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  • In Search of Automatic ORM with REST interface

    - by Dan Ray
    I have this wish that so far Google hasn't been able to fulfill. I want to find a package (ideally in PHP, because I know PHP, but I guess that's not a hard requirement) that you point at a database, it builds an ORM based on what it finds there, and exposes a REST interface over the web. Everything I've found in my searches requires a bunch of code--like, it wants you to build the classes for it, but it'll handle the REST request routing. Or it does database and relational stuff just fine, but you have to build your own methods for all the CRUD actions. That's dumb. REST is well defined. If I wanted to re-invent the wheel, I totally could, but I don't want to. Isn't there somebody who's built a one-shot super-simple auto-RESTing web service package?

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  • Columnstore Case Study #2: Columnstore faster than SSAS Cube at DevCon Security

    - by aspiringgeek
    Preamble This is the second in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in my big deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. See also Columnstore Case Study #1: MSIT SONAR Aggregations Why Columnstore? As stated previously, If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. The Customer DevCon Security provides home & business security services & has been in business for 135 years. I met DevCon personnel while speaking to the Utah County SQL User Group on 20 February 2012. (Thanks to TJ Belt (b|@tjaybelt) & Ben Miller (b|@DBADuck) for the invitation which serendipitously coincided with the height of ski season.) The App: DevCon Security Reporting: Optimized & Ad Hoc Queries DevCon users interrogate a SQL Server 2012 Analysis Services cube via SSRS. In addition, the SQL Server 2012 relational back end is the target of ad hoc queries; this DW back end is refreshed nightly during a brief maintenance window via conventional table partition switching. SSRS, SSAS, & MDX Conventional relational structures were unable to provide adequate performance for user interaction for the SSRS reports. An SSAS solution was implemented requiring personnel to ramp up technically, including learning enough MDX to satisfy requirements. Ad Hoc Queries Even though the fact table is relatively small—only 22 million rows & 33GB—the table was a typical DW table in terms of its width: 137 columns, any of which could be the target of ad hoc interrogation. As is common in DW reporting scenarios such as this, it is often nearly to optimize for such queries using conventional indexing. DevCon DBAs & developers attended PASS 2012 & were introduced to the marvels of columnstore in a session presented by Klaus Aschenbrenner (b|@Aschenbrenner) The Details Classic vs. columnstore before-&-after metrics are impressive. Scenario Conventional Structures Columnstore ? SSRS via SSAS 10 - 12 seconds 1 second >10x Ad Hoc 5-7 minutes (300 - 420 seconds) 1 - 2 seconds >100x Here are two charts characterizing this data graphically.  The first is a linear representation of Report Duration (in seconds) for Conventional Structures vs. Columnstore Indexes.  As is so often the case when we chart such significant deltas, the linear scale doesn’t expose some the dramatically improved values corresponding to the columnstore metrics.  Just to make it fair here’s the same data represented logarithmically; yet even here the values corresponding to 1 –2 seconds aren’t visible.  The Wins Performance: Even prior to columnstore implementation, at 10 - 12 seconds canned report performance against the SSAS cube was tolerable. Yet the 1 second performance afterward is clearly better. As significant as that is, imagine the user experience re: ad hoc interrogation. The difference between several minutes vs. one or two seconds is a game changer, literally changing the way users interact with their data—no mental context switching, no wondering when the results will appear, no preoccupation with the spinning mind-numbing hurry-up-&-wait indicators.  As we’ve commonly found elsewhere, columnstore indexes here provided performance improvements of one, two, or more orders of magnitude. Simplified Infrastructure: Because in this case a nonclustered columnstore index on a conventional DW table was faster than an Analysis Services cube, the entire SSAS infrastructure was rendered superfluous & was retired. PASS Rocks: Once again, the value of attending PASS is proven out. The trip to Charlotte combined with eager & enquiring minds let directly to this success story. Find out more about the next PASS Summit here, hosted this year in Seattle on November 4 - 7, 2014. DevCon BI Team Lead Nathan Allan provided this unsolicited feedback: “What we found was pretty awesome. It has been a game changer for us in terms of the flexibility we can offer people that would like to get to the data in different ways.” Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the second in a series of reports on columnstore implementations, results from DevCon Security, a live customer production app for which performance increased by factors of from 10x to 100x for all report queries, including canned queries as well as reducing time for results for ad hoc queries from 5 - 7 minutes to 1 - 2 seconds. As a result of columnstore performance, the customer retired their SSAS infrastructure. I invite you to consider leveraging columnstore in your own environment. Let me know if you have any questions.

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  • SQLAuthority News Microsoft SQL Server 2008 R2 PowerPivot for Microsoft Excel2010

    Microsoft has really and truly created some buzz for PowerPivot. I have been asked to show the demo of Powerpivot in recent time even when I am doing relational database training. Attached is the few details where everyone can download PowerPivot and use the same. Microsoft SQL Server 2008 R2 – PowerPivot for Microsoft Excel [...]...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • ROracle support for TimesTen In-Memory Database

    - by Sam Drake
    Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in version 1.1-4, ROracle includes support for the Oracle Times Ten In-Memory Database, version 11.2.2. TimesTen is a relational database providing very fast and high throughput through its memory-centric architecture.  TimesTen is designed for low latency, high-volume data, and event and transaction management. A TimesTen database resides entirely in memory, so no disk I/O is required for transactions and query operations. TimesTen is used in applications requiring very fast and predictable response time, such as real-time financial services trading applications and large web applications. TimesTen can be used as the database of record or as a relational cache database to Oracle Database. ROracle provides an interface between R and the database, providing the rich functionality of the R statistical programming environment using the SQL query language. ROracle uses the OCI libraries to handle database connections, providing much better performance than standard ODBC.The latest ROracle enhancements include: Support for Oracle TimesTen In-Memory Database Support for Date-Time using R's POSIXct/POSIXlt data types RAW, BLOB and BFILE data type support Option to specify number of rows per fetch operation Option to prefetch LOB data Break support using Ctrl-C Statement caching support Times Ten 11.2.2 contains enhanced support for analytics workloads and complex queries: Analytic functions: AVG, SUM, COUNT, MAX, MIN, DENSE_RANK, RANK, ROW_NUMBER, FIRST_VALUE and LAST_VALUE Analytic clauses: OVER PARTITION BY and OVER ORDER BY Multidimensional grouping operators: Grouping clauses: GROUP BY CUBE, GROUP BY ROLLUP, GROUP BY GROUPING SETS Grouping functions: GROUP, GROUPING_ID, GROUP_ID WITH clause, which allows repeated references to a named subquery block Aggregate expressions over DISTINCT expressions General expressions that return a character string in the source or a pattern within the LIKE predicate Ability to order nulls first or last in a sort result (NULLS FIRST or NULLS LAST in the ORDER BY clause) Note: Some functionality is only available with Oracle Exalytics, refer to the TimesTen product licensing document for details. Connecting to TimesTen is easy with ROracle. Simply install and load the ROracle package and load the driver. > install.packages("ROracle") > library(ROracle) Loading required package: DBI > drv <- dbDriver("Oracle") Once the ROracle package is installed, create a database connection object and connect to a TimesTen direct driver DSN as the OS user. > conn <- dbConnect(drv, username ="", password="", dbname = "localhost/SampleDb_1122:timesten_direct") You have the option to report the server type - Oracle or TimesTen? > print (paste ("Server type =", dbGetInfo (conn)$serverType)) [1] "Server type = TimesTen IMDB" To create tables in the database using R data frame objects, use the function dbWriteTable. In the following example we write the built-in iris data frame to TimesTen. The iris data set is a small example data set containing 150 rows and 5 columns. We include it here not to highlight performance, but so users can easily run this example in their R session. > dbWriteTable (conn, "IRIS", iris, overwrite=TRUE, ora.number=FALSE) [1] TRUE Verify that the newly created IRIS table is available in the database. To list the available tables and table columns in the database, use dbListTables and dbListFields, respectively. > dbListTables (conn) [1] "IRIS" > dbListFields (conn, "IRIS") [1] "SEPAL.LENGTH" "SEPAL.WIDTH" "PETAL.LENGTH" "PETAL.WIDTH" "SPECIES" To retrieve a summary of the data from the database we need to save the results to a local object. The following call saves the results of the query as a local R object, iris.summary. The ROracle function dbGetQuery is used to execute an arbitrary SQL statement against the database. When connected to TimesTen, the SQL statement is processed completely within main memory for the fastest response time. > iris.summary <- dbGetQuery(conn, 'SELECT SPECIES, AVG ("SEPAL.LENGTH") AS AVG_SLENGTH, AVG ("SEPAL.WIDTH") AS AVG_SWIDTH, AVG ("PETAL.LENGTH") AS AVG_PLENGTH, AVG ("PETAL.WIDTH") AS AVG_PWIDTH FROM IRIS GROUP BY ROLLUP (SPECIES)') > iris.summary SPECIES AVG_SLENGTH AVG_SWIDTH AVG_PLENGTH AVG_PWIDTH 1 setosa 5.006000 3.428000 1.462 0.246000 2 versicolor 5.936000 2.770000 4.260 1.326000 3 virginica 6.588000 2.974000 5.552 2.026000 4 <NA> 5.843333 3.057333 3.758 1.199333 Finally, disconnect from the TimesTen Database. > dbCommit (conn) [1] TRUE > dbDisconnect (conn) [1] TRUE We encourage you download Oracle software for evaluation from the Oracle Technology Network. See these links for our software: Times Ten In-Memory Database,  ROracle.  As always, we welcome comments and questions on the TimesTen and  Oracle R technical forums.

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  • Cloud INaaS from Data Integration companies

    - by llaszews
    Traditional integration IT vendors are also starting to offer INaaS. Infomatica has been the most aggressive integration vendor when it comes to offering INaaS. Informatica has offered INaaS for over five years and continues to add capabilities, has a number of high profile references, and also continues to add out-of-the-box cloud integration with major COTS and SaaS providers. The Informatica Marketplace contains pre-packaged Informatica Cloud end-points and plug-ins. One such MarketPlace solution, is integration with Oracle E-Business Suite using Informatica integration. The Informatica E-Business Suite INaaS offering includes automatic loading and extraction of data between Salesforce CRM and on-premise systems, cloud-to-cloud, flat files, and relational database. The entire Informatica Cloud integration solution runs in an Informatica managed facility (PaaS). When running in a PaaS environment, Informatica offers an option to keep an exact copy of your cloud-based data on-premise for archival, compliance, and enterprise reporting requirements.

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  • Strategies for Indexing Custom Fields in RavenDB

    - by Adrian Thompson Phillips
    In the relational database world, if I was developing a CRM system and wanted to have the user add their own custom fields that are searchable, I could have tables that store the name of the new column, the data type and the value, etc. (which would be less inefficient to index) or I could use the less elegant (but more searchable) solution that software like Dynamics and SharePoint use, whereas I create a load of columns on my aggregate root called CustomInt1, CustomInt2, etc. (which looks dirty and has a limit of how many custom fields a user can have, but has indexing advantages). But my questions is this, in NoSQL databases, what would be the best way of achieving the same thing? My priority would be for searchability. So what would be the best way to store this data? If I used a predefined set of properties (i.e. CustomData1, CustomData2, etc.), because these are all stored as JSON (i.e. strings) in the database, does this make it simpler because I don't have to worry about data types?

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  • [News] Le mouvement NoSQL et MongoDB

    Le mouvement "NoSQL" est une communaut? cr??e dans le but de promouvoir les bases de donn?es non relationnelles (d'o? le terme NoSQL). Dans cet hymne ? ce mouvement, Michael Kennedy, instructeur pour DevelopMentor, d?crit les pr?ceptes de NoSQL en l'illustrant ? travers un moteur finalement peu connu du grand public, MongoDB. A lire, tr?s int?ressant m?me si on ne partage pas l'opinion de cette communaut? : "(...) A basic SQL Server cluster might run you $100,000 just to get it up and running on decent hardware. Rather than leveraging crazy scaling-up options, the NoSQL databases let you scale-out. They make this possible (dare I say easy?) by dropping the relational aspects of a database (...) "

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  • Would a model like this translate well to a document or graph database?

    - by Eric
    I'm trying to understand what types of models that I have traditionally persisted relationally would translate well to some kind of NoSQL database. Suppose I have a model with the following relationships: Product 1-----0..N Order Customer 1-----0..N Order And suppose I need to frequently query things like All Orders, All Products, All Customers, All Orders for Given Customer, All Orders for Given Product. My feeling is that this kind of model would not denormalize cleanly - If I had Product and Customer documents with embedded Orders, both documents would have duplicate orders. So I think I'd need separate documents for all three entities. Does a characteristic like this typically indicate that a document database is not well suited for a given model? Generally speaking, would a document database perform as well as a relational database in this kind of situation? I know very little about graph databases, but I understand that a graph database handles relationships more performantly than a document database - would a graph database be suited for this kind of model?

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  • Because of over incumbent patents, is it possible to safely develop any software without the risk of legal action?

    - by Chris Barry
    Take this System and method for restricting user access rights on the internet based on rating information stored in a relational database There are hundreds of thousands of them out there. So basically you can't program anything really without breaching one of thousands of software patents. If your program succeeds you will be sued by someone! Does this happen all the time and people get silenced? Do trendy startups get hit by things like this? Surely all major web properties would have been hit by the example above by AT&T?

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  • Google I/O 2010 - Data migration in App Engine

    Google I/O 2010 - Data migration in App Engine Google I/O 2010 - Data migration in App Engine App Engine 201 Matthew Blain Learn about the App Engine bulk loader and see an example of migrating data from an external data source into the app engine datastore--and back out. Do you have data stored in a traditional, relational DB which you'd like to upload to App Engine? This session will teach you how. For all I/O 2010 sessions, please go to code.google.com From: GoogleDevelopers Views: 6 0 ratings Time: 44:26 More in Science & Technology

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  • Learn a NoSQL or become a badass with traditional RDMS - Where is/will the work be?

    - by beck
    I'm half way through my MSc and am thinking about my dissertation which I get 3 months to work on full time. Im very comfortable with the traditional Relational Database, the question is should I work on a project where I get a good understanding of something like Cassandra, or should I really push my RDMS knowledge to the limit. Getting great at something like MySQL is a solid safe option, will there really be much work for me with Cassandra in my tool belt? I would love to do either.... Thanks for your opinions and advice.

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  • SQL Peer-to-Peer Dynamic Structured Data Processing Collaboration

    Unstructured and XML semi-structured data is now used more than structured data. But fixed structured data still keeps businesses running day in and day out, which requires consistent predictable highly principled processing for correct results. For this reason, it would be very useful to have a general purpose SQL peer-to-peer collaboration capability that can utilize highly principled hierarchical data processing and its flexible and advanced structured processing to support dynamically structured data and its dynamic structured processing. This flexible dynamic structured processing can change the structure of the data as necessary for the required processing while preserving the relational and hierarchical data principles. This processing will perform freely across remote unrelated peer locations anytime and transparently process unpredictable and unknown structured data and data type changes automatically for immediate processing using automatic metadata maintenance.

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  • ROracle support for TimesTen In-Memory Database

    - by Sherry LaMonica
    Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in version 1.1-4, ROracle includes support for the Oracle Times Ten In-Memory Database, version 11.2.2. TimesTen is a relational database providing very fast and high throughput through its memory-centric architecture.  TimesTen is designed for low latency, high-volume data, and event and transaction management. A TimesTen database resides entirely in memory, so no disk I/O is required for transactions and query operations. TimesTen is used in applications requiring very fast and predictable response time, such as real-time financial services trading applications and large web applications. TimesTen can be used as the database of record or as a relational cache database to Oracle Database. ROracle provides an interface between R and the database, providing the rich functionality of the R statistical programming environment using the SQL query language. ROracle uses the OCI libraries to handle database connections, providing much better performance than standard ODBC.The latest ROracle enhancements include: Support for Oracle TimesTen In-Memory Database Support for Date-Time using R's POSIXct/POSIXlt data types RAW, BLOB and BFILE data type support Option to specify number of rows per fetch operation Option to prefetch LOB data Break support using Ctrl-C Statement caching support Times Ten 11.2.2 contains enhanced support for analytics workloads and complex queries: Analytic functions: AVG, SUM, COUNT, MAX, MIN, DENSE_RANK, RANK, ROW_NUMBER, FIRST_VALUE and LAST_VALUE Analytic clauses: OVER PARTITION BY and OVER ORDER BY Multidimensional grouping operators: Grouping clauses: GROUP BY CUBE, GROUP BY ROLLUP, GROUP BY GROUPING SETS Grouping functions: GROUP, GROUPING_ID, GROUP_ID WITH clause, which allows repeated references to a named subquery block Aggregate expressions over DISTINCT expressions General expressions that return a character string in the source or a pattern within the LIKE predicate Ability to order nulls first or last in a sort result (NULLS FIRST or NULLS LAST in the ORDER BY clause) Note: Some functionality is only available with Oracle Exalytics, refer to the TimesTen product licensing document for details. Connecting to TimesTen is easy with ROracle. Simply install and load the ROracle package and load the driver. > install.packages("ROracle") > library(ROracle) Loading required package: DBI > drv <- dbDriver("Oracle") Once the ROracle package is installed, create a database connection object and connect to a TimesTen direct driver DSN as the OS user. > conn <- dbConnect(drv, username ="", password="", dbname = "localhost/SampleDb_1122:timesten_direct") You have the option to report the server type - Oracle or TimesTen? > print (paste ("Server type =", dbGetInfo (conn)$serverType)) [1] "Server type = TimesTen IMDB" To create tables in the database using R data frame objects, use the function dbWriteTable. In the following example we write the built-in iris data frame to TimesTen. The iris data set is a small example data set containing 150 rows and 5 columns. We include it here not to highlight performance, but so users can easily run this example in their R session. > dbWriteTable (conn, "IRIS", iris, overwrite=TRUE, ora.number=FALSE) [1] TRUE Verify that the newly created IRIS table is available in the database. To list the available tables and table columns in the database, use dbListTables and dbListFields, respectively. > dbListTables (conn) [1] "IRIS" > dbListFields (conn, "IRIS") [1] "SEPAL.LENGTH" "SEPAL.WIDTH" "PETAL.LENGTH" "PETAL.WIDTH" "SPECIES" To retrieve a summary of the data from the database we need to save the results to a local object. The following call saves the results of the query as a local R object, iris.summary. The ROracle function dbGetQuery is used to execute an arbitrary SQL statement against the database. When connected to TimesTen, the SQL statement is processed completely within main memory for the fastest response time. > iris.summary <- dbGetQuery(conn, 'SELECT SPECIES, AVG ("SEPAL.LENGTH") AS AVG_SLENGTH, AVG ("SEPAL.WIDTH") AS AVG_SWIDTH, AVG ("PETAL.LENGTH") AS AVG_PLENGTH, AVG ("PETAL.WIDTH") AS AVG_PWIDTH FROM IRIS GROUP BY ROLLUP (SPECIES)') > iris.summary SPECIES AVG_SLENGTH AVG_SWIDTH AVG_PLENGTH AVG_PWIDTH 1 setosa 5.006000 3.428000 1.462 0.246000 2 versicolor 5.936000 2.770000 4.260 1.326000 3 virginica 6.588000 2.974000 5.552 2.026000 4 <NA> 5.843333 3.057333 3.758 1.199333 Finally, disconnect from the TimesTen Database. > dbCommit (conn) [1] TRUE > dbDisconnect (conn) [1] TRUE We encourage you download Oracle software for evaluation from the Oracle Technology Network. See these links for our software: Times Ten In-Memory Database,  ROracle.  As always, we welcome comments and questions on the TimesTen and  Oracle R technical forums.

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  • Q&amp;A: Will my favourite ORM Foo work with SQL Azure?

    - by Eric Nelson
    short answer: Quite probably, as SQL Azure is very similar to SQL Server longer answer: Object Relational Mappers (ORMs) that work with SQL Server are likely but not guaranteed to work with SQL Azure. The differences between the RDBMS versions are small – but may cause problems, for example in tools used to create the mapping between objects and tables or in generated SQL from the ORM which expects “certain things” :-) More specifically: ADO.NET Entity Framework / LINQ to Entities can be used with SQL Azure, but the Visual Studio designer does not currently work. You will need to point the designer at a version of your database running of SQL Server to create the mapping, then change the connection details to run against SQL Azure. LINQ to SQL has similar issues to ADO.NET Entity Framework above NHibernate can be used against SQL Azure DevExpress XPO supports SQL Azure from version 9.3 DataObjects.Net supports SQL Azure Open Access from Telerik works “seamlessly”  - their words not mine :-) The list above is by no means comprehensive – please leave a comment with details of other ORMs that work (or do not work) with SQL Azure. Related Links: General guidelines and limitations of SQL Azure SQL Azure vs SQL Server

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  • Random MongoDb Syntax: Updates

    - by Liam McLennan
    I have a MongoDb collection called tweets. Each document has a property system_classification. If the value of system_classification is ‘+’ I want to change it to ‘positive’. For a regular relational database the query would be: update tweets set system_classification = 'positive' where system_classification = '+' the MongoDb equivalent is: db.tweets.update({system_classification: '+'}, {$set: {system_classification:'positive'}}, false, true) Parameter Description { system_classification: '+' } the first parameter identifies the documents to select { $set: { system_classification: 'positive' } } the second parameter is an operation ($set) and the parameter to that operation {system_classification: ‘positive’} false the third parameter indicates if this is a regular update or an upsert (true for upsert) true the final parameter indicates if the operation should be applied to all selected documents (or just the first)

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  • Software development, basics of design, conventions and scalability

    - by goce ribeski
    I need to improve my programming skills in order to achieve better scalability for the software I'm working on. Purpose is to learn the rules of adding new modules and features, so when it comes to maintaining existing ones there is some concept. So, I'm looking for a good book, tutorial or websites where I can continue to read about this. Currently, what I know and what I do is: to design relational database(3NF), make separate class for each table put that in MVC implement modular programming ...write code and hope for the best... I presume that next things I need to learn more deeply are: programming codex(naming, commenting, conventions...), organize functions building interfaces organizing custom made libraries, organizing API that I'm using, documenting, team work... ... At last what my job is, it does't need to affect your answer, PHP CodeIgniter developer.

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  • Upcoming Database Design Pre-Cons

    - by drsql
    In July and October, I will be doing my "How To Design a Relational Database" full day conference in two places. First on July 26 for the East Iowa SQL Saturday , and then for the big daddy SQLPASS Summit in Charlotte, NC on October 14. You can see the entire abstract here on the SQL PASS site. It is essentially the same concept as last year, but this year I am making a few big changes to really give the people what they have desired (and am truly glad to have a swing at it several months...(read more)

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  • how to convince other we should move to hadoop?

    - by Ramy
    Everything I've read about Hadoop seems like exactly the technology we need to make our enterprise more scalable. We have terabytes of raw data that is in non-relational form (text files of some kind). We're quickly approaching the upper limits of what our centralized file server can handle and everyone is aware of this. Most people on the tech team, especially the more junior members of the tech team are all in favor of moving from the central file system to HDFS. The problem is, there is one key (most senior, etc.) member of the team who is resisting this change and every time Hadoop comes up, he tells us that we could simply add another file server and be in the clear. So, my question (and yes, it's really subjective, but I need more help with this than any of my other questions) is what steps can we take to get upper management to move forward with Hadoop despite the hesitation of one member of the team?

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  • how to convince other we should move to hadoop?

    - by Ramy
    Everything I've read about Hadoop seems like exactly the technology we need to make our enterprise more scalable. We have terabytes of raw data that is in non-relational form (text files of some kind). We're quickly approaching the upper limits of what our centralized file server can handle and everyone is aware of this. Most people on the tech team, especially the more junior members of the tech team are all in favor of moving from the central file system to HDFS. The problem is, there is one key (most senior, etc.) member of the team who is resisting this change and every time Hadoop comes up, he tells us that we could simply add another file server and be in the clear. So, my question (and yes, it's really subjective, but I need more help with this than any of my other questions) is what steps can we take to get upper management to move forward with Hadoop despite the hesitation of one member of the team?

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  • SSC Clinic: Can Implementing "Optimize for Ad Hoc Queries" Boost Performance for the SQLServerCentral.com and Simple-Talk.Com SQL Servers?

    With the introduction of the instance-level option “optimize for ad hoc workloads” in SQL Server 2008, DBAs have a tool to deal with a problem known as plan cache pollution, or plan cache bloat. It’s often caused when one-time use ad hoc queries are sent to SQL Server from Object-Relational Mapping (ORM) solutions, such as LINQ, NHibernate, or Entity Framework. The problem can prevent SQL Server from using its available memory optimally, potentially hurting performance. Get smart with SQL Backup ProGet faster, smaller backups with integrated verification.Quickly and easily DBCC CHECKDB your backups. Learn more.

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  • Architecture for html5 multiplayer game?

    - by Tihomir Iliev
    Hello I want to write a HTML5 multiplayer game in which there are rooms with two players answering a series of questions with 3 possible answers, 10sec/question, which are being downloaded from a server. It will have some ratings and so on. I want to make it as scalable as possible. I wonder what technologies to use to accomplish that. HTML5, CSS3 and JavaScript obviously. But what about the server-side? I have been researching and found that Socket.IO + Node.js + mongoDB would do the job but after doing some more research it maybe not. Can you suggest me some kind of architecture for doing this game? Free technologies, if possible. Or what to read and from where to start in order to understand how to do it. Thanx in advance! P.S. I have an experience with HTML5, CSS3, JavaScript, C#, ASP.NET MVC and relational db's.

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  • Oracle University Neue Kurse (KW 14)

    - by swalker
    In der letzten Woche wurden von Oracle University folgende neue Kurse (bzw. Versionen davon) veröffentlicht: Database Oracle Data Modeling and Relational Database Design (4 Tage) Fusion Middleware Oracle Directory Services 11g: Administration (5 Tage) Oracle Unified Directory 11g: Services Deployment Essentials (2 Tage) Oracle GoldenGate 11g Management Pack: Overview (1 Tag) Oracle SOA Suite 11g: Essential Concepts NEU (German version - 3 Tage) Business Intelligence & Datawarehousing Oracle Database 11g: Data Mining Techniques (2 Tage) Oracle Solaris Oracle Solaris 10 System Administration for HP-UX Administrators (5 Tage) E-Business Suites R12.x Oracle Time and Labor Fundamentals Wenn Sie weitere Einzelheiten erfahren oder sich über Kurstermine informieren möchten, wenden Sie sich einfach an Ihr lokales Oracle University-Team in. Bleiben Sie in Verbindung mit Oracle University: LinkedIn OracleMix Twitter Facebook Google+

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  • Writing a Data Access Layer (DAL) for SQL Server

    In this tip, I am going to show you how you can create a Data Access Layer (to store, retrieve and manage data in relational database) in ADO .NET. I will show how you can make it data provider independent, so that you don't have to re-write your data access layer if the data storage source changes and also you can reuse it in other applications that you develop. Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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  • How Would You Design This Table?

    - by sooprise
    I have to create a table where each row needs to store 50 number values. Each row will always need to store 50 number values. If this was a smaller number of values, I would just make fields for each of the values, but because there are 50, this approach seems a bit cumbersome (but since it will always be 50 values, maybe this is the correct approach?). Is there a way to store an array of values in a field? This seems like a nice solution, but the concept is almost identical to creating a relational database.

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  • Point me to info about constructing filters (of lists)

    - by jah
    I would like some pointers to information which would help me understand how to go about providing the ability to filter a list of entities by their attributes as well as by attributes of related entities. As an example, imagine a web app which provides order management of some kind. Orders and related entities are stored in a relational database. And imagine that the app has an interface which lists the orders. The problem is: how does one allow the list to be filtered by, for example:- order number (an attribute) line item name (an attribute of a n-n related entity) some text in an administrative note related to the order (text found in an attribute of a 1-1 related entity) I'm trying to discover whether there is something like a standard, efficient way to construct the queries and the filtering form; or some possible strategies; or any theory on the topic; or some example code. My google foo fails me.

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