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• Databases in Source Control

  - by Grant Fritchey

  I’ve been working as a database professional for quite a long time. But originally, I was a developer. And I loved being a developer. There was this constant feedback loop of a job well done, your code compiled and it ran. Every time this happened successfully, you’d check it into source control. These days you have to add another step; the code passed all the tests, unit, line, regression, qa, whatever, then into source control it goes. As a matter of fact, when I first made the jump from developer to DBA/database developer/database professional, source control was the one thing I couldn’t believe was missing from the DBA toolbox. Come to find out, source control was only the beginning of what was missing from your standard DBAs set of skills. Don’t get me wrong. I’m not disrespecting the DBA. They’re focused where they should be, on your production data. But there has to be a method for developing applications that include databases and the database side of that development and deployment process has long been lacking. This lack of development and deployment methodologies is a part of what has given rise to some of the wackier implementations of Object Relational Mapping tools, the NoSQL movement, and some of the other foul cursing that is directed towards databases, DBAs, and database development by application developers. Some of that is well earned. A lot isn’t. But it is a fact that database professionals, in general, do not have as sophisticated a model for managing development and deployment as application developers do. We could charge out and start trying to come up with our own standards and methods. I’m sure people have done exactly that. However, I’m lazy, and not terribly bright. Rather than try to invent a whole new process, I’m going to look to my developer roots and choose instead to emulate the developers. They’re sitting over there across the hall from me working with SCRUM/Agile/Waterfall/Object Driven/Feature Driven/Test Driven development processes that they’ve been polishing for years. What if I just started working on database development the same way they work on code development? Win! Ah, but now I have to have a mechanism for treating my database like application code. First, I need a method for getting it into source control. That’s where Red Gate’s SQL Source Control comes into the picture. SQL Source Control works within SQL Server Management Studio to connect your database objects up to the source control system of your choice. Right out of the box SQL Source Control can link to TFS, SVN or Vault. With a little work you can connect it to Git or just about any other source control system. With the ability to get my database into source control, a lot of possibilities for more direct integration with the application development teams open up.

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• Windows Azure Use Case: Web Applications

  - by BuckWoody

  This is one in a series of posts on when and where to use a distributed architecture design in your organization's computing needs. You can find the main post here: http://blogs.msdn.com/b/buckwoody/archive/2011/01/18/windows-azure-and-sql-azure-use-cases.aspx  Description: Many applications have a requirement to be located outside of the organization’s internal infrastructure control. For instance, the company website for a brick-and-mortar retail company may want to post not only static but interactive content to be available to their external customers, and not want the customers to have access inside the organization’s firewall. There are also cases of pure web applications used for a great many of the internal functions of the business. This allows for remote workers, shared customer/employee workloads and data and other advantages. Some firms choose to host these web servers internally, others choose to contract out the infrastructure to an “ASP” (Application Service Provider) or an Infrastructure as a Service (IaaS) company. In any case, the design of these applications often resembles the following: In this design, a server (or perhaps more than one) hosts the presentation function (http or https) access to the application, and this same system may hold the computational aspects of the program. Authorization and Access is controlled programmatically, or is more open if this is a customer-facing application. Storage is either placed on the same or other servers, hosted within an RDBMS or NoSQL database, or a combination of the options, all coded into the application. High-Availability within this scenario is often the responsibility of the architects of the application, and by purchasing more hosting resources which must be built, licensed and configured, and manually added as demand requires, although some IaaS providers have a partially automatic method to add nodes for scale-out, if the architecture of the application supports it. Disaster Recovery is the responsibility of the system architect as well. Implementation: In a Windows Azure Platform as a Service (PaaS) environment, many of these architectural considerations are designed into the system. The Azure “Fabric” (not to be confused with the Azure implementation of Application Fabric - more on that in a moment) is designed to provide scalability. Compute resources can be added and removed programmatically based on any number of factors. Balancers at the request-level of the Fabric automatically route http and https requests. The fabric also provides High-Availability for storage and other components. Disaster recovery is a shared responsibility between the facilities (which have the ability to restore in case of catastrophic failure) and your code, which should build in recovery. In a Windows Azure-based web application, you have the ability to separate out the various functions and components. Presentation can be coded for multiple platforms like smart phones, tablets and PC’s, while the computation can be a single entity shared between them. This makes the applications more resilient and more object-oriented, and lends itself to a SOA or Distributed Computing architecture. It is true that you could code up a similar set of functionality in a traditional web-farm, but the difference here is that the components are built into the very design of the architecture. The API’s and DLL’s you call in a Windows Azure code base contains components as first-class citizens. For instance, if you need storage, it is simply called within the application as an object.  Computation has multiple options and the ability to scale linearly. You also gain another component that you would either have to write or bolt-in to a typical web-farm: the Application Fabric. This Windows Azure component provides communication between applications or even to on-premise systems. It provides authorization in either person-based or claims-based perspectives. SQL Azure provides relational storage as another option, and can also be used or accessed from on-premise systems. It should be noted that you can use all or some of these components individually. Resources: Design Strategies for Scalable Active Server Applications - http://msdn.microsoft.com/en-us/library/ms972349.aspx  Physical Tiers and Deployment  - http://msdn.microsoft.com/en-us/library/ee658120.aspx

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• Big Data: Size isn’t everything

  - by Simon Elliston Ball

  Big Data has a big problem; it’s the word “Big”. These days, a quick Google search will uncover terabytes of negative opinion about the futility of relying on huge volumes of data to produce magical, meaningful insight. There are also many clichéd but correct assertions about the difficulties of correlation versus causation, in massive data sets. In reading some of these pieces, I begin to understand how climatologists must feel when people complain ironically about “global warming” during snowfall. Big Data has a name problem. There is a lot more to it than size. Shape, Speed, and…err…Veracity are also key elements (now I understand why Gartner and the gang went with V’s instead of S’s). The need to handle data of different shapes (Variety) is not new. Data developers have always had to mold strange-shaped data into our reporting systems, integrating with semi-structured sources, and even straying into full-text searching. However, what we lacked was an easy way to add semi-structured and unstructured data to our arsenal. New “Big Data” tools such as MongoDB, and other NoSQL (Not Only SQL) databases, or a graph database like Neo4J, fill this gap. Still, to many, they simply introduce noise to the clean signal that is their sensibly normalized data structures. What about speed (Velocity)? It’s not just high frequency trading that generates data faster than a single system can handle. Many other applications need to make trade-offs that traditional databases won’t, in order to cope with high data insert speeds, or to extract quickly the required information from data streams. Unfortunately, many people equate Big Data with the Hadoop platform, whose batch driven queries and job processing queues have little to do with “velocity”. StreamInsight, Esper and Tibco BusinessEvents are examples of Big Data tools designed to handle high-velocity data streams. Again, the name doesn’t do the discipline of Big Data any favors. Ultimately, though, does analyzing fast moving data produce insights as useful as the ones we get through a more considered approach, enabled by traditional BI? Finally, we have Veracity and Value. In many ways, these additions to the classic Volume, Velocity and Variety trio acknowledge the criticism that without high-quality data and genuinely valuable outputs then data, big or otherwise, is worthless. As a discipline, Big Data has recognized this, and data quality and cleaning tools are starting to appear to support it. Rather than simply decrying the irrelevance of Volume, we need as a profession to focus how to improve Veracity and Value. Perhaps we should just declare the ‘Big’ silent, embrace these new data tools and help develop better practices for their use, just as we did the good old RDBMS? What does Big Data mean to you? Which V gives your business the most pain, or the most value? Do you see these new tools as a useful addition to the BI toolbox, or are they just enabling a dangerous trend to find ghosts in the noise?

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• Fast Data: Go Big. Go Fast.

  - by Dain C. Hansen

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 For those of you who may have missed it, today’s second full day of Oracle OpenWorld 2012 started with a rumpus. Joe Tucci, from EMC outlined the human face of big data with real examples of how big data is transforming our world. And no not the usual tried-and-true weblog examples, but real stories about taxi cab drivers in Singapore using big data to better optimize their routes as well as folks just trying to get a better hair cut. Next we heard from Thomas Kurian who talked at length about the important platform characteristics of Oracle’s Cloud and more specifically Oracle’s expanded Cloud Services portfolio. Especially interesting to our integration customers are the messaging support for Oracle’s Cloud applications. What this means is that now Oracle’s Cloud applications have a lightweight integration fabric that on-premise applications can communicate to it via REST-APIs using Oracle SOA Suite. It’s an important element to our strategy at Oracle that supports this idea that whether your requirements are for private or public, Oracle has a solution in the Cloud for all of your applications and we give you more deployment choice than any vendor. If this wasn’t enough to get the juices flowing, later that morning we heard from Hasan Rizvi who outlined in his Fusion Middleware session the four most important enterprise imperatives: Social, Mobile, Cloud, and a brand new one: Fast Data. Today, Rizvi made an important step in the definition of this term to explain that he believes it’s a convergence of four essential technology elements: Event Processing for event filtering, business rules – with Oracle Event Processing Data Transformation and Loading - with Oracle Data Integrator Real-time replication and integration – with Oracle GoldenGate Analytics and data discovery – with Oracle Business Intelligence Each of these four elements can be considered (and architect-ed) together on a single integrated platform that can help customers integrate any type of data (structured, semi-structured) leveraging new styles of big data technologies (MapReduce, HDFS, Hive, NoSQL) to process more volume and variety of data at a faster velocity with greater results.  Fast data processing (and especially real-time) has always been our credo at Oracle with each one of these products in Fusion Middleware. For example, Oracle GoldenGate continues to be made even faster with the recent 11g R2 Release of Oracle GoldenGate which gives us some even greater optimization to Oracle Database with Integrated Capture, as well as some new heterogeneity capabilities. With Oracle Data Integrator with Big Data Connectors, we’re seeing much improved performance by running MapReduce transformations natively on Hadoop systems. And with Oracle Event Processing we’re seeing some remarkable performance with customers like NTT Docomo. Check out their upcoming session at Oracle OpenWorld on Wednesday to hear more how this customer is using Event processing and Big Data together. If you missed any of these sessions and keynotes, not to worry. There's on-demand versions available on the Oracle OpenWorld website. You can also checkout our upcoming webcast where we will outline some of these new breakthroughs in Data Integration technologies for Big Data, Cloud, and Real-time in more details. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";}

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• Oracle Big Data Software Downloads

  - by Mike.Hallett(at)Oracle-BI&EPM

  Companies have been making business decisions for decades based on transactional data stored in relational databases. Beyond that critical data, is a potential treasure trove of less structured data: weblogs, social media, email, sensors, and photographs that can be mined for useful information. Oracle offers a broad integrated portfolio of products to help you acquire and organize these diverse data sources and analyze them alongside your existing data to find new insights and capitalize on hidden relationships. Oracle Big Data Connectors Downloads here, includes: Oracle SQL Connector for Hadoop Distributed File System Release 2.1.0 Oracle Loader for Hadoop Release 2.1.0 Oracle Data Integrator Companion 11g Oracle R Connector for Hadoop v 2.1 Oracle Big Data Documentation The Oracle Big Data solution offers an integrated portfolio of products to help you organize and analyze your diverse data sources alongside your existing data to find new insights and capitalize on hidden relationships. Oracle Big Data, Release 2.2.0 - E41604_01 zip (27.4 MB) Integrated Software and Big Data Connectors User's Guide HTML PDF Oracle Data Integrator (ODI) Application Adapter for Hadoop Apache Hadoop is designed to handle and process data that is typically from data sources that are non-relational and data volumes that are beyond what is handled by relational databases. Typical processing in Hadoop includes data validation and transformations that are programmed as MapReduce jobs. Designing and implementing a MapReduce job usually requires expert programming knowledge. However, when you use Oracle Data Integrator with the Application Adapter for Hadoop, you do not need to write MapReduce jobs. Oracle Data Integrator uses Hive and the Hive Query Language (HiveQL), a SQL-like language for implementing MapReduce jobs. Employing familiar and easy-to-use tools and pre-configured knowledge modules (KMs), the application adapter provides the following capabilities: Loading data into Hadoop from the local file system and HDFS Performing validation and transformation of data within Hadoop Loading processed data from Hadoop to an Oracle database for further processing and generating reports Oracle Database Loader for Hadoop Oracle Loader for Hadoop is an efficient and high-performance loader for fast movement of data from a Hadoop cluster into a table in an Oracle database. It pre-partitions the data if necessary and transforms it into a database-ready format. Oracle Loader for Hadoop is a Java MapReduce application that balances the data across reducers to help maximize performance. Oracle R Connector for Hadoop Oracle R Connector for Hadoop is a collection of R packages that provide: Interfaces to work with Hive tables, the Apache Hadoop compute infrastructure, the local R environment, and Oracle database tables Predictive analytic techniques, written in R or Java as Hadoop MapReduce jobs, that can be applied to data in HDFS files You install and load this package as you would any other R package. Using simple R functions, you can perform tasks such as: Access and transform HDFS data using a Hive-enabled transparency layer Use the R language for writing mappers and reducers Copy data between R memory, the local file system, HDFS, Hive, and Oracle databases Schedule R programs to execute as Hadoop MapReduce jobs and return the results to any of those locations Oracle SQL Connector for Hadoop Distributed File System Using Oracle SQL Connector for HDFS, you can use an Oracle Database to access and analyze data residing in Hadoop in these formats: Data Pump files in HDFS Delimited text files in HDFS Hive tables For other file formats, such as JSON files, you can stage the input in Hive tables before using Oracle SQL Connector for HDFS. Oracle SQL Connector for HDFS uses external tables to provide Oracle Database with read access to Hive tables, and to delimited text files and Data Pump files in HDFS. Related Documentation Cloudera's Distribution Including Apache Hadoop Library HTML Oracle R Enterprise HTML Oracle NoSQL Database HTML Recent Blog Posts Big Data Appliance vs. DIY Price Comparison Big Data: Architecture Overview Big Data: Achieve the Impossible in Real-Time Big Data: Vertical Behavioral Analytics Big Data: In-Memory MapReduce Flume and Hive for Log Analytics Building Workflows in Oozie

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• Java Developer Days India Trip Report

  - by reza_rahman

  You are probably aware of Oracle's decision to discontinue the relatively resource intensive regional JavaOnes in favor of more Java Developer Days, virtual events and deeper involvement with independent conferences. In comparison to the regional JavaOnes, Java Developer Days are smaller, shorter (typically one full day), more focused (mostly Oracle speakers/topics) and more local (targeting cities). For those who have been around the Java ecosystem for a few years, they are basically the current incarnation of the highly popular and developer centric Sun Tech Days. October 21st through October 25th I spoke at Java Developer Days India. This was basically three separate but identical events in the cities of Pune (October 21st), Chennai (October 24th) and Bangalore (October 25th). For those with some familiarity with India, other than Hyderabad these cities are India's IT powerhouses. The events were basically focused on Java EE. I delivered five of the sessions (yes, you read that right), while my friend NetBeans Group Product Manager Ashwin Rao delivered three talks. Jagadish Ramu from the GlassFish team India helped me out in Bangalore by delivering two sessions. It was also a pleasure to introduce my co-contributor to the Cargo Tracker Java EE Blue Prints project Vijay Nair at Bangalore during the opening talk. I thought it was a great dynamic between Ashwin and I flipping between talking about the new features and demoing live code in NetBeans. The following were my sessions (source PDF and abstracts posted as usual on my SlideShare account): JavaEE.Next(): Java EE 7, 8, and Beyond Building Java HTML5/WebSocket Applications with JSR 356 What’s New in Java Message Service 2 JAX-RS 2: New and Noteworthy in the RESTful Web Services API Using NoSQL with JPA, EclipseLink and Java EE The event went well and was packed in all three cities. The Q&A was great and Indian developers were particularly generous with kind words :-). It seemed the event and our presence was appreciated in the truest sense which I must say is a rarity. The events were exhausting but very rewarding at the same time. As hectic as the three city trip was I tried to see at least some of the major sights (mostly at night) since this was my very first time to India. I think the slideshow below is a good representation of the riddle wrapped up in an enigma that is India (and the rest of the Indian sub-continent for that matter): Ironically enough what struck me the most during this trip is the woman pictured below - Shushma. My chauffeur, tour guide and friend for a day, she fluidly navigated the madness that is Mumbai traffic with skills that would make Evel Knievel blush while simultaneously pointing out sights and prompting me to take pictures (Mumbai was my stopover and gateway to/from India). In some ways she is probably the most potent symbol of the new India. When we parted ways I told her she should take solace in the fact she has won mostly without a fight a potentially hazardous battle her sisters across the Arabian sea are still fighting. I'm not sure she entirely understood the significance of what I told her. I hope that she did. I also had occasion to take a pretty cool local bus ride from Chennai to Bangalore instead of yet another boring flight. All in all I really enjoyed the trip to India and hope to return again soon. Jai Hind :-)!

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• Big Data – Beginning Big Data – Day 1 of 21

  - by Pinal Dave

  What is Big Data? I want to learn Big Data. I have no clue where and how to start learning about it. Does Big Data really means data is big? What are the tools and software I need to know to learn Big Data? I often receive questions which I mentioned above. They are good questions and honestly when we search online, it is hard to find authoritative and authentic answers. I have been working with Big Data and NoSQL for a while and I have decided that I will attempt to discuss this subject over here in the blog. In the next 21 days we will understand what is so big about Big Data. Big Data – Big Thing! Big Data is becoming one of the most talked about technology trends nowadays. The real challenge with the big organization is to get maximum out of the data already available and predict what kind of data to collect in the future. How to take the existing data and make it meaningful that it provides us accurate insight in the past data is one of the key discussion points in many of the executive meetings in organizations. With the explosion of the data the challenge has gone to the next level and now a Big Data is becoming the reality in many organizations. Big Data – A Rubik’s Cube I like to compare big data with the Rubik’s cube. I believe they have many similarities. Just like a Rubik’s cube it has many different solutions. Let us visualize a Rubik’s cube solving challenge where there are many experts participating. If you take five Rubik’s cube and mix up the same way and give it to five different expert to solve it. It is quite possible that all the five people will solve the Rubik’s cube in fractions of the seconds but if you pay attention to the same closely, you will notice that even though the final outcome is the same, the route taken to solve the Rubik’s cube is not the same. Every expert will start at a different place and will try to resolve it with different methods. Some will solve one color first and others will solve another color first. Even though they follow the same kind of algorithm to solve the puzzle they will start and end at a different place and their moves will be different at many occasions. It is  nearly impossible to have a exact same route taken by two experts. Big Market and Multiple Solutions Big Data is exactly like a Rubik’s cube – even though the goal of every organization and expert is same to get maximum out of the data, the route and the starting point are different for each organization and expert. As organizations are evaluating and architecting big data solutions they are also learning the ways and opportunities which are related to Big Data. There is not a single solution to big data as well there is not a single vendor which can claim to know all about Big Data. Honestly, Big Data is too big a concept and there are many players – different architectures, different vendors and different technology. What is Next? In this 31 days series we will be exploring many essential topics related to big data. I do not claim that you will be master of the subject after 31 days but I claim that I will be covering following topics in easy to understand language. Architecture of Big Data Big Data a Management and Implementation Different Technologies – Hadoop, Mapreduce Real World Conversations Best Practices Tomorrow In tomorrow’s blog post we will try to answer one of the very essential questions – What is 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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• Database – Beginning with Cloud Database As A Service

  - by Pinal Dave

  I love my weekend projects. Everybody does different activities in their weekend – like traveling, reading or just nothing. Every weekend I try to do something creative and different in the database world. The goal is I learn something new and if I enjoy my learning experience I share with the world. This weekend, I decided to explore Cloud Database As A Service – Morpheus. In my career I have managed many databases in the cloud and I have good experience in managing them. I should highlight that today’s applications use multiple databases from SQL for transactions and analytics, NoSQL for documents, In-Memory for caching to Indexing for search.  Provisioning and deploying these databases often require extensive expertise and time.  Often these databases are also not deployed on the same infrastructure and can create unnecessary latency between the application layer and the databases.  Not to mention the different quality of service based on the infrastructure and the service provider where they are deployed. Moreover, there are additional problems that I have experienced with traditional database setup when hosted in the cloud: Database provisioning & orchestration Slow speed due to hardware issues Poor Monitoring Tools High network latency Now if you have a great software and expert network engineer, you can continuously work on above problems and overcome them. However, not every organization have the luxury to have top notch experts in the field. Now above issues are related to infrastructure, but there are a few more problems which are related to software/application as well. Here are the top three things which can be problems if you do not have application expert: Replication and Clustering Simple provisioning of the hard drive space Automatic Sharding Well, Morpheus looks like a product build by experts who have faced similar situation in the past. The product pretty much addresses all the pain points of developers and database administrators. What is different about Morpheus is that it offers a variety of databases from MySQL, MongoDB, ElasticSearch to Reddis as a service.  Thus users can pick and chose any combination of these databases.  All of them can be provisioned in a matter of minutes with a simple and intuitive point and click user interface.  The Morpheus cloud is built on Solid State Drives (SSD) and is designed for high-speed database transactions.  In addition it offers a direct link to Amazon Web Services to minimize latency between the application layer and the databases. Here are the few steps on how one can get started with Morpheus. Follow along with me.  First go to http://www.gomorpheus.com and register for a new and free account. Step 1: Signup It is very simple to signup for Morpheus. Step 2: Select your database   I use MySQL for my daily routine, so I have selected MySQL. Upon clicking on the big red button to add Instance, it prompted a dialogue of creating a new instance.   Step 3: Create User Now we just have to create a user in our portal which we will use to connect to a database hosted at Morpheus. Click on your database instance and it will bring you to User Screen. Over here you will notice once again a big red button to create a new user. I created a user with my first name.   Step 4: Configure your MySQL client I used MySQL workbench and connected to MySQL instance, which I had created with an IP address and user.   That’s it! You are connecting to MySQL instance. Now you can create your objects just like you would create on your local box. You will have all the features of the Morpheus when you are working with your database. Dashboard While working with Morpheus, I was most impressed with its dashboard. In future blog posts, I will write more about this feature.  Also with Morpheus you use the same process for provisioning and connecting with other databases: MongoDB, ElasticSearch and Reddis. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: MySQL, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• top Tweets SOA Partner Community &ndash; June 2012

  - by JuergenKress

  Send your tweets @soacommunity #soacommunity and follow us at http://twitter.com/soacommunity Simone Geib Contact me directly for ideas how to improve http://bit.ly/advancedsoasuite and additional posts, presentations, white papers, #soasuite SOA CommunitySOA Community Newsletter May 2012 https://soacommunity.wordpress.com /2012/05/28/soa-community-newsletter-may-2012/ #soacommunity Simone Geib #soasuite advanced OTN page has become too cluttered. Broke it into separate pages to start with. http://bit.ly/advancedsoasuite SOA CommunitySOA Management with Enterprise Manager Cloud Control 12c and Business Transaction Management 12c Demo https://soacommunity.wordpress.com /2012/05/21/soa-management-with-enterprise-manager-cloud-control-12c-and-business-transaction-management-12c-demo/ #soacommunity OracleBlogs June Webcast: SOA Gateway Implementation and Troubleshooting (2 sessions) http://ow.ly/1kbRFA OTNArchBeatEvery cloud needs an SOA lining: analyst | @JoeMcKendrick http://zd.net/KTgMHk ServiceTechSymposium New session just posted to calendar: "NoSQL for Data Services, Data Virtualization & Big Data" by Guido Schmutz, Trivadis AG ://ow.ly/bjjOe OTNArchBeat?Every cloud needs an SOA lining: analyst | @JoeMcKendrick http://zd.net/KTgMHk Debra Lilley looks good - real proof people are using the apps ! RT @fteter:Very cool Fusion Applications Help site: http://bit.ly/L3nvOR #FusionApps OTNArchBeat How to Set JVM Parameters in Oracle SOA 11G | Francis Ip http://bit.ly/JBDYPj demed"rapid proliferation of cloud computing will drive convergence of SOA and cloud paradigms" http://ovum.com/2012/05/18/soa-paves-the-way-for-cloud/ SOA Community Sending out invitations to our advanced Fusion Middleware Summer Camps! Want to learn more register for the community http://www.oracle.com/goto/emea/soa SOA Community Middleware Oracle Excellence Awards 2012 - HAPPY NEW YEAR! https://soacommunity.wordpress.com/ 2012/05/31/middleware-oracle-excellence-awards-2012 happy-new-year/ #soacommunity #opn #opnaward #specialization #oracle Simone Geib #oraclesoa performance tuning resources. All in one: docs, blogs, WPs, ppts: http://bit.ly/soa_resources OracleBlogs Middleware Oracle Excellence Awards 2012 - HAPPY NEW YEAR! http://ow.ly/1k9ri0 ServiceTechSymposiumNew session just posted to Symposium calendar: "Service Modeling & BPM Business Value Patterns" by Jürgen Kress, Oracle http://www.servicetechsymposium.com/ agenda2012.php #service_modeling_and_bpm _business_value_patterns SOA Community Happy New Year #soacommunity thanks for the business! Time for a drink ;-) http://pic.twitter.com/zkK08KWB Jan van ZoggelUsing execute-sql() function for Name-Value pair lookups in Oracle Service Bus http://wp.me/p1H430-jZ SOA Community Middleware Oracle Excellence Awards 2012&ndash;HAPPY NEW YEAR! http://wp.me/p10C8u-q4 orclateamsoa A-Team Blog #ateam: BPM 11g Deployment & Instance Migration - I have seen a number of request lately asking how to http://ow.ly/1jZ0h8 OTNArchBeat Who should ‘own’ the Enterprise Architecture? | Michael Glas http://bit.ly/K0ge0Q Oracle UPK & Tutor TOMORROW! (June 23rd) - UPK Professional Webinar at Noon ET: Discover why user adoption is a key factor for the http://bit.ly/LjZjdx Sabine Leitner Finance Event im Design-Hotel beim Barbeque: 21. Juni FRA mit Kunden SV Informatik, Schufa, LBBW http://bit.ly/JtwE3v #Oracle @itevent OracleEnterpriseMgr SOA Management with Enterprise Manager Cloud Control 12c and Business Transaction Management 12c Demo http://ow.ly/b3WP1 #em12c ServiceTechSymposium New session just posted to Symposium calendar: "Elastic SOA in the Cloud" by Steve Millidge, C2B2 Consulting http://www.servicetechsymposium.com /agenda2012.php #elastic_soa_in_the_cloud OTNArchBeat Securing Heterogeneous Systems Using Oracle Web Services Manager by @rluttikhuizen & Jens Peters http://bit.ly/KjShFi Oracleteamsoa A-Team Blog #ateam: How to Set JVM Parameters in Oracle SOA 11G http://ow.ly/1k2cnl SOA Community Oracle Service Registry in an automated (Maven) SOA/BPM build http://redstack.wordpress.com /2012/05/22/using-oracle-service-registry-in-an-automated-maven-soabpm-build/ #soacommunity #redstack #soa #osr #opn SOA CommunityHigh demand for advanced Fusion Middleware Summer Camps! Want to learn more register for the #soacommunity http://www.oracle.com/goto/emea/soa OracleBlogs? How to Set JVM Parameters in Oracle SOA 11G http://ow.ly/1k1UTv SOA Community top Tweets SOA Partner Community &ndash; May 2012 http://wp.me/p10C8u-pP ServiceTechSymposium New session just posted to Symposium calendar: "SOA Governance at EDP: A Global Energy Company" by Manuel Rosa, Link http://www.servicetechsymposium.com/ agenda2012.php #soa_governance_at_edp For regular information on Oracle SOA Suite become a member in the SOA Partner Community for registration please visit  www.oracle.com/goto/emea/soa (OPN account required) Blog Twitter LinkedIn Mix Forum Technorati Tags: soacommunity,twitter,Oracle,SOA Community,Jürgen Kress,OPN,SOA,BPM

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• Big Data – Beginning Big Data Series Next Month in 21 Parts

  - by Pinal Dave

  Big Data is the next big thing. There was a time when we used to talk in terms of MB and GB of the data. However, the industry is changing and we are now moving to a conversation where we discuss about data in Petabyte, Exabyte and Zettabyte. It seems that the world is now talking about increased Volume of the data. In simple world we all think that Big Data is nothing but plenty of volume. In reality Big Data is much more than just a huge volume of the data. When talking about the data we need to understand about variety and volume along with volume. Though Big data look like a simple concept, it is extremely complex subject when we attempt to start learning the same. My Journey I have recently presented on Big Data in quite a few organizations and I have received quite a few questions during this roadshow event. I have collected all the questions which I have received and decided to post about them on the blog. In the month of October 2013, on every weekday we will be learning something new about Big Data. Every day I will share a concept/question and in the same blog post we will learn the answer of the same. Big Data – Plenty of Questions I received quite a few questions during my road trip. Here are few of the questions. I want to learn Big Data – where should I start? Do I need to know SQL to learn Big Data? What is Hadoop? There are so many organizations talking about Big Data, and every one has a different approach. How to start with big Data? Do I need to know Java to learn about Big Data? What is different between various NoSQL languages. I will attempt to answer most of the questions during the month long series in the next month. Big Data – Big Subject Big Data is a very big subject and I no way claim that I will be covering every single big data concept in this series. However, I promise that I will be indeed sharing lots of basic concepts which are revolving around Big Data. We will discuss from fundamentals about Big Data and continue further learning about it. I will attempt to cover the concept so simple that many of you might have wondered about it but afraid to ask. Your Role! During this series next month, I need your one help. Please keep on posting questions you might have related to big data as blog post comments and on Facebook Page. I will monitor them closely and will try to answer them as well during this series. Now make sure that you do not miss any single blog post in this series as every blog post will be linked to each other. You can subscribe to my feed or like my Facebook page or subscribe via email (by entering email in the blog post). Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Big Data, PostADay, SQL, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Bridging Two Worlds: Big Data and Enterprise Data

  - by Dain C. Hansen

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} The big data world is all the vogue in today’s IT conversations. It’s a world of volume, velocity, variety – tantalizing us with its untapped potential. It’s a world of transformational game-changing technologies that have already begun to alter the information management landscape. One of the reasons that big data is so compelling is that it’s a universal challenge that impacts every one of us. Whether it is healthcare, financial, manufacturing, government, retail - big data presents a pressing problem for many industries: how can so much information be processed so quickly to deliver the ‘bigger’ picture? With big data we’re tapping into new information that didn’t exist before: social data, weblogs, sensor data, complex content, and more. What also makes big data revolutionary is that it turns traditional information architecture on its head, putting into question commonly accepted notions of where and how data should be aggregated processed, analyzed, and stored. This is where Hadoop and NoSQL come in – new technologies which solve new problems for managing unstructured data. And now for some worst practices that I'd recommend that you please not follow: Worst Practice Lesson 1: Throw away everything that you already know about data management, data integration tools, and start completely over. One shouldn’t forget what’s already running in today’s IT. Today’s Business Analytics, Data Warehouses, Business Applications (ERP, CRM, SCM, HCM), and even many social, mobile, cloud applications still rely almost exclusively on structured data – or what we’d like to call enterprise data. This dilemma is what today’s IT leaders are up against: what are the best ways to bridge enterprise data with big data? And what are the best strategies for dealing with the complexities of these two unique worlds? Worst Practice Lesson 2: Throw away all of your existing business applications … because they don’t run on big data yet. Bridging the two worlds of big data and enterprise data means considering solutions that are complete, based on emerging Hadoop technologies (as well as traditional), and are poised for success through integrated design tools, integrated platforms that connect to your existing business applications, as well as and support real-time analytics. Leveraging these types of best practices translates to improved productivity, lowered TCO, IT optimization, and better business insights. Worst Practice Lesson 3: Separate out [and keep separate] your big data sandboxes from all the current enterprise IT systems. Don’t mix sand among playgrounds. We didn't tell you that you wouldn't get dirty doing this. Correlation between the two worlds is key. The real advantage to analyzing big data comes when you can correlate it with the existing data in your data warehouse or your current applications to make sense of the larger patterns. If you have not followed these worst practices 1-3 then you qualify for the first step of our journey: bridging the two worlds of enterprise data and big data. Over the next several weeks we’ll be discussing this topic along with several others around big data as it relates to data integration. We welcome you to join us in the conversation by following us on twitter on #BridgingBigData or download our latest white paper and resource kit: Big Data and Enterprise Data: Bridging Two Worlds.

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• Top 10 Linked Blogs of 2010

  - by Bill Graziano

  Each week I send out a SQL Server newsletter and include links to interesting blog posts.  I’ve linked to over 500 blog posts so far in 2010.  Late last year I started storing those links in a database so I could do a little reporting.  I tend to link to posts related to the OLTP engine.  I also try to link to the individual blogger in the group blogs.  Unfortunately that wasn’t possible for the SQLCAT and CSS blogs.  I also have a real weakness for posts related to PASS. These are the top 10 blogs that I linked to during the year ordered by the number of posts I linked to. Paul Randal – Paul writes extensively on the internals of the relational engine.  Lots of great posts around transactions, transaction log, disaster recovery, corruption, indexes and DBCC.  I also linked to many of his SQL Server myths posts. Glenn Berry – Glenn writes very interesting posts on how hardware affects SQL Server.  I especially like his posts on the various CPU platforms.  These aren’t necessarily topics that I’m searching for but I really enjoy reading them. The SQLCAT Team – This Microsoft team focuses on the largest and most interesting SQL Server installations.  The regularly publish white papers and best practices. SQL Server CSS Team – These are the top engineers from the Microsoft Customer Service and Support group.  These are the folks you finally talk to after your case has been escalated about 20 times.  They write about the interesting problems they find. Brent Ozar – The posts I linked to mostly focused on the relational engine: CPU, NUMA, SSD drives, performance monitoring, etc.  But Brent writes about a real variety of topics including blogging, social networking, speaking, the MCM, SQL Azure and anything else that seems to strike his fancy.  His posts are always well written and though provoking. Jeremiah Peschka – A number of Jeremiah’s posts weren’t about SQL Server.  He’s very active in the “NoSQL” area and I linked to a number of those posts.  I think it’s important for people to know what other technologies are out there. Brad McGehee – Brad writes about being a DBA including maintenance plans, DBA checklists, compression and audit. Thomas LaRock – I linked to a variety of posts from PBM to networking to 24 Hours of PASS to TDE.  Just a real variety of topics.  Tom always writes with an interesting style usually mixing in a movie theme and/or bacon. Aaron Bertrand – Many of my links this year were Denali features.  He also had a great series on bad habits to kick. Michael J. Swart – This last one surprised me.  There are some well known SQL Server bloggers below Michael on this list.  I linked to posts on indexes, hierarchies, transactions and I/O performance and a variety of other engine related posts.  All are interesting and well thought out.  Many of his non-SQL posts are also very good.  He seems to have an interest in puzzles and other brain teasers.  Michael, I won’t be surprised again!

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• Today's Links (6/30/2011)

  - by Bob Rhubart

  James Gosling Says He Doesn't Care About Java But here's the rest of the story: "What I really care about is the Java Virtual Machine as a concept," says Gosling, "because that is the thing that ties it all together; it's the thing that makes Java the language possible; it's the thing that makes things work on all kinds of different platforms; and it makes all kinds of languages able to coexist." Virtual Developer Day: SOA Accelerate Your Development with Oracle SOA Suite. Learn how in this FREE on-line workshop with Hands-on labs July 12th 9 am to 1:30 PM PST" July 12th 9 am to 1:30 PM PST Podcast: Toronto Architect Day Panel Discussion Part 3 (of 4) is now available, in which the panel (including Oracle ACE Director Cary Millsap and InfoQ editor and co-founder Floyd Marinescu) discusses public vs private cloud as the best strategy for small businesses and start-ups. WebLogic Weekly for June 27th, 2011 | James Bayer Bayer shares the latest resources for those with WebLogic on the brain. Griffiths Waite at Oracle Open World | Mark Simpson Oracle ACE Director Mark Simpson share information on the presentations he's scheduled to give at Oracle OpenWorld San Francisco 2011. Kscope Solid Service Bus Implementations Peter Paul van de Beek's Kscope11 presentation "is aimed at supporting architects and especially developers to choose the right integration infrastructure for a job." Migration To Java EE 6 With Spring 3 - ...Could Become "Interesting" | Adam Bien "Put simply, big data implies datasets so large they can't normally be processed using a standard transactional database," says David Dorf. "The term 'noSQL' is often used in this context as well." Book Review: "Designing With the Mind In Mind" | Abhinav Agarwal According to Abhinav Agarwal, Jeff Johnson's new book is about "the theory of how the mind perceives information, of how humans understand what they read, and how our eyes are attuned to paying attention to not just what's happening in front of us but also at the periphery of our vision." BPM 11g Advanced Workshop | Martien van den Akker Martien van den Akker shares his thoughts on both the workshop he recently attended and on the Oracle BPM 11g product. Fusion Applications - What You Need To Know: Product Families | Floyd Teter "Fusion Applications are organized into seven groups of related products called Product Families," observes Oracle ACE Director Floyd Teter. "While the product features are organized according to the Business Process Model and can cross the boundaries of product families, the product family groupings are an easy way to wrap your mind around Fusion Apps." Grid Control: Refreshing Weblogic Domains | Dave Best Dave Best shares tips for avoiding problems when using grid control to centrally manage/monitor your environment. Webcast: Oracle to Announce Datanomic Integration Plans The combination of Datanomic technology and the previous acquisition of Silver Creek Systems will deliver a complete, integrated and best-of-breed solution for Data Quality. Learn about Oracle’s strategy and product plans and how the new products acquired from Datanomic will impact your organization. July 19, 2011, 8:00am PT / 11:00am ET. Speakers include Michael Weingartner (Vice President, Product Development, Oracle), Martin Boyd (Senior Director, Product Strategy, Oracle), and Dain Hansen (Director, Product Marketing, Fusion Middleware, Oracle).

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• Visual Studio 2010 Best Practices

  - by Etienne Tremblay

  I’d like to thank Packt for providing me with a review version of Visual Studio 2010 Best Practices eBook. In fairness I also know the author Peter having seen him speak at DevTeach on many occasions.  I started by looking at the table of content to see what this book was about, knowing that “best practices” is a real misnomer I wanted to see what they were.  I really like the fact that he starts the book by really saying they are not really best practices but actually recommend practices.  As a Team Foundation Server user I found that chapter 2 was more for the open source crowd and I really skimmed it.  The portion on Branching was well documented, although I’m not a fan of the testing branch myself, but the rest was right on. The section on merge remote changes (bring the outside to you) paradigm is really important and was touched on. Chapter 3 has good solid practices on low level constructs like generics and exceptions. Chapter 4 dives into architectural practices like decoupling, distributed architecture and data based architecture.  DTOs and ORMs are touched on briefly as is NoSQL. Chapter 5 is about deployment and is really a great primer on all the “packaging” technologies like Visual Studio Setup and Deployment (depreciated in 2012), Click Once and WIX the major player outside of commercial solutions.  This is a nice section on how to move from VSSD to WIX this is going to be important in the coming years due to the fact that VS 2012 doesn’t support VSSD. In chapter 6 we dive into automated testing practices, including test coverage, mocking, TDD, SpecDD and Continuous Testing.  Peter covers all those concepts really nicely albeit succinctly. Being a book on recommended practices I find this is really good. I really enjoyed chapter 7 that gave me a lot of great tips to enhance my Visual Studio “experience”.  Tips on organizing projects where good.  Also even though I knew about configurations I like that he put that in there so you can move all your settings to another machine, a lot of people don’t know about that. Quick find and Resharper are also briefly covered.  He touches on macros (depreciated in 2012).  Finally he touches on Continuous Integration a very important concept in today’s ALM landscape. Chapter 8 is all about Parallelization, threads, Async, division of labor, reactive extensions.  All those concepts are touched on and again generalized approaches to those modern problems are giving.       Chapter 9 goes into distributed apps, the most used and accepted practice in the industry for .NET projects the chapter tackles concepts like Scalability, Messaging and Cloud (the flavor of the month of distributed apps, although I think this will stick ;-)).  He also looks a protocols TCP/UDP and how to debug distributed apps.  He touches on logging and health monitoring. Chapter 10 tackles recommended practices for web services starting with implementing WCF services, which goes into all sort of goodness like how to host in IIS or self-host.  How to manual test WCF services, also a section on authentication and authorization.  ASP.NET Web services are also touched on in that chapter All in all a good read, nice tips and accepted practices.  I like the conciseness of the subjects and Peter touches on a lot of things in this book and uses a lot of the current technologies flavors to explain the concepts.   Cheers, ET

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• Big Data – Operational Databases Supporting Big Data – Columnar, Graph and Spatial Database – Day 14 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned the importance of the Key-Value Pair Databases and Document Databases in the Big Data Story. In this article we will understand the role of Columnar, Graph and Spatial Database supporting Big Data Story. Now we will see a few of the examples of the operational databases. Relational Databases (The day before yesterday’s post) NoSQL Databases (The day before yesterday’s post) Key-Value Pair Databases (Yesterday’s post) Document Databases (Yesterday’s post) Columnar Databases (Tomorrow’s post) Graph Databases (Today’s post) Spatial Databases (Today’s post) Columnar Databases  Relational Database is a row store database or a row oriented database. Columnar databases are column oriented or column store databases. As we discussed earlier in Big Data we have different kinds of data and we need to store different kinds of data in the database. When we have columnar database it is very easy to do so as we can just add a new column to the columnar database. HBase is one of the most popular columnar databases. It uses Hadoop file system and MapReduce for its core data storage. However, remember this is not a good solution for every application. This is particularly good for the database where there is high volume incremental data is gathered and processed. Graph Databases For a highly interconnected data it is suitable to use Graph Database. This database has node relationship structure. Nodes and relationships contain a Key Value Pair where data is stored. The major advantage of this database is that it supports faster navigation among various relationships. For example, Facebook uses a graph database to list and demonstrate various relationships between users. Neo4J is one of the most popular open source graph database. One of the major dis-advantage of the Graph Database is that it is not possible to self-reference (self joins in the RDBMS terms) and there might be real world scenarios where this might be required and graph database does not support it. Spatial Databases  We all use Foursquare, Google+ as well Facebook Check-ins for location aware check-ins. All the location aware applications figure out the position of the phone with the help of Global Positioning System (GPS). Think about it, so many different users at different location in the world and checking-in all together. Additionally, the applications now feature reach and users are demanding more and more information from them, for example like movies, coffee shop or places see. They are all running with the help of Spatial Databases. Spatial data are standardize by the Open Geospatial Consortium known as OGC. Spatial data helps answering many interesting questions like “Distance between two locations, area of interesting places etc.” When we think of it, it is very clear that handing spatial data and returning meaningful result is one big task when there are millions of users moving dynamically from one place to another place & requesting various spatial information. PostGIS/OpenGIS suite is very popular spatial database. It runs as a layer implementation on the RDBMS PostgreSQL. This makes it totally unique as it offers best from both the worlds. Courtesy: mushroom network Tomorrow In tomorrow’s blog post we will discuss about very important components of the Big Data Ecosystem – Hive. 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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• Big Data – ClustrixDB – Extreme Scale SQL Database with Real-time Analytics, Releases Software Download – NewSQL

  - by Pinal Dave

  There are so many things to learn and there is so little time we all have. As we have little time we need to be selective to learn whatever we learn. I believe I know quite a lot of things in SQL but I still do not know what is around SQL. I have started to learn about NewSQL recently. If you wonder what is NewSQL I encourage all of you to read my blog post about NewSQL over here Big Data – Buzz Words: What is NewSQL – Day 10 of 21. NewSQL databases are quickly becoming popular – providing the scale of NoSQL with the SQL features and transactions. As a part of learning NewSQL database, I have recently started to learn about ClustrixDB. ClustrixDB has been the most mature NewSQL database used by some of the largest internet sites in the world for over 3 years, with extensive SQL support. In addition to scale, it provides fast real-time analytics by bringing massively parallel processing (MPP), available only in warehousing databases, to the transactional database. The reason I am more intrigued about learning ClustrixDB is their recent announcement on Oct 31. ClustrixDB was only available as an appliance, but now with their software release on Oct 31, everyone can use it. It is now available as forever free for up to 12 cores with community support, and there is a 45 day trial for unlimited cluster sizes. With the forever free world, I am indeed interested in ClustrixDB now. I know that few of the leading eCommerce sites in the world uses them for their transactional database. Here are few of the details I have quickly noted for ClustrixDB. ClustrixDB allows user to: Scale by simply adding nodes to the cluster with a single command Run billions of transactions a day Run fast real-time analytics Achieve high-availability with recovery from node failure Manages itself Easily migrate from MySQL as it is nearly plug-and-play compatible, use MySQL drivers, tools and replication. While I was going through the documentation I realized that ClustrixDB also has extensive support for SQL features including complex queries involving joins on a dozen or more tables, aggregates, sorts, sub-queries. It also supports stored procedures, triggers, foreign keys, partitioned and temporary tables, and fully online schema changes. It is indeed a very matured product and SQL solution. Indeed Clusterix sound very promising solution, I decided to dig a bit deeper to understand who are current customers of the Clustrix as they exist in the industry for quite a few years. Their client list is indeed very interesting and here is my quick research about them. Twoo.com – Europe’s largest social discovery (dating) site runs 4.4 Billion Transactions a day with table sizes over a Terabyte, on a 168 core cluster. EngageBDR – Top 3 in the online advertising category uses ClustrixDB to serve 6.9 billion ads a day through real-time bidding platform. Their reports went from 4 hours to 15 seconds. NoMoreRack – Top 2 fastest growing e-commerce company in US used ClustrixDB for high availability and fast growth through Amazon cloud. MakeMyTrip – India’s leading travel site runs on ClustrixDB with two clusters running as multi-master in Chennai and Bangalore. Many enterprises such as AOL, CSC, Rakuten, Symantec use ClustrixDB when their applications need scale. I must accept that I am impressed with the information I have learned so far and now is the time to do some hand’s on experience with their product. I want to learn this technology so in future when it is about NewSQL, I know what I am talking about. Read more why Clustrix explains why you ClustrixDB might be the right database for you. Download ClustrixDB with me today and install it on your machine so in future when we discuss the technical aspects of it, we all are on the same page. The software can be downloaded here. Reference : Pinal Dave (http://blog.SQLAuthority.com)Filed under: Big Data, MySQL, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Clustrix

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• Head in the Clouds

  - by Tony Davis

  We're just past the second anniversary of the launch of Windows Azure. A couple of years' experience with Azure in the industry has provided some obvious success stories, but has deflated some of the initial marketing hyperbole. As a general principle, Azure seems to work well in providing a Service-Oriented Architecture for services in enterprises that suffer wide fluctuations in demand. Instead of being obliged to provide hardware sufficient for the occasional peaks in demand, one can hire capacity only when it is needed, and the cost of hosting an application is no longer a capital cost. It enables companies to avoid having to scale out hardware for peak periods only to see it underused for the rest of the time. A customer-facing application such as a concert ticketing system, which suffers high demand in short, predictable bursts of activity, is a great example of an application that would work well in Azure. However, moving existing applications to Azure isn't something to be done on impulse. Unless your application is .NET-based, and consists of 'stateless' components that communicate via queues, you are probably in for a lot of redevelopment work. It makes most sense for IT departments who are already deep in this .NET mindset, and who also want 'grown-up' methods of staging, testing, and deployment. Azure fits well with this culture and offers, as a bonus, good Visual Studio integration. The most-commonly stated barrier to porting these applications to Azure is the problem of reconciling the use of the cloud with legislation for data privacy and security. Putting databases in the cloud is a sticky issue for many and impossible for some due to compliance and security issues, the need for direct control over data, and so on. In the face of feedback from the early adopters of Azure, Microsoft has broadened the architectural choices to cater for a wide range of requirements. As well as SQL Azure Database (SAD) and Azure storage, the unstructured 'BLOB and Entity-Attribute-Value' NoSQL storage alternative (which equates more closely with folders and files than a database), Windows Azure offers a wide range of storage options including use of services such as oData: developers who are programming for Windows Azure can simply choose the one most appropriate for their needs. Secondly, and crucially, the Windows Azure architecture allows you the freedom to produce hybrid applications, where only those parts that need cloud-based hosting are deployed to Azure, whereas those parts that must unavoidably be hosted in a corporate datacenter can stay there. By using a hybrid architecture, it will seldom, if ever, be necessary to move an entire application to the cloud, along with personal and financial data. For example that we could port to Azure only put those parts of our ticketing application that capture and process tickets orders. Once an order is captured, the financial side can be processed in our own data center. In short, Windows Azure seems to be a very effective way of providing services that are subject to wide but predictable fluctuations in demand. Have you come to the same conclusions, or do you think I've got it wrong? If you've had experience with Azure, would you recommend it? It would be great to hear from you. Cheers, Tony.

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• Java EE suitablity for a social network using Cassandra datastore ??

  - by Marcos

  We are in the process of making some important technology decisions for a social networking application. We're planning to have Cassandra(a NoSQL database to support efficient data storage). We would be using Hector(a Java client) to interact with Cassandra. 1.) Would Java EE be a good choice over PHP for a social networking application in terms of performance, scalabilty & complexities? 2.) Another possible implementation strategy, Is it suitable to have backend alone in Java and rest in PHP? 3.) What differences(as compared to PHP) it makes in terms of costs at various stages of application development, deployment and maintenance ? 4.) What are the things to keep in mind as we move along with Java development& deployment(as we are relatively new to the Java background) ? 5.) If you could list some major production deployments of similar type(social network) applications in Java. Thank you!

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• How do we greatly optimize our MySQL database (or replace it) when using joins?

  - by jkaz

  Hi there, This is the first time I'm approaching an extremely high-volume situation. This is an ad server based on MySQL. However, the query that is used incorporates a lot of JOINs and is generally just slow. (This is Rails ActiveRecord, btw) sel = Ads.find(:all, :select = '*', :joins = "JOIN campaigns ON ads.campaign_id = campaigns.id JOIN users ON campaigns.user_id = users.id LEFT JOIN countries ON countries.campaign_id = campaigns.id LEFT JOIN keywords ON keywords.campaign_id = campaigns.id", :conditions = [flashstr + "keywords.word = ? AND ads.format = ? AND campaigns.cenabled = 1 AND (countries.country IS NULL OR countries.country = ?) AND ads.enabled = 1 AND campaigns.dailyenabled = 1 AND users.uenabled = 1", kw, format, viewer['country'][0]], :order = order, :limit = limit) My questions: Is there an alternative database like MySQL that has JOIN support, but is much faster? (I know there's Postgre, still evaluating it.) Otherwise, would firing up a MySQL instance, loading a local database into memory and re-loading that every 5 minutes help? Otherwise, is there any way I could switch this entire operation to Redis or Cassandra, and somehow change the JOIN behavior to match the (non-JOIN-able) nature of NoSQL? Thank you!

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• Best architecture for a social media app

  - by Sky

  Hey guys, Im working on promising project that develops a new social media app for web and mobile. We are at begin defining functionalities. Nevertheless, I'm thinking ahead on architecture. So I'm asking: 1 - Whats the best plataform to develop the core of this aplication that will have a Rest API interface. 2 - Whats the best database that will scale and grow with my application. As far as I researched, these were the answers I found most interesting: For database: Cassandra NoSQL DB, amazing scalabilty, amazing write performance, good read performance (will be improved on 0.6). I think i will choose that one. Zookeer for transactions on Cassandra. I think that 2 technologies rly good for that propose. What do you think guys? On the front end that will serve the REST API, i dont have a final candidate. For this one i have questions based on Perfomance X Scalabilty X Fast Development/Maintenance. Java or .Net As far as I researched, brings the best balance of this requisits. Python, pearl and Rail, has the best (Fast Development/Maintenance), but sux on all other. C or C++ I dont even consider, because its (Fast Development/Maintenance) sux... So what do you guy think about it?

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• Speeding up inner-joins and subqueries while restricting row size and table membership

  - by hiffy

  I'm developing an rss feed reader that uses a bayesian filter to filter out boring blog posts. The Stream table is meant to act as a FIFO buffer from which the webapp will consume 'entries'. I use it to store the temporary relationship between entries, users and bayesian filter classifications. After a user marks an entry as read, it will be added to the metadata table (so that a user isn't presented with material they have already read), and deleted from the stream table. Every three minutes, a background process will repopulate the Stream table with new entries (i.e. whenever the daemon adds new entries after the checks the rss feeds for updates). Problem: The query I came up with is hella slow. More importantly, the Stream table only needs to hold one hundred unread entries at a time; it'll reduce duplication, make processing faster and give me some flexibility with how I display the entries. The query (takes about 9 seconds on 3600 items with no indexes): insert into stream(entry_id, user_id) select entries.id, subscriptions_users.user_id from entries inner join subscriptions_users on subscriptions_users.subscription_id = entries.subscription_id where subscriptions_users.user_id = 1 and entries.id not in (select entry_id from metadata where metadata.user_id = 1) and entries.id not in (select entry_id from stream where user_id = 1); The query explained: insert into stream all of the entries from a user's subscription list (subscriptions_users) that the user has not read (i.e. do not exist in metadata) and which do not already exist in the stream. Attempted solution: adding limit 100 to the end speeds up the query considerably, but upon repeated executions will keep on adding a different set of 100 entries that do not already exist in the table (with each successful query taking longer and longer). This is close but not quite what I wanted to do. Does anyone have any advice (nosql?) or know a more efficient way of composing the query?

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• Should I Use Anchor, Button Or Form Submit For "Follow" Feature In Rails

  - by James

  I am developing an application in Rails 3 using a nosql database. I am trying to add a "Follow" feature similar to twitter or github. In terms of markup, I have determined that there are three ways to do this. 1) Use a regular anchor. (Github Uses This Method) <a href="/users/follow?target=Joe">Follow</a> 2) Use a button. (Twitter Uses This Method) <button href="/friendships/create/">Follow</button> 3) Use a form with a submit button. (Has some advantages for me, but I haven't see anyone do it yet.) <form method="post" id="connection_new" class="connection_new" action="/users/follow"> <input type="hidden" value="60d7b563355243796dd8496e17d36329" name="target" id="target"> <input type="submit" value="Follow" name="commit" id="connection_submit"> </form> Since I want to store the user_id in the database and not the username, options 1 and 2 will force me to do a database query to get the actual user_id, whereas option 3 will allow me to store the user_id in a hidden form field so that I don't have to do any database lookups. I can just get the id from the params hash on form submission. I have successfully got each of these methods working, but I would like to know what is the best way to do this. Which way is more semantic, secure, better for spiders, etc...? Is there a reason both twitter and github don't use forms to do this? Any guidance would be appreciated. I am leaning towards using the form method since then I don't have to query the db to get the id of the user, but I am worried that there must be a reason the big guys are just using anchors or buttons for this. I am a newb so go easy on me if I am totally missing something. Thanks!

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• Do all the HTML5 storage systems work together ?

  - by azera

  While there are a lot of good stuff about html5, one thing I don't get is the redondant storage mechanism, first there is localstorage and sessionstorage, which are key value stores, one is for one instance of the app ("one tab"), and the other works for all the instances of that application so they can share data. Both are saved when you close your browser and have a limited size (usually 5MB), that's great and everything would be nice if we stopped there. But then there is the "Web SQL Database", which has the same security system as the localstorage, the same size limit, the same everything except it works like/is sqlite, with tables and sql syntax and all of that. And the bummer is, they don't work on the same data at all ! This is not two way to access your data, this is really two storage for every html 5 app out there (not created by default yes, but still you see my point). What I would like to know is, is there a reason for both of this mechanisms to exist at the same time ? Or did they just look at sql and nosql movement to pick the best then went "screw it let's add both !" ? Why not implement local/session storage as a table inside web sql db ?

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• mysql: storing arbitrary data

  - by Hailwood

  Background: I was asking a question on stack overflow regarding creating tables on the fly where this conversation ensued: This smells like a terrible idea! In fact, it smells just like this one. What in the world do you want to use this for? – deceze @deceze: very true, However, How else would you store the contents of these CSV files. They must be stored in mysql for indexing. The only solid fact about them is that they all have a mobile column with a standard format. The CSV can have an arbitrary amount of columns with an arbitrary amount of rows. They can (with no exaggeration) range from a single row, 35 column csv to an 80k row single column CSV. I am open to other ideas. – Hailwood There are many solutions for this, from attribute-value schemas to JSON storage and NoSQL storage. Open a new question about it. Whatever you do though, don't dynamically create tables! – deceze Question: So my question is, What would you say is the best way to store this data? Are you in agreement with deceze about not creating dynamic tables?

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• Cassandra instead of MySQL for social networking app

  - by Christopher McCann

  I am in the middle of building a new app which will have very similar features to Facebook and although obviously it wont ever have to deal with the likes of 400,000,000 million users it will still be used by a substantial user base and most of them will demand it run very very quickly. I have extensive experience with MySQL but a social app offers complexities which MySQL is not well suited too. I know Facebook, Twitter etc have moved towards Cassandra for a lot of their data but I am not sure how far to go with it. For example would you store such things as user data - username, passwords, addresses etc in Cassandra? Would you store e-mails, comments, status updates etc in Cassandra? I have also read alot that something like neo4j is much better for representing the friend relationships used by social apps as it is a graph database. I am only just starting down the NoSQL route so any guidance is greatly appreciated. Would anyone be able to advise me on this? I hope I am not being too general!

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