffer mColorBuffer; private ByteBuffer mIndexBuffer;} So it suggests to draw a cube using triangles. My question is: can I draw the same cube using GL_TPOLYGON? If so, isn't that an easier/more understandable way to do things?

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  • DRBD and MySQL - Virtualbox Setup

    DRBD is a Linux project that provides a real-time distributed filesystem. Sean Hull demonstrates how to use Sun's virtualbox software to create a pair of VMs, then configure those VMs with DRBD, and finally install and test MySQL running on volumes sitting on DRBD.

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  • DRBD and MySQL - Virtualbox Setup

    DRBD is a Linux project that provides a real-time distributed filesystem. Sean Hull demonstrates how to use Sun's virtualbox software to create a pair of VMs, then configure those VMs with DRBD, and finally install and test MySQL running on volumes sitting on DRBD.

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  • Tellago releases a RESTful API for BizTalk Server business rules

    - by Charles Young
    Jesus Rodriguez has blogged recently on Tellago Devlabs' release of an open source RESTful API for BizTalk Server Business Rules.   This is an excellent addition to the BizTalk ecosystem and I congratulate Tellago on their work.   See http://weblogs.asp.net/gsusx/archive/2011/02/08/tellago-devlabs-a-restful-api-for-biztalk-server-business-rules.aspx   The Microsoft BRE was originally designed to be used as an embedded library in .NET applications. This is reflected in the implementation of the Rules Engine Update (REU) Service which is a TCP/IP service that is hosted by a Windows service running locally on each BizTalk box. The job of the REU is to distribute rules, managed and held in a central database repository, across the various servers in a BizTalk group.   The engine is therefore distributed on each box, rather than exploited behind a central rules service.   This model is all very well, but proves quite restrictive in enterprise environments. The problem is that the BRE can only run legally on licensed BizTalk boxes. Increasingly we need to deliver rules capabilities across a more widely distributed environment. For example, in the project I am working on currently, we need to surface decisioning capabilities for use within WF workflow services running under AppFabric on non-BTS boxes. The BRE does not, currently, offer any centralised rule service facilities out of the box, and hence you have to roll your own (and then run your rules services on BTS boxes which has raised a few eyebrows on my current project, as all other WCF services run on a dedicated server farm ).   Tellago's API addresses this by providing a RESTful API for querying the rules repository and executing rule sets against XML passed in the request payload. As Jesus points out in his post, using a RESTful approach hugely increases the reach of BRE-based decisioning, allowing simple invocation from code written in dynamic languages, mobile devices, etc.   We developed our own SOAP-based general-purpose rules service to handle scenarios such as the one we face on my current project. SOAP is arguably better suited to enterprise service bus environments (please don't 'flame' me - I refuse to engage in the RESTFul vs. SOAP war). For example, on my current project we use claims based authorisation across the entire service bus and use WIF and WS-Federation for this purpose.   We have extended this to the rules service. I can't release the code for commercial reasons :-( but this approach allows us to legally extend the reach of BRE far beyond the confines of the BizTalk boxes on which it runs and to provide general purpose decisioning capabilities on the bus.   So, well done Tellago.   I haven't had a chance to play with the API yet, but am looking forward to doing so.

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  • Article Sharing &ndash; Windows Azure Memcached Plugin

    - by Shaun
    I just found that David Aiken, a windows azure developer and evangelist, wrote a cool article about how to use Memcached in Windows Azure through the new feature Azure Plugin. http://www.davidaiken.com/2011/01/11/windows-azure-memcached-plugin/ I think the best solution for distributed cache in Azure would be the Windows Azure AppFabric Caching but since it’s only in CTP and avaiable in the US data center David’s solution would be the best. Only one thing I’m concerning about, is the stability of windows verion Memcached.

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  • Oracle Fusion Applications Data Sheets Are Now Available

    - by David Hope-Ross
    For customers chomping at the bit for more information on Oracle Fusion applications, there is good news. We’ve just published  a complete library of data sheets for Oracle Fusion Applications. Included are SCM applications like Fusion Distributed Order Orchestration, Fusion Inventory Management, and Fusion Product Hub. And customers interested in sourcing and procurement should review documents that address Oracle Fusion Sourcing ,Oracle Fusion Procurement Contracts, Oracle Fusion Purchasing, Oracle Fusion Self Service Procurement, and Oracle Fusion Supplier Portal.

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  • MapRedux - PowerShell and Big Data

    - by Dittenhafer Solutions
    MapRedux – #PowerShell and #Big Data Have you been hearing about “big data”, “map reduce” and other large scale computing terms over the past couple of years and been curious to dig into more detail? Have you read some of the Apache Hadoop online documentation and unfortunately concluded that it wasn't feasible to setup a “test” hadoop environment on your machine? More recently, I have read about some of Microsoft’s work to enable Hadoop on the Azure cloud. Being a "Microsoft"-leaning technologist, I am more inclinded to be successful with experimentation when on the Windows platform. Of course, it is not that I am "religious" about one set of technologies other another, but rather more experienced. Anyway, within the past couple of weeks I have been thinking about PowerShell a bit more as the 2012 PowerShell Scripting Games approach and it occured to me that PowerShell's support for Windows Remote Management (WinRM), and some other inherent features of PowerShell might lend themselves particularly well to a simple implementation of the MapReduce framework. I fired up my PowerShell ISE and started writing just to see where it would take me. Quite simply, the ScriptBlock feature combined with the ability of Invoke-Command to create remote jobs on networked servers provides much of the plumbing of a distributed computing environment. There are some limiting factors of course. Microsoft provided some default settings which prevent PowerShell from taking over a network without administrative approval first. But even with just one adjustment, a given Windows-based machine can become a node in a MapReduce-style distributed computing environment. Ok, so enough introduction. Let's talk about the code. First, any machine that will participate as a remote "node" will need WinRM enabled for remote access, as shown below. This is not exactly practical for hundreds of intended nodes, but for one (or five) machines in a test environment it does just fine. C:> winrm quickconfig WinRM is not set up to receive requests on this machine. The following changes must be made: Set the WinRM service type to auto start. Start the WinRM service. Make these changes [y/n]? y Alternatively, you could take the approach described in the Remotely enable PSRemoting post from the TechNet forum and use PowerShell to create remote scheduled tasks that will call Enable-PSRemoting on each intended node. Invoke-MapRedux Moving on, now that you have one or more remote "nodes" enabled, you can consider the actual Map and Reduce algorithms. Consider the following snippet: $MyMrResults = Invoke-MapRedux -MapReduceItem $Mr -ComputerName $MyNodes -DataSet $dataset -Verbose Invoke-MapRedux takes an instance of a MapReduceItem which references the Map and Reduce scriptblocks, an array of computer names which are the remote nodes, and the initial data set to be processed. As simple as that, you can start working with concepts of big data and the MapReduce paradigm. Now, how did we get there? I have published the initial version of my PsMapRedux PowerShell Module on GitHub. The PsMapRedux module provides the Invoke-MapRedux function described above. Feel free to browse the underlying code and even contribute to the project! In a later post, I plan to show some of the inner workings of the module, but for now let's move on to how the Map and Reduce functions are defined. Map Both the Map and Reduce functions need to follow a prescribed prototype. The prototype for a Map function in the MapRedux module is as follows. A simple scriptblock that takes one PsObject parameter and returns a hashtable. It is important to note that the PsObject $dataset parameter is a MapRedux custom object that has a "Data" property which offers an array of data to be processed by the Map function. $aMap = { Param ( [PsObject] $dataset ) # Indicate the job is running on the remote node. Write-Host ($env:computername + "::Map"); # The hashtable to return $list = @{}; # ... Perform the mapping work and prepare the $list hashtable result with your custom PSObject... # ... The $dataset has a single 'Data' property which contains an array of data rows # which is a subset of the originally submitted data set. # Return the hashtable (Key, PSObject) Write-Output $list; } Reduce Likewise, with the Reduce function a simple prototype must be followed which takes a $key and a result $dataset from the MapRedux's partitioning function (which joins the Map results by key). Again, the $dataset is a MapRedux custom object that has a "Data" property as described in the Map section. $aReduce = { Param ( [object] $key, [PSObject] $dataset ) Write-Host ($env:computername + "::Reduce - Count: " + $dataset.Data.Count) # The hashtable to return $redux = @{}; # Return Write-Output $redux; } All Together Now When everything is put together in a short example script, you implement your Map and Reduce functions, query for some starting data, build the MapReduxItem via New-MapReduxItem and call Invoke-MapRedux to get the process started: # Import the MapRedux and SQL Server providers Import-Module "MapRedux" Import-Module “sqlps” -DisableNameChecking # Query the database for a dataset Set-Location SQLSERVER:\sql\dbserver1\default\databases\myDb $query = "SELECT MyKey, Date, Value1 FROM BigData ORDER BY MyKey"; Write-Host "Query: $query" $dataset = Invoke-SqlCmd -query $query # Build the Map function $MyMap = { Param ( [PsObject] $dataset ) Write-Host ($env:computername + "::Map"); $list = @{}; foreach($row in $dataset.Data) { # Write-Host ("Key: " + $row.MyKey.ToString()); if($list.ContainsKey($row.MyKey) -eq $true) { $s = $list.Item($row.MyKey); $s.Sum += $row.Value1; $s.Count++; } else { $s = New-Object PSObject; $s | Add-Member -Type NoteProperty -Name MyKey -Value $row.MyKey; $s | Add-Member -type NoteProperty -Name Sum -Value $row.Value1; $list.Add($row.MyKey, $s); } } Write-Output $list; } $MyReduce = { Param ( [object] $key, [PSObject] $dataset ) Write-Host ($env:computername + "::Reduce - Count: " + $dataset.Data.Count) $redux = @{}; $count = 0; foreach($s in $dataset.Data) { $sum += $s.Sum; $count += 1; } # Reduce $redux.Add($s.MyKey, $sum / $count); # Return Write-Output $redux; } # Create the item data $Mr = New-MapReduxItem "My Test MapReduce Job" $MyMap $MyReduce # Array of processing nodes... $MyNodes = ("node1", "node2", "node3", "node4", "localhost") # Run the Map Reduce routine... $MyMrResults = Invoke-MapRedux -MapReduceItem $Mr -ComputerName $MyNodes -DataSet $dataset -Verbose # Show the results Set-Location C:\ $MyMrResults | Out-GridView Conclusion I hope you have seen through this article that PowerShell has a significant infrastructure available for distributed computing. While it does take some code to expose a MapReduce-style framework, much of the work is already done and PowerShell could prove to be the the easiest platform to develop and run big data jobs in your corporate data center, potentially in the Azure cloud, or certainly as an academic excerise at home or school. Follow me on Twitter to stay up to date on the continuing progress of my Powershell MapRedux module, and thanks for reading! Daniel

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  • How to exclude copy local referenced assemblies from a VSIX

    - by Daniel Cazzulino
    When you add library references to project that are not reference assemblies or installed in the GAC, Visual Studio defaults to setting Copy Local to True: If, however, those dependencies are distributed by some other means (i.e. another extension, or are part of VS private assemblies, or whatever) and you want to avoid including them in your VSIX, you can add the following property to the project file: &lt;PropertyGroup&gt; ... &lt;IncludeCopyLocalReferencesInVSIXContainer&gt;false&lt;/IncludeCopyLocalReferencesInVSIXContainer&gt;Read full article

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  • CentOS / Redhat: Setup NFS v4.0 File Server

    <b>nixCraft: </b>"How do I setup NFS v4.0 distributed file system access server under CentOS / RHEL v5.x for sharing files with UNIX and Linux workstations? How to export a directory with NFSv4? How to mount a directory with NFSv4?"

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  • Move Data into the grid for scalable, predictable response times

    - by JuergenKress
    CloudTran is pleased to introduce the availability of the CloudTran Transaction and Persistence Manager for creating scalable, reliable data services on the Oracle Coherence In-Memory Data Grid (IMDG). Use of IMDG architectures has been key to handling today’s web-scale loads because it eliminates database latency by storing important and frequently access data in memory instead of on disk. The CloudTran product lets developers easily use an IMDG for full ACID-compliant transactions without having to be concerned about the location or spread of data. The system has its own implementation of fast, scalable distributed transactions that does NOT depend on XA protocols but still guarantees all ACID properties. Plus, CloudTran asynchronously replicates data going into the IMDG to back-end datastores and back-up data centers, again ensuring ACID properties. CloudTran can be accessed through Java Persistence API (JPA via TopLink Grid) and now, through a new Low-Level API, or LLAPI. This is ideal for use in SOA applications that need data reliability, high availability, performance, and scalability. It is still in its limited beta release, the LLAPI gives developers the ability to use standard put/remove logic available in Coherence and then wrap logic with simple Spring annotations or XML+AspectJ to start transactions. An important feature of LLAPI is the ability to join transactions. This is a common outcome for SOA applications that need to reduce network traffic by aggregating data into single cache entries and then doing SOA service processing in the node holding the data. This results in the need to orchestrate transaction processing across multiple service calls. CloudTran has the capability to handle these “multi-client” transactions at speed with no loss in ACID properties. Developing software around an IMDG like Oracle Coherence is an important choice for today’s web-scale applications and services. But this introduces new architectural considerations to maintain scalability in light of increased network loads and data movement. Without using CloudTran, developers are faced with an incredibly difficult task to ensure data reliability, availability, performance, and scalability when working with an IMDG. Working with highly distributed data that is entirely volatile while stored in memory presents numerous edge cases where failures can result in data loss. The CloudTran product takes care of all of this, leaving developers with the confidence and peace of mind that all data is processed correctly. For those interested in evaluating the CloudTran product and IMDGs, take a look at this link for more information: http://www.CloudTran.com/downloadAPI.ph , or send your questions to [email protected]. SOA & BPM Partner Community For regular information on Oracle SOA Suite become a member in the SOA & BPM Partner Community for registration please visit  www.oracle.com/goto/emea/soa (OPN account required) If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Mix Forum Technorati Tags: CloudTran,data grid,M,SOA Community,Oracle SOA,Oracle BPM,BPM,Community,OPN,Jürgen Kress

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  • Découvrir Hadoop, avec un tutoriel traduit par Stéphane Dupont

    Bonjour,Je vous présente ce tutoriel traduit par Stéphane Dupont intitulé : Tutoriel Hadoop Hadoop est un système distribué, tolérant aux pannes, pour le stockage de données et qui est hautement scalable. Cette capacité de monter en charge est le résultat d'un stockage en cluster à haute bande passante et répliqué, connu sous l'acronyme de HDFS (Hadoop Distributed File System) et d'un traitement distribué...

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  • WildPackets Monitors Diverse Networks

    WildPackets offers portable network analysis products which are designed for use on enterprise networks and in test and measurement labs, plus distributed network analysis solutions for enterprise-wide applications.

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  • Best Ruby Git library?

    - by Jeff Welling
    Which is the best Git library in Ruby to use? Git, Grit, Rugged, Other? Background: I'm the current maintainer of TicGit-ng which is a distributed offline ticket system built on git, and I've read and heard over and over again that Grit is the one I should use because it supersedes the Git gem, but there seems to be either a lack of documentation or a lack of features because myself and others have failed in trying to switch from the deprecated-but-functional Git to the newer Grit gem.

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