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• Oracle Magazine - OWB 11gR2 and Heterogeneous Databases

  - by David Allan

  There's a nice article titled 'Oracle Warehouse Builder 11g Release 2 and Heterogeneous Databases' from Oracle ACE director and cofounder of Rittman Mead Consulting, Mark Rittman in the May/June 2010 Oracle Magazine that covers the heterogeneous database support in OWB 11gR2: http://www.oracle.com/technology/oramag/oracle/10-may/o30bi.html Big thanks to Mark for this write up. There is an Oracle white paper on the support here and for examples of this extensibility you can go to the OWB blog archive where there are quite a few posts. I would recommend the following interesting posts out of the archive architecture overview, bulk file loading, MySQL open connectivity and MySQL bulk extract as interesting posts amongst others.

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• Ameristar Wins with Oracle GoldenGate’s Heterogeneous Real-Time Data Integration

  - by Irem Radzik

  Today we announced a press release about another successful project with Oracle GoldenGate. This time at Ameristar. Ameristar is a casino gaming company and needed a single data integration solution to connect multiple heterogeneous systems to its Teradata data warehouse. The project involves integration of Ameristar’s promotional and gaming data from 14 data sources across its 7 casino hotel properties in real time into a central Teradata data warehouse. The source systems include the Aristocrat gaming and MGT promotional management platforms running on Microsoft SQL Server 2000 databases. As you can notice, there was no Oracle Database involved in this project, but Ameristar’s IT leadership knew that  GoldenGate’s strong heterogeneous and real-time data integration capabilities is the right technology for their data warehousing project. With GoldenGate Ameristar was able to reduce data latency to the enterprise data warehouse, and use this real-time customer information for marketing teams in improving overall customer experience. Ameristar customers receive more targeted and timely campaign offers, and the company has more up-to-date visibility into financial metrics of the company. One other key benefit the company experienced with GoldenGate is in operational costs. The previous data capture solution Ameristar used was trigger based and required a lot of effort to manage. They needed dedicated IT staff to maintain it. With GoldenGate, the solution runs seamlessly without needing a fully-dedicated staff, giving the IT team at Ameristar more resources for their other IT projects. If you want to learn more about GoldenGate and the latest features for Oracle Database and non-Oracle databases, please watch our on demand webcast about Oracle GoldenGate 11g Release 2.

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• Cross-Platform Migration using Heterogeneous Data Guard

  - by Roy F. Swonger

  Most people think of Data Guard as a disaster recovery solution, and it certainly excels in that role. However, did you know that you can also use Data Guard for platform migration under some conditions? While you would normally have your primary and standby Data Guard systems running on the same OS and hardware platform, there are some heterogeneous combinations of primary and stanby system that are supported by Data Guard Physical Standby. One example of heterogenous Data Guard support is the ability to go between Linux and Windows on many processor architectures. Another is the support for environments that are running HP-UX on both PA-RIsC and Itanium hardware. Brand new in 11.2.0.2 is the ability to have both SPARC Solaris and IBM AIX on Power Systems in the same Data Guard environment. See My Oracle Support note 413484.1 for all the details about supported platform combinations. So, why mention this in an upgrade blog? Simple: much of the time required for a platform migration is usually spent copying files from one system to another. If you are moving between systems that are supported by heterogenous Data Guard, then you can reduce that migration downtime to a matter of minutes. This can be a big win when downtime is at a premium (and isn't downtime always at a premium? In addition, you get the benefit of being able to keep the old and new environments synchronized until you are sure the migration is successful! A great case study of using Data Guard for a technology refresh is located on this OTN page. The case study showing CERN's methodology isn't highlighted as a link on the overview page, but it is clickable. As always, make sure you are fully versed on the details and restrictions by reading the available documentation and MOS notes. Happy migrating!

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• Heterogeneous Datacenter Management with Enterprise Manager 12c

  - by Joe Diemer

  The following is a Guest Blog, contributed by Bryce Kaiser, Product Manager at Blue MedoraWhen I envision a perfect datacenter, it would consist of technologies acquired from a single vendor across the entire server, middleware, application, network, and storage stack - Apps to Disk - that meets your organization’s every IT requirement with absolute best-of-breed solutions in every category.   To quote a familiar motto, your datacenter would consist of "Hardware and Software, Engineered to Work Together".  In almost all cases, practical realities dictate something far less than the IT Utopia mentioned above.   You may wish to leverage multiple vendors to keep licensing costs down, a single vendor may not have an offering in the IT category you need, or your preferred vendor may quite simply not have the solution that meets your needs.    In other words, your IT needs dictate a heterogeneous IT environment.  Heterogeneity, however, comes with additional complexity. The following are two pretty typical challenges:1) No End-to-End Visibility into the Enterprise Wide Application Deployment. Each vendor solution which is added to an infrastructure may bring its own tooling creating different consoles for different vendor applications and platforms.2) No Visibility into Performance Bottlenecks. When multiple management tools operate independently, you lose diagnostic capabilities including identifying cross-tier issues with database, hung-requests, slowness, memory leaks and hardware errors/failures causing DB/MW issues. As adoption of Oracle Enterprise Manager (EM) has increased, especially since the release of Enterprise Manager 12c, Oracle has seen an increase in the number of customers who want to leverage their investments in EM to manage non-Oracle workloads.  Enterprise Manager provides a single pane of glass view into their entire datacenter.  By creating a highly extensible framework via the Oracle EM Extensibility Development Kit (EDK), Oracle has provided the tooling for business partners such as my company Blue Medora as well as customers to easily fill gaps in the ecosystem and enhance existing solutions.  As mentioned in the previous post on the Enterprise Manager Extensibility Exchange, customers have access to an assortment of Oracle and Partner provided solutions through this Exchange, which is accessed at http://www.oracle.com/goto/emextensibility.  Currently, there are over 80 Oracle and partner provided plug-ins across the EM 11g and EM 12c versions.  Blue Medora is one of those contributing partners, for which you will find 3 of our solutions including our flagship plugin for VMware.  Let's look at Blue Medora’s VMware plug-in as an example to what I'm trying to convey.  Here is a common situation solved by true visibility into your entire stack:Symptoms•    My database is bogging down, however the database appears okay internally.  Maybe it’s starved for resources?•    My OS tooling is showing everything is “OK”.  Something doesn’t add up. Root cause•    Through the VMware plugin we can see the problem is actually on the virtualization layer Solution•    From within Enterprise Manager  -- the same tool you use for all of your database tuning -- we can overlay the data of the database target, host target, and virtual machine target for a true picture of the true root cause. Here is the console view: Perhaps your monitoring conditions are more specific to your environment.  No worries, Enterprise Manager still has you covered.  With Metric Extensions you have the “Next Generation” of User-Defined Metrics, which easily bring the power of your existing management scripts into a single console while leveraging the proven Enterprise Manager framework. Simply put, Oracle Enterprise manager boasts a growing ecosystem that provides the single pane of glass for your entire datacenter from the database and beyond.  Bryce can be contacted at [email protected]

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• Invoke Haskell function with heterogeneous arguments?

  - by thurn

  I'm currently working on a Haskell project which automatically tests some functions based on an XML specification. The XML specification gives the arguments to each function and the expected result that the function will provide (the arguments are of many different types). I know how to extract the function arguments from the XML and parse them using the read function, but I haven't figured out how to invoke the function using the arguments I get out. What I basically want is to read and store the arguments in a heterogeneous list (my current thinking is to use a list of type Data.Dynamic) and then invoke the function, passing this heterogeneous list as its argument list. Is this possible? Modifying the functions under test is not an option.

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• heterogeneous comparisons in python3

  - by Matt Anderson

  I'm 99+% still using python 2.x, but I'm trying to think ahead to the day when I switch. So, I know that using comparison operators (less/greater than, or equal to) on heterogeneous types that don't have a natural ordering is no longer supported in python3.x -- instead of some consistent (but arbitrary) result we raise TypeError instead. I see the logic in that, and even mostly think its a good thing. Consistency and refusing to guess is a virtue. But what if you essentially want the python2.x behavior? What's the best way to go about getting it? For fun (more or less) I was recently implementing a Skip List, a data structure that keeps its elements sorted. I wanted to use heterogeneous types as keys in the data structure, and I've got to compare keys to one another as I walk the data structure. The python2.x way of comparing makes this really convenient -- you get an understandable ordering amongst elements that have a natural ordering, and some ordering amongst those that don't. Consistently using a sort/comparison key like (type(obj).__name__, obj) has the disadvantage of not interleaving the objects that do have a natural ordering; you get all your floats clustered together before your ints, and your str-derived class separates from your strs. I came up with the following: import operator def hetero_sort_key(obj): cls = type(obj) return (cls.__name__+'_'+cls.__module__, obj) def make_hetero_comparitor(fn): def comparator(a, b): try: return fn(a, b) except TypeError: return fn(hetero_sort_key(a), hetero_sort_key(b)) return comparator hetero_lt = make_hetero_comparitor(operator.lt) hetero_gt = make_hetero_comparitor(operator.gt) hetero_le = make_hetero_comparitor(operator.le) hetero_ge = make_hetero_comparitor(operator.gt) Is there a better way? I suspect one could construct a corner case that this would screw up -- a situation where you can compare type A to B and type A to C, but where B and C raise TypeError when compared, and you can end up with something illogical like a > b, a < c, and yet b > c (because of how their class names sorted). I don't know how likely it is that you'd run into this in practice.

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• Cassandra on heterogeneous servers

  - by happy-coding

  I am currently running 4 cassandra nodes with the following hardware in a Apache Cassandra cluster: AMD Athlon 64 X2 6000+ 8G RAM 750G hard disk It shows not such a good writing performance and a really bad read performance with sometimes also timeouts. I was wondering if it makes sense to add 2 nodes with a different hardware (8 CPUs and more RAM) to improve this. Or does a cassandra cluster works best with the same hardware in every node? Thanks & best regards

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• Heterogeneous queries require the ANSI_NULLS

  - by Dezigo

  I wrote a trigger. USE [TEST] GO /****** Object: Trigger [dbo].[TR_POSTGRESQL_UPDATE_YC] Script Date: 05/26/2010 08:54:03 ******/ SET ANSI_NULLS ON GO SET QUOTED_IDENTIFIER ON GO ALTER TRIGGER [dbo].[TR_POSTGRESQL_UPDATE_YC] ON [dbo].[BCT_CNTR_EVENTS] FOR INSERT AS BEGIN DECLARE @MOVE_TIME varchar(14); DECLARE @MOVE_TIME_FORMATED varchar(20); DECLARE @RELEASE_NOTE varchar(32); DECLARE @CMR_NUMBER varchar(15); DECLARE @MOVE_TYPE varchar(2); SELECT @MOVE_TIME = inserted.move_time ,@MOVE_TYPE = inserted.move_type ,@RELEASE_NOTE = inserted.release_note ,@CMR_NUMBER = inserted.cmr_number FROM inserted IF(@MOVE_TYPE = 'YC') BEGIN SET @MOVE_TIME_FORMATED = SUBSTRING(@MOVE_TIME,1,4) + '-' + SUBSTRING(@MOVE_TIME,5,2) + '-' + SUBSTRING(@MOVE_TIME,7,2) + ' 00:00:00' --UPDATE OpenQuery(POSTGRESQL_SERV,'SELECT visit_cmr,visit_timestamp,visit_pin FROM VISIT') -- SET visit_cmr = @RELEASE_NOTE -- WHERE visit_timestamp = @MOVE_TIME_FORMATED -- AND visit_pin = right(@CMR_NUMBER,5) -- AND visit_cmr IS NULL END SET NOCOUNT ON; END When I have inserted a row,I have get an error **Heterogeneous queries require the ANSI_NULLS and ANSI_WARNINGS options to be set for the connection. This ensures consistent query semantics. Enable these options and then reissue your query.** Then I ofcourse SET SET ANSI_WARNINGS is ON but it`s not work for me. (trigger fo linked server postgresql) I have restarted a server. not work again.

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• Heterogeneous NSTreeController

  - by andyvn22

  I have an NSTreeController (supplying content to an NSOutlineView). I'd like the top-level objects to be of one class, and all other objects (so, children at any level) to be of another. What's the best way to go about this? I'll need to somehow change the behavior of at least add, addChild, insert, and insertChild, I suppose. I was hoping, though, to find a simple way to account for this in only one location, rather than changing four separate methods.

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• What would be the safest way to store objects of classes derived from a common interface in a common

  - by Svenstaro

  I'd like to manage a bunch of objects of classes derived from a shared interface class in a common container. To illustrate the problem, let's say I'm building a game which will contain different actors. Let's call the interface IActor and derive Enemy and Civilian from it. Now, the idea is to have my game main loop be able to do this: // somewhere during init std::vector<IActor> ActorList; Enemy EvilGuy; Civilian CoolGuy; ActorList.push_back(EvilGuy); ActorList.push_back(CoolGuy); and // main loop while(!done) { BOOST_FOREACH(IActor CurrentActor, ActorList) { CurrentActor.Update(); CurrentActor.Draw(); } } ... or something along those lines. This example obviously won't work but that is pretty much the reason I'm asking here. I'd like to know: What would be the best, safest, highest-level way to manage those objects in a common heterogeneous container? I know about a variety of approaches (Boost::Any, void*, handler class with boost::shared_ptr, Boost.Pointer Container, dynamic_cast) but I can't decide which would be the way to go here. Also I'd like to emphasize that I want to stay away as far as possible from manual memory management or nested pointers. Help much appreciated :).

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• How to call virtual function of an object in C++

  - by SoonDead

  I'm struggling with calling a virtual function in C++. I'm not experienced in C++, I mainly use C# and Java so I might have some delusions, but bear with me. I have to write a program where I have to avoid dynamic memory allocation if possible. I have made a class called List: template <class T> class List { public: T items[maxListLength]; int length; List() { length = 0; } T get(int i) const { if (i >= 0 && i < length) { return items[i]; } else { throw "Out of range!"; } }; // set the value of an already existing element void set(int i, T p) { if (i >= 0 && i < length) { items[i] = p; } else { throw "Out of range!"; } } // returns the index of the element int add(T p) { if (length >= maxListLength) { throw "Too many points!"; } items[length] = p; return length++; } // removes and returns the last element; T pop() { if (length > 0) { return items[--length]; } else { throw "There is no element to remove!"; } } }; It just makes an array of the given type, and manages the length of it. There is no need for dynamic memory allocation, I can just write: List<Object> objects; MyObject obj; objects.add(obj); MyObject inherits form Object. Object has a virtual function which is supposed to be overridden in MyObject: struct Object { virtual float method(const Input& input) { return 0.0f; } }; struct MyObject: public Object { virtual float method(const Input& input) { return 1.0f; } }; I get the elements as: objects.get(0).method(asdf); The problem is that even though the first element is a MyObject, the Object's method function is called. I'm guessing there is something wrong with storing the object in an array of Objects without dynamically allocating memory for the MyObject, but I'm not sure. Is there a way to call MyObject's method function? How? It's supposed to be a heterogeneous collection btw, so that's why the inheritance is there in the first place. If there is no way to call the MyObject's method function, then how should I make my list in the first place?

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• Resolving harmless binding errors in WPF II : 2 approaches for removing data binding errors due to heterogeneous types in a hierarchical view

  - by akjoshi

  This is a continuation post to my previous post Resolving harmless binding errors in WPF in which I talked about various ways of  resolving different binding errors etc. I recently came across another situation in which we get these binding errors and how they can be resolved. Problem: If you have a tree with 2 types of items in it and you use different DataTypes for each of them, then you will get binding errors because of missing Properties in either one of the item. In our case we had binding...(read more)

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• How to use boost::fusion::transform on heterogeneous containers?

  - by Kyle

  Boost.org's example given for fusion::transform is as follows: struct triple { typedef int result_type; int operator()(int t) const { return t * 3; }; }; // ... assert(transform(make_vector(1,2,3), triple()) == make_vector(3,6,9)); Yet I'm not "getting it." The vector in their example contains elements all of the same type, but a major point of using fusion is containers of heterogeneous types. What if they had used make_vector(1, 'a', "howdy") instead? int operator()(int t) would need to become template<typename T> T& operator()(T& const t) But how would I write the result_type? template<typename T> typedef T& result_type certainly isn't valid syntax, and it wouldn't make sense even if it was, because it's not tied to the function.

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• Tools to manage large network of heterogeneous web applications?

  - by Andrew

  I recently started a new job where I've been tasked with managing a global network of heterogenous web applications. There's very little documentation. My first order of business is to create an inventory of all of the web applications. Are there any tools out there to manage a large group of web apps? I'd like to collect a large dataset for each website including: logins for web based control panels logins to FTP/ssh accounts Google analytics tracking code for each site 3rd party libraries used SSL certs, issuers, and expiration dates etc I know I could keep the information in Excel or build a custom database, but I'm hoping there's already a tool out there to help me with this.

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• OpenJDK In The News: AMD and Oracle to Collaborate in the OpenJDK Community [..]

  - by $utils.escapeXML($entry.author)

  During the JavaOne™ 2012 Strategy Keynote, AMD (NYSE: AMD) announced its participation in OpenJDK™ Project “Sumatra” in collaboration with Oracle and other members of the OpenJDK community to help bring heterogeneous computing capabilities to Java™ for server and cloud environments. The OpenJDK Project “Sumatra” will explore how the Java Virtual Machine (JVM), as well as the Java language and APIs, might be enhanced to allow applications to take advantage of graphics processing unit (GPU) acceleration, either in discrete graphics cards or in high-performance graphics processor cores such as those found in AMD accelerated processing units (APUs).“Affirming our plans to contribute to the OpenJDK Project represents the next step towards bringing heterogeneous computing to millions of Java developers and can potentially lead to future developments of new hardware models, as well as server and cloud programming paradigms,” said Manju Hegde, corporate vice president, Heterogeneous Applications and Developer Solutions at AMD. “AMD has an established track record of collaboration with open-software development communities from OpenCL™ to the Heterogeneous System Architecture (HSA) Foundation, and with this initiative we will help further the development of graphics acceleration within the Java community.”“We expect our work with AMD and other OpenJDK participants in Project “Sumatra” will eventually help provide Java developers with the ability to quickly leverage GPU acceleration for better performance,” said Georges Saab, vice president, Software Development, Java Platform Group at Oracle. "We hope individuals and other organizations interested in this exciting development will follow AMD's lead by joining us in Project “Sumatra."Quotes taken from the first press release from AMD mentioning OpenJDK, titled "AMD and Oracle to Collaborate in the OpenJDK Community to Explore Heterogeneous Computing for Java ".

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• What strategies are efficient to handle concurrent reads on heterogeneous multi-core architectures?

  - by fabrizioM

  I am tackling the challenge of using both the capabilities of a 8 core machine and a high-end GPU (Tesla 10). I have one big input file, one thread for each core, and one for the the GPU handling. The Gpu thread, to be efficient, needs a big number of lines from the input, while the Cpu thread needs only one line to proceed (storing multiple lines in a temp buffer was slower). The file doesn't need to be read sequentially. I am using boost. My strategy is to have a mutex on the input stream and each thread locks - unlocks it. This is not optimal because the gpu thread should have a higher precedence when locking the mutex, being the fastest and the most demanding one. I can come up with different solutions but before rush into implementation I would like to have some guidelines. What approach do you use / recommend ?

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• PROUHD: RAID for the end-user

  <b>Linuxconfig:</b> "Therefore, there is currently no storage solution that manages heterogeneous storage devices efficiently. In this article, we propose such a solution and we call it PROUHD (Pool of RAID Over User Heterogeneous Devices)."

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• Prevent coersion to a single type in unlist() or c(); passing arguments to wrapper functions

  - by Leo Alekseyev

  Is there a simple way to flatten a list while retaining the original types of list constituents?.. Is there a way to programmatically construct a heterogeneous list?.. For instance, I want to create a simple wrapper for functions like png(filename,width,height) that would take device name, file name, and a list of options. The naive approach would be something like my.wrapper <- function(dev,name,opts) { do.call(dev,c(filename=name,opts)) } or similar code with unlist(list(...)). This doesn't work because opts gets coerced to character, and the resulting call is e.g. png(filename,width="500",height="500"). If there's no straightforward way to create heterogeneous lists like that, is there a standard idiomatic way to splice arguments into functions without naming them explicitly (e.g. do.call(dev,list(filename=name,width=opts["width"]))? -- Edit -- Gavin Simpson answered both questions below in his discussion about constructing wrapper functions. Let me give a summary of the answer to the title question: It is possible to construct a heterogeneous list with c() provided the arguments to c() are lists. To wit: > foo <- c("a","b"); bar <- 1:3 > c(foo,bar) [1] "a" "b" "1" "2" "3" > c(list(foo),list(bar)) [[1]] [1] "a" "b" [[2]] [1] 1 2 3 > c(as.list(foo),as.list(bar)) ## this creates a flattened heterogeneous list [[1]] [1] "a" [[2]] [1] "b" [[3]] [1] 1 [[4]] [1] 2 [[5]] [1] 3

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• Oracle's Global Single Schema

  - by david.butler(at)oracle.com

  Maximizing business process efficiencies in a heterogeneous environment is very difficult. The difficulty stems from the fact that the various applications across the Information Technology (IT) landscape employ different integration standards, different message passing strategies, and different workflow engines. Vendors such as Oracle and others are delivering tools to help IT organizations manage the complexities introduced by these differences. But the one remaining intractable problem impacting efficient operations is the fact that these applications have different definitions for the same business data. Business data is your business information codified for computer programs to use. A good data model will represent the way your organization does business. The computer applications your organization deploys to improve operational efficiency are built to operate on the business data organized into this schema.  If the schema does not represent how you do business, the applications on that schema cannot provide the features you need to achieve the desired efficiencies. Business processes span these applications. Data problems break these processes rendering them far less efficient than they need to be to achieve organization goals. Thus, the expected return on the investment in these applications is never realized. The success of all business processes depends on the availability of accurate master data.  Clearly, the solution to this problem is to consolidate all the master data an organization uses to run its business. Then clean it up, augment it, govern it, and connect it back to the applications that need it. Until now, this obvious solution has been difficult to achieve because no one had defined a data model sufficiently broad, deep and flexible enough to support transaction processing on all key business entities and serve as a master superset to all other operational data models deployed in heterogeneous IT environments. Today, the situation has changed. Oracle has created an operational data model (aka schema) that can support accurate and consistent master data across heterogeneous IT systems. This is foundational for providing a way to consolidate and integrate master data without having to replace investments in existing applications. This Global Single Schema (GSS) represents a revolutionary breakthrough that allows for true master data consolidation. Oracle has deep knowledge of applications dating back to the early 1990s.  It developed applications in the areas of Supply Chain Management (SCM), Product Lifecycle Management (PLM), Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), Human Capital Management (HCM), Financials and Manufacturing. In addition, Oracle applications were delivered for key industries such as Communications, Financial Services, Retail, Public Sector, High Tech Manufacturing (HTM) and more. Expertise in all these areas drove requirements for GSS. The following figure illustrates Oracle's unique position that enabled the creation of the Global Single Schema. GSS Requirements Gathering GSS defines all the key business entities and attributes including Customers, Contacts, Suppliers, Accounts, Products, Services, Materials, Employees, Installed Base, Sites, Assets, and Inventory to name just a few. In addition, Oracle delivers GSS pre-integrated with a wide variety of operational applications.  Business Process Automation EBusiness is about maximizing operational efficiency. At the highest level, these 'operations' span all that you do as an organization.  The following figure illustrates some of these high-level business processes. Enterprise Business Processes Supplies are procured. Assets are maintained. Materials are stored. Inventory is accumulated. Products and Services are engineered, produced and sold. Customers are serviced. And across this entire spectrum, Employees do the procuring, supporting, engineering, producing, selling and servicing. Not shown, but not to be overlooked, are the accounting and the financial processes associated with all this procuring, manufacturing, and selling activity. Supporting all these applications is the master data. When this data is fragmented and inconsistent, the business processes fail and inefficiencies multiply. But imagine having all the data under these operational business processes in one place. ·            The same accurate and timely customer data will be provided to all your operational applications from the call center to the point of sale. ·            The same accurate and timely supplier data will be provided to all your operational applications from supply chain planning to procurement. ·            The same accurate and timely product information will be available to all your operational applications from demand chain planning to marketing. You would have a single version of the truth about your assets, financial information, customers, suppliers, employees, products and services to support your business automation processes as they flow across your business applications. All company and partner personnel will access the same exact data entity across all your channels and across all your lines of business. Oracle's Global Single Schema enables this vision of a single version of the truth across the heterogeneous operational applications supporting the entire enterprise. Global Single Schema Oracle's Global Single Schema organizes hundreds of thousands of attributes into 165 major schema objects supporting over 180 business application modules. It is designed for international operations, and extensibility.  The schema is delivered with a full set of public Application Programming Interfaces (APIs) and an Integration Repository with modern Service Oriented Architecture interfaces to make data available as a services (DaaS) to business processes and enable operations in heterogeneous IT environments. ·         Key tables can be extended with unlimited numbers of additional attributes and attribute groups for maximum flexibility.  o    This enables model extensions that reflect business entities unique to your organization's operations. ·         The schema is multi-organization enabled so data manipulation can be controlled along organizational boundaries. ·         It uses variable byte Unicode to support over 31 languages. ·         The schema encodes flexible date and flexible address formats for easy localizations. No matter how complex your business is, Oracle's Global Single Schema can hold your business objects and support your global operations. Oracle's Global Single Schema identifies and defines the business objects an enterprise needs within the context of its business operations. The interrelationships between the business objects are also contained within the GSS data model. Their presence expresses fundamental business rules for the interaction between business entities. The following figure illustrates some of these connections.   Interconnected Business Entities Interconnecte business processes require interconnected business data. No other MDM vendor has this capability. Everyone else has either one entity they can master or separate disconnected models for various business entities. Higher level integrations are made available, but that is a weak architectural alternative to data level integration in this critically important aspect of Master Data Management.    

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• The Best Data Integration for Exadata Comes from Oracle

  - by maria costanzo

  Oracle Data Integrator and Oracle GoldenGate offer unique and optimized data integration solutions for Oracle Exadata. For example, customers that choose to feed their data warehouse or reporting database with near real-time throughout the day, can do so without decreasing  performance or availability of source and target systems. And if you ask why real-time, the short answer is: in today’s fast-paced, always-on world, business decisions need to use more relevant, timely data to be able to act fast and seize opportunities. A longer response to "why real-time" question can be found in a related blog post. If we look at the solution architecture, as shown on the diagram below,  Oracle Data Integrator and Oracle GoldenGate are both uniquely designed to take full advantage of the power of the database and to eliminate unnecessary middle-tier components. Oracle Data Integrator (ODI) is the best bulk data loading solution for Exadata. ODI is the only ETL platform that can leverage the full power of Exadata, integrate directly on the Exadata machine without any additional hardware, and by far provides the simplest setup and fastest overall performance on an Exadata system. We regularly see customers achieving a 5-10 times boost when they move their ETL to ODI on Exadata. For  some companies the performance gain is even much higher. For example a large insurance company did a proof of concept comparing ODI vs a traditional ETL tool (one of the market leaders) on Exadata. The same process that was taking 5hrs and 11 minutes to complete using the competing ETL product took 7 minutes and 20 seconds with ODI. Oracle Data Integrator was 42 times faster than the conventional ETL when running on Exadata.This shows that Oracle's own data integration offering helps you to gain the most out of your Exadata investment with a truly optimized solution. GoldenGate is the best solution for streaming data from heterogeneous sources into Exadata in real time. Oracle GoldenGate can also be used together with Data Integrator for hybrid use cases that also demand non-invasive capture, high-speed real time replication. Oracle GoldenGate enables real-time data feeds from heterogeneous sources non-invasively, and delivers to the staging area on the target Exadata system. ODI runs directly on Exadata to use the database engine power to perform in-database transformations. Enterprise Data Quality is integrated with Oracle Data integrator and enables ODI to load trusted data into the data warehouse tables. Only Oracle can offer all these technical benefits wrapped into a single intelligence data warehouse solution that runs on Exadata. Compared to traditional ETL with add-on CDC this solution offers: §  Non-invasive data capture from heterogeneous sources and avoids any performance impact on source §  No mid-tier; set based transformations use database power §  Mini-batches throughout the day –or- bulk processing nightly which means maximum availability for the DW §  Integrated solution with Enterprise Data Quality enables leveraging trusted data in the data warehouse In addition to Starwood Hotels and Resorts, Morrison Supermarkets, United Kingdom’s fourth-largest food retailer, has seen the power of this solution for their new BI platform and shared their story with us. Morrisons needed to analyze data across a large number of manufacturing, warehousing, retail, and financial applications with the goal to achieve single view into operations for improved customer service. The retailer deployed Oracle GoldenGate and Oracle Data Integrator to bring new data into Oracle Exadata in near real-time and replicate the data into reporting structures within the data warehouse—extending visibility into operations. Using Oracle's data integration offering for Exadata, Morrisons produced financial reports in seconds, rather than minutes, and improved staff productivity and agility. You can read more about Morrison’s success story here and hear from Starwood here. From an Irem Radzik article.

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• Intelligent Conflict Detection and Resolution

  - by Doug Reid

  0 false 18 pt 18 pt 0 0 false false false /* 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-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin;} Conflict Detection and Resolution in Oracle GoldenGate11gR2 has gone through a significant overhaul. The improvements that have been made to this area are substantial and will make it easier for customers to implement complex, heterogeneous GoldenGate configurations. GoldenGate has provided methods for conflict detection and resolution for a number of past releases, but at Oracle we have the opportunity to take advantage of some of the great ideas in this area. Oracle has had feature rich conflict detection and resolution framework in other products, which has been implemented in Oracle GoldenGate 11gR2. These improvements are geared toward helping customers more easily implement advanced configurations that require conflict detection and resolution by providing a robust framework for conflict detection for all DML statements and resolution via pre-built methods, all with less code and simpler syntax than in prior releases. Conflict Detection and Resolution in Oracle GoldenGate 11gR2 is available for our supported heterogeneous platforms, which includes Oracle Database, MySQL, Sybase ASE, SQL Server, and DB2 Linux, Unix, Windows, z/OS, plus DB2 on i Series, which is newly supported in this release. Additional information on the Conflict Detection and Resolution capabilities can be found in our documentation. 

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• Data Source Security Part 4

  - by Steve Felts

  So far, I have covered Client Identity and Oracle Proxy Session features, with WLS or database credentials.  This article will cover one more feature, Identify-based pooling.  Then, there is one more topic to cover - how these options play with transactions.Identity-based Connection Pooling An identity based pool creates a heterogeneous pool of connections.  This allows applications to use a JDBC connection with a specific DBMS credential by pooling physical connections with different DBMS credentials.  The DBMS credential is based on either the WebLogic user mapped to a database user or the database user directly, based on the “use database credentials” setting as described earlier. Using this feature enabled with “use database credentials” enabled seems to be what is proposed in the JDBC standard, basically a heterogeneous pool with users specified by getConnection(user, password). The allocation of connections is more complex if Enable Identity Based Connection Pooling attribute is enabled on the data source.  When an application requests a database connection, the WebLogic Server instance selects an existing physical connection or creates a new physical connection with requested DBMS identity. The following section provides information on how heterogeneous connections are created:1. At connection pool initialization, the physical JDBC connections based on the configured or default “initial capacity” are created with the configured default DBMS credential of the data source.2. An application tries to get a connection from a data source.3a. If “use database credentials” is not enabled, the user specified in getConnection is mapped to a DBMS credential, as described earlier.  If the credential map doesn’t have a matching user, the default DBMS credential is used from the datasource descriptor.3b. If “use database credentials” is enabled, the user and password specified in getConnection are used directly.4. The connection pool is searched for a connection with a matching DBMS credential.5. If a match is found, the connection is reserved and returned to the application.6. If no match is found, a connection is created or reused based on the maximum capacity of the pool: - If the maximum capacity has not been reached, a new connection is created with the DBMS credential, reserved, and returned to the application.- If the pool has reached maximum capacity, based on the least recently used (LRU) algorithm, a physical connection is selected from the pool and destroyed. A new connection is created with the DBMS credential, reserved, and returned to the application. It should be clear that finding a matching connection is more expensive than a homogeneous pool.  Destroying a connection and getting a new one is very expensive.  If you can use a normal homogeneous pool or one of the light-weight options (client identity or an Oracle proxy connection), those should be used instead of identity based pooling. Regardless of how physical connections are created, each physical connection in the pool has its own DBMS credential information maintained by the pool. Once a physical connection is reserved by the pool, it does not change its DBMS credential even if the current thread changes its WebLogic user credential and continues to use the same connection. To configure this feature, select Enable Identity Based Connection Pooling.  See http://docs.oracle.com/cd/E24329_01/apirefs.1211/e24401/taskhelp/jdbc/jdbc_datasources/EnableIdentityBasedConnectionPooling.html  "Enable identity-based connection pooling for a JDBC data source" in Oracle WebLogic Server Administration Console Help. You must make the following changes to use Logging Last Resource (LLR) transaction optimization with Identity-based Pooling to get around the problem that multiple users will be accessing the associated transaction table.- You must configure a custom schema for LLR using a fully qualified LLR table name. All LLR connections will then use the named schema rather than the default schema when accessing the LLR transaction table.  - Use database specific administration tools to grant permission to access the named LLR table to all users that could access this table via a global transaction. By default, the LLR table is created during boot by the user configured for the connection in the data source. In most cases, the database will only allow access to this user and not allow access to mapped users. Connections within Transactions Now that we have covered the behavior of all of these various options, it’s time to discuss the exception to all of the rules.  When you get a connection within a transaction, it is associated with the transaction context on a particular WLS instance. When getting a connection with a data source configured with non-XA LLR or 1PC (using the JTS driver) with global transactions, the first connection obtained within the transaction is returned on subsequent connection requests regardless of the values of username/password specified and independent of the associated proxy user session, if any. The connection must be shared among all users of the connection when using LLR or 1PC. For XA data sources, the first connection obtained within the global transaction is returned on subsequent connection requests within the application server, regardless of the values of username/password specified and independent of the associated proxy user session, if any.  The connection must be shared among all users of the connection within a global transaction within the application server/JVM.

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• setting permissions of python module (python setup install)

  - by SetJmp

  I am configuring a distutils-based setup.py for a python module that is to be installed on a heterogeneous set of resources. Due to the heterogeneity, the location where the module is installed is not the same on each host however disutils picks the host-specific location. I find that the module is installed without o+rx permissions using disutils (in spite of setting umask ahead of running setup.py). One solution is to manually correct this problem, however I would like an automated means that works on heterogeneous install targets. For example, is there a way to extract the ending location of the installation from within setup.py? Any other suggestions? Thanks! SetJmp

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• NoSQL is not about object databases

  - by Bertrand Le Roy

  NoSQL as a movement is an interesting beast. I kinda like that it’s negatively defined (I happen to belong myself to at least one other such a-community). It’s not in its roots about proposing one specific new silver bullet to kill an old problem. it’s about challenging the consensus. Actually, blindly and systematically replacing relational databases with object databases would just replace one set of issues with another. No, the point is to recognize that relational databases are not a universal answer -although they have been used as one for so long- and recognize instead that there’s a whole spectrum of data storage solutions out there. Why is it so hard to recognize, by the way? You are already using some of those other data storage solutions every day. Let me cite a few: The file system Active Directory XML / JSON documents The Web e-mail Logs Excel files EXIF blobs in your photos Relational databases And yes, object databases It’s just a fact of modern life. Notice by the way that most of the data that you use every day is unstructured and thus mostly unsuitable for relational storage. It really is more a matter of recognizing it: you are already doing NoSQL. So what happens when for any reason you need to simultaneously query two or more of these heterogeneous data stores? Well, you build an index of sorts combining them, and that’s what you query instead. Of course, there’s not much distance to travel from that to realizing that querying is better done when completely separated from storage. So why am I writing about this today? Well, that’s something I’ve been giving lots of thought, on and off, over the last ten years. When I built my first CMS all that time ago, one of the main problems my customers were facing was to manage and make sense of the mountain of unstructured data that was constituting most of their business. The central entity of that system was the file system because we were dealing with lots of Word documents, PDFs, OCR’d articles, photos and static web pages. We could have stored all that in SQL Server. It would have worked. Ew. I’m so glad we didn’t. Today, I’m working on Orchard (another CMS ;). It’s a pretty young project but already one of the questions we get the most is how to integrate existing data. One of the ideas I’ll be trying hard to sell to the rest of the team in the next few months is to completely split the querying from the storage. Not only does this provide great opportunities for performance optimizations, it gives you homogeneous access to heterogeneous and existing data sources. For free.

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• Any experience on open source database synchronization open source solutions? [on hold]

  - by Boris Pavlovic

  I'm considering few database synchronization open source solutions. The system in need for data synchronization is composed of instances of different types of databases, i.e. heterogeneous system. There are few candidates: Symmetric DS Talend's Data Integration with support for data synchronization Continuent's Tungsteen Replication Daffodil Replicator OS Do you have any real world experience with any of these tools?

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