A few days ago the second beta of Groovy 2.3 got released. One of the major new Groovy 2.3 features are traits. A trait is a reusable set of methods and fields that can be added to one or more classes. A class can be composed out of multiple traits without using multiple inheritance (and therefore avoiding the diamond problem). Basic usage The following piece of code shows a basic definition of a trait in Groovy 2.3. trait SwimmingAbility { def swim() { println "swimming.." } } A trait definition looks very similar to a class definition. This trait defines a single method swim(). We can add this trait to a class using the implements keyword: class Goldfish implements SwimmingAbility { .. } Now we are able to call the swim() methods on Goldfish objects: def goldfish = new Goldfish() goldfish.swim() So far we could have accomplished the same using inheritance. The difference is that we can add multiple traits to a single class. So let's define another trait: trait FlyingAbility { def fly() { println "flying.." } } We can now create a new class that makes use of both traits: class Duck implements SwimmingAbility, FlyingAbility { .. } Ducks can swim and fly now: def duck = new Duck() duck.swim() duck.fly() this inside traits Inside traits the this keyword represents the implementing instance. This means you can write the following: trait FlyingAbility { def fly() { println "${this.class.name} is flying.." } } In case of the Duck class from above this will print Duck is flying.. if we call duck.fly(). A more complex example Now let's look at an example that shows some more features of Groovy traits trait Trader { int availableMoney = 0 private int tradesDone = 0 def buy(Item item) { if (item.price <= availableMoney) { availableMoney -= item.price tradesDone += 1 println "${getName()} bought ${item.name}" } } def sell(Item item) { .. } abstract String getName() } Like Groovy classes traits support properties. Here the property availableMoney will become private and public getter / setter methods will be generated. These methods can be accessed on implementing classes.tradesDone is a private variable that cannot be accessed outside the Trader trait. Within this trait we defined an abstract method getName(). This method has to be implemented by classes that make use of this trait. Let's create a class that implements our Trader trait: class Merchant implements Trader { String name String getName() { return this.name } } A Merchant is now be able to buy items: def bike = new Item(name: 'big red bike', price: 750) def paul = new Merchant(name: 'paul') paul.availableMoney = 2000 paul.buy(bike) // prints "paul bought big red bike" println paul.availableMoney // 1250 Extending from traits, Overriding and conflict resolution A trait can inherit functionality from another trait using the extends keyword: trait Dealer { def getProfit() { ... } def deal() { ... } } trait CarDealer extends Dealer { def deal() { ... } } Here the CarDealer trait extends Dealer and overrides the deal() method of Dealer. Trait methods can also be overwritten in implementing classes: class OnlineCarDealer implements CarDealer { def deal() { ... } } If a class implements more than one trait it is possible to create a conflict. That's the case if two or more traits define a method with an identical signature: trait Car { def drive() { ... } } trait Bike { def drive() { ... } } class DrivingThing implements Car, Bike { ... } In such a situation the last declared trait wins (Bike in this example). Conclusion I think traits are a very useful concept and I am happy to see them in Groovy. Other than Groovy mixins traits work at compile time and can therefore be accessed from Java code. For further reading I can recommend the Groovy 2.3 Trait documentation.

If you need to compare the java.io.file.Path object, be aware that Path.endsWith(String) will ONLY match another sub-element of Path object in your original path, not the path name string portion! If you want to match the string name portion, you would need to call the Path.toString() first. For example // Match all jar files. Files.walk(dir).forEach(path -> { if (path.toString().endsWith(".jar")) System.out.println(path); }); With out the "toString()" you will spend many fruitless hours wonder why your program didn't work.

There are many false ideas around about Java 8. Among these is the idea that Java 8 brings closures to Java.

What's New in this Release? Aspose development team is happy to announce the monthly release of Aspose.Words for Java &.NET 14.3.0. Aspose.Words now supports insertion of OLE objects such as another Microsoft Word document or a Microsoft Excel chart. A new public method, InsertOleObject, has been introduced in the DocumentBuilder class. This method can be used to insert an embedded or linked OLE object from a file into a Word document. Aspose.Words’ rendering engine now partially supports EUDC (End-User-Defined-Characters) fonts. Please find below the description of how EUDC fonts works on Windows. In this first implementation, Aspose.Words uses a single EUDC font. When rendering a document to fixed-page formats, this font is searched among the specified font sources by “EUDC” family name. Starting from Aspose.Words 14.3.0, Best Fit position of data labels in pie charts is partially supported. In previous versions labels with best fit position were rendered as if they had the inside end position. Currently we use a modified Open Office algorithm to set the best fit position of data labels. The list of new and improved features in this release are listed below Public API for insertion of OLE objects both linked and embedded Outline, Shadow, Reflection, Glow and Fill text effects for rendering text inside DrawingML shapes EUDC fonts rendering partially supported “PDF Logical Structure” export reworked, significantly improving memory usage Support OLE embedding of documents and files Feature Write an article about how to work with Table of contents in Aspose.Words Add tag support Support BestFit position of Pie chart's data labels. Support style:text-decoration attribute of Paragraph tag. Preserve private characters in EUDC.TTE during rendering to Pdf Support HTML table row borders in HTML import Support text outline effect. Support text fill effect. Support text shadow effect. Support text reflection effect Support text glow effect. Support text effects applied to text in Dml Shape or in SmartArt. Implement reading text effects from rPr in DML. Support inheriting styles from parent objects. Add image compression options for different image types Add a link to the online documentation in the DLLs only release Default run properties lose lang attribute value on DOCX to DOC conversions Padding for image in table is lost when rendering to Pdf Consider using "Don't vertically align cells containing floating objects" compatibility option when exporting to HTML Shape in table's cell is improperly horizontally aligned to center after export to HTML is now fixed Floating shape is now properly vertically positioned after export to HTML Warning : Unkno/wn ProgId value 'Visio.Drawing.11'. This might cause inaccessible OLE embedding Charts (DrawingML) issue fixed and now render correctly in Pdf file Aspose.Words now properly work in Jdeveloper IDE OLE object cannot be edited after re saving the document Diagram connectors are inverted/flipped after conversion from Docx to pdf WordArt letters are condensing issue is resolved Condensed character spacing is lost is fixed Relative hyperlink with Unicode is now properly saved to Pdf Add pre-built Document Explorer JAR to Java release. Aspose.Words does not take in account style set in . Table now looks correctly while converting html to doc. Hyperlinks split into multiple fragments/links in output PDF Horizontal table position is corrected. Document.UpdateFields Does not Update TOC in DOCX Content in the output html is overlapped at many places in Html Different table justify alignment for different compatibilityMode values. CSS selectors now work for , , and elements Chart Legend/Series now render correctly in output Pdf file Data labels with best fit position are rendering at correct places in Chart Offset of the hyperlink text line is off by a few pixels in output Pdf Hyperlinks split into multiple fragments/links in output PDF is fixed Document.UpdateFields is enhanced and update SUM formula field Paragraph's first line indent increases is fixed when exported to HTM Space before a paragraph following a floating element is too large after HTML to DOCX conversion is now fixd Block-level SVG image become inline after HTML to DOCX conversion Problem with vertical paragraph spacing is resolved when importing HTML using InsertHtml method Shape rotation is fixed after conversion from Doc to Pdf Text color is changed after conversion from Docx to WordML/Doc Word Table indentation is now corrected when is placed inside Arrows on the Lines gets distorted when converting to Pdf is now fixed A space character is exported to PDF output between Japanese and Numeric characters is fixed Line Shape from Header is merged with the top border of Table in Body Docx to WordML conversion issue resolved with content control Junk text is rendered in fixed page formats Positions of some DrawingML circles are now preserved during rendering A row and some content is rendering at the bottom of previous page is fixed Header table rows and images are now preserved in PDF List items issue fixed, now line up correctly after conversion from RTF to HTML Conversion from Docm to Doc creates corrupted document now fixed Hyperlink for an icon is now preserved during HTML to PDF conversion Text overlapping is fixed after conversion from Docx to Pdf Text position change is fixed after conversion from Docx to Pdf Other most recent bug fixes are also included in this release Newly added documentation pages and articles Some new tips and articles have now been added into Aspose.Words for .NET documentation that may guide you briefly how to use Aspose.Words for performing different tasks like the followings. How Aspose.Words Uses True Type Fonts How to Extract Images from a Document Overview: Aspose.Words Aspose.Words is a word processing component that enables .NET, Java & Android applications to read, write and modify Word documents without using Microsoft Word. Other useful features include document creation, content and formatting manipulation, mail merge abilities, reporting features, TOC updated/rebuilt, Embedded OOXML, Footnotes rendering and support of DOCX, DOC, WordprocessingML, HTML, XHTML, TXT and PDF formats (requires Aspose.Pdf). It supports both 32-bit and 64-bit operating systems. You can even use Aspose.Words for .NET to build applications with Mono. More about Aspose.Words Homepage Aspose.Words for .NET Homepage Java Word Library Download Aspose.Words for .NET Download Aspose.Words for Java Demos for Aspose.Words Contact Information Aspose Pty Ltd Suite 163, 79 Longueville Road Lane Cove, NSW, 2066 Australia Aspose - Your File Format Experts [email protected] Phone: 888.277.6734 Fax: 866.810.9465

Before some time I have written a blog post – Converting a C# object into JSON string in that post one of reader, Thomas Levesque commented that mostly people are using JSON.NET a popular high performance JSON for creating for .NET Created by James Newton- King. I agree with him if we are using .NET Framework 4.0 or higher version for earlier version still JavaScriptSerializer is good. So in this post we are going to learn How we can convert C# object into JSON string with JSON.NET framework. What is JSON.NET: JSON.NET is a very high performance framework compared to other serializer for converting C# object into JSON string. It is created by James Newton-Kind. You can find more information about this framework from following link. http://james.newtonking.com/json How to convert C# object into JSON string with JSON.NET framework: For this I am going to use old application that I have used in previous post. Following is a employee class with two properties first name and last name. public class Employee { public string FirstName { get; set; } public string LastName { get; set; } } I have created same object of “Employee” class as I have created in previous post like below. Employee employee=new Employee {FirstName = "Jalpesh", LastName = "Vadgama"}; Now it’s time to add JSON.NET Nuget package. You install Nuget package via following command. I have installed like below. Now we are done with adding NuGet package. Following is code I have written to convert C# object into JSON string. string jsonString = Newtonsoft.Json.JsonConvert.SerializeObject(employee); Console.WriteLine(jsonString); Let's run application and following is a output as expected. That’s it. It’s very easy. Hope you like it. Stay tuned for more.

In this post, we will take a look at how we can create an object pool in Java. In recent times, JVM performance has been multiplied manifold and so object creation is no longer considered as expensive as it was done earlier. But there are few objects, for which creation of new object still seems to be slight costly as they are not considered as lightweight objects. e.g.: database connection objects, parser objects, thread creation etc. In any application we need to create multiple such objects. Since creation of such objects is costly, it’s a sure hit for the performance of any application. It would be great if we can reuse the same object again and again. Object Pools are used for this purpose. Basically, object pools can be visualized as a storage where we can store such objects so that stored objects can be used and reused dynamically. Object pools also controls the life-cycle of pooled objects. As we understood the requirement, let’s come to real stuff. Fortunately, there are various open source object pooling frameworks available, so we do not need to reinvent the wheel. In this post we will be using apache commons pool to create our own object pool. At the time of writing this post Version 2.2 is the latest, so let us use this. The basic thing we need to create is- 1. A pool to store heavyweight objects (pooled objects). 2. A simple interface, so that client can - a.) Borrow pooled object for its use. b.) Return the borrowed object after its use. Let’s start with Parser Objects. Parsers are normally designed to parse some document like xml files, html files or something else. Creating new xml parser for each xml file (having same structure) is really costly. One would really like to reuse the same (or few in concurrent environment) parser object(s) for xml parsing. In such scenario, we can put some parser objects into pool so that they can be reused as and when needed. Below is a simple parser declaration: package blog.techcypher.parser; /** * Abstract definition of Parser. * * @author abhishek * */ public interface Parser { /** * Parse the element E and set the result back into target object T. * * @param elementToBeParsed * @param result * @throws Exception */ public void parse(E elementToBeParsed, T result) throws Exception; /** * Tells whether this parser is valid or not. This will ensure the we * will never be using an invalid/corrupt parser. * * @return */ public boolean isValid(); /** * Reset parser state back to the original, so that it will be as * good as new parser. * */ public void reset(); } Let’s implement a simple XML Parser over this as below: package blog.techcypher.parser.impl; import blog.techcypher.parser.Parser; /** * Parser for parsing xml documents. * * @author abhishek * * @param * @param */ public class XmlParser implements Parser { private Exception exception; @Override public void parse(E elementToBeParsed, T result) throws Exception { try { System.out.println("[" + Thread.currentThread().getName()+ "]: Parser Instance:" + this); // Do some real parsing stuff. } catch(Exception e) { this.exception = e; e.printStackTrace(System.err); throw e; } } @Override public boolean isValid() { return this.exception == null; } @Override public void reset() { this.exception = null; } } At this point, as we have parser object we should create a pool to store these objects. Here, we will be using GenericObjectPool to store the parse objects. Apache commons pool has already build-in classes for pool implementation. GenericObjectPool can be used to store any object. Each pool can contain same kind of object and they have factory associated with them. GenericObjectPool provides a wide variety of configuration options, including the ability to cap the number of idle or active instances, to evict instances as they sit idle in the pool, etc. If you want to create multiple pools for different kind of objects (e.g. parsers, converters, device connections etc.) then you should use GenericKeyedObjectPool . package blog.techcypher.parser.pool; import org.apache.commons.pool2.PooledObjectFactory; import org.apache.commons.pool2.impl.GenericObjectPool; import org.apache.commons.pool2.impl.GenericObjectPoolConfig; import blog.techcypher.parser.Parser; /** * Pool Implementation for Parser Objects. * It is an implementation of ObjectPool. * * It can be visualized as- * +-------------------------------------------------------------+ * | ParserPool | * +-------------------------------------------------------------+ * | [Parser@1, Parser@2,...., Parser@N] | * +-------------------------------------------------------------+ * * @author abhishek * * @param * @param */ public class ParserPool extends GenericObjectPool>{ /** * Constructor. * * It uses the default configuration for pool provided by * apache-commons-pool2. * * @param factory */ public ParserPool(PooledObjectFactory> factory) { super(factory); } /** * Constructor. * * This can be used to have full control over the pool using configuration * object. * * @param factory * @param config */ public ParserPool(PooledObjectFactory> factory, GenericObjectPoolConfig config) { super(factory, config); } } As we can see, the constructor of pool requires a factory to manage lifecycle of pooled objects. So we need to create a parser factory which can create parser objects. Commons pool provide generic interface for defining a factory(PooledObjectFactory). PooledObjectFactory create and manage PooledObjects . These object wrappers maintain object pooling state, enabling PooledObjectFactory methods to have access to data such as instance creation time or time of last use. A DefaultPooledObject is provided, with natural implementations for pooling state methods. The simplest way to implement a PoolableObjectFactory is to have it extend BasePooledObjectFactory . This factory provides a makeObject() that returns wrap(create()) where create and wrap are abstract. We provide an implementation of create to create the underlying objects that we want to manage in the pool and wrap to wrap created instances in PooledObjects. So, here is our factory implementation for parser objects- package blog.techcypher.parser.pool; import org.apache.commons.pool2.BasePooledObjectFactory; import org.apache.commons.pool2.PooledObject; import org.apache.commons.pool2.impl.DefaultPooledObject; import blog.techcypher.parser.Parser; import blog.techcypher.parser.impl.XmlParser; /** * Factory to create parser object(s). * * @author abhishek * * @param * @param */ public class ParserFactory extends BasePooledObjectFactory> { @Override public Parser create() throws Exception { return new XmlParser(); } @Override public PooledObject> wrap(Parser parser) { return new DefaultPooledObject>(parser); } @Override public void passivateObject(PooledObject> parser) throws Exception { parser.getObject().reset(); } @Override public boolean validateObject(PooledObject> parser) { return parser.getObject().isValid(); } } Now, at this point we have successfully created our pool to store parser objects and we have a factory as well to manage the life-cycle of parser objects. You should notice that, we have implemented couple of extra methods- 1. boolean validateObject(PooledObject obj): This is used to validate an object borrowed from the pool or returned to the pool based on configuration. By default, validation remains off. Implementing this ensures that client will always get a valid object from the pool. 2. void passivateObject(PooledObject obj): This is used while returning an object back to pool. In the implementation we can reset the object state, so that the object behaves as good as a new object on another borrow. Since, we have everything in place, let’s create a test to test this pool. Pool clients can – 1. Get object by calling pool.borrowObject() 2. Return the object back to pool by calling pool.returnObject(object) Below is our code to test Parser Pool- package blog.techcypher.parser; import static org.junit.Assert.fail; import java.util.concurrent.ArrayBlockingQueue; import java.util.concurrent.ExecutorService; import java.util.concurrent.ThreadPoolExecutor; import java.util.concurrent.TimeUnit; import java.util.concurrent.atomic.AtomicInteger; import junit.framework.Assert; import org.apache.commons.pool2.impl.GenericObjectPoolConfig; import org.junit.Before; import org.junit.Test; import blog.techcypher.parser.pool.ParserFactory; import blog.techcypher.parser.pool.ParserPool; /** * Test case to test- * 1. object creation by factory * 2. object borrow from pool. * 3. returning object back to pool. * * @author abhishek * */ public class ParserFactoryTest { private ParserPool pool; private AtomicInteger count = new AtomicInteger(0); @Before public void setUp() throws Exception { GenericObjectPoolConfig config = new GenericObjectPoolConfig(); config.setMaxIdle(1); config.setMaxTotal(1); /*---------------------------------------------------------------------+ |TestOnBorrow=true --> To ensure that we get a valid object from pool | |TestOnReturn=true --> To ensure that valid object is returned to pool | +---------------------------------------------------------------------*/ config.setTestOnBorrow(true); config.setTestOnReturn(true); pool = new ParserPool(new ParserFactory(), config); } @Test public void test() { try { int limit = 10; ExecutorService es = new ThreadPoolExecutor(10, 10, 0L, TimeUnit.MILLISECONDS, new ArrayBlockingQueue(limit)); for (int i=0; i parser = null; try { parser = pool.borrowObject(); count.getAndIncrement(); parser.parse(null, null); } catch (Exception e) { e.printStackTrace(System.err); } finally { if (parser != null) { pool.returnObject(parser); } } } }; es.submit(r); } es.shutdown(); try { es.awaitTermination(1, TimeUnit.MINUTES); } catch (InterruptedException ignored) {} System.out.println("Pool Stats:\n Created:[" + pool.getCreatedCount() + "], Borrowed:[" + pool.getBorrowedCount() + "]"); Assert.assertEquals(limit, count.get()); Assert.assertEquals(count.get(), pool.getBorrowedCount()); Assert.assertEquals(1, pool.getCreatedCount()); } catch (Exception ex) { fail("Exception:" + ex); } } } Result: [pool-1-thread-1]: Parser Instance:blog.techcypher.parser.impl.XmlParser@fcfa52 [pool-1-thread-2]: Parser Instance:blog.techcypher.parser.impl.XmlParser@fcfa52 [pool-1-thread-3]: Parser Instance:blog.techcypher.parser.impl.XmlParser@fcfa52 [pool-1-thread-4]: Parser Instance:blog.techcypher.parser.impl.XmlParser@fcfa52 [pool-1-thread-5]: Parser Instance:blog.techcypher.parser.impl.XmlParser@fcfa52 [pool-1-thread-8]: Parser Instance:blog.techcypher.parser.impl.XmlParser@fcfa52 [pool-1-thread-7]: Parser Instance:blog.techcypher.parser.impl.XmlParser@fcfa52 [pool-1-thread-9]: Parser Instance:blog.techcypher.parser.impl.XmlParser@fcfa52 [pool-1-thread-6]: Parser Instance:blog.techcypher.parser.impl.XmlParser@fcfa52 [pool-1-thread-10]: Parser Instance:blog.techcypher.parser.impl.XmlParser@fcfa52 Pool Stats: Created:[1], Borrowed:[10] You can easily see that single parser object was created and reused dynamically. Commons Pool 2 stands far better in term of performance and scalability over Commons Pool 1. Also, version 2 includes robust instance tracking and pool monitoring. Commons Pool 2 requires JDK 1.6 or above. There are lots of configuration options to control and manage the life-cycle of pooled objects. And so ends our long post… :-) Hope this article helped. Keep learning!

In the last week I was working on a key project to migrate a BI platform from MySQL to MongoDB. We chose that database due to its support and scalability.

Introduction All developers are very much concerned about performance. If someone say that this increase performance, all the developer are running behind it. It is not a bad practice at all. Rather as per my point of view we must span all our effort related improve the performance of query. “One common question that we find that, if we change the ordering of table join in case of inner join will effect or increase performance” To understand it lets take a simple example of Inner join. There is two tables named Table-A and Table-B. We can us the Inner Join on both the table. Like this FROM [Table-A] AS a INNER JOIN [Table-B] AS b ON a.IDNO = b.IDNO OR FROM [Table-B] AS a INNER JOIN [Table-A] AS b ON a.IDNO = b.IDNO Which one is best for performance? To answer this question we all know that whenever a SQL Query is executed the MS SQL server create several query plans with different join Order and choose the best one. That means the Join order that we are writing in the query may not be executed by execution plan. May be different join order is used by the execution plan. In the above case the execution plan decide which Join order he will chose depends on best possible costing of execution. Here [Table-A] JOIN [Table-B] or [Table-B] JOIN [Table-A], MS SQL Server knows it well that both are same. To understand it Details Lets take an Example Step-1 [ Create Base Table and Insert Some Records ] -- Item Master IF OBJECT_ID(N'dbo.tbl_ITEMDTLS', N'U')IS NOT NULL BEGIN DROP TABLE [dbo].[tbl_ITEMDTLS]; END GO CREATE TABLE [dbo].[tbl_ITEMDTLS] ( ITEMCD INT NOT NULL IDENTITY PRIMARY KEY, ITEMNAME VARCHAR(50) NOT NULL ) GO -- Inserting Records INSERT INTO [dbo].[tbl_ITEMDTLS] (ITEMNAME) VALUES ('ITEM-1'),('ITEM-2'),('ITEM-3'); -- Item UOM Master IF OBJECT_ID(N'dbo.tbl_UOMDTLS', N'U')IS NOT NULL BEGIN DROP TABLE [dbo].[tbl_UOMDTLS]; END GO CREATE TABLE [dbo].[tbl_UOMDTLS] ( UOMCD INT NOT NULL IDENTITY PRIMARY KEY, UOMNAME VARCHAR(50) NOT NULL ) GO -- Inserting Records INSERT INTO [dbo].[tbl_UOMDTLS] (UOMNAME) VALUES ('KG'),('LTR'),('GRM'); GO -- Transaction Table IF OBJECT_ID(N'dbo.tbl_SBILL', N'U')IS NOT NULL BEGIN DROP TABLE [dbo].[tbl_SBILL]; END GO CREATE TABLE [dbo].[tbl_SBILL] ( TRID INT NOT NULL IDENTITY PRIMARY KEY, ITEMCD INT NOT NULL, UOMCD INT NOT NULL, QTY DECIMAL(18,3) NOT NULL, RATE DECIMAL(18,2) NOT NULL, AMOUNT AS QTY * RATE ); GO -- Foreign Key Constraint ALTER TABLE [dbo].[tbl_SBILL] ADD CONSTRAINT FK_ITEM_tbl_SBILL FOREIGN KEY(ITEMCD) REFERENCES [dbo].[tbl_ITEMDTLS](ITEMCD); GO ALTER TABLE [dbo].[tbl_SBILL] ADD CONSTRAINT FK_UOMCD_tbl_SBILL FOREIGN KEY(UOMCD) REFERENCES [dbo].[tbl_UOMDTLS](UOMCD); -- Insert Records INSERT INTO [dbo].[tbl_SBILL] (ITEMCD, UOMCD, QTY, RATE) VALUES (1, 1, 20, 2000),(2, 3, 23, 1400); Step-2 [ Now Make Some JOIN ] SELECT b.TRID, b.ITEMCD, a.ITEMNAME, b.UOMCD, c.UOMNAME, b.QTY, b.RATE, b.AMOUNT FROM [dbo].[tbl_ITEMDTLS] AS a INNER JOIN [dbo].[tbl_SBILL] AS b ON a.ITEMCD = b.ITEMCD INNER JOIN [dbo].[tbl_UOMDTLS] AS c ON b.UOMCD = c.UOMCD; Here [tbl_ITEMDETAILS] JOIN [tbl_SALES] JOIN [tbl_UOMDETAILS] If we look at the Execution Plan We find that [tbl_SALES] JOIN [tbl_ITEMDETAILS] JOIN [tbl_UOMDETAILS] Step-2 [ Now we need to Force Order Hint to maintain Join Order ] SELECT b.TRID, b.ITEMCD, a.ITEMNAME, b.UOMCD, c.UOMNAME, b.QTY, b.RATE, b.AMOUNT FROM [dbo].[tbl_ITEMDTLS] AS a INNER JOIN [dbo].[tbl_SBILL] AS b ON a.ITEMCD = b.ITEMCD INNER JOIN [dbo].[tbl_UOMDTLS] AS c ON b.UOMCD = c.UOMCD OPTION ( QUERYRULEOFF JoinCommute); For this we need the FORCE ORDER Hint. The query optimizer uses different rules to evaluate different plan and one of the rules is called JoinCommute. We can turn it off using the undocumented query hint QUERYRULEOFF. Hope you like it.

Welcome to part 5 of “Be a lazy but a productive android developer” series. If you are a lazy Android developer and looking for image loading library, which could help you to load image(s) asynchronously without writing a logic for downloading and caching images then this article is for you. This series so far: Part 1: We looked at RoboGuice, a dependency injection library by which we can reduce the boiler plate code, save time and there by achieve productivity during Android app development. Part 2: We saw and explored about Genymotion, which is a rocket speed emulator and super-fast emulator as compared to native emulator. And we can use Genymotion while developing apps and can quickly test apps and there by can achieve productivity. Part 3: We understood and explored about JSON Parsing libraries (GSON and Jackson), using which we can increase app performance, we can decrease boilerplate code and there by can optimize productivity. Part 4: We talked about Card UI and explored card library, also created a basic card and simple card list demo. In this part In this part, we are going to talk about some image libraries using which we can load image(s) asynchronously, can cache images and also can download images into the local storage. Required features for loading images Almost every android app has a need to load remote images. While loading remote images, we have to take care of below things: Image loading process must be done in background (i.e. asynchronously) to avoid blocking UI main thread. Image recycling image should be done. Image should be displayed once its loaded successfully. Images should be cached in local memory for the later use. If remote image gets failed (due to network connection or bad url or any other reasons) to load then it should be managed perfectly for avoiding duplicate requests to load the same again, instead it should load if and only if net connection is available. Memory management should be done efficiently. In short, we have to write a code to manage each and every aspects of image loading but there are some awesome libraries available, using which we can load/download image asynchronously. We just have to call the load image method and success/failure callbacks. Asynchronous image loading Consider a case where we are having 50 images and 50 titles and we try to load all the images/text into the listview, it won’t display anything until all the images get downloaded. Here Asynchronous image loading process comes in picture. Asynchronous image loading is nothing but a loading process which happens in background so that it doesn’t block main UI thread and let user to play with other loaded data on the screen. Images will be getting displayed as and when it gets downloaded from background threads. Asynchronous image loading libraries Nostra’s Universal Image loader – https://github.com/nostra13/Android-Universal-Image-Loader Picasso – http://square.github.io/picasso/ UrlImageViewHelper by Koush Volley - By Android team members @ Google Novoda’s Image loader – https://github.com/novoda/ImageLoader Let’s have a look at examples using Picasso and Universal Image loader libraries. Example 1: Nostra’s Universal Image loader Step 1: Initialize ImageLoader configuration ? public class MyApplication extends Application{ @Override public void onCreate() { // TODO Auto-generated method stub super.onCreate(); // Create global configuration and initialize ImageLoader with this configuration ImageLoaderConfiguration config = new ImageLoaderConfiguration.Builder(getApplicationContext()).build(); ImageLoader.getInstance().init(config); } } Step 2: Declare application class inside Application tag in AndroidManifest.xml file ? Step 3: Load image and display into ImageView ? ImageLoader.getInstance().displayImage(objVideo.getThumb(), holder.imgVideo); Now, Universal Image loader also provides a functionality to implement success/failure callback to check whether image loading is failed or successful. ? ImageLoader.getInstance().displayImage(photoUrl, imgView, new ImageLoadingListener() { @Override public void onLoadingStarted(String arg0, View arg1) { // TODO Auto-generated method stub findViewById(R.id.EL3002).setVisibility(View.VISIBLE); } @Override public void onLoadingFailed(String arg0, View arg1, FailReason arg2) { // TODO Auto-generated method stub findViewById(R.id.EL3002).setVisibility(View.GONE); } @Override public void onLoadingComplete(String arg0, View arg1, Bitmap arg2) { // TODO Auto-generated method stub findViewById(R.id.EL3002).setVisibility(View.GONE); } @Override public void onLoadingCancelled(String arg0, View arg1) { // TODO Auto-generated method stub findViewById(R.id.EL3002).setVisibility(View.GONE); } }); Example 2: Picasso Image loading straight way: ? Picasso.with(context).load("http://postimg.org/image/wjidfl5pd/").into(imageView); Image re-sizing: ? Picasso.with(context) .load(imageUrl) .resize(100, 100) .centerCrop() .into(imageView) Example 3: UrlImageViewHelper library It’s an android library that sets an ImageView’s contents from a url, manages image downloading, caching, and makes your coffee too. UrlImageViewHelper will automatically download and manage all the web images and ImageViews. Duplicate urls will not be loaded into memory twice. Bitmap memory is managed by using a weak reference hash table, so as soon as the image is no longer used by you, it will be garbage collected automatically. Image loading straight way: ? UrlImageViewHelper.setUrlDrawable(imgView, "http://yourwebsite.com/image.png"); Placeholder image when image is being downloaded: ? UrlImageViewHelper.setUrlDrawable(imgView, "http://yourwebsite.com/image.png", R.drawable.loadingPlaceHolder); Cache images for a minute only: ? UrlImageViewHelper.setUrlDrawable(imgView, "http://yourwebsite.com/image.png", null, 60000); Example 4: Volley library Yes Volley is a library developed and being managed by some android team members at Google, it was announced by Ficus Kirkpatrick during the last I/O. I wrote an article about Volley library 10 months back , read it and give it a try if you haven’t used it yet. Let’s look at an example of image loading using Volley. Step 1: Take a NetworkImageView inside your xml layout. ? Step 2: Define a ImageCache class Yes you are reading title perfectly, we have to define an ImageCache class for initializing ImageLoader object. ? public class BitmapLruCache extends LruCache implements ImageLoader.ImageCache { public BitmapLruCache() { this(getDefaultLruCacheSize()); } public BitmapLruCache(int sizeInKiloBytes) { super(sizeInKiloBytes); } @Override protected int sizeOf(String key, Bitmap value) { return value.getRowBytes() * value.getHeight() / 1024; } @Override public Bitmap getBitmap(String url) { return get(url); } @Override public void putBitmap(String url, Bitmap bitmap) { put(url, bitmap); } public static int getDefaultLruCacheSize() { final int maxMemory = (int) (Runtime.getRuntime().maxMemory() / 1024); final int cacheSize = maxMemory / 8; return cacheSize; } } Step 3: Create an ImageLoader object and load image Create an ImageLoader object and initialize it with ImageCache object and RequestQueue object. ? ImageLoader.ImageCache imageCache = new BitmapLruCache(); ImageLoader imageLoader = new ImageLoader(Volley.newRequestQueue(context), imageCache); Step 4: Load an image into ImageView ? NetworkImageView imgAvatar = (NetworkImageView) findViewById(R.id.imgDemo); imageView.setImageUrl(url, imageLoader); Which library to use? Can you decide which library you would use? Let us know which and what are the reasons? Selection of the library is always depends on the requirement. Let’s look at the few fact points about each library so that you would able to compare exactly and can take decision. Picasso: It’s just a one liner code to load image using Picasso. No need to initialize ImageLoader and to prepare a singleton instance of image loader. Picasso allows you to specify exact target image size. It’s useful when you have memory pressure or performance issues, you can trade off some image quality for speed. Picasso doesn’t provide a way to prepare and store thumbnails of local images. Sometimes you need to check image loading process is in which state, loading, finished execution, failed or cancelled image loading. Surprisingly It doesn’t provide a callback functionality to check any state. “fetch()” dose not pass back anything. “get()” is for synchronously read, and “load()” is for asynchronously draw a view. Universal Image loader (UIL): It’s the most popular image loading library out there. Actually, it’s based on the Fedor Vlasov’s project which was again probably a very first complete solution and also a most voted answer (for the image loading solution) on Stackoverflow. UIL library is better in documentation and even there’s a demo example which highlights almost all the features. UIL provides an easy way to download image. UIL uses builders for customization. Almost everything can be configured. UIL doesn’t not provide a way to specify image size directly you want to load into a view. It uses some rules based on the size of the view. Indirectly you can do it by mentioning ImageSize argument in the source code and bypass the view size checking. It’s not as flexible as Picasso. Volley: It’s officially by Android dev team, Google but still it’s not documented. It’s just not an image loading library only but an asynchronous networking library Developer has to define ImageCache class their self and has to initialize ImageLoader object with RequestQueue and ImageCache objects. So now I am sure now you can be able to compare libraries. Choosing library is a bit difficult talk because it always depends on the requirement and type of projects. If the project is large then you should go for Picasso or Universal Image loader. If the project is small then you can consider to use Volley librar, because Volley isn’t an image loading library only but it tries to solve a more generic solution.). I suggest you to start with Picasso. If you want more control and customization, go for UIL. Read more: http://blog.bignerdranch.com/3177-solving-the-android-image-loading-problem-volley-vs-picasso/ http://stackoverflow.com/questions/19995007/local-image-caching-solution-for-android-square-picasso-vs-universal-image-load https://plus.google.com/103583939320326217147/posts/bfAFC5YZ3mq Hope you liked this part of “Lazy android developer: Be productive” series. Till the next part, keep exploring image loading libraries mentioned above and enjoy!

Usually if I concentrate I am able to understand most SQL statements. There are times though such as: When a set of tables is not familiar When I did not write the SQL statement When the SQL statement is long and involves many tables and joins When I want to discuss a statement with a colleague All of the above Having a visual representation of a SQL statement can be helpful in deciphering the statement. My visualisation tool of choice for SQL is an Open Source application called Reverse Snowflake Joins (REVJ). As the name implies, this tool shines when it comes to showing you how your tables are related. I have installed the tool on my workstation but when I am on the move I use the online version of the tool. Using the tool is straight forward, simply paste your SQL statement in the text area and generate the diagram, the online version generates an SVG image. I have at times found that the tool struggles with complex CASE statements. In such cases I remove the CASE statement and just include the fields used in the case statement. Below is a sample statement to show REVJ at work. SELECT a.prod_cat_name ,b.prod_name ,c.prod_owner_name ,p.promo_id ,pt.promo_type ,sum(s.units) as total_units ,sum(s.sale_price) as total_sale_price ,sum(prev_s.units) as prev_yr_total_units FROM product_category a JOIN product b ON a.product_cat_id = b.product_cat_id LEFT OUTER JOIN product_owner c ON a.product_cat_id = c.product_cat_id JOIN sales s ON b.product_id = s.product_id JOIN sales prev_s ON s.sale_year = prev_s.sale_year-1 LEFT OUTER JOIN promotion p ON s.promo_id = p.promo_id RIGHT OUTER JOIN promo_type pt ON p.promo_type_id = pt.promo_type_id WHERE pt.promo_type IN ('Email', 'TV') AND a.prod_cat_name = 'Electronics' AND s.sale_year >=2013 GROUP BY a.prod_cat_name ,b.prod_name ,c.prod_owner_name ,p.promo_id ,pt.promo_type HAVING sum(s.units)>100 The generated image shown below. Notice how the filters applied to each table are also shown, further simplifying the task of understanding the SQL statement. For more complex examples have a look at big samples page.

To convert a byte[] array to a String we can simply use the new String(byte[]) constructor. But if the array contains non-printable bytes we don't get a good representation. In Groovy we can use the method encodeHex() to transform a byte[] array to a hex String value. The byteelements are converted to their hexadecimal equivalents. final byte[] printable = [109, 114, 104, 97, 107, 105] // array with non-printable bytes 6, 27 (ACK, ESC) final byte[] nonprintable = [109, 114, 6, 27, 104, 97, 107, 105] assert new String(printable) == 'mrhaki' assert new String(nonprintable) != 'mr haki' // encodeHex() returns a Writable final Writable printableHex = printable.encodeHex() assert printableHex.toString() == '6d7268616b69' final nonprintableHex = nonprintable.encodeHex().toString() assert nonprintableHex == '6d72061b68616b69' // Convert back assert nonprintableHex.decodeHex() == nonprintable Code written with Groovy 2.2.1

I’m going to start by discussing the Spring WebMVC configuration to compile and run Java without an IDE.

Java is the most widely used language in the world ([citation needed]), and everyone has an opinion about it. Due to it being mainstream, it is usually mocked, and sometimes rightly so, but sometimes the criticism just doesn’t touch reality. I’ll try to explain my favorite 5 misconceptions about Java. Java is slow – that might have been true for Java 1.0, and initially may sounds logical, since java is not compiled to binary, but to bytecode, which is in turn interpreted. However, modern versions of the JVM are very, very optimized (JVM optimizations is a topic worth not just an article, but a whole book) and this is no longer remotely true. As noted here, Java is even on-par with C++ in some cases. And it is certainly not a good idea to make a joke about Java being slow if you are a Ruby or PHP developer. Java is too verbose – here we need to split the language from the SDK and from other libraries. There is some verbosity in the JDK (e.g. java.io), which is: 1. easily overcome with de-facto standard libraries like guava 2. a good thing As for language verbosity, the only reasonable point were anonymous classes. Which are no longer an issue in Java 8 with the the functional additions. Getters and setters, Foo foo = new Foo() instead of using val – that is (possibly) boilerplate, but it’s not verbose – it doesn’t add conceptual weight to the code. It doesn’t take more time to write, read or understand. Other libraries – it is indeed pretty scary to see a class like AbstractCommonAsyncFacadeFactoryManagerImpl. But that has nothing to do with Java. It can be argued that sometimes these long names make sense, it can also be argued that they are as complex because the underlying abstraction is unnecessarily complicated, but either way, it is a design decision taken per-library, and nothing that the language or the SDK impose per-se. It is common to see overengineered stuff, but Java in no way pushes you in that direction – stuff can be done in a simple way with any language. You can certainly have AbstractCommonAsyncFacadeFactoryManagerImpl in Ruby, just there wasn’t a stupid architect that thought it’s a good idea and who uses Ruby. If “big, serious, heavy” companies were using Ruby, I bet we’d see the same. Enterprise Java frameworks are bloatware – that was certainly true back in 2002 when EJB 2 was in use (or “has been”, I’m too young to remember). And there are still some overengineered and bloated application servers that you don’t really need. The fact that people are using them is their own problem. You can have a perfectly nice, readable, easy to configure and deploy web application with a framework like Spring, Guice or even CDI; with a web framework like Spring-MVC, Play, Wicket, and even the latest JSF. Or even without any framework, if you feel like you don’t want to reuse the evolved-through-real-world-use frameworks. You can have an application using a message queue, a NoSQL and a SQL database, Amazon S3 file storage, and whatnot, without any accidental complexity. It’s true that people still like to overeingineer stuff, and add a couple of layers where they are not needed, but the fact that frameworks give you this ability doesn’t mean they make you do it. For example, here’s an application that crawls government documents, indexes them, and provides a UI for searching and subscribing. Sounds sort-of simple, and it is. It is written in Scala (in a very java way), but uses only java frameworks – spring, spring-mvc, lucene, jackson, guava. I guess you can start maintaining pretty fast, because it is straightforward. You can’t prototype quickly with Java – this is sort-of related to the previous point – it is assumed that working with Java is slow, and that’s why if you are a startup, or a weekend/hackathon project, you should use Ruby (with Rails), Python, Node JS or anything else that allows you to quickly prototype, to save & refresh, to painlessly iterate. Well, that is simply not true, and I don’t know even where it comes from. Maybe from the fact that big companies with heavy processes use Java, and so making a java app is taking more time. And Save-and-Refresh might look daunting to a beginner, but anyone who has programmed in Java (for the web) for a while, has to know a way to automate that (otherwise he’s a n00b, right?). I’ve summarized the possible approaches, and all of them are mostly OK. Another example here (which may be used as an example for the above point as well) – I made did this project for verifying secure password storage of websites within a weekend + 1 day to fix stuff in the evening. Including the security research. Spring-MVC, JSP templates, MongoDB. Again – quick and easy. You can do nothing in Java without an IDE – of course you can – you can use notepad++, vim, emacs. You will just lack refactoring, compile-on-save, call hierarchies. It would be just like programming in PHP or Python or javascript. The IDE vs Editor debate is a long one, but you can use Java without an IDE. It just doesn’t make sense to do so, because you get so much more from the IDE than from a text editor + command line tools. You may argue that I’m able to write nice and simple java applications quickly because I have a lot of experience, I know precisely which tools to use (and which not) and that I’m of some rare breed of developers with common sense. And while I’ll be flattered by that, I am no different than the good Ruby developer or the Python guru you may be. It’s just that java is too widespread to have only good developers and tools. if so many people were using other language, then probably the same amount of crappy code would’ve been generated. (And PHP is already way ahead even with less usage). I’m the last person not to laugh on jokes about Java, and it certainly isn’t the silver bullet language, but I’d be happier if people had less misconceptions either because of anecdotal evidence, or due to previous bad experience a-la “I hate Java since my previous company where the project was very bloated”. Not only because I don’t like people being biased, but because you may start your next project with a language that will not work, just because you’ve heard “Java is bad”.

It’s a common pattern for command line tools to have multiple subcommands that run off of a single executable. For example, git fetch origin and git commit --amend both use the same executable /usr/bin/git to run. Each subcommand has its own set of required and optional parameters. This pattern is fairly easy to implement in your own Python command-line utilities using argparse. Here is a script that pretends to be git and provides the above two commands and arguments. #!/usr/bin/env python import argparse import sys class FakeGit(object): def __init__(self): parser = argparse.ArgumentParser( description='Pretends to be git', usage='''git [] The most commonly used git commands are: commit Record changes to the repository fetch Download objects and refs from another repository ''') parser.add_argument('command', help='Subcommand to run') # parse_args defaults to [1:] for args, but you need to # exclude the rest of the args too, or validation will fail args = parser.parse_args(sys.argv[1:2]) if not hasattr(self, args.command): print 'Unrecognized command' parser.print_help() exit(1) # use dispatch pattern to invoke method with same name getattr(self, args.command)() def commit(self): parser = argparse.ArgumentParser( description='Record changes to the repository') # prefixing the argument with -- means it's optional parser.add_argument('--amend', action='store_true') # now that we're inside a subcommand, ignore the first # TWO argvs, ie the command (git) and the subcommand (commit) args = parser.parse_args(sys.argv[2:]) print 'Running git commit, amend=%s' % args.amend def fetch(self): parser = argparse.ArgumentParser( description='Download objects and refs from another repository') # NOT prefixing the argument with -- means it's not optional parser.add_argument('repository') args = parser.parse_args(sys.argv[2:]) print 'Running git fetch, repository=%s' % args.repository if __name__ == '__main__': FakeGit() The argparse library gives you all kinds of great stuff. You can run ./git.py --help and get the following: usage: git [] The most commonly used git commands are: commit Record changes to the repository fetch Download objects and refs from another repository Pretends to be git positional arguments: command Subcommand to run optional arguments: -h, --help show this help message and exit You can get help on a particular subcommand with ./git.py commit --help. usage: git.py [-h] [--amend] Record changes to the repository optional arguments: -h, --help show this help message and exit --amend Want bash completion on your awesome new command line utlity? Try argcomplete, a drop in bash completion for Python + argparse.

There is actually nothing very special about writing a Spring-boot web application purely using Scala, it just works! In this blog entry, I will slowly transform a Java based Spring-boot application completely to Scala - the Java based sample is available at this github location - https://github.com/bijukunjummen/spring-boot-mvc-test To start with, I had the option of going with either a maven based build or gradle based build - I opted to go with a gradle based build as gradle has a greatscala plugin, so for scala support the only changes to a build.gradle build script is the following: ... apply plugin: 'scala' ... jar { baseName = 'spring-boot-scala-web' version = '0.1.0' } dependencies { ... compile 'org.scala-lang:scala-library:2.10.2' ... } Essentially adding in the scala plugin and specifying the version of the scala-library. Now, I have one entity, a Hotel class, it transforms to the following with Scala: package mvctest.domain .... @Entity class Hotel { @Id @GeneratedValue @BeanProperty var id: Long = _ @BeanProperty var name: String = _ @BeanProperty var address: String = _ @BeanProperty var zip: String = _ } Every property is annotated with @BeanProperty annotation to instruct scala to generate the Java bean based getter and setter on the variables. With the entity in place a Spring-data repository for CRUD operations on this entity transforms from: import mvctest.domain.Hotel; import org.springframework.data.repository.CrudRepository; public interface HotelRepository extends CrudRepository { } to the following in Scala: import org.springframework.data.repository.CrudRepository import mvctest.domain.Hotel import java.lang.Long trait HotelRepository extends CrudRepository[Hotel, Long] And the Scala based controller which uses this repository to list the Hotels - vi... import org.springframework.web.bind.annotation.RequestMapping import org.springframework.stereotype.Controller import mvctest.service.HotelRepository import org.springframework.beans.factory.annotation.Autowired import org.springframework.ui.Model @Controller @RequestMapping(Array("/hotels")) class HotelController @Autowired() (private val hotelRepository: HotelRepository) { @RequestMapping(Array("/list")) def list(model: Model) = { val hotels = hotelRepository.findAll() model.addAttribute("hotels", hotels) "hotels/list" } } Here the constructor autowiring of the HotelRepository just works!. Do note the slightly awkward way of specifying the @Autowired annotation for constructor based injection. Finally, Spring-boot based application requires a main class to bootstrap the entire application, where this bootstrap class looks like this with Java: @Configuration @EnableAutoConfiguration @ComponentScan public class SampleWebApplication { public static void main(String[] args) { SpringApplication.run(SampleWebApplication.class, args); } } In scala, though I needed to provide two classes, one to specify the annotation and other to bootstrap the application, there may be better way to do this(blame it on my lack of Scala depth!) - package mvctest import org.springframework.context.annotation.Configuration import org.springframework.boot.autoconfigure.EnableAutoConfiguration import org.springframework.context.annotation.ComponentScan import org.springframework.boot.SpringApplication @Configuration @EnableAutoConfiguration @ComponentScan class SampleConfig object SampleWebApplication extends App { SpringApplication.run(classOf[SampleConfig]); } and that's it, with this set-up the entire application just works, the application can be started up with the following: ./gradlew build && java -jar build/libs/spring-boot-scala-web-0.1.0.jar and the sample endpoint listing the hotels accessed at this url: http://localhost:8080/hotels/list I have the entire git project available at this github location: https://github.com/bijukunjummen/spring-boot-scala-web In conclusion, Scala can be considered a first class citizen for a Spring-boot based application and there is no special configuration required to get a Scala based Spring-boot application to work. It just works!

So I finally made the decision on trying to learn Scala. Little did I know I was in for another round of IntelliJ integration hell. Let me rephrase that: IntelliJ with Gradle hell. I love Gradle. I love IntelliJ. However, the combination of the two is sometimes enough to drive me utterly crazy. Now take for example the Scala integration. I made the most simple Gradle build possible that compiles a standard Hello World application. apply plugin: 'scala' apply plugin: 'idea' repositories{ mavenCentral() mavenLocal() } dependencies{ compile 'org.slf4j:slf4j-api:1.7.5' compile "org.scala-lang:scala-library:2.10.4" compile "org.scala-lang:scala-compiler:2.10.4" testCompile "junit:junit:4.11" } task run(type: JavaExec, dependsOn: classes) { main = 'Main' classpath sourceSets.main.runtimeClasspath classpath configurations.runtime } First I stumbled upon the first issue: the Scala gradle plugin is incompatible with Java 8. Not a big issue, but this meant changing my java environment for this build, so it is a nuisance. Once this was fixed, the Gradle build succeeded and Hello World was printed out. I opened up IntelliJ and made sure the Scala plugin was installed. Then I imported the project using the Gradle build file. Everything looked okay, IntelliJ recognized the Scala source folder and provided the correct editor for the Scala source file. Then I tried to run the Main class. This resulted in a NoClassDefFoundException. IntelliJ didn’t want to compile my source classes. So I started digging. Apparently, the project was lacking a Scala facet. I’d expected IntelliJ to automatically add this once it saw I was using the scala plugin but it didn’t. So I tried manually adding the facet and there I got stuck. See, the facet requires you to state which scala compiler library you want to use. Luckily IntelliJ correctly added the jars to the classpath, so I was able to choose the correct jar. This, however, did not fix the issue as IntelliJ now complained it could not locate the scala runtime library (scala-library*.jar). This library was however included in the build. If you were to choose the runtime library as the scala library, it would complain it cannot find the compiler library. And this is where I am now: deadlocked. There is an issue in the bugtracker of IntelliJ here but it’s been eerily quiet at Jetbrains on this issue. As it is, it’s impossible to use IntelliJ with Gradle and Scala unless you’re willing to execute every bit of code including unit tests with Gradle instead of the IDE (which in effect defeats the purpose of an IDE). And I’ll die before adopting yet another build framework (SBT) that is supposed to work. Honestly, I really don’t know whether I want to learn Scala anymore. Just the fact that you can’t compile Scala in the most popular IDE at the moment when using the most popular build tool at the moment is something I cannot comprehend. Forcing me to adopt a Scala-specific build tool is unacceptable to me. If I were TypeSafe, I’d put an engineer on this and fix this as this would seriously aid in promoting the language. If it were easy to adopt Scala in an existing build cycle, it would pop up on more radars than it would right now. But it’s not just Scala and IntelliJ: most newer JVM languages struggle with IntelliJ. This is a real pity as this either forces me to change my IDE (i.e. Ceylon has its own IDE based on Eclipse) or not consider the language. As it is, the current viable option with IntelliJ is Java and Groovy (and Kotlin, but it’s not even near production ready quality). Wouldn’t it be nice to only need one IDE for all development? I couldn’t care less if it would cost $500, I just want things to work. I’d love to be able to write my AngularJS front-end that’s consuming my Scala/Java hydrid backend reading data from a MongoDB that’s feeded data from my Arduino sensors (for which I’ve written and uploaded the sketch from that same IDE).

Performance tuning SELECT statements can be a time consuming task which in my opinion follows Pareto principle’s. 20% effort is likely give you an 80% performance improvement. To get another 20% performance improvement you probably need to spend 80% of the time. Unless you work on the planet Venus where each day on Venus is equal to 243 Earth days, delivery deadlines are likely to mean you will not have enough time to put into tuning your SQL queries. After years writing and running SQL statements I began to develop a mental check-list of things I looked at when trying to improve query performance. These are the things I check before moving on to query plans and reading the sometimes complicated documentation of the database I am working on. My check-list is by no means comprehensive or scientific, more like a back of the envelope calculation but can I can say that most of the time I do get performance improvements following these simple steps. The check-list follows. Check Indexes There should be indexes on all fields used in the WHERE and JOIN portions of the SQL statement. Take the 3-Minute SQL performance test. Regardless of your score be sure to read through the answers as they are informative. Limit Size of Your Working Data Set Examine the tables used in the SELECT statement to see if you can apply filters in the WHERE clause of your statement. A classic example is when a query initially worked well when there were only a few thousand rows in the table. As the application grew the query slowed down. The solution may be as simple as restricting the query to looking at the current month’s data. When you have queries that have sub-selects, look to apply filtering to the inner statement of the sub-selects as opposed to the outer statements. Only Select Fields You Need Extra fields often increase the grain of the data returned and thus result in more (detailed) data being returned to the SQL client. Additionally: When using reporting and analytical applications, sometimes the slow report performance is because the reporting tool has to do the aggregation as data is received in detailed form. Occasionally the query may run quickly enough but your problem could be a network related issue as large amounts of detailed data are sent to the reporting server across the network. When using a column-oriented DBMS only the columns you have selected will be read from disk, the less columns you include in your query the less IO overhead. Remove Unnecessary Tables The reasons for removing unnecessary tables are the same as the reasons for removing fields not needed in the select statement. Writing SQL statements is a process that usually takes a number of iterations as you write and test your SQL statements. During development it is possible that you add tables to the query that may not have any impact on the data returned by the SQL code. Once the SQL is correct I find many people do not review their script and remove tables that do not have any impact or use in the final data returned. By removing the JOINS to these unnecessary tables you reduce the amount of processing the database has to do. Sometimes, much like removing columns you may find your reduce the data bring brought back by the database. Remove OUTER JOINS This can easier said than done and depends on how much influence you have in changing table content. One solution is to remove OUTER JOINS by placing placeholder rows in both tables. Say you have the following tables with an OUTER JOIN defined to ensure all data is returned: customer_id customer_name 1 John Doe 2 Mary Jane 3 Peter Pan 4 Joe Soap customer_id sales_person NULL Newbee Smith 2 Oldie Jones 1 Another Oldie NULL Greenhorn The solution is to add a placeholder row in the customer table and update all NULL values in the sales table to the placeholder key. customer_id customer_name 0 NO CUSTOMER 1 John Doe 2 Mary Jane 3 Peter Pan 4 Joe Soap customer_id sales_person 0 Newbee Smith 2 Oldie Jones 1 Another Oldie 0 Greenhorn Not only have you removed the need for an OUTER JOIN you have also standardised how sales people with no customers are represented. Other developers will not have to write statements such as ISNULL(customer_id, “No customer yet”). Remove Calculated Fields in JOIN and WHERE Clauses This is another one of those that may at times be easier said than done depending on your permissions to make changes to the schema. This can be done by creating a field with the calculated values used in the join on the table. Given the following SQL statement: FROM sales a JOIN budget b ON ((year(a.sale_date)* 100) + month(a.sale_date)) = b.budget_year_month Performance can be improved by adding a column with the year and month in the sales table. The updated SQL statement would be as follows: SELECT * FROM PRODUCTSFROM sales a JOIN budget b ON a.sale_year_month = b.budget_year_month Conclusion The recommendations boil down to a few short pointers check for indexes work with the smallest data set required remove unnecessary fields and tables and remove calculations in your JOIN and WHERE clauses. If all these recommendations fail to improve your SQL query performance my last suggestion is you move to Venus. All you will need is a single day to tune your SQL.

want to add java 8 support to kepler? java 8 has not yet landed in our standard download packages . but you can add it to your existing eclipse kepler package. i’ve got three different eclipse installations running java 8: a brand new kepler sr2 installation of the eclipse ide for java developers; a slightly used kepler sr1 installation of the eclipse for rcp/rap developers (with lots of other features already added); and a nightly build (dated march 24/2014) of eclipse 4.4 sdk. the jdt team recommends that you start from kepler sr2, the second and final service release for kepler (but using the exact same steps, i’ve installed it into kepler sr1 and sr2 packages). there are some detailed instructions for adding java 8 support by installing a feature patch in the eclipsepedia wiki . the short version is this: from kepler sr2, use the “help > install new software…” menu option to open the “available software” dialog; enter http://download.eclipse.org/eclipse/updates/4.3-p-builds/ into the “work with” field (highlighted below); put a checkbox next to “eclipse java 8 support (for kepler sr2)” (highlighted below); click “next”, click “next”, read and accept the license, and click “finish” watch the pretty progress bar move relatively quickly across the bottom of the window; and restart eclipse when prompted. select “help > install new software…” to open the available software dialog. voila! support for java 8 is installed. if you’ve already got the java 8 jdk installed and the corresponding jre is the default on your system, you’re done. if you’re not quite ready to make the leap to a java 8 jre, there’s still hope (my system is still configured with java 7 as the default). install the java 8 jdk; open the eclipse preferences, and navigate to “java > installed jres”; java runtime environment preferences click “add…”; select “standard vm”, click “next”; enter the path to the java 8 jre (note that this varies depending on platform, and how you obtain and install the bits); java 8 jre definition click “finish”. before closing the preferences window, you can set your workspace preference to use the newly-installed java 8 jre. or, if you’re just planning to experiment with java 8 for a while, you can configure this on a project-by-project basis. in the create a java project dialog, specify that your project will use a javase-1.8 jre. it’s probably better to do this on the project as this will become a project setting that will follow the project into your version control system. next step… learn how wrong my initial impressions of java 8 were (hint: it’s far better). the lambda is so choice. if you have the means, i highly recommend picking one up. about these ads

Recently, I had to take some content in markdown, specifically markdown extra, and convert it to a series of PDFs styled with a specific branding. While some will argue that PDFs are dead and “long live the web”, many of us still need to produce PDFs for one reason or another. In this case I had to take markdown extra, with some html sprinkled in, clean it up, and convert it to a styled PDF. What follows is how I did that using QueryPath for the cleanup and DOMPDF to make the conversion. The Setup At the root of this little app was a PHP script with the dependencies managed through composer. The composer.json file looked like: { "name": "foo/bar", "description": "Convert markdown to PDF.", "type": "application", "require": { "php": ">=5.3.0", "michelf/php-markdown": "1.4.*", "dompdf/dompdf" : "0.6.*", "querypath/querypath": "3.*", "masterminds/html5": "1.*" } } Turning the Markdown into HTML Within the script I started with a file we’ll call $file. Form here it was easy using the official markdown extra conversion utility. $markdown = file_get_contents($file); $markdownParser = new \Michelf\MarkdownExtra(); $html = $markdownParser->transform($markdown); This produces the html needed to go inside the body of an html page. From here I wrapped it in a document because I could easily link to a CSS file for styling purposes. DOMPDF supports quite a bit of CSS 2.1. $html = '' . $html . '’; pdf.css is where you can style the PDF. If you know how to style web pages using CSS you can manage to style a PDF document. Cleaning Up The Content There were a number of places html had been injected into the markdown that was either broken, unwanted in a PDF, or an edge case that DOMPDF didn’t support. To make these changes I used QueryPath. For example, I needed to take relative links, normally used in generation of a website, and add a domain name to them: $dom = \HTML5::loadHTML($html); $links = htmlqp($dom, 'a'); foreach ($links as $link) { $href = $link->attr('href'); if (substr($href, 0, 1) == '/' && substr($href, 1, 1) != '/') { $link->attr('href', $domain_name . $href); } } $html = \HTML5::saveHTML($dom); Note, I used the HTML5 parser and writer rather than the built-in one designed for xhtml and HTML 4. This is because DOMPDF attempts to work with HTML5 and I wanted to keep that consistent from the beginning. Converting to PDF There is a little setup before using DOMPDF. It has a built in autoloader which should be disabled and needs a config file. In my case I used the default config file and handled this with: define('DOMPDF_ENABLE_AUTOLOAD', false); require_once __DIR__ . '/vendor/dompdf/dompdf/dompdf_config.inc.php'; The conversion was fairly straight forward. I used a snippet like: $dompdf = new DOMPDF(); $dompdf->load_html($html); $dompdf->render(); $output = $dompdf->output(); file_put_contents(‘path/to/file.pdf', $output); DOMPDF has a lot of options and some quirks. It wasn’t exactly designed for composer. For example, if you want to work with custom fonts you need to get the project from git and install submodules. Despite the quirks, needing to cleanup some of the html, and brand the documents, I was able to write a conversion script that handled dozens of documents quickly. Almost all of my time was on html cleanup and css styling.

In SQL Server management studio, using, View, Registered Servers (Ctrl+Alt+G) set up the servers that you want to execute the same query across all servers for, right click the group, select new query. Then when you execute the query, the results will come back with the first column showing you the database instance that that row came from.