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• ASP.Net Layered app - Share Entity Data Model amongst layers

  - by Chris Klepeis

  How can I share the auto-generated entity data model (generated object classes) amongst all layers of my C# web app whilst only granting query access in the data layer? This uses the typical 3 layer approach: data, business, presentation. My data layer returns an IEnumerable<T> to my business layer, but I cannot return type T to the presentation layer because I do not want the presentation layer to know of the existence of the data layer - which is where the entity framework auto-generated my classes. It was recommended to have a seperate layer with just the data model, but I'm unsure how to seperate the data model from the query functionality the entity framework provides.

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• How does jQuery store data with .data()?

  - by TK

  I am a little confused how jQuery stores data with .data() functions. Is this something called expando? Or is this using HTML5 Web Storage although I think this is very unlikely? The documentation says: The .data() method allows us to attach data of any type to DOM elements in a way that is safe from circular references and therefore from memory leaks. As I read about expando, it seems to have a rick of memory leak. Unfortunately my skills are not enough to read and understand jQuery code itself, but I want to know how jQuery stores such data by using data(). http://api.jquery.com/data/

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• Accessing and Updating Data in ASP.NET: Filtering Data Using a CheckBoxList

  Filtering Database Data with Parameters, an earlier installment in this article series, showed how to filter the data returned by ASP.NET's data source controls. In a nutshell, the data source controls can include parameterized queries whose parameter values are defined via parameter controls. For example, the SqlDataSource can include a parameterized SelectCommand, such as: SELECT * FROM Books WHERE Price > @Price. Here, @Price is a parameter; the value for a parameter can be defined declaratively using a parameter control. ASP.NET offers a variety of parameter controls, including ones that use hard-coded values, ones that retrieve values from the querystring, and ones that retrieve values from session, and others. Perhaps the most useful parameter control is the ControlParameter, which retrieves its value from a Web control on the page. Using the ControlParameter we can filter the data returned by the data source control based on the end user's input. While the ControlParameter works well with most types of Web controls, it does not work as expected with the CheckBoxList control. The ControlParameter is designed to retrieve a single property value from the specified Web control, but the CheckBoxList control does not have a property that returns all of the values of its selected items in a form that the CheckBoxList control can use. Moreover, if you are using the selected CheckBoxList items to query a database you'll quickly find that SQL does not offer out of the box functionality for filtering results based on a user-supplied list of filter criteria. The good news is that with a little bit of effort it is possible to filter data based on the end user's selections in a CheckBoxList control. This article starts with a look at how to get SQL to filter data based on a user-supplied, comma-delimited list of values. Next, it shows how to programmatically construct a comma-delimited list that represents the selected CheckBoxList values and pass that list into the SQL query. Finally, we'll explore creating a custom parameter control to handle this logic declaratively. Read on to learn more! Read More >

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• SQLAuthority News – Fast Track Data Warehouse 3.0 Reference Guide

  - by pinaldave

  http://msdn.microsoft.com/en-us/library/gg605238.aspx I am very excited that Fast Track Data Warehouse 3.0 reference guide has been announced. As a consultant I have always enjoyed working with Fast Track Data Warehouse project as it truly expresses the potential of the SQL Server Engine. Here is few details of the enhancement of the Fast Track Data Warehouse 3.0 reference architecture. The SQL Server Fast Track Data Warehouse initiative provides a basic methodology and concrete examples for the deployment of balanced hardware and database configuration for a data warehousing workload. Balance is measured across the key components of a SQL Server installation; storage, server, application settings, and configuration settings for each component are evaluated. Description Note FTDW 3.0 Architecture Basic component architecture for FT 3.0 based systems. New Memory Guidelines Minimum and maximum tested memory configurations by server socket count. Additional Startup Options Notes for T-834 and setting for Lock Pages in Memory. Storage Configuration RAID1+0 now standard (RAID1 was used in FT 2.0). Evaluating Fragmentation Query provided for evaluating logical fragmentation. Loading Data Additional options for CI table loads. MCR Additional detail and explanation of FTDW MCR Rating. Read white paper on fast track data warehousing. Reference: Pinal Dave (http://blog.SQLAuthority.com)   Filed under: Business Intelligence, Data Warehousing, PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQL White Papers, SQLAuthority News, T SQL, Technology

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• Accessing and Updating Data in ASP.NET: Filtering Data Using a CheckBoxList

  Filtering Database Data with Parameters, an earlier installment in this article series, showed how to filter the data returned by ASP.NET's data source controls. In a nutshell, the data source controls can include parameterized queries whose parameter values are defined via parameter controls. For example, the SqlDataSource can include a parameterized SelectCommand, such as: SELECT * FROM Books WHERE Price > @Price. Here, @Price is a parameter; the value for a parameter can be defined declaratively using a parameter control. ASP.NET offers a variety of parameter controls, including ones that use hard-coded values, ones that retrieve values from the querystring, and ones that retrieve values from session, and others. Perhaps the most useful parameter control is the ControlParameter, which retrieves its value from a Web control on the page. Using the ControlParameter we can filter the data returned by the data source control based on the end user's input. While the ControlParameter works well with most types of Web controls, it does not work as expected with the CheckBoxList control. The ControlParameter is designed to retrieve a single property value from the specified Web control, but the CheckBoxList control does not have a property that returns all of the values of its selected items in a form that the CheckBoxList control can use. Moreover, if you are using the selected CheckBoxList items to query a database you'll quickly find that SQL does not offer out of the box functionality for filtering results based on a user-supplied list of filter criteria. The good news is that with a little bit of effort it is possible to filter data based on the end user's selections in a CheckBoxList control. This article starts with a look at how to get SQL to filter data based on a user-supplied, comma-delimited list of values. Next, it shows how to programmatically construct a comma-delimited list that represents the selected CheckBoxList values and pass that list into the SQL query. Finally, we'll explore creating a custom parameter control to handle this logic declaratively. Read on to learn more! Read More >

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• extjs data store load data on fly

  - by CKeven

  I'm trying to create a data store that will load the data schema and records on fly. Here is the current code i have and I'm not sure how to setup the array reader properly since i don't have the schema before query returns. ds = new Ext.data.Store({ url: 'http://10.10.97.83/cgi-bin/cgiip.exe/WService=wsdev/majax/jsbrdgx.p', baseParams: { cr: Ext.util.JSON.encode(omgtobxParms) }, reader: new Ext.data.ArrayReader({ //root:data.value.records }, col_names) }); {"name": "tmp_buy_book", "schema": [ { "name": "a", "type": "C"}, { "name": "b", "type": "C"} "records": [["1", ""], ["1",""]]}

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• Big Data – Buzz Words: What is MapReduce – Day 7 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned what is Hadoop. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – MapReduce. What is MapReduce? MapReduce was designed by Google as a programming model for processing large data sets with a parallel, distributed algorithm on a cluster. Though, MapReduce was originally Google proprietary technology, it has been quite a generalized term in the recent time. MapReduce comprises a Map() and Reduce() procedures. Procedure Map() performance filtering and sorting operation on data where as procedure Reduce() performs a summary operation of the data. This model is based on modified concepts of the map and reduce functions commonly available in functional programing. The library where procedure Map() and Reduce() belongs is written in many different languages. The most popular free implementation of MapReduce is Apache Hadoop which we will explore tomorrow. Advantages of MapReduce Procedures The MapReduce Framework usually contains distributed servers and it runs various tasks in parallel to each other. There are various components which manages the communications between various nodes of the data and provides the high availability and fault tolerance. Programs written in MapReduce functional styles are automatically parallelized and executed on commodity machines. The MapReduce Framework takes care of the details of partitioning the data and executing the processes on distributed server on run time. During this process if there is any disaster the framework provides high availability and other available modes take care of the responsibility of the failed node. As you can clearly see more this entire MapReduce Frameworks provides much more than just Map() and Reduce() procedures; it provides scalability and fault tolerance as well. A typical implementation of the MapReduce Framework processes many petabytes of data and thousands of the processing machines. How do MapReduce Framework Works? A typical MapReduce Framework contains petabytes of the data and thousands of the nodes. Here is the basic explanation of the MapReduce Procedures which uses this massive commodity of the servers. Map() Procedure There is always a master node in this infrastructure which takes an input. Right after taking input master node divides it into smaller sub-inputs or sub-problems. These sub-problems are distributed to worker nodes. A worker node later processes them and does necessary analysis. Once the worker node completes the process with this sub-problem it returns it back to master node. Reduce() Procedure All the worker nodes return the answer to the sub-problem assigned to them to master node. The master node collects the answer and once again aggregate that in the form of the answer to the original big problem which was assigned master node. The MapReduce Framework does the above Map () and Reduce () procedure in the parallel and independent to each other. All the Map() procedures can run parallel to each other and once each worker node had completed their task they can send it back to master code to compile it with a single answer. This particular procedure can be very effective when it is implemented on a very large amount of data (Big Data). The MapReduce Framework has five different steps: Preparing Map() Input Executing User Provided Map() Code Shuffle Map Output to Reduce Processor Executing User Provided Reduce Code Producing the Final Output Here is the Dataflow of MapReduce Framework: Input Reader Map Function Partition Function Compare Function Reduce Function Output Writer In a future blog post of this 31 day series we will explore various components of MapReduce in Detail. MapReduce in a Single Statement MapReduce is equivalent to SELECT and GROUP BY of a relational database for a very large database. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – HDFS. 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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• SQL Developer Data Modeler v3.3 Early Adopter: Search

  - by thatjeffsmith

  photo: Stuck in Customs via photopin cc The next version of Oracle SQL Developer Data Modeler is now available as an Early Adopter (read, beta) release. There are many new major feature enhancements to talk about, but today’s focus will be on the brand new Search mechanism. Data, data, data – SO MUCH data Google has made countless billions of dollars around a very efficient and intelligent search business. People have become accustomed to having their data accessible AND searchable. Data models can have thousands of entities or tables, each having dozens of attributes or columns. Imagine how hard it could be to find what you’re looking for here. This is the challenge we have tackled head-on in v3.3. Same location as the Search toolbar in Oracle SQL Developer (and most web browsers) Here’s how it works: Search as you type – wicked fast as the entire model is loaded into memory Supports regular expressions (regex) Results loaded to a new panel below Search across designs, models Search EVERYTHING, or filter by type Save your frequent searches Save your search results as a report Open common properties of object in search results and edit basic properties on-the-fly Want to just watch the video? We have a new Oracle Learning Library resource available now which introduces the new and improved Search mechanism in SQL Developer Data Modeler. Go watch the video and then come back. Some Screenshots This will be a pretty easy feature to pick up. Search is intuitive – we’ve already learned how to do search. Now we just have a better interface for it in SQL Developer Data Modeler. But just in case you need a couple of pointers… The SYS data dictionary in model form with Search Results If I type ‘translation’ in the search dialog, then the results will come up as hits are ‘resolved.’ By default, everything is searched, although I can filter the results after-the-fact. You can see where the search finds a match in the ‘Content’ column Save the Results as a Report If you limit the search results to a category and a model, then you can save the results as a report. All of the usual suspects You can optionally include the search string, which displays in the top of of the report as ‘PATTERN.’ You can save you common reporting setups as a template and reuse those as well. Here’s a sample HTML report: Yes, I like to search my search results report! Two More Ways to Search You can search ‘in context’ by opening the ‘Find’ dialog from an active design. You can do this using the ‘Search’ toolbar button or from a model context menu. Searching a specific model Instead of bringing up the old modal Find dialog, you now get to use the new and improved Search panel. Notice there’s no ‘Model’ drop-down to select and that the active Search form is now in the Search panel versus the search toolbar up top. What else is new in SQL Developer Data Modeler version 3.3? All kinds of goodies. You can send your model to Excel for quick edits/reviews and suck the changes back into your model, you can share objects between models, and much much more. You’ll find new videos and blog posts on the subject in the new few days and weeks. Enjoy! If you have any feedback or want to report bugs, please visit our forums.

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• Big Data – Operational Databases Supporting Big Data – Key-Value Pair Databases and Document Databases – Day 13 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned the importance of the Relational Database and NoSQL database in the Big Data Story. In this article we will understand the role of Key-Value Pair Databases and Document Databases Supporting Big Data Story. Now we will see a few of the examples of the operational databases. Relational Databases (Yesterday’s post) NoSQL Databases (Yesterday’s post) Key-Value Pair Databases (This post) Document Databases (This post) Columnar Databases (Tomorrow’s post) Graph Databases (Tomorrow’s post) Spatial Databases (Tomorrow’s post) Key Value Pair Databases Key Value Pair Databases are also known as KVP databases. A key is a field name and attribute, an identifier. The content of that field is its value, the data that is being identified and stored. They have a very simple implementation of NoSQL database concepts. They do not have schema hence they are very flexible as well as scalable. The disadvantages of Key Value Pair (KVP) database are that they do not follow ACID (Atomicity, Consistency, Isolation, Durability) properties. Additionally, it will require data architects to plan for data placement, replication as well as high availability. In KVP databases the data is stored as strings. Here is a simple example of how Key Value Database will look like: Key Value Name Pinal Dave Color Blue Twitter @pinaldave Name Nupur Dave Movie The Hero As the number of users grow in Key Value Pair databases it starts getting difficult to manage the entire database. As there is no specific schema or rules associated with the database, there are chances that database grows exponentially as well. It is very crucial to select the right Key Value Pair Database which offers an additional set of tools to manage the data and provides finer control over various business aspects of the same. Riak Rick is one of the most popular Key Value Database. It is known for its scalability and performance in high volume and velocity database. Additionally, it implements a mechanism for collection key and values which further helps to build manageable system. We will further discuss Riak in future blog posts. Key Value Databases are a good choice for social media, communities, caching layers for connecting other databases. In simpler words, whenever we required flexibility of the data storage keeping scalability in mind – KVP databases are good options to consider. Document Database There are two different kinds of document databases. 1) Full document Content (web pages, word docs etc) and 2) Storing Document Components for storage. The second types of the document database we are talking about over here. They use Javascript Object Notation (JSON) and Binary JSON for the structure of the documents. JSON is very easy to understand language and it is very easy to write for applications. There are two major structures of JSON used for Document Database – 1) Name Value Pairs and 2) Ordered List. MongoDB and CouchDB are two of the most popular Open Source NonRelational Document Database. MongoDB MongoDB databases are called collections. Each collection is build of documents and each document is composed of fields. MongoDB collections can be indexed for optimal performance. MongoDB ecosystem is highly available, supports query services as well as MapReduce. It is often used in high volume content management system. CouchDB CouchDB databases are composed of documents which consists fields and attachments (known as description). It supports ACID properties. The main attraction points of CouchDB are that it will continue to operate even though network connectivity is sketchy. Due to this nature CouchDB prefers local data storage. Document Database is a good choice of the database when users have to generate dynamic reports from elements which are changing very frequently. A good example of document usages is in real time analytics in social networking or content management system. Tomorrow In tomorrow’s blog post we will discuss about various other Operational Databases supporting 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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• The data reader returned by the store data provider does not have enough columns

  - by molgan

  Hello I get the following error when I try to execute a stored procedure: "The data reader returned by the store data provider does not have enough columns" When I in the sql-manager execute it like this: DECLARE @return_value int, @EndDate datetime EXEC @return_value = [dbo].[GetSomeDate] @SomeID = 91, @EndDate = @EndDate OUTPUT SELECT @EndDate as N'@EndDate' SELECT 'Return Value' = @return_value GO It returns the value properly.... @SomeDate = '2010-03-24 09:00' And in my app I have: if (_entities.Connection.State == System.Data.ConnectionState.Closed) _entities.Connection.Open(); using (EntityCommand c = new EntityCommand("MyAppEntities.GetSomeDate", (EntityConnection)this._entities.Connection)) { c.CommandType = System.Data.CommandType.StoredProcedure; EntityParameter paramSomeID = new EntityParameter("SomeID", System.Data.DbType.Int32); paramSomeID.Direction = System.Data.ParameterDirection.Input; paramSomeID.Value = someID; c.Parameters.Add(paramSomeID); EntityParameter paramSomeDate = new EntityParameter("SomeDate", System.Data.DbType.DateTime); SomeDate.Direction = System.Data.ParameterDirection.Output; c.Parameters.Add(paramSomeDate); int retval = c.ExecuteNonQuery(); return (DateTime?)c.Parameters["SomeDate"].Value; Why does it complain about columns? I googled on error and someone said something about removing RETURN in sp, but I dont have any RETURN there. last like is like SELECT @SomeDate = D.SomeDate FROM .... /M

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• ASP.NET server data persistence

  - by Wayne Werner

  Hi, I'm not really sure exactly how the question should be phrased, so please be patient if I ask the wrong thing. I'm writing an ASP.NET application using VB as the code behind language. I have a data access class that connects to the DB to run the query (parameterized, of course), and another class to perform the validation tasks - I access this class from my aspx page. What I would like is to be able to store the data server side and wait for the user to choose from a few options based on the validity of the data. But unless my understanding is completely off, having persistent data objects on the server will give problems when multiple users connect? My ultimate goal is that once the data has been validated the end user can't modify it. Currently I'm validating the data, but I still have to retrieve it from the web form AFTER the user says OK, which obviously leaves open the possibility of injecting bad data either accidentally (unlikely) or on purpose (also unlikely for the use, but I'd prefer not to take the chance). So am I completely off in my understanding? If so, can someone point me to a resource that provides some instructions on keeping persistent data on the server, or provide instruction? Thanks!

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• SQLAuthority News – Best Practices for Data Warehousing with SQL Server 2008 R2

  - by pinaldave

  An integral part of any BI system is the data warehouse—a central repository of data that is regularly refreshed from the source systems. The new data is transferred at regular intervals  by extract, transform, and load (ETL) processes. This whitepaper talks about what are best practices for Data Warehousing. This whitepaper discusses ETL, Analysis, Reporting as well relational database. The main focus of this whitepaper is on mainly ‘architecture’ and ‘performance’. Download Best Practices for Data Warehousing with SQL Server 2008 R2 Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Data Warehousing, PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• Nagy dobás készül az Oracle adatányászati felületen, Oracle Data Mining

  - by Fekete Zoltán

  Ahogyan már a tavaly oszi Oracle OpenWorld hírekben és eloadásokban is láthattuk a beharangozót, az Oracle nagy dobásra készül az adatbányászati fronton (Oracle Data Mining), mégpedig a remekül használható adatbányászati motor grafikus felületének a kiterjesztésével. Ha jól megfigyeljük ezt az utóbbi linket, az eddigi grafikus felület már Oracle Data Miner Classic néven fut. Hogyan is lehet használni az Oracle Data Mining-ot? - Oracle Data Miner (ingyenesen letöltheto GUI az OTN-rol) - Java-ból és PL/SQL-bol, Oracle Data Mining JDeveloper and SQL Developer Extensions - Excel felületrol, Oracle Spreadsheet Add-In for Predictive Analytics - ODM Connector for mySAP BW Oracle Data Mining technikai információ.

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• Google I/O 2012 - Big Data: Turning Your Data Problem Into a Competitive Advantage

  Google I/O 2012 - Big Data: Turning Your Data Problem Into a Competitive Advantage Ju-kay Kwek, Navneet Joneja Can businesses get practical value from web-scale data without building proprietary web-scale infrastructure? This session will explore how new Google data services can be used to solve key data storage, transformation and analysis challenges. We will look at concrete case studies demonstrating how real life businesses have successfully used these solutions to turn data into a competitive business asset. For all I/O 2012 sessions, go to developers.google.com From: GoogleDevelopers Views: 1 0 ratings Time: 52:39 More in Science & Technology

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• Data-Driven SOA with Oracle Data Integrator

  - by Irem Radzik

  v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Cambria","serif"; mso-fareast-font-family:"MS Mincho";} By Mike Eisterer, Data integration is more than simply moving data in bulk or in real-time, it is also about unifying information for improved business agility and integrating it in today’s service-oriented architectures. SOA enables organizations to easily define services which may then be discovered and leveraged by varying consumers. These consumers may be applications, customer facing portals, or complex business rules which are assembling services to automate process. Data as a foundational service provider is a key component of today’s successful SOA implementations. Oracle offers the broadest and most integrated portfolio of products to help you define, organize, orchestrate and consume data services. If you are attending Oracle OpenWorld next week, you will have ample opportunity to see the latest Oracle Data Integrator live in action and work with it yourself in two offered Hands-on Labs. Visit the hands-on lab to gain experience firsthand: Oracle Data Integrator and Oracle SOA Suite: Hands-on- Lab (HOL10480) Wed Oct 3rd 11:45AM Marriott Marquis- Salon 1/2 To learn more about Oracle Data Integrator, please visit our Introduction Hands-on LAB: Introduction to Oracle Data Integrator (HOL10481) Mon Oct 1st 3:15PM, Marriott Marquis- Salon 1/2 If you are not able to attend OpenWorld, please check out our latest resources for Data Integration.

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• Free for personal use license?

  - by Lance May

  I'm trying desperately to find a software licensing model that would allow me to make my product completely open to the public domain for personal use/modification, but would be able to be sold commercially. I know such a beast exists, and I'm sure in many flavors. I just can't find it. ;( What I'm hoping for is a way to allow people the opportunity to benefit from the product in an "open source" fashion, while still allowing me to have a revenue on it to be able to continue development full time. Thanks much in advance.

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• Subsetting a data frame in a function using another data frame as parameter

  - by lecodesportif

  I would like to submit a data frame to a function and use it to subset another data frame. This is the basic data frame: foo <- data.frame(var1= c('1', '1', '1', '2', '2', '3'), var2=c('A', 'A', 'B', 'B', 'C', 'C')) I use the following function to find out the frequencies of var2 for specified values of var1. foobar <- function(x, y, z){ a <- subset(x, (x$var1 == y)) b <- subset(a, (a$var2 == z)) n=nrow(b) return(n) } Examples: foobar(foo, 1, "A") # returns 2 foobar(foo, 1, "B") # returns 1 foobar(foo, 3, "C") # returns 1 This works. But now I want to submit a data frame of values to foobar. Instead of the above examples, I would like to submit df to foobar and get the same results as above (2, 1, 1) df <- data.frame(var1=c('1','1','3'), var2=c("A", "B", "C")) When I change foobar to accept two arguments like foobar(foo, df) and use y[, c(var1)] and y[, c(var2)] instead of the two parameters x and y it still doesn't work. Which way is there to do this?

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• Personal project/idea database and tracking

  - by cbrulak

  How do you keep track of your personal projects and ideas? If you come up with this amazing idea how do you write it down? Notepad? Some text file somewhere? How do you track your progress,etc? I'm not talking about FogBugz,etc as they are for tracking team work, I'm talking about tracking my ideas and projects and any associated content (notes,screenshots,etc) Can you put your solution on a thumb drive? Any suggestions for other developers?

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• Managing Data Dependecies of Java Classes that Load Data from the Classpath at Runtime

  - by Martin Potthast

  What is the simplest way to manage dependencies of Java classes to data files present in the classpath? More specifically: How should data dependencies be annotated? Perhaps using Java annotations (e.g., @Data)? Or rather some build entries in a build script or a properties file? Is there build tool that integrates and evaluates such information (Ant, Scons, ...)? Do you have examples? Consider the following scenario: A few lines of Ant create a Jar from my sources that includes everything found on the classpath. Then jarjar is used to remove all .class files that are not necessary to execute, say, class Foo. The problem is that all the data files that class Bar depends upon are still there in the Jar. The ideal deployment script, however, would recognize that the data files on which only class Bar depends can be removed while data files on which class Foo depends must be retained. Any hints?

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• Best way to implement user-powered data validation

  - by vegetables

  I run a product recommendation engine and I'm hitting a few snags. I'm looking to see if anyone has any recommendations on what I should do to minimize these issues. Here's how the site works: Users come to the site and are presented with product recommendations based on some criteria. If a user knows of a product that is not in our system, they can add it by providing the product name and manufacturer. We take that information, and: Hit one API to gather all the product meta-data (and to validate the product spelling, etc). If the product is not in this first API, we do not allow it in our system. Use the information from step 1 to hit another API for pricing information (gathered from many places online). For the sake of discussion, assume that I am searching both APIs in the most efficient/successful manner possible. For the most part, this works very well. I'd say ~80% of our data is perfectly accurate, but there are a few issues: Sometimes the pricing API (Step 2) doesn't have any information for the product. The way the pricing API is built, it will always return something (theoretically, the closest possible match), and there's no guarantee that the product name is spelled exactly the same way in both APIs, so there's no automated way of knowing if it's the right product. When the pricing API finds the right product, occasionally it has outdated, or even invalid pricing data (e.g. if it screen-scraped the wrong price from a website). Since the site was fairly small at first, I was able to manually verify every product that was added to the website. However, the site has grown to the point where this is taking several hours per day, and is just not efficient use of my time. So, my question is: Aside from hiring someone (or getting an intern) to validate all the data manually, what would be the best system of letting my userbase self-manage the data. Specifically, how can I allow users to edit the data while minimizing the risk of someone ambushing my website, or accidentally setting the data incorrectly.

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• data handling with javascript

  - by Vincent Warmerdam

  Python has a very neat package called pandas which allows for quick data transformation; tables, aggregation, that sort of thing. A lot of these types of functionality can also be found in the python itertools module. The plyR package in R is also very similar. Usually one woud use this functionality to produce a table which is later visualized with a plot. I am personally very fond of d3, and I would like to allow the user to first indicate what type of data aggregation he wants on the dataset before it is visualized. The visualisation in question involves making a heatmap where the user gets to select the size of the bins of the heatmap beforehand (I want d3 to project this through leaflet). I want to visually select the ideal size of the bins for the heatmap. The way I work now is that I take the dataset, aggregate it with python and then manually load it in d3. This is a process that takes a lot of human effort and I was wondering if the data aggregation can be done through the javascript of the browser. I couldn't find a package for javascript specifically built for data, suggesting (to me) that this is a bad idea and that one should not use javascript for the data handling. Is there a good module/package for javascript to handle data aggregation? Is it a good/bad idea to do the data aggregation in javascript (performance wise)?

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• Customizing the NUnit GUI for data-driven testing

  - by rwong

  My test project consists of a set of input data files which is fed into a piece of legacy third-party software. Since the input data files for this software are difficult to construct (not something that can be done intentionally), I am not going to add new input data files. Each input data file will be subject to a set of "test functions". Some of the test functions can be invoked independently. Other test functions represent the stages of a sequential operation - if an earlier stage fails, the subsequent stages do not need to be executed. I have experimented with the NUnit parametrized test case (TestCaseAttribute and TestCaseSourceAttribute), passing in the list of data files as test cases. I am generally satisfied with the the ability to select the input data for testing. However, I would like to see if it is possible to customize its GUI's tree structure, so that the "test functions" become the children of the "input data". For example: File #1 CheckFileTypeTest GetFileTopLevelStructureTest CompleteProcessTest StageOneTest StageTwoTest StageThreeTest File #2 CheckFileTypeTest GetFileTopLevelStructureTest CompleteProcessTest StageOneTest StageTwoTest StageThreeTest This will be useful for identifying the stage that failed during the processing of a particular input file. Is there any tips and tricks that will enable the new tree layout? Do I need to customize NUnit to get this layout?

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• Test Data in a Distributed System

  - by Davin Tryon

  A question that has been vexing me lately has been about how to effectively test (end-to-end) features in a distributed system. Particuarly, how to effectively manage (through time) test data for feature testing. The system in question is a typical SOA setup. The composition is done in JavaScript when call to several REST APIs. Each service is built as an independent block. Each service has some kind of persistent storage (SQL Server in most cases). The main issue at the moment is how to approach test data when testing end-to-end features. Functional end-to-end testing occurs through the UI, and it is therefore necessary for test data to be set up before the test run (this could be manual or automated testing). As is typical in a distributed system, identifiers from one service are used as a link in another service. So, some level of synchronization needs to be present in the data to effectively test. What is the best way to manage and set up this data after a successful deployment to a test environment? For example, is it better to manage this test data inside each service? Or package it together with the testing suite? Does that testing suite exist as a separate project? I'm interested in design guidance about how to store and manage this test data as the application features evolve.

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• Data Management Business Continuity Planning

  Business Continuity Governance In order to ensure data continuity for an organization, they need to ensure they know how to handle a data or network emergency because all systems have the potential to fail. Data Continuity Checklist: Disaster Recovery Plan/Policy Backups Redundancy Trained Staff Business Continuity Policies In order to protect data in case of any emergency a company needs to put in place a Disaster recovery plan and policies that can be executed by IT staff to ensure the continuity of the existing data and/or limit the amount of data that is not contiguous.  A disaster recovery plan is a comprehensive statement of consistent actions to be taken before, during and after a disaster, according to Geoffrey H. Wold. He also states that the primary objective of disaster recovery planning is to protect the organization in the event that all or parts of its operations and/or computer services are rendered unusable. Furthermore, companies can mandate through policies that IT must maintain redundant hardware in case of any hardware failures and redundant network connectivity incase the primary internet service provider goes down.  Additionally, they can require that all staff be trained in regards to the Disaster recovery policy to ensure that all parties evolved are knowledgeable to execute the recovery plan. Business Continuity Procedures Business continuity procedure vary from organization to origination, however there are standard procedures that most originations should follow. Standard Business Continuity Procedures Backup and Test Backups to ensure that they work Hire knowledgeable and trainable staff  Offer training on new and existing systems Regularly monitor, test, maintain, and upgrade existing system hardware and applications Maintain redundancy regarding all data, and critical business functionality

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• How to choose how to store data?

  - by Eldros

  Give a man a fish and you feed him for a day. Teach a man to fish and you feed him for a lifetime. - Chinese Proverb I could ask what kind of data storage I should use for my actual project, but I want to learn to fish, so I don't need to ask for a fish each time I begin a new project. So, until I used two methods to store data on my non-game project: XML files, and relational databases. I know that there is also other kind of database, of the NoSQL kind. However I wouldn't know if there is more choice available to me, or how to choose in the first place, aside arbitrary picking one. So the question is the following: How should I choose the kind of data storage for a game project? And I would be interested on the following criterion when choosing: The size of the project. The platform targeted by the game. The complexity of the data structure. Added Portability of data amongst many project. Added How often should the data be accessed Added Multiple type of data for a same application Any other point you think is of interest when deciding what to use. EDIT I know about Would it be better to use XML/JSON/Text or a database to store game content?, but thought it didn't address exactly my point. Now if I am wrong, I would gladely be shown the error in my ways.

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