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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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  • Big Data – Final Wrap and What Next – Day 21 of 21

    - by Pinal Dave
    In yesterday’s blog post we explored various resources related to learning Big Data and in this blog post we will wrap up this 21 day series on Big Data. I have been exploring various terms and technology related to Big Data this entire month. It was indeed fun to write about Big Data in 21 days but the subject of Big Data is much bigger and larger than someone can cover it in 21 days. My first goal was to write about the basics and I think we have got that one covered pretty well. During this 21 days I have received many questions and answers related to Big Data. I have covered a few of the questions in this series and a few more I will be covering in the next coming months. Now after understanding Big Data basics. I am personally going to do a list of the things next. I thought I will share the same with you as this will give you a good idea how to continue the journey of the Big Data. Build a schedule to read various Apache documentations Watch all Pluralsight Courses Explore HortonWorks Sandbox Start building presentation about Big Data – this is a great way to learn something new Present in User Groups Meetings on Big Data Topics Write more blog posts about Big Data I am going to continue learning about Big Data – I want you to continue learning Big Data. Please leave a comment how you are going to continue learning about Big Data. I will publish all the informative comments on this blog with due credit. I want to end this series with the infographic by UMUC. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Thoughts of Cloud Development/Google App Engine

    - by jiewmeng
    I use mainly PHP for web development, but recently, I started thinking about using Google App Engine. It doesn't use PHP which I am already familiar with, so there will be a steeper learning curve. Probably using Python/Django. But I think it maybe worthwhile. Some advantages I see: Focus on App/Development. No need to setup/maintain server ... no more server configs Scales automatically Pay for what you use. Free for low usage Reliable, it's Google after all Some concerns though: Does database with no joins pose a problem for those who used App Engine before? Do I have to upload to Google just to test? Will it be slow compared to testing locally? What are your thoughts and opinions? Why would you use or not use App Engine?

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  • HG: fork web app project to separate API code from app code

    - by cs_brandt
    I have a web app thats been in active development for about 8 months now and its becoming apparent that the project has a need to maintain a separation between app specific code and our OO Javascript API. What I would like to do is have another repository with the following general structure of the js API code. repo_name | +---build | +---build_tools | +---doc | +---src | +---js Of course this structure is different from the original web app directory structure. If I make changes to this new repository how could I pull in those changes to the web app repository without unintentionally removing files or modifying the directory structure of the web app repository?

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  • Partner Webcast - Focus on Oracle Data Profiling and Data Quality 11g

    - by lukasz.romaszewski(at)oracle.com
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-ansi-language:RO;} Partner Webcast Focus on Oracle Data Profiling and Data Quality 11g February 24th, 12am  CET   Oracle offers an integrated suite Data Quality software architected to discover and correct today's data quality problems and establish a platform prepared for tomorrow's yet unknown data challenges. Oracle Data Profiling provides data investigation, discovery, and profiling in support of quality, migration, integration, stewardship, and governance initiatives. It includes a broad range of features that expand upon basic profiling, including automated monitoring, business-rule validation, and trend analysis. Oracle Data Quality for Data Integrator provides cleansing, standardization, matching, address validation, location enrichment, and linking functions for global customer data and operational business data. It ensures that data adheres to established standards that are adaptable to fit each organization's specific needs.  Both single - and double - byte data are processed in local languages to provide a unique and centralized view of customers, products and services.   During this in-person briefing, Data Integration Solution Specialists will be providing a technical overview and a walkthrough.   Agenda ·         Oracle Data Integration Strategy overview ·         A focus on Oracle Data Profiling and Oracle Data Quality for Data Integrator: o   Oracle Data Profiling o   Oracle Data Quality for Data Integrator o   Live demoo   Q&A Delivery Format  This FREE online LIVE eSeminar will be delivered over the Web and Conference Call. Registrations   received less than 24hours  prior to start time may not receive confirmation to attend. To register , click here. For any questions please contact [email protected]

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  • Ubuntu App Submission won't allow the "free" bubble to be checked

    - by Compt
    I am at the final stages of the Ubuntu App Developer Showdown, and I'm right at the point where I am submitting my app. The problem I run in to however, is that even though buy is at $0.00, it will not allow me to click on the "free" button, and keep that configuration saved. So when I go to "preview your app", it shows it saying "USD $0.00 ---- Buy" instead of saying "Free ---- Install". So I was wondering if it makes any difference or not.

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  • What are the complications involved in this startup:Payments through authorization of fingerprints?

    - by jim859
    I want to make a mobile application where by people can send payments by authorization of finger prints. An email id will be registered and their finger print(unique for everyone) will be stored on our server.Person A and Person B are already registered and have installed the app.A and B deposit some money through our app from their credit card. When a person(Person A) want to send money to other people(person B), person B will ask person A to authorize his/her finger print on person B's mobile.The finger print will be retrieved from our servers and the payment will be made to person B. Person A will open the app (later or at that time) and confirm that yes he/she has authorized his/her finger print for the transaction.If person A has actually done the transaction,no problem.If person A has unknowingly or forcibly and opts that he/she has not authorized his/her finger print,money will be deducted from person B's account. What are the problems/vulnerabilities here,how can it be solved. Any other ways you can suggest to facilitate the transaction

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  • iPhone app: How to implement in-app purchased game levels

    - by Wonderflonium
    So, I understand that it's possible to set up in-app purchases for iPhone apps to purchase non-consumables like game levels. I understand the logic behind the purchase part, but what I don't understand is, how can I deliver the new game level. For example: I build an app that contains the first level and they purchase additional levels. Is it better to build all the other levels into the app and whenever they purchase the app, it unlocks it with a plist entry or something? That doesn't seem very update-able to me. Every time I come up with a new level, I'd have to update the app. So, what I don't understand then, is what is how do I package up a level and download it as a separate entity that can accessed by the game? Would the level just be some XML with images in a ZIP folder or something? How does the level get added to the game? What are best practices for this type of thing? I Googled and have found NOTHING about this. I'm a little bit confused by the concept and any help would be appreciated. I'm not looking for someone to write the game for me, I just need pointed in the right direction so I can develop it on my own.

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  • iPhone - packaging multiple app in a single app

    - by karim
    Hi, I would like to package multiple app in a single app. So donwloading one app and install that in an iPhone will install 3/4 apps. Something like java midlet suits having multiple Midlets in a single jar file. Is it possible by using multiple target or bundle, aggregate target etc.?

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  • Bundle module with app on Google App Engine

    - by Oscar Reyes
    This may be a basic question but how can I include a module with my app. I'm very new to python and what I want to do is to include this module simplejson with my app, but after downloading it I have no idea what to do next :( This is how the module looks like after unzip it. I don't know what files to move to my app.

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  • Big Data – Buzz Words: What is HDFS – Day 8 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned what is MapReduce. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – HDFS. What is HDFS ? HDFS stands for Hadoop Distributed File System and it is a primary storage system used by Hadoop. It provides high performance access to data across Hadoop clusters. It is usually deployed on low-cost commodity hardware. In commodity hardware deployment server failures are very common. Due to the same reason HDFS is built to have high fault tolerance. The data transfer rate between compute nodes in HDFS is very high, which leads to reduced risk of failure. HDFS creates smaller pieces of the big data and distributes it on different nodes. It also copies each smaller piece to multiple times on different nodes. Hence when any node with the data crashes the system is automatically able to use the data from a different node and continue the process. This is the key feature of the HDFS system. Architecture of HDFS The architecture of the HDFS is master/slave architecture. An HDFS cluster always consists of single NameNode. This single NameNode is a master server and it manages the file system as well regulates access to various files. In additional to NameNode there are multiple DataNodes. There is always one DataNode for each data server. In HDFS a big file is split into one or more blocks and those blocks are stored in a set of DataNodes. The primary task of the NameNode is to open, close or rename files and directory and regulate access to the file system, whereas the primary task of the DataNode is read and write to the file systems. DataNode is also responsible for the creation, deletion or replication of the data based on the instruction from NameNode. In reality, NameNode and DataNode are software designed to run on commodity machine build in Java language. Visual Representation of HDFS Architecture Let us understand how HDFS works with the help of the diagram. Client APP or HDFS Client connects to NameSpace as well as DataNode. Client App access to the DataNode is regulated by NameSpace Node. NameSpace Node allows Client App to connect to the DataNode based by allowing the connection to the DataNode directly. A big data file is divided into multiple data blocks (let us assume that those data chunks are A,B,C and D. Client App will later on write data blocks directly to the DataNode. Client App does not have to directly write to all the node. It just has to write to any one of the node and NameNode will decide on which other DataNode it will have to replicate the data. In our example Client App directly writes to DataNode 1 and detained 3. However, data chunks are automatically replicated to other nodes. All the information like in which DataNode which data block is placed is written back to NameNode. High Availability During Disaster Now as multiple DataNode have same data blocks in the case of any DataNode which faces the disaster, the entire process will continue as other DataNode will assume the role to serve the specific data block which was on the failed node. This system provides very high tolerance to disaster and provides high availability. If you notice there is only single NameNode in our architecture. If that node fails our entire Hadoop Application will stop performing as it is a single node where we store all the metadata. As this node is very critical, it is usually replicated on another clustered as well as on another data rack. Though, that replicated node is not operational in architecture, it has all the necessary data to perform the task of the NameNode in the case of the NameNode fails. The entire Hadoop architecture is built to function smoothly even there are node failures or hardware malfunction. It is built on the simple concept that data is so big it is impossible to have come up with a single piece of the hardware which can manage it properly. We need lots of commodity (cheap) hardware to manage our big data and hardware failure is part of the commodity servers. To reduce the impact of hardware failure Hadoop architecture is built to overcome the limitation of the non-functioning hardware. Tomorrow In tomorrow’s blog post we will discuss the importance of the relational database in Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Oracle Data Integration 12c: Perspectives of Industry Experts, Customers and Partners

    - by Irem Radzik
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 As you may have seen from our recent blog posts on Oracle Data Integrator 12c and Oracle GoldenGate 12c, we are very excited to share with you the great new features the 12c release brings to Oracle’s data integration solutions. And, fortunately we are not alone in this sentiment. Since the press announcement October 17th, which incorporates our customers' and experts' testimonials, we have seen positive comments in leading technology publications and social media as well. Here are some examples: In CIO and PCWorld you can find Joab Jackson’s article, Oracle Data Integrator 12c ready for real-time analysis, where wrote about the tight integration between Oracle Data Integrator and Oracle GoldenGate . He noted “Heeding the call from enterprise customers who clamor for more immediacy in their data-driven reports, Oracle has updated its data-integration software portfolio so that it can more rapidly deliver data to data warehouses and analysis applications.” Integration Developer News’ Vance McCarthy wrote the article Oracle Ships ‘Future Proofs’ Integration Tools for Traditional, Cloud, Big Data, Real-Time Projects and mentioned that “Oracle Data Integrator 12c and Oracle GoldenGate 12c sport a wide range of improvements to let devs more easily deliver data integration for cloud, analytics, big data and other new projects that leverage multiple datasets for business.“ InformationWeek’s Doug Henschen gave a great overview to several key features including the new flow-based UI in Oracle Data Integrator. Doug said “Oracle Data Integrator 12c introduces a complete makeover of the job-building experience, while real-time oriented GoldenGate 12c introduces performance gains “. In Database Trends and Applications’ article Oracle Strengthens Data Integration with Release of Oracle Data Integrator 12c and Oracle GoldenGate 12c highlighted the productivity aspect of the new solution with his remarks: “tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c enables developers to leverage Oracle GoldenGate’s low overhead, real-time change data capture completely within the Oracle Data Integrator Studio without additional training”. We are also thrilled about what our customers and partners have to say about our products and the new release. And we are equally excited to share those perspectives with you in our upcoming launch video webcast on November 12th. SolarWorld Industries America’s Senior Database Manager, Russ Toyama will join our executives in our studio in Redwood Shores to discuss GoldenGate’s core benefits and the new release, while Surren Partharb, CTO of Strategic Technology Services for BT, and Mark Rittman, CTO of Rittman Mead, will provide their comments via the interviews conducted in the UK. This interactive panel discussion in the video webcast will unveil the new release with the expertise of our development executives and the great insight from our customers and partners. In addition, our product experts will be available online to answer chat questions. This is really a great opportunity to learn how Oracle's data integration offering has changed the integration and replication technology space with the new release, and established itself as the new leader. If you have not registered for this free event yet, you can do so via this link. We will run the live event at 8am PT/4pm GMT, followed by a replay of the event with live chat for Q&A  at 10am PT/6pm GMT. The replay will be available on-demand for those who register but cannot attend either session on November 12th. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif"; mso-fareast-font-family:"Times New Roman";}

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  • Visual Studio App.config XML Transformation

    - by João Angelo
    Visual Studio 2010 introduced a much-anticipated feature, Web configuration transformations. This feature allows to configure a web application project to transform the web.config file during deployment based on the current build configuration (Debug, Release, etc). If you haven’t already tried it there is a nice step-by-step introduction post to XML transformations on the Visual Web Developer Team Blog and for a quick reference on the supported syntax you have this MSDN entry. Unfortunately there are some bad news, this new feature is specific to web application projects since it resides in the Web Publishing Pipeline (WPP) and therefore is not officially supported in other project types like such as a Windows applications. The keyword here is officially because Vishal Joshi has a nice blog post on how to extend it’s support to app.config transformations. However, the proposed workaround requires that the build action for the app.config file be changed to Content instead of the default None. Also from the comments to the said post it also seems that the workaround will not work for a ClickOnce deployment. Working around this I tried to remove the build action change requirement and at the same time add ClickOnce support. This effort resulted in a single MSBuild project file (AppConfig.Transformation.targets) available for download from GitHub. It integrates itself in the build process so in order to add app.config transformation support to an existing Windows Application Project you just need to import this targets file after all the other import directives that already exist in the *.csproj file. Before – Without App.config transformation support ... <Import Project="$(MSBuildToolsPath)\Microsoft.CSharp.targets" /> <Target Name="BeforeBuild"> </Target> <Target Name="AfterBuild"> </Target> </Project> After – With App.config transformation support ... <Import Project="$(MSBuildToolsPath)\Microsoft.CSharp.targets" /> <Import Project="C:\MyExtensions\AppConfig.Transformation.targets" /> <Target Name="BeforeBuild"> </Target> <Target Name="AfterBuild"> </Target> </Project> As a final disclaimer, the testing time was limited so any problem that you find let me know. The MSBuild project invokes the mage tool so the Framework SDK must be installed. Update: I finally had some spare time and was able to check the problem reported by Geoff Smith and believe the problem is solved. The Publish command inside Visual Studio triggers a build workflow different than through MSBuild command line and this was causing problems. I posted a new version in GitHub that should now support ClickOnce deployment with app.config tranformation from within Visual Studio and MSBuild command line. Also here is a link for the sample application used to test the new version using the Publish command with the install location set to be from a CD-ROM or DVD-ROM and selected that the application will not check for updates. Thanks to Geoff for spotting the problem.

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  • New Big Data Appliance Security Features

    - by mgubar
    The Oracle Big Data Appliance (BDA) is an engineered system for big data processing.  It greatly simplifies the deployment of an optimized Hadoop Cluster – whether that cluster is used for batch or real-time processing.  The vast majority of BDA customers are integrating the appliance with their Oracle Databases and they have certain expectations – especially around security.  Oracle Database customers have benefited from a rich set of security features:  encryption, redaction, data masking, database firewall, label based access control – and much, much more.  They want similar capabilities with their Hadoop cluster.    Unfortunately, Hadoop wasn’t developed with security in mind.  By default, a Hadoop cluster is insecure – the antithesis of an Oracle Database.  Some critical security features have been implemented – but even those capabilities are arduous to setup and configure.  Oracle believes that a key element of an optimized appliance is that its data should be secure.  Therefore, by default the BDA delivers the “AAA of security”: authentication, authorization and auditing. Security Starts at Authentication A successful security strategy is predicated on strong authentication – for both users and software services.  Consider the default configuration for a newly installed Oracle Database; it’s been a long time since you had a legitimate chance at accessing the database using the credentials “system/manager” or “scott/tiger”.  The default Oracle Database policy is to lock accounts thereby restricting access; administrators must consciously grant access to users. Default Authentication in Hadoop By default, a Hadoop cluster fails the authentication test. For example, it is easy for a malicious user to masquerade as any other user on the system.  Consider the following scenario that illustrates how a user can access any data on a Hadoop cluster by masquerading as a more privileged user.  In our scenario, the Hadoop cluster contains sensitive salary information in the file /user/hrdata/salaries.txt.  When logged in as the hr user, you can see the following files.  Notice, we’re using the Hadoop command line utilities for accessing the data: $ hadoop fs -ls /user/hrdataFound 1 items-rw-r--r--   1 oracle supergroup         70 2013-10-31 10:38 /user/hrdata/salaries.txt$ hadoop fs -cat /user/hrdata/salaries.txtTom Brady,11000000Tom Hanks,5000000Bob Smith,250000Oprah,300000000 User DrEvil has access to the cluster – and can see that there is an interesting folder called “hrdata”.  $ hadoop fs -ls /user Found 1 items drwx------   - hr supergroup          0 2013-10-31 10:38 /user/hrdata However, DrEvil cannot view the contents of the folder due to lack of access privileges: $ hadoop fs -ls /user/hrdata ls: Permission denied: user=drevil, access=READ_EXECUTE, inode="/user/hrdata":oracle:supergroup:drwx------ Accessing this data will not be a problem for DrEvil. He knows that the hr user owns the data by looking at the folder’s ACLs. To overcome this challenge, he will simply masquerade as the hr user. On his local machine, he adds the hr user, assigns that user a password, and then accesses the data on the Hadoop cluster: $ sudo useradd hr $ sudo passwd $ su hr $ hadoop fs -cat /user/hrdata/salaries.txt Tom Brady,11000000 Tom Hanks,5000000 Bob Smith,250000 Oprah,300000000 Hadoop has not authenticated the user; it trusts that the identity that has been presented is indeed the hr user. Therefore, sensitive data has been easily compromised. Clearly, the default security policy is inappropriate and dangerous to many organizations storing critical data in HDFS. Big Data Appliance Provides Secure Authentication The BDA provides secure authentication to the Hadoop cluster by default – preventing the type of masquerading described above. It accomplishes this thru Kerberos integration. Figure 1: Kerberos Integration The Key Distribution Center (KDC) is a server that has two components: an authentication server and a ticket granting service. The authentication server validates the identity of the user and service. Once authenticated, a client must request a ticket from the ticket granting service – allowing it to access the BDA’s NameNode, JobTracker, etc. At installation, you simply point the BDA to an external KDC or automatically install a highly available KDC on the BDA itself. Kerberos will then provide strong authentication for not just the end user – but also for important Hadoop services running on the appliance. You can now guarantee that users are who they claim to be – and rogue services (like fake data nodes) are not added to the system. It is common for organizations to want to leverage existing LDAP servers for common user and group management. Kerberos integrates with LDAP servers – allowing the principals and encryption keys to be stored in the common repository. This simplifies the deployment and administration of the secure environment. Authorize Access to Sensitive Data Kerberos-based authentication ensures secure access to the system and the establishment of a trusted identity – a prerequisite for any authorization scheme. Once this identity is established, you need to authorize access to the data. HDFS will authorize access to files using ACLs with the authorization specification applied using classic Linux-style commands like chmod and chown (e.g. hadoop fs -chown oracle:oracle /user/hrdata changes the ownership of the /user/hrdata folder to oracle). Authorization is applied at the user or group level – utilizing group membership found in the Linux environment (i.e. /etc/group) or in the LDAP server. For SQL-based data stores – like Hive and Impala – finer grained access control is required. Access to databases, tables, columns, etc. must be controlled. And, you want to leverage roles to facilitate administration. Apache Sentry is a new project that delivers fine grained access control; both Cloudera and Oracle are the project’s founding members. Sentry satisfies the following three authorization requirements: Secure Authorization:  the ability to control access to data and/or privileges on data for authenticated users. Fine-Grained Authorization:  the ability to give users access to a subset of the data (e.g. column) in a database Role-Based Authorization:  the ability to create/apply template-based privileges based on functional roles. With Sentry, “all”, “select” or “insert” privileges are granted to an object. The descendants of that object automatically inherit that privilege. A collection of privileges across many objects may be aggregated into a role – and users/groups are then assigned that role. This leads to simplified administration of security across the system. Figure 2: Object Hierarchy – granting a privilege on the database object will be inherited by its tables and views. Sentry is currently used by both Hive and Impala – but it is a framework that other data sources can leverage when offering fine-grained authorization. For example, one can expect Sentry to deliver authorization capabilities to Cloudera Search in the near future. Audit Hadoop Cluster Activity Auditing is a critical component to a secure system and is oftentimes required for SOX, PCI and other regulations. The BDA integrates with Oracle Audit Vault and Database Firewall – tracking different types of activity taking place on the cluster: Figure 3: Monitored Hadoop services. At the lowest level, every operation that accesses data in HDFS is captured. The HDFS audit log identifies the user who accessed the file, the time that file was accessed, the type of access (read, write, delete, list, etc.) and whether or not that file access was successful. The other auditing features include: MapReduce:  correlate the MapReduce job that accessed the file Oozie:  describes who ran what as part of a workflow Hive:  captures changes were made to the Hive metadata The audit data is captured in the Audit Vault Server – which integrates audit activity from a variety of sources, adding databases (Oracle, DB2, SQL Server) and operating systems to activity from the BDA. Figure 4: Consolidated audit data across the enterprise.  Once the data is in the Audit Vault server, you can leverage a rich set of prebuilt and custom reports to monitor all the activity in the enterprise. In addition, alerts may be defined to trigger violations of audit policies. Conclusion Security cannot be considered an afterthought in big data deployments. Across most organizations, Hadoop is managing sensitive data that must be protected; it is not simply crunching publicly available information used for search applications. The BDA provides a strong security foundation – ensuring users are only allowed to view authorized data and that data access is audited in a consolidated framework.

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  • How to present a stable data model in a public API that allows internal data structures to be changed without breaking the public view of the data?

    - by Max Palmer
    I am in the process of developing an application that allows users to write C# scripts. These scripts allow users to call selected methods and to access and manipulate data in a document. This works well, however, in the development version, scripts access the document's (internal) data structures directly. This means that if we were to change the internal data model/structure, there is a good chance that someone's script will no longer compile. We obviously want to prevent this breaking change from happening, but still want to allow the user to write sensible C# code (whilst not restricting how we develop our internal data model as a result). We therefore need to decouple our scripting API and its data structures from our internal methods and data structures. We've a few ideas as to how we might allow the user to access a what is effectively a stable public version of the document's internal data*, but I wanted to throw the question out there to someone who might have some real experience of this problem. NB our internal document's data structure is quite complex and it could be quite difficult to wrap. We know we want to expose as little as possible in our public API, especially as once it's out there, it's out there for good. Can anyone help? How do scripting languages / APIs decouple their public API and data structures from their internal data structures? Is there no real alternative to having to write a complex interaction layer? If we need to do this, what's a good approach or pattern for wrapping complex data structures that include nested objects, including collections? I've looked at the API facade pattern, which looks like it's trying to address these kinds of issues, but are there alternatives? *One idea is to build a data facade that is kept stable across versions of our application. The facade exposes a set of facade data objects that are used in the script code. These maintain backwards compatibility and wrap access to our internal document's data model.

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  • Google App Engine - Figure out the time the current request reached the app engine

    - by Spines
    Is there a way I can figure out the time the current request reached the app engine? For example a user might make a request to my app, but due to app engine latencies my code might not start handling the request until one second later, is there a way I can figure out that the user has already had to wait one second? The reason I want to know how to do this is because I want to do different things based on if the user already had to wait. If the user already had to wait a significant amount of time I will just serve them a page out of the cache, if the user hasn't had to wait yet then I will serve them a page which takes a while to render.

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  • in app purchases question

    - by bdt
    I am looking into the iPhone in app purchased models and need to implement a subscription. Ex content will be available for 24 hours. Now the most important thing is that it needs to be available on all the other devices, so bought on the iPhone, viewable on the iPad. I'm not sure how this works ? I need to store some information on the developer server but is this the transaction id and current date/time so when launching the app on the iPad, you will attempt to buy the content again. Apple will see that this user already bought that and hopefully returns the transaction ID. At that moment I can verify if the time limit it still valid or not. Can anyone confirm this method off working? If this is correct is there a 'renew'?

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  • Using App Engine to update a database in a app

    - by tyczj
    I have been reading about app engine but I still dont know what I can and cant do with it in a android application. Basically what I want to do is be able to create/manage a database in the cloud that the app can pull down and update the local database if needed. Creation and managing would be done outside of the app by me. I dont know much about all of this as I am just getting started with it but I already have an application made, I just want to add this feature to it. I have never written any sort of Web Service calls or anything either but I have used them to get data and such Can this be done? Any tutorials out there to help me out?

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  • Best practices for App Idea ownership and shares

    - by JOG
    I am developing apps on my sparetime. I am the sole developer, and two non-programmer friends of mine provide vision, content, algorithms and ideas. We always agree happily on all the features, todos and prioritizations. But naturally, coding it is the biggest part. When selling, we agree on splitting profit equally, that is 33% each. But version 1.0 naturally does not sell much. And I go on to try to make the app more viral. This includes tons of stuff where the others are of little help. Examples: Adding support for sharing, facebook connect, gameifying, letting users add content, home page, support, maintenance, server services to make it easier for to update content. The list is long. Suddenly I will be doing 100% of a lot of work but only "own" a third of the income. My friends may either "fade out" of the project after 1.0, or they continue to contribute, but with less value and I would rather exchange them for more programmers or graphic designers. The effort they made to version 1.0 is worth a lot to the app and I realize I would have never done it without them. But I am doing all the work in the end. It is hard to negotiate about splitting 90, 5, 5 instead of 33% each, because the idea is still theirs. How to solve this? What are the best practices to regard the ownership of the app? What kind of agreements could I make that make it beneficial and motivational for me to continue developing the app?

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  • Authenticate native mobile app using a REST API

    - by Supercell
    I'm starting a new project soon, which is targeting mobile application for all major mobile platforms (iOS, Android, Windows). It will be a client-server architecture. The app is both informational and transactional. For the transactional part, they're required to have an account and log in before a transaction can be made. I'm new to mobile development, so I don't know how the authentication part is done on these platforms. The clients will communicate with the server through a REST API. Will be using HTTPS ofcourse. I haven't yet decided if I want the user to log in when they open the app, or only when they perform a transaction. I got the following questions: 1) Like the Facebook application, you only enter your credentials when you open the application for the first time. After that, you're automatically signed in every time you open the app. How does one accomplish this? Just simply by encrypting and storing the credentials on the device and sending them every time the app starts? 2) Do I need to authenticate the user for each (transactional) request made to the REST API or use a token based approach? Please feel free to suggest other ways for authentication. Thanks!

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  • Why Cornell University Chose Oracle Data Masking

    - by Troy Kitch
    One of the eight Ivy League schools, Cornell University found itself in the unfortunate position of having to inform over 45,000 University community members that their personal information had been breached when a laptop was stolen. To ensure this wouldn’t happen again, Cornell took steps to ensure that data used for non-production purposes is de-identified with Oracle Data Masking. A recent podcast highlights why organizations like Cornell are choosing Oracle Data Masking to irreversibly de-identify production data for use in non-production environments. Organizations often copy production data, that contains sensitive information, into non-production environments so they can test applications and systems using “real world” information. Data in non-production has increasingly become a target of cyber criminals and can be lost or stolen due to weak security controls and unmonitored access. Similar to production environments, data breaches in non-production environments can cost millions of dollars to remediate and cause irreparable harm to reputation and brand. Cornell’s applications and databases help carry out the administrative and academic mission of the university. They are running Oracle PeopleSoft Campus Solutions that include highly sensitive faculty, student, alumni, and prospective student data. This data is supported and accessed by a diverse set of developers and functional staff distributed across the university. Several years ago, Cornell experienced a data breach when an employee’s laptop was stolen.  Centrally stored backup information indicated there was sensitive data on the laptop. With no way of knowing what the criminal intended, the university had to spend significant resources reviewing data, setting up service centers to handle constituent concerns, and provide free credit checks and identity theft protection services—all of which cost money and took time away from other projects. To avoid this issue in the future Cornell came up with several options; one of which was to sanitize the testing and training environments. “The project management team was brought in and they developed a project plan and implementation schedule; part of which was to evaluate competing products in the market-space and figure out which one would work best for us.  In the end we chose Oracle’s solution based on its architecture and its functionality.” – Tony Damiani, Database Administration and Business Intelligence, Cornell University The key goals of the project were to mask the elements that were identifiable as sensitive in a consistent and efficient manner, but still support all the previous activities in the non-production environments. Tony concludes,  “What we saw was a very minimal impact on performance. The masking process added an additional three hours to our refresh window, but it was well worth that time to secure the environment and remove the sensitive data. I think some other key points you can keep in mind here is that there was zero impact on the production environment. Oracle Data Masking works in non-production environments only. Additionally, the risk of exposure has been significantly reduced and the impact to business was minimal.” With Oracle Data Masking organizations like Cornell can: Make application data securely available in non-production environments Prevent application developers and testers from seeing production data Use an extensible template library and policies for data masking automation Gain the benefits of referential integrity so that applications continue to work Listen to the podcast to hear the complete interview.  Learn more about Oracle Data Masking by registering to watch this SANS Institute Webcast and view this short demo.

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  • Removing Barriers to Create Effective Data Models

    After years of creating and maintaining data models, I have started to notice common barriers that decrease the accuracy and usefulness of models. In my opinion, the main causes of these barriers are the lack of knowledge and communication from within a company. The lack of knowledge in regards to data models or data modeling can take many forms. Company Culture Knowledge Whether documented or undocumented, existing business rules of a company can affect how data is modeled. For example, if a company only allows 1 assigned person per customer to be able to manipulate a customer’s record then then a data model that includes an associated table that joins customers and employee’s would be unneeded because that would allow for the possibility of multiple employees to handle a customer because of the potential for a many to many relationship between Customers and Employees. Technical Knowledge Depending on the data modeler’s proficiency in modeling data they can inadvertently cause issues and/or complications with a design without even noticing. It is important that companies share data modeling responsibilities so that the models are developed from multiple perspectives of a system, company and the original problem.  In addition, the tools that a company selects to create data models can also affect the accuracy of the model if designer are not familiar with the tools or the tools are too complex to use for the designer. Existing System Knowledge In order for a data modeler to model data for an existing system so that new changes can be applied to a system then they need to at least know the basic concepts of a system so that they can work within it. This will promote reusability of data and prevent the chance of duplicating data. Project Knowledge This should be pretty obvious, but it is very hard to create an accurate data model without knowing what data needs to be modeled. I have always found it strange that I have been asked to start modeling data prior to a client formalizing any requirements. Usually when this happens I have to make several iterations to a model, and the client still does not know exactly what they want.  In addition additional issues can arise when certain stakeholders of a project are not consulted prior to the design or after the project is over because it can cause miss understandings and confusion by the end user as well as possibly not solving the original problem for which a project is intended to solve. One common thread between each type of knowledge is that they can all be avoided through the use of good communication. For example, if a modeler is new to a company then they should ask older employees about any business specific rules that may be documented or undocumented that must be applied to projects in general. Furthermore, if a modeler is not really familiar with a specific data modeling software then they need to speak up and ask for help form other employees or their manager. This will not only help the modeler in the project, but also help them in future projects that they do for the company. Additionally, if a project is not clearly defined prior to a data modeler being assigned the modeling project then it is their responsibility to communicate with the other stakeholders to clarify any part of a project that is unclear so that the data model that is created is accurately aligned with a project.

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  • Google App. Engine for RoR and Python apps

    - by RPK
    I fairly understand that this Q+A site is programmers destination and questions on hosting are not permitted here, but anyone who has heard of Google's App. Engine is well aware that this question is suited for this site only. Google App. Engine supports either Java or Python interpreter. I want to know what type of applications can be hosted on this engine? If my Python or RoR application needs a database behind, will this engine support it? For RoR applications, which interpreter to choose? What are the advantages of Google App.Engine over a local IDE?

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