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  • Disaster recovery backup of files/photos for personal use

    - by Renesis
    I'm looking for the best method to store a backup of important files and 5+ years of digital photos that is safe from some type of fire/flood disaster in my home. I'm looking for: Affordable: Less than $100/yr or first-time cost. Reliable: At least a smaller chance of failing than there is of fire or flood Easy for initial backup and to add to, and at least semi-easy to recover. I recently purchased a small home safe for physical vitals. It was inexpensive, solid, and is fire/water safe. If I had a physical copy of the digital files, the safe would work fine for this, but I don't know what to store in it that adequately meets the requirements above. Hard drive - I read that the danger of it not spinning up makes a hard drive a bad choice for this type of storage, although it was my first thought and would definitely be the simplest choice - very easy to take out once a month and add files to. DVDs - Way too much of a hassle for both backup and restore. Tape - No idea on the affordability of this option Online - Given that I have at least 300GB already and ever-increasing megapixels means ever-bigger files, and my ISP upload is about 2Mb at the best, this just doesn't sound like a good option for me, but I could be convinced. Other - Have I missed something? Also, I'm already covered both for sync between computers (Dropbox) and a nightly backup of these files (External HDD). The problem with the nightly backup is obviously that it's always with the computer and in a disaster would be destroyed along with it. Is anyone else doing something similar? Is the HDD as poor of a choice as I read, or is it a feasible option? Maybe two to reduce the likelihood of failure?

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  • Making Spring Data JPA work with DataNucleus (GAE) (Spring Boot)

    - by xybrek
    There are several hints that Spring Data works with Google App Engine like: http://tommysiu.blogspot.com/2014/01/spring-data-on-gae-part-1.html http://blog.eisele.net/2009/07/spring-300m3-on-google-appengine-with.html Much of the examples are not "Spring Boot" so I've been trying to retrofit things with it. However, I've been stuck with this error for days and days: [INFO] Caused by: java.lang.NullPointerException [INFO] at org.datanucleus.api.jpa.metamodel.SingularAttributeImpl.isVersion(SingularAttributeImpl.java:79) [INFO] at org.springframework.data.jpa.repository.support.JpaMetamodelEntityInformation.findVersionAttribute(JpaMetamodelEntityInformation.java:102) [INFO] at org.springframework.data.jpa.repository.support.JpaMetamodelEntityInformation.<init>(JpaMetamodelEntityInformation.java:79) [INFO] at org.springframework.data.jpa.repository.support.JpaEntityInformationSupport.getMetadata(JpaEntityInformationSupport.java:65) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactory.getEntityInformation(JpaRepositoryFactory.java:149) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactory.getTargetRepository(JpaRepositoryFactory.java:88) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactory.getTargetRepository(JpaRepositoryFactory.java:68) [INFO] at org.springframework.data.repository.core.support.RepositoryFactorySupport.getRepository(RepositoryFactorySupport.java:158) [INFO] at org.springframework.data.repository.core.support.RepositoryFactoryBeanSupport.initAndReturn(RepositoryFactoryBeanSupport.java:224) [INFO] at org.springframework.data.repository.core.support.RepositoryFactoryBeanSupport.afterPropertiesSet(RepositoryFactoryBeanSupport.java:210) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactoryBean.afterPropertiesSet(JpaRepositoryFactoryBean.java:92) [INFO] at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory$6.run(AbstractAutowireCapableBeanFactory.java:1602) [INFO] at java.security.AccessController.doPrivileged(Native Method) [INFO] at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.invokeInitMethods(AbstractAutowireCapableBeanFactory.java:1599) [INFO] at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.initializeBean(AbstractAutowireCapableBeanFactory.java:1549) [INFO] ... 40 more Where, I'm trying to use Spring Data JPA with DataNucleus/AppEngine: @Configuration @ComponentScan @EnableJpaRepositories @EnableTransactionManagement class JpaApplicationConfig { private static final Logger logger = Logger .getLogger(JpaApplicationConfig.class.getName()); @Bean public EntityManagerFactory entityManagerFactory() { logger.info("Loading Entity Manager..."); return Persistence .createEntityManagerFactory("transactions-optional"); } @Bean public PlatformTransactionManager transactionManager() { logger.info("Loading Transaction Manager..."); final JpaTransactionManager txManager = new JpaTransactionManager(); txManager.setEntityManagerFactory(entityManagerFactory()); return txManager; } } I've tested Persistence.createEntityManagerFactory("transactions-optional"); to see if the app can persist using this EMF, well, it does, so I am sure that this EMF works fine. The problem is the "wiring" up with the Spring Data JPA, can anybody help?

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  • Parse and read data frame in C?

    - by user253656
    I am writing a program that reads the data from the serial port on Linux. The data are sent by another device with the following frame format: |start | Command | Data | CRC | End | |0x02 | 0x41 | (0-127 octets) | | 0x03| ---------------------------------------------------- The Data field contains 127 octets as shown and octet 1,2 contains one type of data; octet 3,4 contains another data. I need to get these data I know how to write and read data to and from a serial port in Linux, but it is just to write and read a simple string (like "ABD") My issue is that I do not know how to parse the data frame formatted as above so that I can: get the data in octet 1,2 in the Data field get the data in octet 3,4 in the Data field get the value in CRC field to check the consistency of the data Here the sample snip code that read and write a simple string from and to a serial port in Linux: int writeport(int fd, char *chars) { int len = strlen(chars); chars[len] = 0x0d; // stick a <CR> after the command chars[len+1] = 0x00; // terminate the string properly int n = write(fd, chars, strlen(chars)); if (n < 0) { fputs("write failed!\n", stderr); return 0; } return 1; } int readport(int fd, char *result) { int iIn = read(fd, result, 254); result[iIn-1] = 0x00; if (iIn < 0) { if (errno == EAGAIN) { printf("SERIAL EAGAIN ERROR\n"); return 0; } else { printf("SERIAL read error %d %s\n", errno, strerror(errno)); return 0; } } return 1; } Does anyone please have some ideas? Thanks all.

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  • Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 1

    - by rajbk
    The Open Data Protocol, referred to as OData, is a new data-sharing standard that breaks down silos and fosters an interoperative ecosystem for data consumers (clients) and producers (services) that is far more powerful than currently possible. It enables more applications to make sense of a broader set of data, and helps every data service and client add value to the whole ecosystem. WCF Data Services (previously known as ADO.NET Data Services), then, was the first Microsoft technology to support the Open Data Protocol in Visual Studio 2008 SP1. It provides developers with client libraries for .NET, Silverlight, AJAX, PHP and Java. Microsoft now also supports OData in SQL Server 2008 R2, Windows Azure Storage, Excel 2010 (through PowerPivot), and SharePoint 2010. Many other other applications in the works. * This post walks you through how to create an OData feed, define a shape for the data and pre-filter the data using Visual Studio 2010, WCF Data Services and the Entity Framework. A sample project is attached at the bottom of Part 2 of this post. Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 2 Create the Web Application File –› New –› Project, Select “ASP.NET Empty Web Application” Add the Entity Data Model Right click on the Web Application in the Solution Explorer and select “Add New Item..” Select “ADO.NET Entity Data Model” under "Data”. Name the Model “Northwind” and click “Add”.   In the “Choose Model Contents”, select “Generate Model From Database” and click “Next”   Define a connection to your database containing the Northwind database in the next screen. We are going to expose the Products table through our OData feed. Select “Products” in the “Choose your Database Object” screen.   Click “Finish”. We are done creating our Entity Data Model. Save the Northwind.edmx file created. Add the WCF Data Service Right click on the Web Application in the Solution Explorer and select “Add New Item..” Select “WCF Data Service” from the list and call the service “DataService” (creative, huh?). Click “Add”.   Enable Access to the Data Service Open the DataService.svc.cs class. The class is well commented and instructs us on the next steps. public class DataService : DataService< /* TODO: put your data source class name here */ > { // This method is called only once to initialize service-wide policies. public static void InitializeService(DataServiceConfiguration config) { // TODO: set rules to indicate which entity sets and service operations are visible, updatable, etc. // Examples: // config.SetEntitySetAccessRule("MyEntityset", EntitySetRights.AllRead); // config.SetServiceOperationAccessRule("MyServiceOperation", ServiceOperationRights.All); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } } Replace the comment that starts with “/* TODO:” with “NorthwindEntities” (the entity container name of the Model we created earlier).  WCF Data Services is initially locked down by default, FTW! No data is exposed without you explicitly setting it. You have explicitly specify which Entity sets you wish to expose and what rights are allowed by using the SetEntitySetAccessRule. The SetServiceOperationAccessRule on the other hand sets rules for a specified operation. Let us define an access rule to expose the Products Entity we created earlier. We use the EnititySetRights.AllRead since we want to give read only access. Our modified code is shown below. public class DataService : DataService<NorthwindEntities> { public static void InitializeService(DataServiceConfiguration config) { config.SetEntitySetAccessRule("Products", EntitySetRights.AllRead); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } } We are done setting up our ODataFeed! Compile your project. Right click on DataService.svc and select “View in Browser” to see the OData feed. To view the feed in IE, you must make sure that "Feed Reading View" is turned off. You set this under Tools -› Internet Options -› Content tab.   If you navigate to “Products”, you should see the Products feed. Note also that URIs are case sensitive. ie. Products work but products doesn’t.   Filtering our data OData has a set of system query operations you can use to perform common operations against data exposed by the model. For example, to see only Products in CategoryID 2, we can use the following request: /DataService.svc/Products?$filter=CategoryID eq 2 At the time of this writing, supported operations are $orderby, $top, $skip, $filter, $expand, $format†, $select, $inlinecount. Pre-filtering our data using Query Interceptors The Product feed currently returns all Products. We want to change that so that it contains only Products that have not been discontinued. WCF introduces the concept of interceptors which allows us to inject custom validation/policy logic into the request/response pipeline of a WCF data service. We will use a QueryInterceptor to pre-filter the data so that it returns only Products that are not discontinued. To create a QueryInterceptor, write a method that returns an Expression<Func<T, bool>> and mark it with the QueryInterceptor attribute as shown below. [QueryInterceptor("Products")] public Expression<Func<Product, bool>> OnReadProducts() { return o => o.Discontinued == false; } Viewing the feed after compilation will only show products that have not been discontinued. We also confirm this by looking at the WHERE clause in the SQL generated by the entity framework. SELECT [Extent1].[ProductID] AS [ProductID], ... ... [Extent1].[Discontinued] AS [Discontinued] FROM [dbo].[Products] AS [Extent1] WHERE 0 = [Extent1].[Discontinued] Other examples of Query/Change interceptors can be seen here including an example to filter data based on the identity of the authenticated user. We are done pre-filtering our data. In the next part of this post, we will see how to shape our data. Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 2 Foot Notes * http://msdn.microsoft.com/en-us/data/aa937697.aspx † $format did not work for me. The way to get a Json response is to include the following in the  request header “Accept: application/json, text/javascript, */*” when making the request. This is easily done with most JavaScript libraries.

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  • Storage Virtualization Gets Serious

    Virtually Speaking: A torrent of products are being unleashed to meet the challenges of backing up virtual machines. From cloud storage to golden image management, virtualization technologies for storage are on the move.

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  • Survey of MySQL Storage Engines

    <b>Database Journal:</b> "MySQL has an interesting architecture that sets it apart from some other enterprise database systems. It allows you to plug in different modules to handle storage. What that means to end users is that it is quite flexible, offering an interesting array of different storage engines with different features, strengths, and tradeoffs."

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  • Big Data Matters with ODI12c

    - by Madhu Nair
    contributed by Mike Eisterer On October 17th, 2013, Oracle announced the release of Oracle Data Integrator 12c (ODI12c).  This release signifies improvements to Oracle’s Data Integration portfolio of solutions, particularly Big Data integration. Why Big Data = Big Business Organizations are gaining greater insights and actionability through increased storage, processing and analytical benefits offered by Big Data solutions.  New technologies and frameworks like HDFS, NoSQL, Hive and MapReduce support these benefits now. As further data is collected, analytical requirements increase and the complexity of managing transformations and aggregations of data compounds and organizations are in need for scalable Data Integration solutions. ODI12c provides enterprise solutions for the movement, translation and transformation of information and data heterogeneously and in Big Data Environments through: The ability for existing ODI and SQL developers to leverage new Big Data technologies. A metadata focused approach for cataloging, defining and reusing Big Data technologies, mappings and process executions. Integration between many heterogeneous environments and technologies such as HDFS and Hive. Generation of Hive Query Language. Working with Big Data using Knowledge Modules  ODI12c provides developers with the ability to define sources and targets and visually develop mappings to effect the movement and transformation of data.  As the mappings are created, ODI12c leverages a rich library of prebuilt integrations, known as Knowledge Modules (KMs).  These KMs are contextual to the technologies and platforms to be integrated.  Steps and actions needed to manage the data integration are pre-built and configured within the KMs.  The Oracle Data Integrator Application Adapter for Hadoop provides a series of KMs, specifically designed to integrate with Big Data Technologies.  The Big Data KMs include: Check Knowledge Module Reverse Engineer Knowledge Module Hive Transform Knowledge Module Hive Control Append Knowledge Module File to Hive (LOAD DATA) Knowledge Module File-Hive to Oracle (OLH-OSCH) Knowledge Module  Nothing to beat an Example: To demonstrate the use of the KMs which are part of the ODI Application Adapter for Hadoop, a mapping may be defined to move data between files and Hive targets.  The mapping is defined by dragging the source and target into the mapping, performing the attribute (column) mapping (see Figure 1) and then selecting the KM which will govern the process.  In this mapping example, movie data is being moved from an HDFS source into a Hive table.  Some of the attributes, such as “CUSTID to custid”, have been mapped over. Figure 1  Defining the Mapping Before the proper KM can be assigned to define the technology for the mapping, it needs to be added to the ODI project.  The Big Data KMs have been made available to the project through the KM import process.   Generally, this is done prior to defining the mapping. Figure 2  Importing the Big Data Knowledge Modules Following the import, the KMs are available in the Designer Navigator. v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Figure 3  The Project View in Designer, Showing Installed IKMs Once the KM is imported, it may be assigned to the mapping target.  This is done by selecting the Physical View of the mapping and examining the Properties of the Target.  In this case MOVIAPP_LOG_STAGE is the target of our mapping. Figure 4  Physical View of the Mapping and Assigning the Big Data Knowledge Module to the Target Alternative KMs may have been selected as well, providing flexibility and abstracting the logical mapping from the physical implementation.  Our mapping may be applied to other technologies as well. The mapping is now complete and is ready to run.  We will see more in a future blog about running a mapping to load Hive. To complete the quick ODI for Big Data Overview, let us take a closer look at what the IKM File to Hive is doing for us.  ODI provides differentiated capabilities by defining the process and steps which normally would have to be manually developed, tested and implemented into the KM.  As shown in figure 5, the KM is preparing the Hive session, managing the Hive tables, performing the initial load from HDFS and then performing the insert into Hive.  HDFS and Hive options are selected graphically, as shown in the properties in Figure 4. Figure 5  Process and Steps Managed by the KM What’s Next Big Data being the shape shifting business challenge it is is fast evolving into the deciding factor between market leaders and others. Now that an introduction to ODI and Big Data has been provided, look for additional blogs coming soon using the Knowledge Modules which make up the Oracle Data Integrator Application Adapter for Hadoop: Importing Big Data Metadata into ODI, Testing Data Stores and Loading Hive Targets Generating Transformations using Hive Query language Loading Oracle from Hadoop Sources For more information now, please visit the Oracle Data Integrator Application Adapter for Hadoop web site, http://www.oracle.com/us/products/middleware/data-integration/hadoop/overview/index.html Do not forget to tune in to the ODI12c Executive Launch webcast on the 12th to hear more about ODI12c and GG12c. Normal 0 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";}

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  • MySQL Exotic Storage Engines

    <b>Database Journal:</b> "MySQL has an interesting architecture that sets it apart from some other enterprise database systems. It allows you to plug in different modules to handle storage. What that means to end users is that it is quite flexible, offering an interesting array of different storage engines with different features, strengths, and tradeoffs."

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  • Virtual Machine Storage Provisioning and best practises

    If you're using Virtualization technology, then at some point you'll have run out of (or will run out of) virtual disk space, & had to provision extra storage; are you confident that you know how to do that? Sean Duffy makes sure you're doing it right, sharing his recommendations and tips in this step-by-step guide to Virtual Machine Storage provisioning for VMware. Follow this advice, and you'll be a Virtualization Veteran in no time.

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  • Right-size IT Budgets with Windows Server 2012 "Storage Spaces"

    - by KeithMayer
    What is the Largest Single Cost Category in Your IT Hardware Budget? If you're like most of the enterprise customer organizations that were surveyed when we were designing Windows Server 2012, your answer is probably the same as theirs: STORAGE! For the organizations we surveyed, we found that as much as 60% of their annual hardware budgets were allocated to expensive hardware SAN solutions due to ever-increasing storage requirements. Wouldn't it be nice to have some of that budget back

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  • Storage device manger regarding NTFS automount at boot time

    - by muneesh
    I am using storage device manager to auto-mount NTFS file system at boot time.But repeatedly, I am trying to uncheck the checkbox listed 'read only mode' in assistant option of storage device manager. I am not able to to auto-mount my NTFS partition in read/write mode. Please suggest a solution regarding this problem? Remember I am repeatedly trying to uncheck read only checkbox but not able to do that!

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  • Survey of MySQL Storage Engines

    MySQL has an interesting architecture that sets it apart from some other enterprise database systems. It allows you to plug in different modules to handle storage. What that means to end users is that it is quite flexible, offering an interesting array of different storage engines with different features, strengths, and tradeoffs.

    Read the article

  • Survey of MySQL Storage Engines

    MySQL has an interesting architecture that sets it apart from some other enterprise database systems. It allows you to plug in different modules to handle storage. What that means to end users is that it is quite flexible, offering an interesting array of different storage engines with different features, strengths, and tradeoffs.

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  • Stack data storage order

    - by Jamie Dixon
    When talking about a stack in either computing or "real" life we usually assume a "first on, last off" type of functionality. Because the idea of a stack is based around something in the physical world, does it matter how the data in the stack is stored? I notice in a lot of examples that the storage of the stack data is quite often done using an array and the newest item added to the stack is placed at the bottom of the array. (like adding a new plate to an existing stack of plates except putting it underneath the other plates rather than on top). As a paradigm, does it matter in what order the data is stored within the stack as long as the operation of the stack acts as expected?

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