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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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  • 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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  • Why your Netapp is so slow...

    - by Darius Zanganeh
    Have you ever wondered why your Netapp FAS box is slow and doesn't perform well at large block workloads?  In this blog entry I will give you a little bit of information that will probably help you understand why it’s so slow, why you shouldn't use it for applications that read and write in large blocks like 64k, 128k, 256k ++ etc..  Of course since I work for Oracle at this time, I will show you why the ZS3 storage boxes are excellent choices for these types of workloads. Netapp’s Fundamental Problem The fundamental problem you have running these workloads on Netapp is the backend block size of their WAFL file system.  Every application block on a Netapp FAS ends up in a 4k chunk on a disk. Reference:  Netapp TR-3001 Whitepaper Netapp has proven this lacking large block performance fact in at least two different ways. They have NEVER posted an SPC-2 Benchmark yet they have posted SPC-1 and SPECSFS, both recently. In 2011 they purchased Engenio to try and fill this GAP in their portfolio. Block Size Matters So why does block size matter anyways?  Many applications use large block chunks of data especially in the Big Data movement.  Some examples are SAS Business Analytics, Microsoft SQL, Hadoop HDFS is even 64MB! Now let me boil this down for you.  If an application such MS SQL is writing data in a 64k chunk then before Netapp actually writes it on disk it will have to split it into 16 different 4k writes and 16 different disk IOPS.  When the application later goes to read that 64k chunk the Netapp will have to again do 16 different disk IOPS.  In comparison the ZS3 Storage Appliance can write in variable block sizes ranging from 512b to 1MB.  So if you put the same MSSQL database on a ZS3 you can set the specific LUNs for this database to 64k and then when you do an application read/write it requires only a single disk IO.  That is 16x faster!  But, back to the problem with your Netapp, you will VERY quickly run out of disk IO and hit a wall.  Now all arrays will have some fancy pre fetch algorithm and some nice cache and maybe even flash based cache such as a PAM card in your Netapp but with large block workloads you will usually blow through the cache and still need significant disk IO.  Also because these datasets are usually very large and usually not dedupable they are usually not good candidates for an all flash system.  You can do some simple math in excel and very quickly you will see why it matters.  Here are a couple of READ examples using SAS and MSSQL.  Assume these are the READ IOPS the application needs even after all the fancy cache and algorithms.   Here is an example with 128k blocks.  Notice the numbers of drives on the Netapp! Here is an example with 64k blocks You can easily see that the Oracle ZS3 can do dramatically more work with dramatically less drives.  This doesn't even take into account that the ONTAP system will likely run out of CPU way before you get to these drive numbers so you be buying many more controllers.  So with all that said, lets look at the ZS3 and why you should consider it for any workload your running on Netapp today.  ZS3 World Record Price/Performance in the SPC-2 benchmark ZS3-2 is #1 in Price Performance $12.08ZS3-2 is #3 in Overall Performance 16,212 MBPS Note: The number one overall spot in the world is held by an AFA 33,477 MBPS but at a Price Performance of $29.79.  A customer could purchase 2 x ZS3-2 systems in the benchmark with relatively the same performance and walk away with $600,000 in their pocket.

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  • Microsoft Cloud Day - the ups and downs

    - by Charles Young
    The term ‘cloud’ can sometimes obscure the obvious.  Today’s Microsoft Cloud Day conference in London provided a good example.  Scott Guthrie was halfway through what was an excellent keynote when he lost network connectivity.  This proved very disruptive to his presentation which centred on a series of demonstrations of the Azure platform in action.  Great efforts were made to find a solution, but no quick fix presented itself.  The venue’s IT facilities were dreadful – no WiFi, poor 3G reception (forget 4G…this is the UK) and, unbelievably, no-one on hand from the venue staff to help with infrastructure issues.  Eventually, after an unscheduled break, a solution was found and Scott managed to complete his demonstrations.  Further connectivity issues occurred during the day. I can say that the cause was prosaic.  A member of the venue staff had interfered with a patch board and inadvertently disconnected Scott Guthrie’s machine from the network by pulling out a cable. I need to state the obvious here.  If your PC is disconnected from the network it can’t communicate with other systems.  This could include a machine under someone’s desk, a mail server located down the hall, a server in the local data centre, an Internet search engine or even, heaven forbid, a role running on Azure. Inadvertently disconnecting a PC from the network does not imply a fundamental problem with the cloud or any specific cloud platform.  Some of the tweeted comments I’ve seen today are analogous to suggesting that, if you accidently unplug your microwave from the mains, this suggests some fundamental flaw with the electricity supply to your house.   This is poor reasoning, to say the least. As far as the conference was concerned, the connectivity issue in the keynote, coupled with some later problems in a couple of presentations, served to exaggerate the perception of poor organisation.   Software problems encountered before the conference prevented the correct set-up of a smartphone app intended to convey agenda information to attendees.  Although some information was available via this app, the organisers decided to print out an agenda at the last moment.  Unfortunately, the agenda sheet did not convey enough information, and attendees were forced to approach conference staff through the day to clarify locations of the various presentations. Despite these problems, the overwhelming feedback from conference attendees was very positive.  There was a real sense of excitement in the morning keynote.  For many, this was their first sight of new Azure features delivered in the ‘spring’ release.  The most common reaction I heard was amazement and appreciation that Azure’s new IaaS features deliver built-in template support for several flavours of Linux from day one.  This coupled with open source SDKs and several presentations on Azure’s support for Java, node.js, PHP, MongoDB and Hadoop served to communicate that the Azure platform is maturing quickly.  The new virtual network capabilities also surprised many attendees, and the much improved portal experience went down very well. So, despite some very irritating and disruptive problems, the event served its purpose well, communicating the breadth and depth of the newly upgraded Azure platform.  I enjoyed the day very much.

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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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  • Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

    - by Compudicted
    Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Weindows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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  • Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

    - by Compudicted
    Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review-again.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Windows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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  • Big Data – Basics of Big Data Architecture – Day 4 of 21

    - by Pinal Dave
    In yesterday’s blog post we understood how Big Data evolution happened. Today we will understand basics of the Big Data Architecture. Big Data Cycle Just like every other database related applications, bit data project have its development cycle. Though three Vs (link) for sure plays an important role in deciding the architecture of the Big Data projects. Just like every other project Big Data project also goes to similar phases of the data capturing, transforming, integrating, analyzing and building actionable reporting on the top of  the data. While the process looks almost same but due to the nature of the data the architecture is often totally different. Here are few of the question which everyone should ask before going ahead with Big Data architecture. Questions to Ask How big is your total database? What is your requirement of the reporting in terms of time – real time, semi real time or at frequent interval? How important is the data availability and what is the plan for disaster recovery? What are the plans for network and physical security of the data? What platform will be the driving force behind data and what are different service level agreements for the infrastructure? This are just basic questions but based on your application and business need you should come up with the custom list of the question to ask. As I mentioned earlier this question may look quite simple but the answer will not be simple. When we are talking about Big Data implementation there are many other important aspects which we have to consider when we decide to go for the architecture. Building Blocks of Big Data Architecture It is absolutely impossible to discuss and nail down the most optimal architecture for any Big Data Solution in a single blog post, however, we can discuss the basic building blocks of big data architecture. Here is the image which I have built to explain how the building blocks of the Big Data architecture works. Above image gives good overview of how in Big Data Architecture various components are associated with each other. In Big Data various different data sources are part of the architecture hence extract, transform and integration are one of the most essential layers of the architecture. Most of the data is stored in relational as well as non relational data marts and data warehousing solutions. As per the business need various data are processed as well converted to proper reports and visualizations for end users. Just like software the hardware is almost the most important part of the Big Data Architecture. In the big data architecture hardware infrastructure is extremely important and failure over instances as well as redundant physical infrastructure is usually implemented. NoSQL in Data Management NoSQL is a very famous buzz word and it really means Not Relational SQL or Not Only SQL. This is because in Big Data Architecture the data is in any format. It can be unstructured, relational or in any other format or from any other data source. To bring all the data together relational technology is not enough, hence new tools, architecture and other algorithms are invented which takes care of all the kind of data. This is collectively called NoSQL. Tomorrow Next four days we will answer the Buzz Words – Hadoop. 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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  • Cutting Subscriber Churn with Media Intelligence

    - by Oracle M&E
    There's lots of talk in media and entertainment companies about using "big data".  But it's often hard to see through the hype and understand how big data brings benefits in the real world.  How about being able to predict with 92% accuracy which subscribers intend to cancel their subscription - and put in place a renewal strategy to dramatically reduce that churn?  That's what Belgian media company De Persgroep has achieved with Oracle's Media Intelligence solution.  "One of the areas in which we're able to achieve beautiful results using big data is the churn prediction," De Persgroep's CIO Luc Verbist explains in a new Oracle video.  "Based on all the data that we collect on websites and all your behavior, payment behavior and so on, we're able to make a prediction model, which, with an accuracy of 92 percent, is able to predict that you probably won't renew your newspaper, anymore. So our approach to renewal is completely different to the people in that segment than towards the other people. And this has brought us a lot of value and a lot of customers who didn't stop their newspaper where else they would have done so." De Persgroep is using Oracle's Big Data Appliance, along with software from Oracle partner NGDATA to build up a detailed "DNA profile" of each individual customer, based on every interaction, in real time.  This means that any change in behavior - a drop in content consumption, a late subscription payment, a negative social media comment - is captured.  Applying advanced data modeling techniques automatically converts those raw interactions into data with real business meaning - like that customer's risk of churning. The very same data profile - comprising hundreds if individual dimensions - can simultaneously drive targeted marketing campaigns - informing audience about new content that's most relevant and encouraging them to subscribe.  It can power content recommendations and personalization right in the content sites and apps. And it can link directly into digital advertising networks via platforms like Oracle's BlueKai data management platform (DMP), to drive increased advertising CPMs. Using Oracle's Media Intelligence solution enables this across De Persgroep's business - comprising eight newspapers and 25 magazines published in Belgium and The Netherlands, and digital properties including websites with 6m daily unique visitors, along with TV and radio stations. "The company strategy is in fact a customer-centric strategy, so we want to get a 360-view about our customers, about our prospects. And the big data project helped us to achieve that goal," says Verbist. Using Oracle's Big Data Appliance to underpin the solution created huge savings.   "The selection of the Big Data Appliance was quite easy.  It was very quick to install, very easy to install, as well. And it was far cheaper than building our own Hadoop cluster. So it was in fact a non-brainer," Verbist explains. Applying Media Intelligence approach has yielded incredible results for De Persgroep, including: Improved products - with a new understanding of how readers are consuming print and digital content across the day Improved customer segmentation - driving a 6X improvement in customer prospecting and acquisition when contacting a specific segment Having the project up and running in three months And that has led to competitive benefits for De Persgroep, as Luc Verbist explains: "one of the results we saw since we started using big data is that we're able to increase the gap between we as the market leader, and the second [by] more than 20 percent."

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  • Big Data – How to become a Data Scientist and Learn Data Science? – Day 19 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the analytics in Big Data Story. In this article we will understand how to become a Data Scientist for Big Data Story. Data Scientist is a new buzz word, everyone seems to be wanting to become Data Scientist. Let us go over a few key topics related to Data Scientist in this blog post. First of all we will understand what is a Data Scientist. In the new world of Big Data, I see pretty much everyone wants to become Data Scientist and there are lots of people I have already met who claims that they are Data Scientist. When I ask what is their role, I have got a wide variety of answers. What is Data Scientist? Data scientists are the experts who understand various aspects of the business and know how to strategies data to achieve the business goals. They should have a solid foundation of various data algorithms, modeling and statistics methodology. What do Data Scientists do? Data scientists understand the data very well. They just go beyond the regular data algorithms and builds interesting trends from available data. They innovate and resurrect the entire new meaning from the existing data. They are artists in disguise of computer analyst. They look at the data traditionally as well as explore various new ways to look at the data. Data Scientists do not wait to build their solutions from existing data. They think creatively, they think before the data has entered into the system. Data Scientists are visionary experts who understands the business needs and plan ahead of the time, this tremendously help to build solutions at rapid speed. Besides being data expert, the major quality of Data Scientists is “curiosity”. They always wonder about what more they can get from their existing data and how to get maximum out of future incoming data. Data Scientists do wonders with the data, which goes beyond the job descriptions of Data Analysist or Business Analysist. Skills Required for Data Scientists Here are few of the skills a Data Scientist must have. Expert level skills with statistical tools like SAS, Excel, R etc. Understanding Mathematical Models Hands-on with Visualization Tools like Tableau, PowerPivots, D3. j’s etc. Analytical skills to understand business needs Communication skills On the technology front any Data Scientists should know underlying technologies like (Hadoop, Cloudera) as well as their entire ecosystem (programming language, analysis and visualization tools etc.) . Remember that for becoming a successful Data Scientist one require have par excellent skills, just having a degree in a relevant education field will not suffice. Final Note Data Scientists is indeed very exciting job profile. As per research there are not enough Data Scientists in the world to handle the current data explosion. In near future Data is going to expand exponentially, and the need of the Data Scientists will increase along with it. It is indeed the job one should focus if you like data and science of statistics. Courtesy: emc Tomorrow In tomorrow’s blog post we will discuss about various Big Data Learning resources. 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 – 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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  • Additional new material WebLogic Community

    - by JuergenKress
    Virtual Developer Conference On Demand - Register Updated Book: WebLogic 12c: Distinctive Recipes - Architecture, Development, Administration by Oracle ACE Director Frank Munz - Blog | YouTube Webcast: Migrating from GlassFish to WebLogic - Replay Reliance Commercial Finance Accelerates Time-to-Market, Improves IT Staff Productivity by 70% - Blog | Oracle Magazine Retrieving WebLogic Server Name and Port in ADF Application by Andrejus Baranovskis, Oracle Ace Director - Blog Using Oracle WebLogic 12c with NetBeans IDEOracle ACE Director Markus Eisele walks you through installing and configuring all the necessary components, and helps you get started with a simple Hello World project. Read the article. Video: Oracle A-Team ADF Mobile Persistence SampleThis video by Oracle Fusion Middleware A-Team architect Steven Davelaar demonstrates how to use the ADF Mobile Persistence Sample JDeveloper extension to generate a fully functional ADF Mobile application that reads and writes data using an ADF BC SOAP web service. Watch the video. Java ME 8 ReleaseDownload Java ME today! This release is an implementation of the Java ME 8 standards JSR 360 (CLDC 8) and JSR 361 (MEEP 8), and includes support of alignment with Java SE 8 language features and APIs, an enhanced services-enabled application platform, the ability to "right-size" the platform to address a wide range of target devices, and more. Learn more Download Java ME SDK 8It includes application development support for Oracle Java ME Embedded 8 platforms and includes plugins for NetBeans 8. See the Java ME 8 Developer Tools Documentation to learn JavaOne 2014 Early Bird RateRegister early to save $400 off the onsite price. With the release of Java 8 this year, we have exciting new sessions and an interactive demo space! NetBeans IDE 8.0 Patch UpdateThe NetBeans Team has released a patch for NetBeans IDE 8.0. Download it today to get fixes that enhance stability and performance. Java 8 Questions ForumFor any questions about this new release, please join the conversation on the Java 8 Questions Forum. Java ME 8: Getting Started with Samples and Demo CodeLearn in few steps how to get started with Java ME 8! The New Java SE 8 FeaturesJava SE 8 introduces enhancements such as lambda expressions that enable you to write more concise yet readable code, better utilize multicore systems, and detect more errors at compile time. See What's New in JDK 8 and the new Java SE 8 documentation portal. Pay Less for Java-Related Books!Save 20% on all new Oracle Press books related to Java. Download the free preview sampler for the Java 8 book written by Herbert Schildt, Maurice Naftain, Henrik Ebbers and J.F. DiMarzio. New book: EJB 3 in Action, Second Edition WebLogic 12c Does WebSockets Getting Started by C2B2 Video: Building Robots with Java Embedded Video: Nighthacking TV Watch presentations by Stephen Chin and community members about Java SE, Java Embedded, Java EE, Hadoop, Robots and more. Migrating the Spring Pet Clinic to Java EE 7 Trip report : Jozi JUG Java Day in Johannesburg How to Build GlassFish 4 from Source 4,000 posts later : The Aquarium WebLogic Partner Community For regular information become a member in the WebLogic Partner Community please visit: http://www.oracle.com/partners/goto/wls-emea ( OPN account required). If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Mix Forum Wiki Technorati Tags: WebLogic,WebLogic Community,Oracle,OPN,Jürgen Kress

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  • PASS Summit 2012: keynote and Mobile BI announcements #sqlpass

    - by Marco Russo (SQLBI)
    Today at PASS Summit 2012 there have been several announcements during the keynote. Moreover, other news have not been highlighted in the keynote but are equally if not more important for the BI community. Let’s start from the big news in the keynote (other details on SQL Server Blog): Hekaton: this is the codename for in-memory OLTP technology that will appear (I suppose) in the next release of the SQL Server relational engine. The improvement in performance and scalability is impressive and it enables new scenarios. I’m curious to see whether it can be used also to improve ETL performance and how it differs from using SSD technology. Updates on Columnstore: In the next major release of SQL Server the columnstore indexes will be updatable and it will be possible to create a clustered index with Columnstore index. This is really a great news for near real-time reporting needs! Polybase: in 2013 it will debut SQL Server 2012 Parallel Data Warehouse (PDW), which will include the Polybase technology. By using Polybase a single T-SQL query will run queries across relational data and Hadoop data. A single query language for both. Sounds really interesting for using BigData in a more integrated way with existing relational databases. And, of course, to load a data warehouse using BigData, which is the ultimate goal that we all BI Pro have, right? SQL Server 2012 SP1: the Service Pack 1 for SQL Server 2012 is available now and it enable the use of PowerPivot for SharePoint and Power View on a SharePoint 2013 installation with Excel 2013. Power View works with Multidimensional cube: the long-awaited feature of being able to use PowerPivot with Multidimensional cubes has been shown by Amir Netz in an amazing demonstration during the keynote. The interesting thing is that the data model behind was based on a many-to-many relationship (something that is not fully supported by Power View with Tabular models). Another interesting aspect is that it is Analysis Services 2012 that supports DAX queries run on a Multidimensional model, enabling the use of any future tool generating DAX queries on top of a Multidimensional model. There are still no info about availability by now, but this is *not* included in SQL Server 2012 SP1. So what about Mobile BI? Well, even if not announced during the keynote, there is a dedicated session on this topic and there are very important news in this area: iOS, Android and Microsoft mobile platforms: the commitment is to get data exploration and visualization capabilities working within June 2013. This should impact at least Power View and SharePoint/Excel Services. This is the type of UI experience we are all waiting for, in order to satisfy the requests coming from users and customers. The important news here is that native applications will be available for both iOS and Windows 8 so it seems that Android will be supported initially only through the web. Unfortunately we haven’t seen any demo, so it’s not clear what will be the offline navigation experience (and whether there will be one). But at least we know that Microsoft is working on native applications in this area. I’m not too surprised that HTML5 is not the magic bullet for all the platforms. The next PASS Business Analytics conference in 2013 seems a good place to see this in action, even if I hope we don’t have to wait other six months before seeing some demo of native BI applications on mobile platforms! Viewing Reporting Services reports on iPad is supported starting with SQL Server 2012 SP1, which has been released today. This is another good reason to install SP1 on SQL Server 2012. If you are at PASS Summit 2012, come and join me, Alberto Ferrari and Chris Webb at our book signing event tomorrow, Thursday 8 2012, at the bookstore between 12:00pm and 12:30pm, or follow one of our sessions!

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  • Fast Data - Big Data's achilles heel

    - by thegreeneman
    At OOW 2013 in Mark Hurd and Thomas Kurian's keynote, they discussed Oracle's Fast Data software solution stack and discussed a number of customers deploying Oracle's Big Data / Fast Data solutions and in particular Oracle's NoSQL Database.  Since that time, there have been a large number of request seeking clarification on how the Fast Data software stack works together to deliver on the promise of real-time Big Data solutions.   Fast Data is a software solution stack that deals with one aspect of Big Data, high velocity.   The software in the Fast Data solution stack involves 3 key pieces and their integration:  Oracle Event Processing, Oracle Coherence, Oracle NoSQL Database.   All three of these technologies address a high throughput, low latency data management requirement.   Oracle Event Processing enables continuous query to filter the Big Data fire hose, enable intelligent chained events to real-time service invocation and augments the data stream to provide Big Data enrichment. Extended SQL syntax allows the definition of sliding windows of time to allow SQL statements to look for triggers on events like breach of weighted moving average on a real-time data stream.    Oracle Coherence is a distributed, grid caching solution which is used to provide very low latency access to cached data when the data is too big to fit into a single process, so it is spread around in a grid architecture to provide memory latency speed access.  It also has some special capabilities to deploy remote behavioral execution for "near data" processing.   The Oracle NoSQL Database is designed to ingest simple key-value data at a controlled throughput rate while providing data redundancy in a cluster to facilitate highly concurrent low latency reads.  For example, when large sensor networks are generating data that need to be captured while analysts are simultaneously extracting the data using range based queries for upstream analytics.  Another example might be storing cookies from user web sessions for ultra low latency user profile management, also leveraging that data using holistic MapReduce operations with your Hadoop cluster to do segmented site analysis.  Understand how NoSQL plays a critical role in Big Data capture and enrichment while simultaneously providing a low latency and scalable data management infrastructure thru clustered, always on, parallel processing in a shared nothing architecture. Learn how easily a NoSQL cluster can be deployed to provide essential services in industry specific Fast Data solutions. See these technologies work together in a demonstration highlighting the salient features of these Fast Data enabling technologies in a location based personalization service. The question then becomes how do these things work together to deliver an end to end Fast Data solution.  The answer is that while different applications will exhibit unique requirements that may drive the need for one or the other of these technologies, often when it comes to Big Data you may need to use them together.   You may have the need for the memory latencies of the Coherence cache, but just have too much data to cache, so you use a combination of Coherence and Oracle NoSQL to handle extreme speed cache overflow and retrieval.   Here is a great reference to how these two technologies are integrated and work together.  Coherence & Oracle NoSQL Database.   On the stream processing side, it is similar as with the Coherence case.  As your sliding windows get larger, holding all the data in the stream can become difficult and out of band data may need to be offloaded into persistent storage.  OEP needs an extreme speed database like Oracle NoSQL Database to help it continue to perform for the real time loop while dealing with persistent spill in the data stream.  Here is a great resource to learn more about how OEP and Oracle NoSQL Database are integrated and work together.  OEP & Oracle NoSQL Database.

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  • New Version 3.1 Endeca Information Discovery Now Available

    - by Mike.Hallett(at)Oracle-BI&EPM
    Normal 0 false false false EN-GB X-NONE X-NONE MicrosoftInternetExplorer4 Business User Self-Service Data Mash-up Analysis and Discovery integrated with OBI11g and Hadoop Oracle Endeca Information Discovery 3.1 (OEID) is a major release that incorporates significant new self-service discovery capabilities for business users, including agile data mashup, extended support for unstructured analytics, and an even tighter integration with Oracle BI.  · Self-Service Data Mashup and Discovery Dashboards: business users can combine information from multiple sources, including their own up-loaded spreadsheets, to conduct analysis on the complete set.  Creating discovery dashboards has been made even easier by intuitive drag-and drop layouts and wizard-based configuration.  Business users can now build new discovery applications in minutes, without depending on IT. · Enhanced Integration with Oracle BI: OEID 3.1 enhances its’ native integration with Oracle Business Intelligence Foundation. Business users can now incorporate information from trusted BI warehouses, leveraging dimensions and attributes defined in Oracle’s Common Enterprise Information Model, but evolve them based on the varying day-to-day demands and requirements that they personally manage. · Deep Unstructured Analysis: business users can gain new insights from a wide variety of enterprise and public sources, helping companies to build an actionable Big Data strategy.  With OEID’s long-standing differentiation in correlating unstructured information with structured data, business users can now perform their own text mining to identify hidden concepts, without having to request support from IT. They can augment these insights with best in class keyword search and pattern matching, all in the context of rich, interactive visualizations and analytic summaries. · Enterprise-Class Self-Service Discovery:  OEID 3.1 enables IT to provide a powerful self-service platform to the business as part of a broader Business Analytics strategy, preserving the value of existing investments in data quality, governance, and security.  Business users can take advantage of IT-curated information to drive discovery across high volumes and varieties of data, and share insights with colleagues at a moment’s notice. · Harvest Content from the Web with the Endeca Web Acquisition Toolkit:  Oracle now provides best-of-breed data access to website content through the Oracle Endeca Web Acquisition Toolkit.  This provides an agile, graphical interface for developers to rapidly access and integrate any information exposed through a web front-end.  Organizations can now cost-effectively include content from consumer sites, industry forums, government or supplier portals, cloud applications, and myriad other web sources as part of their overall strategy for data discovery and unstructured analytics. For more information: OEID 3.1 OTN Software and Documentation Download And Endeca available for download on Software Delivery Cloud (eDelivery) New OEID 3.1 Videos on YouTube Oracle.com Endeca Site /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-fareast-language:EN-US;}

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  • MySQL, An Ideal Choice for The Cloud

    - by Bertrand Matthelié
    As the world's most popular web database, MySQL has quickly become the leading database for the cloud, with most providers offering MySQL-based services. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; 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;} Access our Resource Kit to discover: Why MySQL has become the leading database in the cloud, and how it addresses the critical attributes of cloud-based deployments How ISVs rely on MySQL to power their SaaS offerings Best practices to deploy the world’s most popular open source database in public and private clouds Normal 0 false false false EN-US X-NONE X-NONE You will also find out how you can leverage MySQL together with Hadoop and other technologies to unlock the value of Big Data, either on-premise or in the cloud. Access white papers, webinars, case studies and other resources in /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; 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;} our Resource Kit now!

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  • Starting out NLP - Python + large data set

    - by pencilNero
    Hi, I've been wanting to learn python and do some NLP, so have finally gotten round to starting. Downloaded the english wikipedia mirror for a nice chunky dataset to start on, and have been playing around a bit, at this stage just getting some of it into a sqlite db (havent worked with dbs in the past unfort). But I'm guessing sqlite is not the way to go for a full blown nlp project(/experiment :) - what would be the sort of things I should look at ? HBase (.. and hadoop) seem interesting, i guess i could run then im java, prototype in python and maybe migrate the really slow bits to java... alternatively just run Mysql.. but the dataset is 12gb, i wonder if that will be a problem? Also looked at lucene, but not sure how (other than breaking the wiki articles into chunks) i'd get that to work.. What comes to mind for a really flexible NLP platform (i dont really know at this stage WHAT i want to do.. just want to learn large scale lang analysis tbh) ? Many thanks.

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  • Is it possible to write map/reduce jobs for Amazon Elastic MapReduce using .NET?

    - by Chris
    Is it possible to write map/reduce jobs for Amazon Elastic MapReduce (http://aws.amazon.com/elasticmapreduce/) using .NET languages? In particular I would like to use C#. Preliminary research suggests not. The above URL's marketing text suggests you have a "choice of Java, Ruby, Perl, Python, PHP, R, or C++", without mentioning .NET languages. This Amazon thread (http://developer.amazonwebservices.com/connect/thread.jspa?messageID=136051 -- "Support for C# / F# map/reducers") explicitly says that "currently Amazon Elastic MapReduce does not support Mono platform or languages such as C# or F#." The above suggests that it can't be done. I'm wondering if there are any workarounds, though. For example, can I modify the Elastic MapReduce machine image for my account, and install Mono on there? An alternative, suggested by Amazon FAQs "Using Other Software Required by Your Jar" (http://docs.amazonwebservices.com/ElasticMapReduce/latest/DeveloperGuide/index.html?CHAP_AdvancedTopics.html) and "How to Use Additional Files and Libraries With the Mapper or Reducer" (http://docs.amazonwebservices.com/ElasticMapReduce/latest/DeveloperGuide/index.html?addl_files.html), is to make the first step of the Map/Reduce job be to install Mono on the local instance. That sounds kind of inefficient, but maybe it could work? Maybe a saner alternative would be to try to forgo the convenience of Elastic MapReduce, and manually set up my own Hadoop cluster on EC2. Then I assume I could install Mono without difficulty.

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  • Sharing storage between servers

    - by El Yobo
    I have a PHP based web application which is currently only using one webserver but will shortly be scaling up to another. In most regards this is pretty straightforward, but the application also stores a lot of files on the filesystem. It seems that there are many approaches to sharing the files between the two servers, from the very simple to the reasonably complex. These are the options that I'm aware of Simple network storage NFS SMB/CIFS Clustered filesystems Lustre GFS/GFS2 GlusterFS Hadoop DFS MogileFS What I want is for a file uploaded via one webserver be immediately available if accessed through the other. The data is extremely important and absolutely cannot be lost, so whatever is implemented needs to a) never lose data and b) have very high availability (as good as, or better, than a local filesystem). It seems like the clustered filesystems will also provide faster data access than local storage (for large files) but that isn't of vita importance at the moment. What would you recommend? Do you have any suggestions to add or anything specifically to look out for with the above options? Any suggestions on how to manage backup of data on the clustered filesystems?

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  • What database systems should an startup company consider?

    - by Am
    Right now I'm developing the prototype of a web application that aggregates large number of text entries from a large number of users. This data must be frequently displayed back and often updated. At the moment I store the content inside a MySQL database and use NHibernate ORM layer to interact with the DB. I've got a table defined for users, roles, submissions, tags, notifications and etc. I like this solution because it works well and my code looks nice and sane, but I'm also worried about how MySQL will perform once the size of our database reaches a significant number. I feel that it may struggle performing join operations fast enough. This has made me think about non-relational database system such as MongoDB, CouchDB, Cassandra or Hadoop. Unfortunately I have no experience with either. I've read some good reviews on MongoDB and it looks interesting. I'm happy to spend the time and learn if one turns out to be the way to go. I'd much appreciate any one offering points or issues to consider when going with none relational dbms?

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  • Database solution for 200million writes/day, monthly summarization queries

    - by sb
    Hello. I'm looking for help deciding on which database system to use. (I've been googling and reading for the past few hours; it now seems worthwhile to ask for help from someone with firsthand knowledge.) I need to log around 200 million rows (or more) per 8 hour workday to a database, then perform weekly/monthly/yearly summary queries on that data. The summary queries would be for collecting data for things like billing statements, eg. "How many transactions of type A did each user run this month?" (could be more complex, but that's the general idea). I can spread the database amongst several machines, as necessary, but I don't think I can take old data offline. I'll definitely need to be able to query a month's worth of data, maybe a year. These queries would be for my own use, and wouldn't need to be generated in real-time for an end-user (they could run overnight, if needed). Does anyone have any suggestions as to which databases would be a good fit? P.S. Cassandra looks like it would have no problem handling the writes, but what about the huge monthly table scans? Is anyone familiar with Cassandra/Hadoop MapReduce performance?

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  • Watch YouTube in Windows 7 Media Center

    - by Mysticgeek
    Have you been looking for a way to watch your favorite viral videos from YouTube and Dailymotion from the couch? Today we take a look at an easy to use plugin which allows you to watch streaming video in Windows 7 Media Center. Install Macrotube The first thing we need to do is download and install the plugin called Macrotube (link below) following the defaults through the install wizard. After it’s installed, open Windows 7 Media Center and you’ll find Macrotube in the main menu. Currently there are three services available…YouTube, Dailymotion, and MSN Soapbox. Just select the service where you want to check out some videos. You can browse through different subjects or categories… Or you can search the the service by typing in what you’re looking for…with your remote or keyboard. There is the ability to drill down you search content by date, rating, views, and relevance. There are a few settings available such as the language beta, auto updates, and appearance. Now just kick back and browse through the different services and watch what you want from the comfort of your couch or on your computer. Conclusion This neat project is still in development and the developer is continuing to add changes through updates. It only works with Windows 7 Media Player, but there is a 32 & 64-bit version. Sometimes we experiences certain videos that wouldn’t play and it did crash a few times, but that is to be expected with a work in progress. But overall, this is a cool plugin that will allow you to watch your favorite online content from WMC. Download Macrotube and get more details and troubleshooting help fro the GreenButton forum Similar Articles Productive Geek Tips Using Netflix Watchnow in Windows Vista Media Center (Gmedia)Integrate Hulu Desktop and Windows Media Center in Windows 7Automatically Start Windows 7 Media Center in Live TV ModeWatch TV Programming Without a TV Tuner In Window 7 Media CenterAutomatically Mount and View ISO files in Windows 7 Media Center TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 NachoFoto Searches Images in Real-time Office 2010 Product Guides Google Maps Place marks – Pizza, Guns or Strip Clubs Monitor Applications With Kiwi LocPDF is a Visual PDF Search Tool Download Free iPad Wallpapers at iPad Decor

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  • How many people will be with you during 24HOP?

    - by Rob Farley
    In less than a week, SQLPASS hosts another 24 Hours of PASS event, this time with an array of 24 female speakers (in honour of this month being Women’s History Month). Interestingly, the committee has had a few people ask if there are rules about how the event can be viewed, such as “How many people from any one organisation can watch it?” or “Does it matter if a few people are crowded around the same screen?” From a licensing and marketing perspective, there is value in knowing how many people are watching the event, but there are no restrictions about how the thing is viewed. In fact – if you’re planning to watch any of these events, I want to suggest an idea: Book a meeting room in your office with a projector, and watch 24HOP in there. If you’re planning to have it streaming in the background while you work, obviously this makes life a bit trickier. But if you’re planning to treat it as a training event (a 2-day conference if you like) and block out a bit of time for it (as well you should – there’s going to be some great stuff in there), then why not do it in a way that makes it so that other people can see that you’re watching it, and potentially join you. When an event like this runs, we can see how many different ‘people’ are attending each LiveMeeting session. What we can’t tell is how many actual people there are represented. Jessica Moss spoke to the Adelaide SQL Server User Group a few weeks ago via LiveMeeting, and LiveMeeting told us there were less than a dozen people attending. Really there were at least three times that number, because all the people in the room with me weren’t included. I’d love to imagine that every LiveMeeting attendee represented a crowd in a room, watching a shared screen. So there’s my challenge – don’t let your LiveMeeting session represent just you. Find a way of involving other people. At the very least, you’ll be able to discuss it with them afterwards. Now stick a comment on this post to let me know how many people are going to be joining you. :) If you’re not registered for the event yet, get yourself over to the SQLPASS site and make it happen.

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  • Perfect Your MySQL Database Administrators Skills

    - by Antoinette O'Sullivan
    With its proven ease-of-use, performance, and scalability, MySQL has become the leading database choice for web-based applications, used by high profile web properties including Google, Yahoo!, Facebook, YouTube, Wikipedia and thousands of mid-sized companies. Many organizations deploy both Oracle Database and MySQL side by side to serve different needs, and as a database professional you can find training courses on both topics at Oracle University! Check out the upcoming Oracle Database training courses and MySQL training courses. Even if you're only managing Oracle Databases at this point of time, getting familiar with MySQL Database will broaden your career path with growing job demand. Hone your skills as a MySQL Database Administrator by taking the MySQL for Database Administrators course which teaches you how to secure privileges, set resource limitations, access controls and describe backup and recovery basics. You also learn how to create and use stored procedures, triggers and views. You can take this 5 day course through three delivery methods: Training-on-Demand: Take this course at your own pace and at a time that suits you through this high-quality streaming video delivery. You also get to schedule time on a classroom environment to perform the hands-on exercises. Live-Virtual: Attend a live instructor led event from your own desk. 100s of events already of the calendar in many timezones. In-Class: Travel to an education center to attend this class. A sample of events is shown below:  Location  Date  Delivery Language  Budapest, Hungary  26 November 2012  Hungarian  Prague, Czech Republic  19 November 2012  Czech  Warsaw, Poland  10 December 2012  Polish  Belfast, Northern Ireland  26 November, 2012  English  London, England  26 November, 2012  English  Rome, Italy  19 November, 2012  Italian  Lisbon, Portugal  12 November, 2012  European Portugese  Porto, Portugal  21 January, 2013  European Portugese  Amsterdam, Netherlands  19 November, 2012  Dutch  Nieuwegein, Netherlands  8 April, 2013  Dutch  Barcelona, Spain  4 February, 2013  Spanish  Madrid, Spain  19 November, 2012  Spanish  Mechelen, Belgium  25 February, 2013  English  Windhof, Luxembourg  19 November, 2012  English  Johannesburg, South Africa  9 December, 2012  English  Cairo, Egypt  20 October, 2012  English  Nairobi, Kenya  26 November, 2012  English  Petaling Jaya, Malaysia  29 October, 2012  English  Auckland, New Zealand  5 November, 2012  English  Wellington, New Zealand  23 October, 2012  English  Brisbane, Australia  19 November, 2012  English  Edmonton, Canada  7 January, 2013  English  Vancouver, Canada  7 January, 2013  English  Ottawa, Canada  22 October, 2012  English  Toronto, Canada  22 October, 2012  English  Montreal, Canada  22 October, 2012  English  Mexico City, Mexico  10 December, 2012  Spanish  Sao Paulo, Brazil  10 December, 2012  Brazilian Portugese For more information on this course or any aspect of the MySQL curriculum, visit http://oracle.com/education/mysql.

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  • Silverlight Cream for March 06, 2010 -- #808

    - by Dave Campbell
    In this Issue: András Velvárt, felix corke, Colin Eberhardt, Christopher Bennage, Gergely Orosz, Entity Spaces Team Blog, Mike Taulty(-2-), Jit Ghosh, and Jesse Liberty. Shoutouts: Jeremy Likness expands on the Silverlight Team's post Vancouver Olympics - How'd We Do That? Gavin Wignall has a post up Creating a 360 photograph of an object with Silverlight Photosynth From SilverlightCream.com: Transforming an Ugly Duckling into a Graceful Swan With Expression Blend and Silverlight - Part 2 Intro Animation András Velvárt has part 2 of his Transformation series up at SilverlightShow... he's taking the initro animation to a new length, allowing playback even... cool video tutorial! Free Silverlight 4 beta skin! felix corke has a Silerlight 4 theme up for us all to use. If you like a dark theme like Blend, you'll like this... I like it! Linq to Visual Tree Colin Eberhardt has a great tutorial up for using LINQ to query the WPF or Silverlight Visual Tree while retaining the tree structure. He also has links out to other techniques. XAML Attributes on Separate Lines Christopher Bennage has a post up showing how to easily get all your XAML attributes on separate lines using a VS menu option... I didn't know that! Using built-in, embedded and streamed fonts in Silverlight Gergely Orosz has a post up at ScottLogic going over Fonts in Silverlight -- built-in, embedded, or streamed, and examples with code. EntitySpaces 2010 Two Part Series on Silverlight and WCF Entity Spaces Team Blog has a pair of videos up on Entity Spaces 2010, WCF, and Silverlight. Part 1 is the intro and explanation, part 2 is a full-up app demonstrating it. MEF, Silverlight and the DeploymentCatalog In an attempt to respond fully to a query, Mike Taulty literally pushed the record button and took off on what became a tutorial video on building a real Silverlight app utilizing MEF. Silverlight 4, Experiment with Pluggable Navigation and a WCF Data Service Mike Taulty has an experiment detailed on his blog about pluggable navigation and Silverlight 4. He walks through the history of how we got to this point then takes on in an example... good external links too Enhancing Silverlight Video Experiences with Contextual Data This is a post on the MSDN Magazine site where Jit Ghosh has a great long post about not only Smooth Streaming with Silverlight, but also adding context data to your video. When Is It OK To Hack? Read what all Jesse Liberty gets involved in when he's trying to get something out the door and has to work around a problem. Just about as interesting are the comments ... check it out and leave your own! Stay in the 'Light! Twitter SilverlightNews | Twitter WynApse | WynApse.com | Tagged Posts | SilverlightCream Join me @ SilverlightCream | Phoenix Silverlight User Group Technorati Tags: Silverlight    Silverlight 3    Silverlight 4    MIX10

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