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  • are there any useful datasets available on the web for data mining?

    - by niko
    Hi, Does anyone know any good resource where example (real) data can be downloaded for experimenting statistics and machine learning techniques such as decision trees etc? Currently I am studying machine learning techniques and it would be very helpful to have real data for evaluating the accuracy of various tools. If anyone knows any good resource (perhaps csv, xls files or any other format) I would be very thankful for a suggestion.

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  • Query interface for iPhone CoreData store

    - by JT
    Hi, another iPhone newbie question... I have the following: NSPersistentStoreCoordinator NSManagedObjectContext NSManagedObjectModel Is it possible to run queries directly on the store (since its a sqlite DB)? I'm trying to delete all the records from a tableview, and figured a "DELETE FROM table" would be nice and quick as opposed to looping through the records and removing them manually (which i'm also struggling with). Thanks for your time, James

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  • best way to store list of websites on iphone app

    - by Jonathan
    By best I mean most efficient. So don't go on about subjectiveness. I have a list of websites and I want to store the list on the iphone locally, there must be an URL, title and a small image (like 32x32 max image size). I don't think I should be using CoreData for this. Should I be using a plist?

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  • Big Data: Size isn’t everything

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

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  • Know your Data Lineage

    - by Simon Elliston Ball
    An academic paper without the footnotes isn’t an academic paper. Journalists wouldn’t base a news article on facts that they can’t verify. So why would anyone publish reports without being able to say where the data has come from and be confident of its quality, in other words, without knowing its lineage. (sometimes referred to as ‘provenance’ or ‘pedigree’) The number and variety of data sources, both traditional and new, increases inexorably. Data comes clean or dirty, processed or raw, unimpeachable or entirely fabricated. On its journey to our report, from its source, the data can travel through a network of interconnected pipes, passing through numerous distinct systems, each managed by different people. At each point along the pipeline, it can be changed, filtered, aggregated and combined. When the data finally emerges, how can we be sure that it is right? How can we be certain that no part of the data collection was based on incorrect assumptions, that key data points haven’t been left out, or that the sources are good? Even when we’re using data science to give us an approximate or probable answer, we cannot have any confidence in the results without confidence in the data from which it came. You need to know what has been done to your data, where it came from, and who is responsible for each stage of the analysis. This information represents your data lineage; it is your stack-trace. If you’re an analyst, suspicious of a number, it tells you why the number is there and how it got there. If you’re a developer, working on a pipeline, it provides the context you need to track down the bug. If you’re a manager, or an auditor, it lets you know the right things are being done. Lineage tracking is part of good data governance. Most audit and lineage systems require you to buy into their whole structure. If you are using Hadoop for your data storage and processing, then tools like Falcon allow you to track lineage, as long as you are using Falcon to write and run the pipeline. It can mean learning a new way of running your jobs (or using some sort of proxy), and even a distinct way of writing your queries. Other Hadoop tools provide a lot of operational and audit information, spread throughout the many logs produced by Hive, Sqoop, MapReduce and all the various moving parts that make up the eco-system. To get a full picture of what’s going on in your Hadoop system you need to capture both Falcon lineage and the data-exhaust of other tools that Falcon can’t orchestrate. However, the problem is bigger even that that. Often, Hadoop is just one piece in a larger processing workflow. The next step of the challenge is how you bind together the lineage metadata describing what happened before and after Hadoop, where ‘after’ could be  a data analysis environment like R, an application, or even directly into an end-user tool such as Tableau or Excel. One possibility is to push as much as you can of your key analytics into Hadoop, but would you give up the power, and familiarity of your existing tools in return for a reliable way of tracking lineage? Lineage and auditing should work consistently, automatically and quietly, allowing users to access their data with any tool they require to use. The real solution, therefore, is to create a consistent method by which to bring lineage data from these data various disparate sources into the data analysis platform that you use, rather than being forced to use the tool that manages the pipeline for the lineage and a different tool for the data analysis. The key is to keep your logs, keep your audit data, from every source, bring them together and use the data analysis tools to trace the paths from raw data to the answer that data analysis provides.

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  • How to maintain an ordered table with Core Data (or SQL) with insertions/deletions?

    - by Jean-Denis Muys
    This question is in the context of Core Data, but if I am not mistaken, it applies equally well to a more general SQL case. I want to maintain an ordered table using Core Data, with the possibility for the user to: reorder rows insert new lines anywhere delete any existing line What's the best data model to do that? I can see two ways: 1) Model it as an array: I add an int position property to my entity 2) Model it as a linked list: I add two one-to-one relations, next and previous from my entity to itself 1) makes it easy to sort, but painful to insert or delete as you then have to update the position of all objects that come after 2) makes it easy to insert or delete, but very difficult to sort. In fact, I don't think I know how to express a Sort Descriptor (SQL ORDER BY clause) for that case. Now I can imagine a variation on 1): 3) add an int ordering property to the entity, but instead of having it count one-by-one, have it count 100 by 100 (for example). Then inserting is as simple as finding any number between the ordering of the previous and next existing objects. The expensive renumbering only has to occur when the 100 holes have been filled. Making that property a float rather than an int makes it even better: it's almost always possible to find a new float midway between two floats. Am I on the right track with solution 3), or is there something smarter?

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  • NSURLConnection receives data even if no data was thrown back

    - by Anna Fortuna
    Let me explain my situation. Currently, I am experimenting long-polling using NSURLConnection. I found this and I decided to try it. What I do is send a request to the server with a timeout interval of 300 secs. (or 5 mins.) Here is a code snippet: NSURL *url = [NSURL URLWithString:urlString]; NSURLRequest *request = [NSURLRequest requestWithURL:url cachePolicy:NSURLCacheStorageAllowedInMemoryOnly timeoutInterval:300]; NSData *data = [NSURLConnection sendSynchronousRequest:request returningResponse:&resp error:&err]; Now I want to test if the connection will "hold" the request if no data was thrown back from the server, so what I did was this: if (data != nil) [self performSelectorOnMainThread:@selector(dataReceived:) withObject:data waitUntilDone:YES]; And the function dataReceived: looks like this: - (void)dataReceived:(NSData *)data { NSLog(@"DATA RECEIVED!"); NSString *string = [NSString stringWithUTF8String:[data bytes]]; NSLog(@"THE DATA: %@", string); } Server-side, I created a function that will return a data once it fits the arguments and returns none if nothing fits. Here is a snippet of the PHP function: function retrieveMessages($vardata) { if (!empty($vardata)) { $result = check_data($vardata) //check_data is the function which returns 1 if $vardata //fits the arguments, and 0 if it fails to fit if ($result == 1) { $jsonArray = array('Data' => $vardata); echo json_encode($jsonArray); } } } As you can see, the function will only return data if the $result is equal to 1. However, even if the function returns nothing, NSURLConnection will still perform the function dataReceived: meaning the NSURLConnection still receives data, albeit an empty one. So can anyone help me here? How will I perform long-polling using NSURLConnection? Basically, I want to maintain the connection as long as no data is returned. So how will I do it? NOTE: I am new to PHP, so if my code is wrong, please point it out so I can correct it.

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  • How can I scrape specific data from a website

    - by Stoney
    I'm trying to scrape data from a website for research. The urls are nicely organized in an example.com/x format, with x as an ascending number and all of the pages are structured in the same way. I just need to grab certain headings and a few numbers which are always in the same locations. I'll then need to get this data into structured form for analysis in Excel. I have used wget before to download pages, but I can't figure out how to grab specific lines of text. Excel has a feature to grab data from the web (Data-From Web) but from what I can see it only allows me to download tables. Unfortunately, the data I need is not in tables.

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  • How should I architect my Model and Data Access layer objects in my website?

    - by Robin Winslow
    I've been tasked with designing Data layer for a website at work, and I am very interested in architecture of code for the best flexibility, maintainability and readability. I am generally acutely aware of the value in completely separating out my actual Models from the Data Access layer, so that the Models are completely naive when it comes to Data Access. And in this case it's particularly useful to do this as the Models may be built from the Database or may be built from a Soap web service. So it seems to me to make sense to have Factories in my data access layer which create Model objects. So here's what I have so far (in my made-up pseudocode): class DataAccess.ProductsFromXml extends DataAccess.ProductFactory {} class DataAccess.ProductsFromDatabase extends DataAccess.ProductFactory {} These then get used in the controller in a fashion similar to the following: var xmlProductCreator = DataAccess.ProductsFromXml(xmlDataProvider); var databaseProductCreator = DataAccess.ProductsFromXml(xmlDataProvider); // Returns array of Product model objects var XmlProducts = databaseProductCreator.Products(); // Returns array of Product model objects var DbProducts = xmlProductCreator.Products(); So my question is, is this a good structure for my Data Access layer? Is it a good idea to use a Factory for building my Model objects from the data? Do you think I've misunderstood something? And are there any general patterns I should read up on for how to write my data access objects to create my Model objects?

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  • Most efficient way to store this collection of moduli and remainders?

    - by Bryan
    I have a huge collection of different moduli and associated with each modulus a fairly large list of remainders. I want to store these values so that I can efficiently determine whether an integer is equivalent to any one of the remainders with respect to any of the moduli (it doesn't matter which, I just want a true/false return). I thought about storing these values as a linked-list of balanced binary trees, but I was wondering if there is a better way? EDIT Perhaps a little more detail would be helpful. As for the size of this structure, it will be holding about 10s of thousands of (prime-1) moduli and associated to each modulus will be a variable amount of remainders. Most moduli will only have one or two remainders associated to it, but a very rare few will have a couple hundred associated to it. This is part of a larger program which handles numbers with a couple thousand (decimal) digits. This program will benefit more from this table being as large as possible and being able to be searched quickly. Here's a small part of the dataset where the moduli are in parentheses and the remainders are comma separated: (46) k = 20 (58) k = 15, 44 (70) k = 57 (102) k = 36, 87 (106) k = 66 (156) k = 20, 59, 98, 137 (190) k = 11, 30, 68, 87, 125, 144, 182 (430) k = 234 (520) k = 152, 282 (576) k = 2, 11, 20, 29, 38, 47, 56, 65, 74, ...(add 9 each time), 569 I had said that the moduli were prime, but I was wrong they are each one below a prime.

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  • Metro: Creating an IndexedDbDataSource for WinJS

    - by Stephen.Walther
    The goal of this blog entry is to describe how you can create custom data sources which you can use with the controls in the WinJS library. In particular, I explain how you can create an IndexedDbDataSource which you can use to store and retrieve data from an IndexedDB database. If you want to skip ahead, and ignore all of the fascinating content in-between, I’ve included the complete code for the IndexedDbDataSource at the very bottom of this blog entry. What is IndexedDB? IndexedDB is a database in the browser. You can use the IndexedDB API with all modern browsers including Firefox, Chrome, and Internet Explorer 10. And, of course, you can use IndexedDB with Metro style apps written with JavaScript. If you need to persist data in a Metro style app written with JavaScript then IndexedDB is a good option. Each Metro app can only interact with its own IndexedDB databases. And, IndexedDB provides you with transactions, indices, and cursors – the elements of any modern database. An IndexedDB database might be different than the type of database that you normally use. An IndexedDB database is an object-oriented database and not a relational database. Instead of storing data in tables, you store data in object stores. You store JavaScript objects in an IndexedDB object store. You create new IndexedDB object stores by handling the upgradeneeded event when you attempt to open a connection to an IndexedDB database. For example, here’s how you would both open a connection to an existing database named TasksDB and create the TasksDB database when it does not already exist: var reqOpen = window.indexedDB.open(“TasksDB”, 2); reqOpen.onupgradeneeded = function (evt) { var newDB = evt.target.result; newDB.createObjectStore("tasks", { keyPath: "id", autoIncrement: true }); }; reqOpen.onsuccess = function () { var db = reqOpen.result; // Do something with db }; When you call window.indexedDB.open(), and the database does not already exist, then the upgradeneeded event is raised. In the code above, the upgradeneeded handler creates a new object store named tasks. The new object store has an auto-increment column named id which acts as the primary key column. If the database already exists with the right version, and you call window.indexedDB.open(), then the success event is raised. At that point, you have an open connection to the existing database and you can start doing something with the database. You use asynchronous methods to interact with an IndexedDB database. For example, the following code illustrates how you would add a new object to the tasks object store: var transaction = db.transaction(“tasks”, “readwrite”); var reqAdd = transaction.objectStore(“tasks”).add({ name: “Feed the dog” }); reqAdd.onsuccess = function() { // Tasks added successfully }; The code above creates a new database transaction, adds a new task to the tasks object store, and handles the success event. If the new task gets added successfully then the success event is raised. Creating a WinJS IndexedDbDataSource The most powerful control in the WinJS library is the ListView control. This is the control that you use to display a collection of items. If you want to display data with a ListView control, you need to bind the control to a data source. The WinJS library includes two objects which you can use as a data source: the List object and the StorageDataSource object. The List object enables you to represent a JavaScript array as a data source and the StorageDataSource enables you to represent the file system as a data source. If you want to bind an IndexedDB database to a ListView then you have a choice. You can either dump the items from the IndexedDB database into a List object or you can create a custom data source. I explored the first approach in a previous blog entry. In this blog entry, I explain how you can create a custom IndexedDB data source. Implementing the IListDataSource Interface You create a custom data source by implementing the IListDataSource interface. This interface contains the contract for the methods which the ListView needs to interact with a data source. The easiest way to implement the IListDataSource interface is to derive a new object from the base VirtualizedDataSource object. The VirtualizedDataSource object requires a data adapter which implements the IListDataAdapter interface. Yes, because of the number of objects involved, this is a little confusing. Your code ends up looking something like this: var IndexedDbDataSource = WinJS.Class.derive( WinJS.UI.VirtualizedDataSource, function (dbName, dbVersion, objectStoreName, upgrade, error) { this._adapter = new IndexedDbDataAdapter(dbName, dbVersion, objectStoreName, upgrade, error); this._baseDataSourceConstructor(this._adapter); }, { nuke: function () { this._adapter.nuke(); }, remove: function (key) { this._adapter.removeInternal(key); } } ); The code above is used to create a new class named IndexedDbDataSource which derives from the base VirtualizedDataSource class. In the constructor for the new class, the base class _baseDataSourceConstructor() method is called. A data adapter is passed to the _baseDataSourceConstructor() method. The code above creates a new method exposed by the IndexedDbDataSource named nuke(). The nuke() method deletes all of the objects from an object store. The code above also overrides a method named remove(). Our derived remove() method accepts any type of key and removes the matching item from the object store. Almost all of the work of creating a custom data source goes into building the data adapter class. The data adapter class implements the IListDataAdapter interface which contains the following methods: · change() · getCount() · insertAfter() · insertAtEnd() · insertAtStart() · insertBefore() · itemsFromDescription() · itemsFromEnd() · itemsFromIndex() · itemsFromKey() · itemsFromStart() · itemSignature() · moveAfter() · moveBefore() · moveToEnd() · moveToStart() · remove() · setNotificationHandler() · compareByIdentity Fortunately, you are not required to implement all of these methods. You only need to implement the methods that you actually need. In the case of the IndexedDbDataSource, I implemented the getCount(), itemsFromIndex(), insertAtEnd(), and remove() methods. If you are creating a read-only data source then you really only need to implement the getCount() and itemsFromIndex() methods. Implementing the getCount() Method The getCount() method returns the total number of items from the data source. So, if you are storing 10,000 items in an object store then this method would return the value 10,000. Here’s how I implemented the getCount() method: getCount: function () { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore().then(function (store) { var reqCount = store.count(); reqCount.onerror = that._error; reqCount.onsuccess = function (evt) { complete(evt.target.result); }; }); }); } The first thing that you should notice is that the getCount() method returns a WinJS promise. This is a requirement. The getCount() method is asynchronous which is a good thing because all of the IndexedDB methods (at least the methods implemented in current browsers) are also asynchronous. The code above retrieves an object store and then uses the IndexedDB count() method to get a count of the items in the object store. The value is returned from the promise by calling complete(). Implementing the itemsFromIndex method When a ListView displays its items, it calls the itemsFromIndex() method. By default, it calls this method multiple times to get different ranges of items. Three parameters are passed to the itemsFromIndex() method: the requestIndex, countBefore, and countAfter parameters. The requestIndex indicates the index of the item from the database to show. The countBefore and countAfter parameters represent hints. These are integer values which represent the number of items before and after the requestIndex to retrieve. Again, these are only hints and you can return as many items before and after the request index as you please. Here’s how I implemented the itemsFromIndex method: itemsFromIndex: function (requestIndex, countBefore, countAfter) { var that = this; return new WinJS.Promise(function (complete, error) { that.getCount().then(function (count) { if (requestIndex >= count) { return WinJS.Promise.wrapError(new WinJS.ErrorFromName(WinJS.UI.FetchError.doesNotExist)); } var startIndex = Math.max(0, requestIndex - countBefore); var endIndex = Math.min(count, requestIndex + countAfter + 1); that._getObjectStore().then(function (store) { var index = 0; var items = []; var req = store.openCursor(); req.onerror = that._error; req.onsuccess = function (evt) { var cursor = evt.target.result; if (index < startIndex) { index = startIndex; cursor.advance(startIndex); return; } if (cursor && index < endIndex) { index++; items.push({ key: cursor.value[store.keyPath].toString(), data: cursor.value }); cursor.continue(); return; } results = { items: items, offset: requestIndex - startIndex, totalCount: count }; complete(results); }; }); }); }); } In the code above, a cursor is used to iterate through the objects in an object store. You fetch the next item in the cursor by calling either the cursor.continue() or cursor.advance() method. The continue() method moves forward by one object and the advance() method moves forward a specified number of objects. Each time you call continue() or advance(), the success event is raised again. If the cursor is null then you know that you have reached the end of the cursor and you can return the results. Some things to be careful about here. First, the return value from the itemsFromIndex() method must implement the IFetchResult interface. In particular, you must return an object which has an items, offset, and totalCount property. Second, each item in the items array must implement the IListItem interface. Each item should have a key and a data property. Implementing the insertAtEnd() Method When creating the IndexedDbDataSource, I wanted to go beyond creating a simple read-only data source and support inserting and deleting objects. If you want to support adding new items with your data source then you need to implement the insertAtEnd() method. Here’s how I implemented the insertAtEnd() method for the IndexedDbDataSource: insertAtEnd:function(unused, data) { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function(store) { var reqAdd = store.add(data); reqAdd.onerror = that._error; reqAdd.onsuccess = function (evt) { var reqGet = store.get(evt.target.result); reqGet.onerror = that._error; reqGet.onsuccess = function (evt) { var newItem = { key:evt.target.result[store.keyPath].toString(), data:evt.target.result } complete(newItem); }; }; }); }); } When implementing the insertAtEnd() method, you need to be careful to return an object which implements the IItem interface. In particular, you should return an object that has a key and a data property. The key must be a string and it uniquely represents the new item added to the data source. The value of the data property represents the new item itself. Implementing the remove() Method Finally, you use the remove() method to remove an item from the data source. You call the remove() method with the key of the item which you want to remove. Implementing the remove() method in the case of the IndexedDbDataSource was a little tricky. The problem is that an IndexedDB object store uses an integer key and the VirtualizedDataSource requires a string key. For that reason, I needed to override the remove() method in the derived IndexedDbDataSource class like this: var IndexedDbDataSource = WinJS.Class.derive( WinJS.UI.VirtualizedDataSource, function (dbName, dbVersion, objectStoreName, upgrade, error) { this._adapter = new IndexedDbDataAdapter(dbName, dbVersion, objectStoreName, upgrade, error); this._baseDataSourceConstructor(this._adapter); }, { nuke: function () { this._adapter.nuke(); }, remove: function (key) { this._adapter.removeInternal(key); } } ); When you call remove(), you end up calling a method of the IndexedDbDataAdapter named removeInternal() . Here’s what the removeInternal() method looks like: setNotificationHandler: function (notificationHandler) { this._notificationHandler = notificationHandler; }, removeInternal: function(key) { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function (store) { var reqDelete = store.delete (key); reqDelete.onerror = that._error; reqDelete.onsuccess = function (evt) { that._notificationHandler.removed(key.toString()); complete(); }; }); }); } The removeInternal() method calls the IndexedDB delete() method to delete an item from the object store. If the item is deleted successfully then the _notificationHandler.remove() method is called. Because we are not implementing the standard IListDataAdapter remove() method, we need to notify the data source (and the ListView control bound to the data source) that an item has been removed. The way that you notify the data source is by calling the _notificationHandler.remove() method. Notice that we get the _notificationHandler in the code above by implementing another method in the IListDataAdapter interface: the setNotificationHandler() method. You can raise the following types of notifications using the _notificationHandler: · beginNotifications() · changed() · endNotifications() · inserted() · invalidateAll() · moved() · removed() · reload() These methods are all part of the IListDataNotificationHandler interface in the WinJS library. Implementing the nuke() Method I wanted to implement a method which would remove all of the items from an object store. Therefore, I created a method named nuke() which calls the IndexedDB clear() method: nuke: function () { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function (store) { var reqClear = store.clear(); reqClear.onerror = that._error; reqClear.onsuccess = function (evt) { that._notificationHandler.reload(); complete(); }; }); }); } Notice that the nuke() method calls the _notificationHandler.reload() method to notify the ListView to reload all of the items from its data source. Because we are implementing a custom method here, we need to use the _notificationHandler to send an update. Using the IndexedDbDataSource To illustrate how you can use the IndexedDbDataSource, I created a simple task list app. You can add new tasks, delete existing tasks, and nuke all of the tasks. You delete an item by selecting an item (swipe or right-click) and clicking the Delete button. Here’s the HTML page which contains the ListView, the form for adding new tasks, and the buttons for deleting and nuking tasks: <!DOCTYPE html> <html> <head> <meta charset="utf-8" /> <title>DataSources</title> <!-- WinJS references --> <link href="//Microsoft.WinJS.1.0.RC/css/ui-dark.css" rel="stylesheet" /> <script src="//Microsoft.WinJS.1.0.RC/js/base.js"></script> <script src="//Microsoft.WinJS.1.0.RC/js/ui.js"></script> <!-- DataSources references --> <link href="indexedDb.css" rel="stylesheet" /> <script type="text/javascript" src="indexedDbDataSource.js"></script> <script src="indexedDb.js"></script> </head> <body> <div id="tmplTask" data-win-control="WinJS.Binding.Template"> <div class="taskItem"> Id: <span data-win-bind="innerText:id"></span> <br /><br /> Name: <span data-win-bind="innerText:name"></span> </div> </div> <div id="lvTasks" data-win-control="WinJS.UI.ListView" data-win-options="{ itemTemplate: select('#tmplTask'), selectionMode: 'single' }"></div> <form id="frmAdd"> <fieldset> <legend>Add Task</legend> <label>New Task</label> <input id="inputTaskName" required /> <button>Add</button> </fieldset> </form> <button id="btnNuke">Nuke</button> <button id="btnDelete">Delete</button> </body> </html> And here is the JavaScript code for the TaskList app: /// <reference path="//Microsoft.WinJS.1.0.RC/js/base.js" /> /// <reference path="//Microsoft.WinJS.1.0.RC/js/ui.js" /> function init() { WinJS.UI.processAll().done(function () { var lvTasks = document.getElementById("lvTasks").winControl; // Bind the ListView to its data source var tasksDataSource = new DataSources.IndexedDbDataSource("TasksDB", 1, "tasks", upgrade); lvTasks.itemDataSource = tasksDataSource; // Wire-up Add, Delete, Nuke buttons document.getElementById("frmAdd").addEventListener("submit", function (evt) { evt.preventDefault(); tasksDataSource.beginEdits(); tasksDataSource.insertAtEnd(null, { name: document.getElementById("inputTaskName").value }).done(function (newItem) { tasksDataSource.endEdits(); document.getElementById("frmAdd").reset(); lvTasks.ensureVisible(newItem.index); }); }); document.getElementById("btnDelete").addEventListener("click", function () { if (lvTasks.selection.count() == 1) { lvTasks.selection.getItems().done(function (items) { tasksDataSource.remove(items[0].data.id); }); } }); document.getElementById("btnNuke").addEventListener("click", function () { tasksDataSource.nuke(); }); // This method is called to initialize the IndexedDb database function upgrade(evt) { var newDB = evt.target.result; newDB.createObjectStore("tasks", { keyPath: "id", autoIncrement: true }); } }); } document.addEventListener("DOMContentLoaded", init); The IndexedDbDataSource is created and bound to the ListView control with the following two lines of code: var tasksDataSource = new DataSources.IndexedDbDataSource("TasksDB", 1, "tasks", upgrade); lvTasks.itemDataSource = tasksDataSource; The IndexedDbDataSource is created with four parameters: the name of the database to create, the version of the database to create, the name of the object store to create, and a function which contains code to initialize the new database. The upgrade function creates a new object store named tasks with an auto-increment property named id: function upgrade(evt) { var newDB = evt.target.result; newDB.createObjectStore("tasks", { keyPath: "id", autoIncrement: true }); } The Complete Code for the IndexedDbDataSource Here’s the complete code for the IndexedDbDataSource: (function () { /************************************************ * The IndexedDBDataAdapter enables you to work * with a HTML5 IndexedDB database. *************************************************/ var IndexedDbDataAdapter = WinJS.Class.define( function (dbName, dbVersion, objectStoreName, upgrade, error) { this._dbName = dbName; // database name this._dbVersion = dbVersion; // database version this._objectStoreName = objectStoreName; // object store name this._upgrade = upgrade; // database upgrade script this._error = error || function (evt) { console.log(evt.message); }; }, { /******************************************* * IListDataAdapter Interface Methods ********************************************/ getCount: function () { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore().then(function (store) { var reqCount = store.count(); reqCount.onerror = that._error; reqCount.onsuccess = function (evt) { complete(evt.target.result); }; }); }); }, itemsFromIndex: function (requestIndex, countBefore, countAfter) { var that = this; return new WinJS.Promise(function (complete, error) { that.getCount().then(function (count) { if (requestIndex >= count) { return WinJS.Promise.wrapError(new WinJS.ErrorFromName(WinJS.UI.FetchError.doesNotExist)); } var startIndex = Math.max(0, requestIndex - countBefore); var endIndex = Math.min(count, requestIndex + countAfter + 1); that._getObjectStore().then(function (store) { var index = 0; var items = []; var req = store.openCursor(); req.onerror = that._error; req.onsuccess = function (evt) { var cursor = evt.target.result; if (index < startIndex) { index = startIndex; cursor.advance(startIndex); return; } if (cursor && index < endIndex) { index++; items.push({ key: cursor.value[store.keyPath].toString(), data: cursor.value }); cursor.continue(); return; } results = { items: items, offset: requestIndex - startIndex, totalCount: count }; complete(results); }; }); }); }); }, insertAtEnd:function(unused, data) { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function(store) { var reqAdd = store.add(data); reqAdd.onerror = that._error; reqAdd.onsuccess = function (evt) { var reqGet = store.get(evt.target.result); reqGet.onerror = that._error; reqGet.onsuccess = function (evt) { var newItem = { key:evt.target.result[store.keyPath].toString(), data:evt.target.result } complete(newItem); }; }; }); }); }, setNotificationHandler: function (notificationHandler) { this._notificationHandler = notificationHandler; }, /***************************************** * IndexedDbDataSource Method ******************************************/ removeInternal: function(key) { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function (store) { var reqDelete = store.delete (key); reqDelete.onerror = that._error; reqDelete.onsuccess = function (evt) { that._notificationHandler.removed(key.toString()); complete(); }; }); }); }, nuke: function () { var that = this; return new WinJS.Promise(function (complete, error) { that._getObjectStore("readwrite").done(function (store) { var reqClear = store.clear(); reqClear.onerror = that._error; reqClear.onsuccess = function (evt) { that._notificationHandler.reload(); complete(); }; }); }); }, /******************************************* * Private Methods ********************************************/ _ensureDbOpen: function () { var that = this; // Try to get cached Db if (that._cachedDb) { return WinJS.Promise.wrap(that._cachedDb); } // Otherwise, open the database return new WinJS.Promise(function (complete, error, progress) { var reqOpen = window.indexedDB.open(that._dbName, that._dbVersion); reqOpen.onerror = function (evt) { error(); }; reqOpen.onupgradeneeded = function (evt) { that._upgrade(evt); that._notificationHandler.invalidateAll(); }; reqOpen.onsuccess = function () { that._cachedDb = reqOpen.result; complete(that._cachedDb); }; }); }, _getObjectStore: function (type) { type = type || "readonly"; var that = this; return new WinJS.Promise(function (complete, error) { that._ensureDbOpen().then(function (db) { var transaction = db.transaction(that._objectStoreName, type); complete(transaction.objectStore(that._objectStoreName)); }); }); }, _get: function (key) { return new WinJS.Promise(function (complete, error) { that._getObjectStore().done(function (store) { var reqGet = store.get(key); reqGet.onerror = that._error; reqGet.onsuccess = function (item) { complete(item); }; }); }); } } ); var IndexedDbDataSource = WinJS.Class.derive( WinJS.UI.VirtualizedDataSource, function (dbName, dbVersion, objectStoreName, upgrade, error) { this._adapter = new IndexedDbDataAdapter(dbName, dbVersion, objectStoreName, upgrade, error); this._baseDataSourceConstructor(this._adapter); }, { nuke: function () { this._adapter.nuke(); }, remove: function (key) { this._adapter.removeInternal(key); } } ); WinJS.Namespace.define("DataSources", { IndexedDbDataSource: IndexedDbDataSource }); })(); Summary In this blog post, I provided an overview of how you can create a new data source which you can use with the WinJS library. I described how you can create an IndexedDbDataSource which you can use to bind a ListView control to an IndexedDB database. While describing how you can create a custom data source, I explained how you can implement the IListDataAdapter interface. You also learned how to raise notifications — such as a removed or invalidateAll notification — by taking advantage of the methods of the IListDataNotificationHandler interface.

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  • C# best means to store data locally when offline

    - by mickartz
    I am in the midst of writing a small program (more to experiment with vs 2010 than anything else) Despite being an experiment it has some practical use for our local athletics club. My thought was to access the DB (currently online) to download the current members and store locally on a laptop (this is a MS sql table, used to power the club's website). take the laptop to the event (yes there ARE places that don't have internet coverage), add members to that days race (also a row from a sql table (though no changes would be made to this), record results (new records in 3rd table) Once home, showered and within internet access again, upload/edit the tables as per the race results/member changes etc. So I was thinking i'd do something like write xml files locally with the data, including a field to indicate changes etc? If anyone can point me in a direction i would appreciate it...hell if anyone could tell me if this has a name!!..I'd appreciate it TIA Michael Artz

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  • Core Data multi-threading

    - by JK
    My app starts by presenting a tableview whose datasource is a Core Data SQLite store. When the app starts, a secondary thread with its own store controller and context is created to obtain updates from the web for data in the store. However, any resulting changes to the store are not notified to the fetchedresults controller (I presume because it has its own coordinator) and consequently the table is not updated with store changes. What would be the most efficient way to refresh the context on the main thread? I am considering tracking the objectIDs of any objects changed on the secondary thread, sending those to the main thread when the secondary thread completes and invoking "[context refreshObject:....] Any help would be greatly appreciated.

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  • How to store an object in Riak with the Java client?

    - by Jonas
    I have setup Riak on a Ubuntu machine, and it seam to work if I do riak ping. Now I would like to use the Riak Java client to store an object, but it doesn't work. I get com.basho.riak.client.response.RiakIORuntimeException when I try to store an object. What am I doing wrong? Is there a way to test if I can access riak from my java client? Do I have to create a Bucket first? how? import com.basho.riak.client.RiakClient; import com.basho.riak.client.RiakObject; import com.basho.riak.client.response.FetchResponse; public class RiakTest { public static void main(String[] args) { // connect RiakClient riak = new RiakClient("http://192.168.1.107:8098/riak"); // create object RiakObject o = new RiakObject("mybucket", "mykey", "myvalue"); // store riak.store(o); } }

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  • Best means to store data locally when offline

    - by mickartz
    I am in the midst of writing a small program (more to experiment with vs 2010 than anything else) Despite being an experiment it has some practical use for our local athletics club. My thought was to access the DB (currently online) to download the current members and store locally on a laptop (this is a MS sql table, used to power the club's website). take the laptop to the event (yes there ARE places that don't have internet coverage), add members to that days race (also a row from a sql table (though no changes would be made to this), record results (new records in 3rd table) Once home, showered and within internet access again, upload/edit the tables as per the race results/member changes etc. So I was thinking i'd do something like write xml files locally with the data, including a field to indicate changes etc? If anyone can point me in a direction i would appreciate it...hell if anyone could tell me if this has a name, I'd appreciate it.

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  • Calculating percentiles in Excel with "buckets" data instead of the data list itself

    - by G B
    I have a bunch of data in Excel that I need to get certain percentile information from. The problem is that instead of having the data set made up of each value, I instead have info on the number of or "bucket" data. For example, imagine that my actual data set looks like this: 1,1,2,2,2,2,3,3,4,4,4 The data set that I have is this: Value No. of occurrences 1 2 2 4 3 2 4 3 Is there an easy way for me to calculate percentile information (as well as the median) without having to explode the summary data out to full data set? (Once I did that, I know that I could just use the Percentile(A1:A5, p) function) This is important because my data set is very large. If I exploded the data out, I would have hundreds of thousands of rows and I would have to do it for a couple of hundred data sets. Help!

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  • How to detect the active iTunes store on the iPhone/iPod Touch/iPad?

    - by Paul
    I'd like to be able to determine which store the user connects to from inside my app, so that I can direct them to some appropriate content for their device AND store. Does anyone know how to get this information? Basically, if the user is in the UK, and connects to the UK store, I want my function/method to return GB, if in Korea, I want KR, Australia = AU etc. Any help would be appreciated.

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  • How do I setup a WCF Data Service with an ADO.NET Entity Entity Model in another assembly?

    - by lsb
    Hi! I have an ASP.NET 4.0 website that has an Entity Data Model hooked up to WCF Data Service. When the Service and Model are in the same assembly everything works. Unfortunately, when I move the Model to another "shared" assembly (and change the namespace) the service compiles but throws a 500 error when launched in a browser. The reason I want to have the Model in a common assembly (lets call it RiaTest.Shared) is that I want share common validation code between the client and service (by checking "Reuse types in referenced assemblies" in the Advanced tab of the Add Service Reference dialog). Anyway, I've spent a couple of hours on this to no avail so any help in the regard would be appreciated...

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  • Store image in core data and Retina Display ?

    - by shani
    Hi I have an app that has hundreds of words with 3/4 images for each word. I have 2 versions of each word one for iOS 3 and one for retina display. I wish to save the images as data and connect them to the appropriate word so it will be easy to pull them later. my question is - how do i get the suitable size ? its works great with the @2x wjen you get it from the app file system, but hoe does it supposed to work when i get it from data ? thanks shani

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  • Open Data, Government and Transparency

    - by Tori Wieldt
    A new track at TDC (The Developer's Conference in Sao Paulo, Brazil) is titled Open Data. It deals with open data, government and transparency. Saturday will be a "transparency hacker day" where developers are invited to create applications using open data from the Brazilian government.  Alexandre Gomes, co-lead of the track, says "I want to inspire developers to become "Civic hackers:" developers who create apps to make society better." It is a chance for developers to do well and do good. There are many opportunities for developers, including monitoring government expenditures and getting citizens involved via social networks. The open data movement is growing worldwide. One initiative, the Open Government Partnership, is working to make government data easier to find and access. Making this data easily available means that with the right applications, it will be easier for people to make decisions and suggestions about government policies based on detailed information. Last April, the Open Government Partnership held its annual meeting in Brasilia, the capitol of Brazil. It was a great success showcasing the innovative work being done in open data by governments, civil societies and individuals around the world. For example, Bulgaria now publishes daily data on budget spending for all public institutions. Alexandre Gomes Explains Open Data At TDC, the Open Data track will include a presentation of examples of successful open data projects, an introduction to the semantic web, how to handle big data sets, techniques of data visualization, and how to design APIs.The other track lead is Christian Moryah Miranda, a systems analyst for the Brazilian Government's Ministry of Planning. "The Brazilian government wholeheartedly supports this effort. In order to make our data available to the public, it forces us to be more consistent with our data across ministries, and that's a good step forward for us," he said. He explained the government knows they cannot achieve everything they would like without help from the public. "It is not the government versus the people, rather citizens are partners with the government, and together we can achieve great things!" Miranda exclaimed. Saturday at TDC will be a "transparency hacker day" where developers will be invited to create applications using open data from the Brazilian government. Attendees are invited to pitch their ideas, work in small groups, and present their project at the end of the conference. "For example," Gomes said, "the Brazilian government just released the salaries of all government employees and I can't wait to see what developers can do with that." Resources Open Government Partnership  U.S. Government Open Data ProjectBrazilian Government Open Data ProjectU.K. Government Open Data Project 2012 International Open Government Data Conference 

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  • Hands-on: Ubuntu One music store will rock in Lucid Lynx

    <b>ars Technica:</b> "Canonical, the company behind the Ubuntu Linux distribution, has announced the official launch of the Ubuntu One music store. Integrated into the Rhythmbox music player in the upcoming Ubuntu 10.04 release, the store allows users to purchase downloadable songs and albums."

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  • Master Data Management and Cloud Computing

    - by david.butler(at)oracle.com
    Cloud Computing is all the rage these days. There are many reasons why this is so. But like its predecessor, Service Oriented Architecture, it can fall on hard times if the underlying data is left unmanaged. Master Data Management is the perfect Cloud companion. It can materially increase the chances for successful Cloud initiatives. In this blog, I'll review the nature of the Cloud and show how MDM fits in.   Here's the National Institute of Standards and Technology Cloud definition: •          Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction.   Cloud architectures have three main layers: applications or Software as a Service (SaaS), Platforms as a Service (PaaS), and Infrastructure as a Service (IaaS). SaaS generally refers to applications that are delivered to end-users over the Internet. Oracle CRM On Demand is an example of a SaaS application. Today there are hundreds of SaaS providers covering a wide variety of applications including Salesforce.com, Workday, and Netsuite. Oracle MDM applications are located in this layer of Oracle's On Demand enterprise Cloud platform. We call it Master Data as a Service (MDaaS). PaaS generally refers to an application deployment platform delivered as a service. They are often built on a grid computing architecture and include database and middleware. Oracle Fusion Middleware is in this category and includes the SOA and Data Integration products used to connect SaaS applications including MDM. Finally, IaaS generally refers to computing hardware (servers, storage and network) delivered as a service.  This typically includes the associated software as well: operating systems, virtualization, clustering, etc.    Cloud Computing benefits are compelling for a large number of organizations. These include significant cost savings, increased flexibility, and fast deployments. Cost advantages include paying for just what you use. This is especially critical for organizations with variable or seasonal usage. Companies don't have to invest to support peak computing periods. Costs are also more predictable and controllable. Increased agility includes access to the latest technology and experts without making significant up front investments.   While Cloud Computing is certainly very alluring with a clear value proposition, it is not without its challenges. An IDC survey of 244 IT executives/CIOs and their line-of-business (LOB) colleagues identified a number of issues:   Security - 74% identified security as an issue involving data privacy and resource access control. Integration - 61% found that it is hard to integrate Cloud Apps with in-house applications. Operational Costs - 50% are worried that On Demand will actually cost more given the impact of poor data quality on the rest of the enterprise. Compliance - 49% felt that compliance with required regulatory, legal and general industry requirements (such as PCI, HIPAA and Sarbanes-Oxley) would be a major issue. When control is lost, the ability of a provider to directly manage how and where data is deployed, used and destroyed is negatively impacted.  There are others, but I singled out these four top issues because Master Data Management, properly incorporated into a Cloud Computing infrastructure, can significantly ameliorate all of these problems. Cloud Computing can literally rain raw data across the enterprise.   According to fellow blogger, Mike Ferguson, "the fracturing of data caused by the adoption of cloud computing raises the importance of MDM in keeping disparate data synchronized."   David Linthicum, CTO Blue Mountain Labs blogs that "the lack of MDM will become more of an issue as cloud computing rises. We're moving from complex federated on-premise systems, to complex federated on-premise and cloud-delivered systems."    Left unmanaged, non-standard, inconsistent, ungoverned data with questionable quality can pollute analytical systems, increase operational costs, and reduce the ROI in Cloud and On-Premise applications. As cloud computing becomes more relevant, and more data, applications, services, and processes are moved out to cloud computing platforms, the need for MDM becomes ever more important. Oracle's MDM suite is designed to deal with all four of the above Cloud issues listed in the IDC survey.   Security - MDM manages all master data attribute privacy and resource access control issues. Integration - MDM pre-integrates Cloud Apps with each other and with On Premise applications at the data level. Operational Costs - MDM significantly reduces operational costs by increasing data quality, thereby improving enterprise business processes efficiency. Compliance - MDM, with its built in Data Governance capabilities, insures that the data is governed according to organizational standards. This facilitates rapid and accurate reporting for compliance purposes. Oracle MDM creates governed high quality master data. A unified cleansed and standardized data view is produced. The Oracle Customer Hub creates a single view of the customer. The Oracle Product Hub creates high quality product data designed to support all go-to-market processes. Oracle Supplier Hub dramatically reduces the chances of 'supplier exceptions'. Oracle Site Hub masters locations. And Oracle Hyperion Data Relationship Management masters financial reference data and manages enterprise hierarchies across operational areas from ERP to EPM and CRM to SCM. Oracle Fusion Middleware connects Cloud and On Premise applications to MDM Hubs and brings high quality master data to your enterprise business processes.   An independent analyst once said "Poor data quality is like dirt on the windshield. You may be able to drive for a long time with slowly degrading vision, but at some point, you either have to stop and clear the windshield or risk everything."  Cloud Computing has the potential to significantly degrade data quality across the enterprise over time. Deploying a Master Data Management solution prior to or in conjunction with a move to the Cloud can insure that the data flowing into the enterprise from the Cloud is clean and governed. This will in turn insure that expected returns on the investment in Cloud Computing will be realized.       Oracle MDM has proven its metal in this area and has the customers to back that up. In fact, I will be hosting a webcast on Tuesday, April 10th at 10 am PT with one of our top Cloud customers, the Church Pension Group. They have moved all mainline applications to a hosted model and use Oracle MDM to insure the master data is managed and cleansed before it is propagated to other cloud and internal systems. I invite you join Martin Hossfeld, VP, IT Operations, and Danette Patterson, Enterprise Data Manager as they review business drivers for MDM and hosted applications, how they did it, the benefits achieved, and lessons learned. You can register for this free webcast here.  Hope to see you there.

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