I have talked about human filters and my plan for digital curation. These items are the fruits of those ideas, the items I deemed worthy from my Google Reader feeds. These items are a combination of tech business news, development news and programming tools and techniques. Real-Time Ad Impression Bids Using DynamoDB (Amazon Web Services Blog) The mother of all M&A rumors: AT&T, Verizon to jointly buy Vodafone (GigaOM) Is this the future of memory? A Hybrid Memory Cube spec makes its debut. (GigaOM) Dew Drop – April 2, 2013 (#1,518) (Alvin Ashcraft's Morning Dew) Rosetta Stone acquires Livemocha for $8.5m to move its language learning platform into the cloud (The Next Web) Double Shot #1098 (A Fresh Cup) Extending git (Atlassian Blogs) A Thorough Introduction To Backbone.Marionette (Part 2) (Smashing Magazine Feed) 60 Problem Solving Strategies (Javalobby – The heart of the Java developer community) Why asm.js is a big deal for game developers (HTML5 Zone) Implementing DAL in Play 2.x (Scala), Slick, ScalaTest (Javalobby – The heart of the Java developer community) “It’s Open Source, So the Source is, You Know, Open.” (Javalobby – The heart of the Java developer community) How to Design a Good, Regular API (Javalobby – The heart of the Java developer community) Scalding: Finding K Nearest Neighbors for Fun and Profit (Javalobby – The heart of the Java developer community) The Daily Six Pack: April 2, 2013 (Dirk Strauss) Usually When Developers Are Mean, It Is About Power (Agile Zone – Software Methodologies for Development Managers) Do Predictive Modelers Need to Know Math? (Data Mining and Predictive Analytics) Heroku Forces Customer Upgrade To Fix Critical PostgreSQL Security Hole (TechCrunch) DYNAMO (Lambda the Ultimate – Programming Languages Weblog) FitNesse your ScalaTest with custom Scala DSL (Java Code Geeks) LinkBench: A database benchmark for the social graph (Facebook Engineering's Facebook Notes) Khan Academy Checkbook Scaling to 6 Million Users a Month on GAE (High Scalability) Famo.us, The Framework For Fast And Beautiful HTML5 Apps, Will Be Free Thanks To “Huge Hardware Vendor Interest” (TechCrunch) Why We Need Lambda Expressions in Java – Part 2 (Javalobby – The heart of the Java developer community) I hope you enjoy today’s items, and please participate in the discussions on those sites.

Poor Oddjob, I thought as I read Craig Flichel’s Feature Comparison of Java Job Schedulers featuring Obsidian, Quartz, Cron4j and Spring. Yet again it hasn’t made the grade, it’s been passed over for the scheduling team. Never mind I say, you’re just a little bit different and misunderstood. Let’s have a kick about in the back yard and see what you can do… Real-time Schedule Changes / Real-time Job Configuration Oddjob: Yes Here is Oddjob’s Client GUI, connecting to an instance of Oddjob running as a Windows Service on my home PC. My Oddob instance sends me a reminder email when it’s someone’s birthday, and also tells me when it’s going to rain. The swing UI allows complete configuration of the server. With it I can configure the jobs and their schedules, but unfortunately I can’t control the weather! Ad-hoc Job Submission: Yes Configurable Job Conflicts: Not Really Applicable Ad-hoc job submission is really what Oddjob is all about. Many jobs won’t be scheduled at all and will sit in a folder to be manually run as required. To run a job, scheduled or not, just click ‘run’ from the job menu. Job conflicts aren’t really a problem for Oddjob because it won’t reschedule a job again until it’s finished. If a job’s next slot has passed, you have the choice to run immediately or skip missed runs and reschedule from the current time. If you want concurrent execution you can configure different jobs to run at the same time or use a single schedule and launch the jobs in parallel. Manually Stopping a job is just as easy as running it. Click ‘stop’ from the job menu. Code- and XML-Free Job Configuration Oddjob: Yes You saw this in the first section. Oddjob’s configuration is via a UI and is done in real time. In fact I often start one job as I’m configuring the next. It’s all very interactive. Oddjob uses XML behind the scenes for those that like to see under the hood. Job Event Subscription/Notification Oddjob: Yes It’s very easy to trigger a job based on the completion state of another job. You would have to write code to listen to configuration changes though. Custom Listeners: Undocumented Job Chaining: Yes There’s lots of options for job chaining, sequential, parallel, or cascade, and any nested combinations thereof. Adding a custom Stateful listener would be easy enough, and might be useful if embedding Oddjob but this isn’t the normal use case. The unit tests do this extensively however. Monitoring & Management UI Oddjob: Yes The same UI allows you to see the job state, job by job log messages, the console of an Exec Job, and the run time properties of all the jobs. Zero Configuration Clustering and Load Sharing Oddjob: Kind Of Oddjob has a Grab Job so you can run the same configuration on several servers and have them compete for work. I wrote it as a proof of concept but I’ve never had cause to use it in the field and I haven’t had any reports that others have either. Job Execution Host Affinity: Kind Of In the same way that you add the ‘Grab job’ to many servers to share work, you could in theory just add Grab for a particular job to only certain servers. I guess this is server Affinity? Scripting Language Support in Jobs Oddjob: Yes Oddjob has a Script Job for any language that supports the Java Scripting Framework. JavaScript is shipped by default.With the Script Job you can also interact with Oddjob to use the properties of other jobs, and set variables for other jobs to use. Scheduling Precision Oddjob: Millisecond In theory Oddjob can schedule with millisecond precision, but this isn’t usual practice. Polling for a file every 30 seconds, for instance, is normally fine. Job Scheduling & Management REST API Oddjob: JMX Only No REST API. You can embed the JMX Client easily enough and control everything from Java, but not for other languages. Not yet. Custom Calendar Support Oddjob: Yes Oddjob has the concept of breaking a schedule with another. The breaks can be as flexible as the job schedule itself – define days, weeks or just a few hours off for a task. The Scheduling section of the User Guide has much more on Oddjob’s flexible scheduling capabilities. Conclusion Oddjob has many other features to make automating repetitive tasks easy. One noteworthy feature is the ease of adding custom jobs by just implementing java.lang.Runnable. Oddjob is undeniably an amateur player in the Scheduler league, and one that is often overlooked. With its Apache licence it is completely free and open. Why not check it out when you have an hour or two? You might be pleasantly surprised by the quality of play.

There were several posts lately critical of Scala language, specifically this onehttps://dzone.com/articles/i-dont-scala. It is a well written, critical of Scala post by someone who clearly prefers other languages (i.e. Java) at this point. However, having used Scala exclusively for the last 4 years and having led the company (GridGain Systems) that has been one of the pioneers in Scala adoption boasting one of the largest production code based in Scala across many projects – I can see all too familiar “reasoning” in that post… The biggest issue with Scala’s perception is the deeply varying quality of frameworks and tools that significantly affect one’s perception of the Scala language itself. I’ve been saying openly that SBT and Scalaz projects, for example, have had the cumulatively negative impact on Scala’s initial adoption. While poor engineering behind SBT and colossal snobbism of Scalaz have been well understood – I can addSpray.io to this list as well now. The engineering ineptitude of people behindSpray.io (and the Spray.routing specifically) is worrisome to say the least. When someone takes a test run with Scala and gets exposed to SBT, Scalaz andSpray.io – on top of the existing growing pains of binary compatibly, IDE support and slow compilation – I’m surprised we have even that small community around Scala as it is today. Yet – remove these engineering warts – and Scala provides brilliantly simple, extremely productive and intellectually sutisfying world in which we can express our algorithms. What attracted me the most to Scala almost 5 years ago is its engineering pragmatisms vs. hopeless academic idealism of Haskell or intellectual laziness of dynamically typed languages. That engineering pragmatism coupled with an almost algebraic elegance and simplicity is what makes Scala probably the best general purpose language available today. So, I say to my engineers to look at Scala holistically, away from sub-standard projects, tools and individual snobs. There are plenty of good examples in Scala eco-system where one can learn how to think and ultimately write quality code in Scala: For sane type-level programming look at latest Scala collections For DLS look at ScalaTest For concurrency look at Akka For boundary pushing yet still useful type-level programming look at Shapeless and the list can go on. When tinkering with Scala for the first time always remember that Scala the language is much bigger than the sum of many of its projects – and there are few of them that you probably should stay clear off anyways.

a recent study by gartner predicts a very significant increase in cloud usage by consumers in a few years, due in great part to the ever growing use of smartphone cameras by the average household. in this context, it could be useful to have a smartphone application that is able to upload / download digital content from a cloud provider. in this article, we will construct a basic android prototype that will allow us to plug in the windows azure cloud provider, and use the windows azure toolkit for android ( available at github ) to do all of the basic cloud operations : upload content to cloud storage, browse the storage, download or delete files in cloud storage. once those operations are implemented, we will see how to enable our android application to receive server push notifications . first things first, we need to set up a storage account in the azure cloud: a storage account comes with several options as for data management : we can keep data in blob, table or queue storage. in this article, we will use the blob storage to work with images. the storage account has a primary and secondary access key , either one of the two can be used to execute operations on the storage account. any of those keys can be regenerated if compromised. 1. preliminaries first, the prerequisites: eclipse ide for java android plugin for eclipse ( adt ) windows azure toolkit for android windows azure subscription (you can get a 90-day free trial ) a getting-started document on windows azure toolkit’s github page covers the installation procedure of all the the required software in detail. this whole project ( cloid ) is freely available at github . so here we’ll limit ourselves to presenting the most relevant code sections along with the corresponding screens. the user interface is composed of a few basic activity screens, spawned from the main screen (top center): since we use a technology not for its own sake but according to our needs, let’s start by specifying what we want: public abstract class storage { /** all providers will have accesss to context*/ protected context context; /** all providers will have accesss to sharedpreferences */ protected cloudpreferences prefs; /** all downloads from providers will be saved on sd card */ protected string download_path = "/sdcard/dcim/camera/"; /** * @throws operationexception * */ public storage(context ctx) throws operationexception { context = ctx; prefs = new cloudpreferences(ctx); } /** * @throws operationexception * */ public abstract void uploadtostorage(string file_path) throws operationexception; /** * @throws operationexception * */ public abstract void downloadfromstorage(string file_name) throws operationexception; /** * @throws operationexception * */ public abstract void browsestorage() throws operationexception; /** * @throws operationexception * */ public abstract void deleteinstorage(string file_name) throws operationexception; } the above is the contract that our cloud storage provider will satisfy. we’ll provide a mockstorage implementation that will pretend to carry out a command in order to test our ui (i.e. our scrollable items list, progress bar, exception messages, etc.), so that we can later just plug in azure storage operations. note from our activities screen above, that we can switch anytime between azure storage and mock storage with the press of the toggle button “cloud on/off” in the settings screen, saving the preferences afterward. public class mockstorage extends storage { // code here... @override public void uploadtostorage(string file_path) throws operationexception { donothingbutsleep(); //throw new operationexception( "test error message", // new throwable("reason: upload test") ); } // other methods will also do nothing but sleep... /***/ private void donothingbutsleep(){ try{ thread.sleep(5000l); } catch (interruptedexception iex){ return; } } 2. the azure toolkit the toolkit comes with a sample application called “simple”, and two library jars: access control for android.jar in the wa-toolkit-android\library\accesscontrol\bin folder azure storage for android.jar in the wa-toolkit-android\library\storage\bin folder here we will only use the latter, since we will access directly azure’s blob storage. needless to say, this is not the recommended way , since our credentials will be stored on the handset. a better approach security-wise would be to access azure storage through web services hosted on either azure or other public/private clouds. once the toolkit is ready for use, we need to think a bit about settings . using an azure blob storage only requires 3 fields: an account name , an access key , and a container for our images. the access key is quite a long string (88 characters) and is kind of a pain to type, so one way to do the setup is to configure the android res/values/strings.xml file to set the default values: ... cloid insert-access-key-here pictures ... however, because we may want to overwrite the default values above (e.g. create another container), we will also save the values on the settings screen in android’s sharedpreferences . and now, let’s implement the azurestorage class. 3. azure blob storage operations 3.1. storage initialization the azurestorage constructor gets its data from android preferences (from its superclass), then constructs a connection string used to access the storage account, creates a blob client and retrieves a reference to the container of images. if the user changed the default container “pictures” in settings, then a new (empty) one will be created with that new name. a container is any grouping of blobs under a name. no blob exists outside of a container. // package here // other imports import com.windowsazure.samples.android.storageclient.blobproperties; import com.windowsazure.samples.android.storageclient.cloudblob; import com.windowsazure.samples.android.storageclient.cloudblobclient; import com.windowsazure.samples.android.storageclient.cloudblobcontainer; import com.windowsazure.samples.android.storageclient.cloudblockblob; import com.windowsazure.samples.android.storageclient.cloudstorageaccount; public class azurestorage extends storage { private cloudblobcontainer container; / * @throws operationexception * */ public azurestorage(context ctx) throws operationexception { super(ctx); // set from prefs string acct_name = prefs.getaccountname(); string access_key = prefs.getaccesskey(); // get connection string string storageconn = "defaultendpointsprotocol=http;" + "accountname=" + acct_name + ";accountkey=" + access_key; // get cloudblobcontainer try { // retrieve storage account from storageconn cloudstorageaccount storageaccount = cloudstorageaccount.parse(conn); // create the blob client // to get reference objects for containers and blobs cloudblobclient blobclient = storageaccount.createcloudblobclient(); // retrieve reference to a previously created container container = blobclient.getcontainerreference( prefs.getcontainer() ); container.createifnotexist(); } catch (exception e) { throw new operationexception("error from initblob: " + e.getmessage(), e); } } // code... we will use that container reference cloudblobcontainer throughout our upcoming cloud operations. 3.2. uploading images we will upload a file from android’s gallery to the cloud, keeping the same filename. “screener” is just a utilities class (see github repository) that does a number of useful things, e.g. extracting a file name from its path and setting the right mime type (“image/jpeg”, “image/png”, etc.). the two kinds of blobs are page blobs and block blobs . the (very) short story is that page blobs are optimized for read & write operations, while block blobs let us upload large files efficiently. in particular we can upload multiple blocks in parallel to decrease upload time. here we are uploading a blob (gallery image) as a set of blocks. /** * @throws operationexception */ @override public void uploadtostorage(string file_path) throws operationexception { try { // create or overwrite blob with contents from a local file // use same name than in local storage cloudblockblob blob = container.getblockblobreference( screener.getnamefrompath(file_path) ); file source = new file(file_path); blob.upload( new fileinputstream(source), source.length() ); blob.getproperties().contenttype = screener.getimagemimetype(file_path); blob.uploadproperties(); } catch (exception e) { throw new operationexception("error from uploadtostorage: " + e.getmessage(), e); } } bear in mind that we are not checking if the file already exists in cloud storage. therefore we will overwrite any existing file with the same name as the one we are uploading. that is usually not desirable in production code. here’s the screen flow of the upload operation: 3.3. browsing the cloud for browsing, we store all our blobs in our container into a list of items that we will display in android as a scrollable list of image names in a subclass of android.app.listactivity . once one item in the list is clicked (“touched”) by the user, we want to display some image properties such as the image size (important when deciding to download), its mime type, and the date it was last operated upon. /** * @throws operationexception * */ @override public void browsestorage() throws operationexception{ // reset uri list for refresh - no caching item.itemlist.clear(); // loop over blobs within the container try { for (cloudblob blob : container.listblobs()) { blob.downloadattributes(); blobproperties props = blob.getproperties(); long ksize = props.length/1024; string type = props.contenttype; date lastmodified = props.lastmodified; item item = new item(blob.geturi(), blob.getname(), ksize, type, lastmodified); item.itemlist.add(item); } // end loop } catch (exception e) { throw new operationexception("error from browsestorage: " + e.getmessage(), e); } } here’s the screen flow of the browse operation. pressing on an item on the list displays its details and operations on the image, which we will look at next: 3.4. downloading images our download method is pretty straightforward. note that we are downloading to the android handset’s sd card by using download_path from the superclass. /** * @throws operationexception * */ @override public void downloadfromstorage(string file_name) throws operationexception{ try { for (cloudblob blob : container.listblobs()) { // download the item and save it to a file with the same name as arg if(blob.getname().equals(file_name)){ blob.download( new fileoutputstream(download_path + blob.getname()) ); break; } } } catch (exception e) { throw new operationexception("error from downloadfromstorage: " + e.getmessage(), e); } } and the corresponding ui flow. instead of displaying the image right after the download, we chose to include a link to the gallery (bottom of the screen) where the freshly retrieved image appears on top of the gallery’s stack of pictures: 3.5. deleting images the delete operation performed on a blob up in the cloud is also rather simple: /** * @throws operationexception */ @override public void deleteinstorage(string file_name) throws operationexception{ try { // retrieve reference to a blob named file_name cloudblockblob blob = container.getblockblobreference(file_name); // delete the blob blob.delete(); } catch (exception e) { throw new operationexception("error from deleteinstorage: " + e.getmessage(), e); } } and its associated ui screens series. note that after confirming the operation, and when deletion completes, the browsing list of items is automatically refreshed, and we can see that the image is no longer on the list of blobs in our storage container. 3.6. wrapping up the azurestorage methods are called inside a basic work thread, which will take care of all cloud operations: // called inside a thread try { // get storage instance from factory storage store = storagefactory.getstorageinstance(this, storagefactory.provider.azure_storage); // for the progress bar incrementworkcount(); // do ops switch(operation){ case upload : store.uploadtostorage(path); break; case browse : store.browsestorage(); break; case download : store.downloadfromstorage(path); // refresh gallery sendbroadcast( new intent( intent.action_media_mounted, uri.parse("file://"+ environment.getexternalstoragedirectory()) ) ); break; case delete : store.deleteinstorage(path); break; } // end switch } catch (operationexception e) { recorderror(e); } notice how we are telling the android image gallery to refresh by issuing a broadcast once a new file is downloaded from the cloud to the sd card. there are different ways to do this, but without that call, the gallery won’t show the new image before the next system scheduled media scan. again, for the full code, refer to this project on github. we are done with the basic cloud operations. all we had to do was plug in our azurestorage implementation class and get an instance of it through a factory, with minimal impact on preexisting code. 4. push notifications up to this point we have demonstrated device-initiated communication with the cloud. for cloud-initiated or push communication, the android platform uses google cloud messaging (gcm). in a previous article , i wrote about how to integrate gcm into an existing android application. here we will add a second set of settings for server push. our client code will connect with any gcm server and it will set the status on our main activity (last screen shot on the right) once the information in push preferences is correctly set. 5. conclusions the toolkit documentation is kind of sparse (which is why the community needs more articles like this). also, the sample application doesn’t cover much (maybe the reason why it’s called “simple”), and it has room for improvement. however, the library itself is fully functional, and once we figure out the api, it all works quite nicely. of course, this application is itself pretty basic and doesn’t cover lots of other features, like access control, permissions, metadata, and snapshots. but it is a start.

see also: part i: when to build your data warehouse part ii: building a new schema part iii: location of your data warehouse part iv: extraction, transformation, and load in part i we looked at the advantages of building a data warehouse independent of cubes/a bi system and in part ii we looked at how to architect a data warehouse’s table schema. in part iii, we looked at where to put the data warehouse tables. in part iv, we are going to look at how to populate those tables and keep them in sync with your oltp system. today, our last part in this series, we will take a quick look at the benefits of building the data warehouse before we need it for cubes and bi by exploring our reporting and other options. as i said in part i, you should plan on building your data warehouse when you architect your system up front. doing so gives you a platform for building reports, or even application such as web sites off the aggregated data. as i mentioned in part ii, it is much easier to build a query and a report against the rolled up table than the oltp tables. to demonstrate, i will make a quick pivot table using sql server 2008 r2 powerpivot for excel (or just powerpivot for short!). i have showed how to use powerpivot before on this blog , however, i usually was going against a sql server table, sql azure table, or an odata feed. today we will use a sql server table, but rather than build a powerpivot against the oltp data of northwind, we will use our new rolled up fact table. to get started, i will open up powerpivot and import data from the data warehouse i created in part ii. i will pull in the time, employee, and product dimension tables as well as the fact table. once the data is loaded into powerpivot, i am going to launch a new pivottable. powerpivot understands the relationships between the dimension and fact tables and places the tables in the designed shown below. i am going to drag some fields into the boxes on the powerpivot designer to build a powerful and interactive pivot table. for rows i will choose the category and product hierarchy and sum on the total sales. i’ll make the columns (or pivot on this field) the month from the time dimension to get a sum of sales by category/product by month. i will also drag in year and quarter in my vertical and horizontal slicers for interactive filtering. lastly i will place the employee field in the report filter pane, giving the user the ability to filter by employee. the results look like this, i am dynamically filtering by 1997, third quarter and employee name janet leverling. this is a pretty powerful interactive report build in powerpivot using the four data warehouse tables. if there was no data warehouse, this pivot table would have been very hard for an end user to build. either they or a developer would have to perform joins to get the category and product hierarchy as well as more joins to get the order details and sum of the sales. in addition, the breakout and dynamic filtering by year and quarter, and display by month, are only possible by the dimtime table, so if there were no data warehouse tables, the user would have had to parse out those dateparts. just about the only thing the end user could have done without assistance from a developer or sophisticated query is the employee filter (and even that would have taken some powerpivot magic to display the employee name, unless the user did a join.) of course pivot tables are not the only thing you can create from the data warehouse tables you can create reports, ad hoc query builders, web pages, and even an amazon style browse application. (amazon uses its data warehouse to display inventory and oltp to take your order.) i hope you have enjoyed this series, enjoy your data warehousing.

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