Using Microsoft SQL Server with Scala Slick

April 26, 2018July 24, 2018Database, Scala, Slickmicrosoft sql server, ms sql server, sbt, scala, slick, slick 3.2.3, sql server

This blog post shows simple CRUD operations on Microsoft SQL Server using Scala Slick version 3.2.3. You might be thinking what’s really great about it? Duh! But until Scala Slick 3.2.x was released, using commercial databases was within the horizon of an additional closed source package know as Slick Extensions which supported Slick drivers for following databases Oracle IBM DB2 Microsoft SQL Server Library Continue Reading

Developers Needs SDKMAN Not Super-Man

December 27, 2017August 10, 2018Apache Spark, Java, linux, Scala, SparkClojure, gradle, grails, groovy, java, jdk, kotlin, linux, Manager, maven, openjdk, opensource, packages, sbt, scala, sdkman, Spark, Spring, springboot, technology, vertx

Every developer has pain for setup development environment to his/her machine with lots of the setups. Sometimes, the pain goes beyond while we need to test same application on multiple versions of SDKs or virtual machines. If you are a Mac user, you have the best option called brew installer. But if you are Linux user, your pain is unpredictable. We are JVM stack developers Continue Reading

Cinnamon: Way For Monitoring & Metrics Generation for Akka ActorSystem

July 3, 2017August 10, 2018Akka, Scala, Telemetry#Cinnamon, #telemetry, actosystem, Akka, cluster, gradle, lightbend, Logback, logs, maven, opensource, sbt, scala, technology

We are developing huge applications and deployed on multiple virtual machines and clusters. For monitoring applications, we need to enable logs into our application and analysis that logs with help of some tools like elastic stack. But !! what if we need to check health of application on virtual machines and clusters? For that, we are using several Metrics for system health check like Gauges, Continue Reading

Gatling Integration with Play

August 8, 2016August 8, 2016LoadTesting, Play, Play 2.4.X, Play Framework, Scala, Testingactivator, gatling, htmlReports, lightbend, load testing, LoadTesting, Performance Testing, Performance Tuning, play, Play Application, Play framework, sbt, scala

I have started working on a project which require stress testing using Gatling. I Setup the sbt project on which gatling is working fine. But when I try to integrate it using play framework, it doesn’t work. The project structure for both are different so it doesn’t work for both the project in the same manner. Your build.sbt should be like this: import _root_.io.gatling.sbt.GatlingPlugin import Continue Reading

Getting Asynchronous in Scala : Part 2 (macro, reflection and Async library)

July 13, 2016July 14, 2016ScalaAsynchronous, compile time reflection, FlatSpec, Future, run time reflection, sbt, scala, scala macro

“Our patience will achieve more than our force.” – Edmund Burke The thought above tells about the beauty of being patient. One of the most important trait of a programming language is to be patient for the code segments to complete their execution asynchronously. In this blog we will continue with the Async library and some prerequisite associated with it. RECAP In first blog of Continue Reading

Scala Macros -An overview

July 13, 2016July 14, 2016ScalaAsynchronous, compile time reflection, FlatSpec, Future, run time reflection, sbt, scala, scala macro

OVERVIEW In this blog we will understand the basics of Macros and reflection. The main motive of the blog is to lay a foundation for better understanding of the the ‘Async library’. The ‘MAGIC’ of macros -> Macros can be called ‘special functions’ that are called by the compiler during compilation. These functions are special as using macros we can access the compiler API’s which Continue Reading

Getting Asynchronous in Scala : Part 1 (Future, Callbacks, Combinators etc.)

July 1, 2016August 4, 2016ScalaAsynchronous, Await.result scala, callbacks, Combinators, intellij, sbt, scala future

‘Only you can control your future.’ – Dr. Seuss The above quote has a great correspondence with this blog. In the blog we will discuss what are Future values and how we access them. During our journey we will be visiting,exploring and understanding following checkpoints :- 1). What are future (basics). 2). How to access them. 3). Basics about Macros. 4). The Async library in Continue Reading

Generating, visiting and unit testing grammar using ANTLR4 with Java and Scala

June 22, 2016June 22, 2016ScalaANTLR4, FunSuite, grammar, intellij, java, Logger, Mockito, sbt, scala, scalastyle, ScalaTest, Scoverage, Testing, Unit Testing

“Quality is free, but only to those who are willing to pay heavily for it” – T. DeMarco Now unit testing is not that heavy to pay off so lets start the blog. In this blog we will be continuing the voyage to the kingdom of ANTLR4 RECAP In previous blog we discussed how to test whether a string is grammatically correct or not using Continue Reading

Deploy a Spark Application on Cluster

June 9, 2016August 14, 2018Scala, SparkApache Spark, cluster, deployment, sbt, scala

In one of our previous blog, Setup a Apache Spark Cluster in your Single Standalone Machine, we showed how to setup a standalone cluster for running spark applications. But we never discussed on how to deploy our Spark applications on that cluster. So, in this blog, we will see how to deploy our Spark application on a cluster and use it to run our spark jobs. For Continue Reading

SBT and Github commands using Linux Cronjob for github project

May 18, 2016August 13, 2018Scalacron, CronJob, github, github Commands, Linux CronJob, sbt, Sbt & Github, Using Linux Cronjob

When i was in the middle of my project I encountered a challenge to run SBT and Github commands for my cloned project at regular intervals(say after every hour or two). When I looked up to the problem it seemed a bit challenging until I did not bump into Linux Cronjob(A time based job scheduler ). Alright, for those who do not know about Cronjobs. Continue Reading

Using Spark , Spray and Couchbase for lightening fast REST Api’s

March 18, 2016March 30, 2016Akka, ScalaAkka, Apache Spark, couchbase, n1ql, sbt, scala, Spark, spary

As we all know Apache Spark™ is a fast and general engine for large-scale data processing, and Couchbase is in-memory no-sql database. So by connecting these two we can get a lightening fast speed. In this blog we are focusing on how to make CRUD operations on couchbase with Spark’s speed. I am assuming that you have a basic Spark’s installation and couchbase installation on Continue Reading

Customized Response Time in Gatling Report

February 3, 2016September 7, 2018LoadTesting, Scala, Testing, Testinggatling, LoadTesting, sbt, scala, Testing, tests

Gatling is a highly capable load testing tool which gives high performance. Some times we face problem in customization response time for our application. In this Blog we will analyse how can we customize response time in Gatling. In Global Information Section In graphical format,this Section Displays the Number of Requests captures in the given Load testing. Every requests are displays according to their Response Continue Reading

Using Spark DataFrames for Word Count

October 21, 2015August 14, 2018Apache Spark, Big Data and Fast Data, Scala, Spark, SQLApache Spark, Big Data, sbt, scala, Spark

As we all know that, DataFrame API was introduced in Spark 1.3.0, in March 2015. Its goal was to make distributed processing of “Big Data” more intuitive, by organizing distributed collection of data (known as RDD) into named columns. This enabled both, Engineers & Data Scientists, to use Apache Spark for distributed processing of “Big Data”, with ease. Also, DataFrame API came with many under the hood optimizations Continue Reading

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