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• Big Data Appliance X4-2 Release Announcement

  - by Jean-Pierre Dijcks

  Today we are announcing the release of the 3rd generation Big Data Appliance. Read the Press Release here. Software Focus The focus for this 3rd generation of Big Data Appliance is: Comprehensive and Open - Big Data Appliance now includes all Cloudera Software, including Back-up and Disaster Recovery (BDR), Search, Impala, Navigator as well as the previously included components (like CDH, HBase and Cloudera Manager) and Oracle NoSQL Database (CE or EE). Lower TCO then DIY Hadoop Systems Simplified Operations while providing an open platform for the organization Comprehensive security including the new Audit Vault and Database Firewall software, Apache Sentry and Kerberos configured out-of-the-box Hardware Update A good place to start is to quickly review the hardware differences (no price changes!). On a per node basis the following is a comparison between old and new (X3-2) hardware: Big Data Appliance X3-2 Big Data Appliance X4-2 CPU 2 x 8-Core Intel® Xeon® E5-2660 (2.2 GHz) 2 x 8-Core Intel® Xeon® E5-2650 V2 (2.6 GHz) Memory 64GB 64GB Disk 12 x 3TB High Capacity SAS 12 x 4TB High Capacity SAS InfiniBand 40Gb/sec 40Gb/sec Ethernet 10Gb/sec 10Gb/sec For all the details on the environmentals and other useful information, review the data sheet for Big Data Appliance X4-2. The larger disks give BDA X4-2 33% more capacity over the previous generation while adding faster CPUs. Memory for BDA is expandable to 512 GB per node and can be done on a per-node basis, for example for NameNodes or for HBase region servers, or for NoSQL Database nodes. Software Details More details in terms of software and the current versions (note BDA follows a three monthly update cycle for Cloudera and other software): Big Data Appliance 2.2 Software Stack Big Data Appliance 2.3 Software Stack Linux Oracle Linux 5.8 with UEK 1 Oracle Linux 6.4 with UEK 2 JDK JDK 6 JDK 7 Cloudera CDH CDH 4.3 CDH 4.4 Cloudera Manager CM 4.6 CM 4.7 And like we said at the beginning it is important to understand that all other Cloudera components are now included in the price of Oracle Big Data Appliance. They are fully supported by Oracle and available for all BDA customers. For more information: Big Data Appliance Data Sheet Big Data Connectors Data Sheet Oracle NoSQL Database Data Sheet (CE | EE) Oracle Advanced Analytics Data Sheet

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• Review: Data Modeling 101

  I just recently read “Data Modeling 101”by Scott W. Ambler where he gave an overview of fundamental data modeling skills. I think this article was excellent for anyone who was just starting to learn or refresh their skills in regards to the modeling of data.  Scott defines data modeling as the act of exploring data oriented structures.  He goes on to explain about how data models are actually used by defining three different types of models. Types of Data Models Conceptual Data Model  Logical Data Model (LDMs) Physical Data Model(PDMs) He further expands on modeling by exploring common data modeling notations because there are no industry standards for the practice of data modeling. Scott then defines how to actually model data by expanding on entities, attributes, identities, and relationships which are the basic building blocks of data models. In addition he discusses the value of normalization for redundancy and demoralization for performance. Finally, he discuss ways in which Developers and DBAs can become better data modelers through the use of practice, and seeking guidance from more experienced data modelers.

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• HTML5 data-* (custom data attribute)

  - by Renso

  Goal: Store custom data with the data attribute on any DOM element and retrieve it. Previously under HTML4 we used to use classes to store custom data, something to the affect of <input class="account void limit-5000 over-4999" /> and then have to parse the data out of the class In a book published by Peter-Paul Koch in 2007, ppk on JavaScript, he explains why and how to use custom attributes to make data more accessible to JavaScript, using name-value pairs. Accessing a custom attribute account-limit=5000 is much easier and more intuitive than trying to parse it out of a class, Plus, what if the class name for example "color-5" has a representative class definition in a CSS stylesheet that hides it away or worse some JavaScript plugin that automatically adds 5000 to it, or something crazy like that, just because it is a valid class name. As you can see there are quite a few reasons why using classes is a bad design and why it was important to define custom data attributes in HTML5. Syntax: You define the data attribute by simply prefixing any data item you want to store with any HTML element with "data-". For example to store our customers account data with a hidden input element: <input type="hidden" data-account="void" data-limit=5000 data-over=4999  /> How to access the data: account  -     element.dataset.account limit    -     element.dataset.limit You can also access it by using the more traditional get/setAttribute method or if using jQuery $('#element').attr('data-account','void') Browser support: All except for IE. There is an IE hack around this at http://gist.github.com/362081. Special Note: Be AWARE, do not use upper-case when defining your data elements as it is all converted to lower-case when reading it, so: data-myAccount="A1234" will not be found when you read it with: element.dataset.myAccount Use only lowercase when reading so this will work: element.dataset.myaccount

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• Master Data Management – A Foundation for Big Data Analysis

  - by Manouj Tahiliani

  While Master Data Management has crossed the proverbial chasm and is on its way to becoming mainstream, businesses are being hammered by a new megatrend called Big Data. Big Data is characterized by massive volumes, its high frequency, the variety of less structured data sources such as email, sensors, smart meters, social networks, and Weblogs, and the need to analyze vast amounts of data to determine value to improve upon management decisions. Businesses that have embraced MDM to get a single, enriched and unified view of Master data by resolving semantic discrepancies and augmenting the explicit master data information from within the enterprise with implicit data from outside the enterprise like social profiles will have a leg up in embracing Big Data solutions. This is especially true for large and medium-sized businesses in industries like Retail, Communications, Financial Services, etc that would find it very challenging to get comprehensive analytical coverage and derive long-term success without resolving the limitations of the heterogeneous topology that leads to disparate, fragmented and incomplete master data. For analytical success from Big Data or in other words ROI from Big Data Investments, businesses need to acquire, organize and analyze the deluge of data to make better decisions. There will need to be a coexistence of structured and unstructured data and to maintain a tight link between the two to extract maximum insights. MDM is the catalyst that helps maintain that tight linkage by providing an understanding about the identity, characteristics of Persons, Companies, Products, Suppliers, etc. associated with the Big Data and thereby help accelerate ROI. In my next post I will discuss about patterns for co-existing Big Data Solutions and MDM. Feel free to provide comments and thoughts on above as well as Integration or Architectural patterns.

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• How to Assure an Effective Data Model

  As a general rule in my opinion the effectiveness of a data model can be directly related to the accuracy and complexity of a project’s requirements. For example there is no need to work on very detailed data models when the details surrounding a specific data model have not been defined or even clarified. Developing data models when the clarity of project requirements is limited tends to introduce designed issues because the proper details to create an effective data model are not even known. One way to avoid this issue is to create data models that correspond to the complexity of the existing project requirements so that when requirements are updated then new data models can be created based any new discoveries regarding requirements on a fine grain level.  This allows for data models to be composed of general entities to be created initially when a project’s requirements are very vague and then the entities are refined as new and more substantial requirements are defined or redefined. This promotes communication amongst all stakeholders within a project as they go through the process of defining and finalizing project requirements.In addition, here are some general tips that can be applied to projects in regards to data modeling.Initially model all data generally and slowly reactor the data model as new requirements and business constraints are applied to a project.Ensure that data modelers have the proper tools and training they need to design a data model accurately.Create a common location for all project documents so that everyone will be able to review a project’s data models along with any other project documentation.All data models should follow a clear naming schema that tells readers the intended purpose for the data and how it is going to be applied within a project.

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• Doubts About Core Data NSManagedObject Deep Copy

  - by Jigzat

  Hello everyone, I have a situation where I must copy one NSManagedObject from the main context into an editing context. It sounds unnecessary to most people as I have seen in similar situations described in Stackoverflow but I looks like I need it. In my app there are many views in a tab bar and every view handles different information that is related to the other views. I think I need multiple MOCs since the user may jump from tab to tab and leave unsaved changes in some tab but maybe it saves data in some other tab/view so if that happens the changes in the rest of the views are saved without user consent and in the worst case scenario makes the app crash. For adding new information I got away by using an adding MOC and then merging changes in both MOCs but for editing is not that easy. I saw a similar situation here in Stackoverflow but the app crashes since my data model doesn't seem to use NSMutableSet for the relationships (I don't think I have a many-to-many relationship, just one-to-many) I think it can be modified so I can retrieve the relationships as if they were attributes for (NSString *attr in relationships) { [cloned setValue:[source valueForKey:attr] forKey:attr]; } but I don't know how to merge the changes of the cloned and original objects. I think I could just delete the object from the main context, then merge both contexts and save changes in the main context but I don't know if is the right way to do it. I'm also concerned about database integrity since I'm not sure that the inverse relationships will keep the same reference to the cloned object as if it were the original one. Can some one please enlighten me about this?

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• Core data relationship memory leak

  - by cfihelp

  I have a strange (to me) memory leak when accessing an entity in a relationship. Series and Tiles have an inverse relationship to each other. // set up the fetch request NSFetchRequest *fetchRequest = [[NSFetchRequest alloc] init]; NSEntityDescription *entity = [NSEntityDescription entityForName:@"Series" inManagedObjectContext:managedObjectContext]; [fetchRequest setEntity:entity]; // grab all of the series in the core data store NSError *error = nil; availableSeries = [[NSArray alloc] initWithArray:[managedObjectContext executeFetchRequest:fetchRequest error:&error]]; [fetchRequest release]; // grab one of the series Series *currentSeries = [availableSeries objectAtIndex:1]; // load all of the tiles attached to the series through the relationship NSArray *myTiles = [currentSeries.tile allObjects]; // 16 byte leak here! Instruments reports back that the final line has a 16 byte leak cause by NSPlaceHolderString. Stack trace: 2 UIKit UIApplicationMain 3 UIKit -[UIApplication _run] 4 CoreFoundation CFRunLoopRunInMode 5 CoreFoundation CFRunLoopRunSpecific 6 GraphicsServices PurpleEventCallback 7 UIKit _UIApplicationHandleEvent 8 UIKit -[UIApplication sendEvent:] 9 UIKit -[UIApplication handleEvent:withNewEvent:] 10 UIKit -[UIApplication _runWithURL:sourceBundleID:] 11 UIKit -[UIApplication _performInitializationWithURL:sourceBundleID:] 12 Memory -[AppDelegate_Phone application:didFinishLaunchingWithOptions:] /Users/cfish/svnrepo/Memory/src/Memory/iPhone/AppDelegate_Phone.m:49 13 UIKit -[UIViewController view] 14 Memory -[HomeScreenController_Phone viewDidLoad] /Users/cfish/svnrepo/Memory/src/Memory/iPhone/HomeScreenController_Phone.m:58 15 CoreData -[_NSFaultingMutableSet allObjects] 16 CoreData -[_NSFaultingMutableSet willRead] 17 CoreData -[NSFaultHandler retainedFulfillAggregateFaultForObject:andRelationship:withContext:] 18 CoreData -[NSSQLCore retainedRelationshipDataWithSourceID:forRelationship:withContext:] 19 CoreData -[NSSQLCore newFetchedPKsForSourceID:andRelationship:] 20 CoreData -[NSSQLCore rawSQLTextForToManyFaultStatement:stripBindVariables:swapEKPK:] 21 Foundation +[NSString stringWithFormat:] 22 Foundation -[NSPlaceholderString initWithFormat:locale:arguments:] 23 CoreFoundation _CFStringCreateWithFormatAndArgumentsAux 24 CoreFoundation _CFStringAppendFormatAndArgumentsAux 25 Foundation _NSDescriptionWithLocaleFunc 26 CoreFoundation -[NSObject respondsToSelector:] 27 libobjc.A.dylib class_respondsToSelector 28 libobjc.A.dylib lookUpMethod 29 libobjc.A.dylib _cache_addForwardEntry 30 libobjc.A.dylib _malloc_internal I think I'm missing something obvious but I can't quite figure out what. Thanks for your help! Update: I've copied the offending chunk of code to the first part of applicationDidFinishLaunching and it still leaks. Could there be something wrong with my model?

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• Implementation of "Automatic Lightweight Migration" for Core Data (iPhone)

  - by RickiG

  Hi I would like to make my app able to do an automatic lightweight migration when I add new attributes to my core data model. In the guide from Apple this is the only info on the subject I could find: Automatic Lightweight Migration To request automatic lightweight migration, you set appropriate flags in the options dictionary you pass in addPersistentStoreWithType:configuration:URL:options:error:. You need to set values corresponding to both the NSMigratePersistentStoresAutomaticallyOption and the NSInferMappingModelAutomaticallyOption keys to YES: NSError *error; NSURL *storeURL = <#The URL of a persistent store#>; NSPersistentStoreCoordinator *psc = <#The coordinator#>; NSDictionary *options = [NSDictionary dictionaryWithObjectsAndKeys: [NSNumber numberWithBool:YES], NSMigratePersistentStoresAutomaticallyOption, [NSNumber numberWithBool:YES], NSInferMappingModelAutomaticallyOption, nil]; if (![psc addPersistentStoreWithType:<#Store type#> configuration:<#Configuration or nil#> URL:storeURL options:options error:&error]) { // Handle the error. } My NSPersistentStoreCoordinator is initialized in this way: - (NSPersistentStoreCoordinator *)persistentStoreCoordinator { if (persistentStoreCoordinator != nil) { return persistentStoreCoordinator; } NSURL *storeUrl = [NSURL fileURLWithPath: [[self applicationDocumentsDirectory] stringByAppendingPathComponent: @"FC.sqlite"]]; NSError *error = nil; persistentStoreCoordinator = [[NSPersistentStoreCoordinator alloc] initWithManagedObjectModel:[self managedObjectModel]]; if (![persistentStoreCoordinator addPersistentStoreWithType:NSSQLiteStoreType configuration:nil URL:storeUrl options:nil error:&error]) { NSLog(@"Unresolved error %@, %@", error, [error userInfo]); abort(); } return persistentStoreCoordinator; } I am having trouble seeing where and how I should add the Apple code to get the Automatic Lightweight Migration working?

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• SQL SERVER – Why Do We Need Data Quality Services – Importance and Significance of Data Quality Services (DQS)

  - by pinaldave

  Databases are awesome.  I’m sure my readers know my opinion about this – I have made SQL Server my life’s work after all!  I love technology and all things computer-related.  Of course, even with my love for technology, I have to admit that it has its limits.  For example, it takes a human brain to notice that data has been input incorrectly.  Computer “brains” might be faster than humans, but human brains are still better at pattern recognition.  For example, a human brain will notice that “300” is a ridiculous age for a human to be, but to a computer it is just a number.  A human will also notice similarities between “P. Dave” and “Pinal Dave,” but this would stump most computers. In a database, these sorts of anomalies are incredibly important.  Databases are often used by multiple people who rely on this data to be true and accurate, so data quality is key.  That is why the improved SQL Server features Master Data Management talks about Data Quality Services.  This service has the ability to recognize and flag anomalies like out of range numbers and similarities between data.  This allows a human brain with its pattern recognition abilities to double-check and ensure that P. Dave is the same as Pinal Dave. A nice feature of Data Quality Services is that once you set the rules for the program to follow, it will not only keep your data organized in the future, but go to the past and “fix up” any data that has already been entered.  It also allows you do combine data from multiple places and it will apply these rules across the board, so that you don’t have any weird issues that crop up when trying to fit a round peg into a square hole. There are two parts of Data Quality Services that help you accomplish all these neat things.  The first part is DQL Server, which you can think of as the hardware component of the system.  It is installed on the side of (it needs to install separately after SQL Server is installed) SQL Server and runs quietly in the background, performing all its cleanup services. DQS Client is the user interface that you can interact with to set the rules and check over your data.  There are three main aspects of Client: knowledge base management, data quality projects and administration.  Knowledge base management is the part of the system that allows you to set the rules, or program the “knowledge base,” so that your database is clean and consistent. Data Quality projects are what run in the background and clean up the data that is already present.  The administration allows you to check out what DQS Client is doing, change rules, and generally oversee the entire process.  The whole process is user-friendly and a pleasure to use.  I highly recommend implementing Data Quality Services in your database. Here are few of my blog posts which are related to Data Quality Services and I encourage you to try this out. SQL SERVER – Installing Data Quality Services (DQS) on SQL Server 2012 SQL SERVER – Step by Step Guide to Beginning Data Quality Services in SQL Server 2012 – Introduction to DQS SQL SERVER – DQS Error – Cannot connect to server – A .NET Framework error occurred during execution of user-defined routine or aggregate “SetDataQualitySessions” – SetDataQualitySessionPhaseTwo SQL SERVER – Configuring Interactive Cleansing Suggestion Min Score for Suggestions in Data Quality Services (DQS) – Sensitivity of Suggestion SQL SERVER – Unable to DELETE Project in Data Quality Projects (DQS) Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Data Quality Services, DQS

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• Welcome Oracle Data Integration 12c: Simplified, Future-Ready Solutions with Extreme Performance

  - by Irem Radzik

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 The big day for the Oracle Data Integration team has finally arrived! It is my honor to introduce you to Oracle Data Integration 12c. Today we announced the general availability of 12c release for Oracle’s key data integration products: Oracle Data Integrator 12c and Oracle GoldenGate 12c. The new release delivers extreme performance, increase IT productivity, and simplify deployment, while helping IT organizations to keep pace with new data-oriented technology trends including cloud computing, big data analytics, real-time business intelligence. With the 12c release Oracle becomes the new leader in the data integration and replication technologies as no other vendor offers such a complete set of data integration capabilities for pervasive, continuous access to trusted data across Oracle platforms as well as third-party systems and applications. Oracle Data Integration 12c release addresses data-driven organizations’ critical and evolving data integration requirements under 3 key themes: Future-Ready Solutions Extreme Performance Fast Time-to-Value       There are many new features that support these key differentiators for Oracle Data Integrator 12c and for Oracle GoldenGate 12c. In this first 12c blog post, I will highlight only a few:·Future-Ready Solutions to Support Current and Emerging Initiatives: Oracle Data Integration offer robust and reliable solutions for key technology trends including cloud computing, big data analytics, real-time business intelligence and continuous data availability. Via the tight integration with Oracle’s database, middleware, and application offerings Oracle Data Integration will continue to support the new features and capabilities right away as these products evolve and provide advance features. E    Extreme Performance: Both GoldenGate and Data Integrator are known for their high performance. The new release widens the gap even further against competition. Oracle GoldenGate 12c’s Integrated Delivery feature enables higher throughput via a special application programming interface into Oracle Database. As mentioned in the press release, customers already report up to 5X higher performance compared to earlier versions of GoldenGate. Oracle Data Integrator 12c introduces parallelism that significantly increases its performance as well. Fast Time-to-Value via Higher IT Productivity and Simplified Solutions:  Oracle Data Integrator 12c’s new flow-based declarative UI brings superior developer productivity, ease of use, and ultimately fast time to market for end users.  It also gives the ability to seamlessly reuse mapping logic speeds development.Oracle GoldenGate 12c ‘s Integrated Delivery feature automatically optimally tunes the process, saving time while improving performance. This is just a quick glimpse into Oracle Data Integrator 12c and Oracle GoldenGate 12c. On November 12th we will reveal much more about the new release in our video webcast "Introducing 12c for Oracle Data Integration". Our customer and partner speakers, including SolarWorld, BT, Rittman Mead will join us in launching the new release. Please join us at this free event to learn more from our executives about the 12c release, hear our customers’ perspectives on the new features, and ask your questions to our experts in the live Q&A. Also, please continue to follow our blogs, tweets, and Facebook updates as we unveil more about the new features of the latest release. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

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• Best Practices - Core allocation

  - by jsavit

  This post is one of a series of "best practices" notes for Oracle VM Server for SPARC (also called Logical Domains) Introduction SPARC T-series servers currently have up to 4 CPU sockets, each of which has up to 8 or (on SPARC T3) 16 CPU cores, while each CPU core has 8 threads, for a maximum of 512 dispatchable CPUs. The defining feature of Oracle VM Server for SPARC is that each domain is assigned CPU threads or cores for its exclusive use. This avoids the overhead of software-based time-slicing and emulation (or binary rewriting) of system state-changing privileged instructions used in traditional hypervisors. To create a domain, administrators specify either the number of CPU threads or cores that the domain will own, as well as its memory and I/O resources. When CPU resources are assigned at the individual thread level, the logical domains constraint manager attempts to assign threads from the same cores to a domain, and avoid "split core" situations where the same CPU core is used by multiple domains. Sometimes this is unavoidable, especially when domains are allocated and deallocated CPUs in small increments. Why split cores can matter Split core allocations can silenty reduce performance because multiple domains with different address spaces and memory contents are sharing the core's Level 1 cache (L1$). This is called false cache sharing since even identical memory addresses from different domains must point to different locations in RAM. The effect of this is increased contention for the cache, and higher memory latency for each domain using that core. The degree of performance impact can be widely variable. For applications with very small memory working sets, and with I/O bound or low-CPU utilization workloads, it may not matter at all: all machines wait for work at the same speed. If the domains have substantial workloads, or are critical to performance then this can have an important impact: This blog entry was inspired by a customer issue in which one CPU core was split among 3 domains, one of which was the control and service domain. The reported problem was increased I/O latency in guest domains, but the root cause might be higher latency servicing the I/O requests due to the control domain being slowed down. What to do about it Split core situations are easily avoided. In most cases the logical domain constraint manager will avoid it without any administrative action, but it can be entirely prevented by doing one of the several actions: Assign virtual CPUs in multiples of 8 - the number of threads per core. For example: ldm set-vcpu 8 mydomain or ldm add-vcpu 24 mydomain. Each domain will then be allocated on a core boundary. Use the whole core constraint when assigning CPU resources. This allocates CPUs in increments of entire cores instead of virtual CPU threads. The equivalent of the above commands would be ldm set-core 1 mydomain or ldm add-core 3 mydomain. Older syntax does the same thing by adding the -c flag to the add-vcpu, rm-vcpu and set-vcpu commands, but the new syntax is recommended. When whole core allocation is used an attempt to add cores to a domain fails if there aren't enough completely empty cores to satisfy the request. See https://blogs.oracle.com/sharakan/entry/oracle_vm_server_for_sparc4 for an excellent article on this topic by Eric Sharakan. Don't obsess: - if the workloads have minimal CPU requirements and don't need anywhere near a full CPU core, then don't worry about it. If you have low utilization workloads being consolidated from older machines onto a current T-series, then there's no need to worry about this or to assign an entire core to domains that will never use that much capacity. In any case, make sure the most important domains have their own CPU cores, in particular the control domain and any I/O or service domain, and of course any important guests. Summary Split core CPU allocation to domains can potentially have an impact on performance, but the logical domains manager tends to prevent this situation, and it can be completely and simply avoided by allocating virtual CPUs on core boundaries.

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• Best way to store date/time into core data

  - by Dave

  Hi, For each course I am storing the day of the week the class the user has...and the start and end time and room no. What would be the best approach in terms of data type, Like for storing time?? so that when I pull it out I can display it e.g 1:00 PM. Thanks!

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• Using Solaris pkg to list all setuid or setgid programs

  - by darrenm

  $ pkg contents -a mode=4??? -a mode=2??? -t file -o pkg.name,path,mode We can also add a package name on the end to restrict it to just that single package eg: $ pkg contents -a mode=4??? -a mode=2??? -t file -o pkg.name,path,mode core-os PKG.NAME PATH MODE system/core-os usr/bin/amd64/newtask 4555 system/core-os usr/bin/amd64/uptime 4555 system/core-os usr/bin/at 4755 system/core-os usr/bin/atq 4755 system/core-os usr/bin/atrm 4755 system/core-os usr/bin/crontab 4555 system/core-os usr/bin/mail 2511 system/core-os usr/bin/mailx 2511 system/core-os usr/bin/newgrp 4755 system/core-os usr/bin/pfedit 4755 system/core-os usr/bin/su 4555 system/core-os usr/bin/tip 4511 system/core-os usr/bin/write 2555 system/core-os usr/lib/utmp_update 4555 system/core-os usr/sbin/amd64/prtconf 2555 system/core-os usr/sbin/amd64/swap 2555 system/core-os usr/sbin/amd64/sysdef 2555 system/core-os usr/sbin/amd64/whodo 4555 system/core-os usr/sbin/prtdiag 2755 system/core-os usr/sbin/quota 4555 system/core-os usr/sbin/wall 2555

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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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• 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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• Core Data to-many relationship in code

  - by Jan Bezemer

  I have three entities: Session, User and Test. A session has 0-many users and a user can perform 0-6 tests. (I say 0 but in the real application always at least 1 is required, at least 1 user for a session and at least 1 test for a user. But I say 0 to express an empty start.) All entities have their own specific data attributes too. A user has a name, A session has a name, a test has six values to be filled in by the user, and so on. But my issue is with the relationships. How do I set multiple users and have them added to one session (same goes for multiple tests for one user). How do I show the content in a right way? How do I show a session that has multiple users and these users having completed multiple tests? Here's my code so far with regard to issue 1: Session *session = [NSEntityDescription insertNewObjectForEntityForName:@"Session" inManagedObjectContext:context]; session.name = @"Session 1"; User *users = [NSEntityDescription insertNewObjectForEntityForName:@"User" inManagedObjectContext:context]; users.age = [NSNumber numberWithInt:28]; users.session = session; //sessie.users = users; [sessie addUserObject:users]; With regard to issue 2: I can log the session, but I can't get the user(s) logged from a session. NSFetchRequest *fetchRequest = [[NSFetchRequest alloc] init]; NSEntityDescription *entity = [NSEntityDescription entityForName:@"Session" inManagedObjectContext:context]; [fetchRequest setEntity:entity]; NSArray *fetchedObjects = [context executeFetchRequest:fetchRequest error:&error]; for (Session *info in fetchedObjects) { NSLog(@"Name: %@", info.name); NSLog(@"Having problems with this: %@",info.user); //User *details = info.user; //NSLog(@"User: %@", details.age); }

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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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• Store XML data in Core Data

  - by ct2k7

  Hi, is there any easy way of store XML data into core data? Currently, my app just pulls the values from the XML file directly, however, this isn't efficient for XML files which holds over 100 entries, thus storing the data in Core Data would be the best option. XML file is called/downloaded/parsed ever time the app opens. With the Core Data, the XML data would be downloaded ever 3600 seconds or so, and refresh the current data in the core data, to reduce the loading time when opening the app. Any ideas on how I can do this? Having reviewed the developer documentation, it doesn't look very tasty.

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• Objective C, Core Data issue

  - by Jaime Rae

  I'm following a tutorial in "More iPhone 3 Development. In the code, they have a line: NSManagedObjectContext *managedObjectContext = appDelegate.managedObjectContext; I get an error: "accessing unknown 'managedObjectContext' getter method" on that line. I've downloaded his sample code and his program runs fine with that line of code. I've tried rewriting the code and I've even copied and pasted his code into my program, but I still get the error. I am using the newest SDK, and I'm wondering if something might have changed so this getter method doesn't work anymore, but I do not get any warning about deprecation. Does anyone know what is going on, or better yet, a better way to write this line and not get the error. Thanks LadyDev

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• addObject for one/many-to-many relationships in core data for iPhone

  - by David S

  Hello everyone, I have the following 2 Entity’s in my xcdatamodel:

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• core data date format question

  - by iphonedevcybin

  i have my table sorted by date - long format with time and everything. i want to format timeStamp to dd,mm,yyyy and send use it as titleforheaderinsection method...how and where do i do this?

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• Implement delegates for Core Data's fetched results controller or not

  - by Spanky

  What advantage is there to implementing the four delegate methods: (void)controllerWillChangeContent:(NSFetchedResultsController *)controller (void)controller:(NSFetchedResultsController *)controller didChangeSection:(id )sectionInfo atIndex:(NSUInteger)sectionIndex forChangeType:(NSFetchedResultsChangeType)type (void)controller:(NSFetchedResultsController *)controller didChangeObject:(id)anObject atIndexPath:(NSIndexPath *)indexPath forChangeType:(NSFetchedResultsChangeType)type newIndexPath:(NSIndexPath *)newIndexPath (void)controllerDidChangeContent:(NSFetchedResultsController *)controller rather than implement: (void)controllerDidChangeContent:(NSFetchedResultsController *)controller Any help appreciated // :)

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• Multi-property "transactions" in Core Data / NSManagedObject / NSFetchedResultsController?

  - by Martijn Thé

  Hi, Is it possible to set multiple properties of an NSManagedObject and have the NSFetchedResultsController call controllerDidChangeContent: only once? In other words, is it possible to say something like: [managedObject beginChanges]; [managedObject setPropertyA:@"Foo"]; [managedObject setPropertyB:@"Bar"]; [managedObject commitChanges]; and then have the NSFetchedResultsController call controllerDidChangeContent: (and the other methods) only one time? Thanks!

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• Implement delegates for Core Data or not

  - by Spanky

  What advantage is there to implementing the four delegate methods: (void)controllerWillChangeContent:(NSFetchedResultsController *)controller (void)controller:(NSFetchedResultsController *)controller didChangeSection:(id )sectionInfo atIndex:(NSUInteger)sectionIndex forChangeType:(NSFetchedResultsChangeType)type (void)controller:(NSFetchedResultsController *)controller didChangeObject:(id)anObject atIndexPath:(NSIndexPath *)indexPath forChangeType:(NSFetchedResultsChangeType)type newIndexPath:(NSIndexPath *)newIndexPath (void)controllerDidChangeContent:(NSFetchedResultsController *)controller rather than implement: (void)controllerDidChangeContent:(NSFetchedResultsController *)controller Any help appreciated // :)

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