Home » Author Archives: Munish Gupta

Author Archives: Munish Gupta

Munish K Gupta is a senior architect working in a leading IT services company. His experience is in building Online Portals, SaaS Platforms, CRM Solutions and Transaction Processing Systems. He is author of the book - Akka Essentials.

Software Transactional Memory (STM)

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The Actor Model is based on the premise of small independent processes working in isolation and where the state can be updated only via message passing. The actors hold the state within themselves, but the asynchronous message passing means there is no guarantee that a stable view of the state can be provided to the calling components. For transactional systems ...

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Adding Turbochargers to JEE Apps

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One of the key roles, I play is evangelizing Akka within my local community. As part of the discussions, the question/doubt usually in people’s mind is how can Akka provide better scalability and concurrency against a well written Java/JEE application. Since the underlying hardware/JVM remains the same, how can the actor model ooze out more power than the traditional JEE ...

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Application Scalability: Still elusive for Enterprises Apps

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The advent of the Consumer Business application like Facebook, Twitter has changed the definition of Application Scalability. Decade back 10 million+ was a large user base, Facebook will touch 1Billion+ users by end of this year. There are hordes of applications in 100+ million user range. The techniques and approaches employed by these large Consumer Business Applications are different from ...

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Top 5 Picks of Google IO 2012

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Google IO 2012 developer conference has just concluded last week amid lot of fanfare. I for one think that Google has lot more influence on Enterprise technology than it seems. Some of what Enterprises see as latest and greatest of technology (such as Map Reduce) has been pioneered in Google a while ago. This is one the main reasons why ...

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Consumerization of IT – What it means for the Architect

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Consumerization is described as the trend for IT to first emerge in the Consumer space and subsequently makes its way into the enterprise world. But what exactly in the consumer world, that is making the users, demand the similar things from the enterprise IT. To understand the underlying need, we need to first examine the basic requirements of the user. ...

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Akka STM – Playing PingPong with STM Refs and Agents

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PingPong is a classic example where 2 players (or threads) access a shared resource – PingPong Table and pass the Ball (state variable) between each other. With any shared resource, unless we synchronize the access, the threads can run into potential deadlock situation. The PingPong algorithm is very simple if my turn { update whose turn is next ping/pong -log ...

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Implementing Master Slave / Grid Computing Pattern in Akka

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Master Slave pattern is a prime example of fault tolerance and parallel computation. The idea behind the pattern is to partition the work into identical sub tasks which are then delegated to Slaves. These slave node or instances will process the work task and send back the result to the master. The master will then compile the resultsreceivedfrom all the ...

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Processing 10 million messages with Akka

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Akka Actors promise concurrency. What better way to simulate that and see if how much time it takes to process 10 million messages using commodity hardware and software without any low level tunings.I wrote the entire 10 million messages processing in Java and the overall results astonished me. When I ran the program on my iMac machine with an intel ...

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MapReduce for dummies

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Continuing the coverage on Hadoop component, we will go through the MapReduce component. MapReduce is a concept that has been programming model of LISP. But before we jump into MapReduce, lets start with an example to understand how MapReduce works. Given a couple of sentences, write a program that counts the number of words. Now, the traditional thinking when solving ...

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Application Performance and Antipatterns

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Any application you pick up, there are some issues – big or small. There will be copy-paste code, mistakes, algorithms which could have better thought through. But what distinguishes an antipattern from these normal errors is that like patterns these antipatterns are recurring throughout the code base. In my recent experience in dealing with performance issues, I had observed certain ...

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