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Creating a front-end JavaScript project can be a daunting task due to the sheer volume of choices available while deciding the tech stack. First, you need to decide the JavaScript framework or library for your project. Do you plan to use the latest ES2015 language features in your code? If yes, then you need a transpiler because your browser probably doesn’t support them yet. Then you require a bundling tool to get your code loaded in the browser. You may want to minify the code for faster load time. To automate all these steps, you need a build script. You may want to deploy your project on a local web server during development. Some setup is required for that. Finally, you need to include some testing framework in your project to write unit tests.

Hystrix is a fault tolerance library that is very useful for managing failures in a distributed environment like microservices. Suppose we have a service A dependent on service B, which is in turn dependent on service C.

A -> B -> C

Let’s say a call is made from A to B. To serve this request, B needs to call C but there’s a communication failure between them. If the call from B to C is wrapped in Hystrix mechanism, we prevent the failure being propagated to A. Because B couldn’t fetch the actual information from C, Hystrix gives us the option of declaring a fallback value to be used in this case, if feasible.

Recently I delved into the RxJava library. In this post I will demonstrate how RxJava Observables can be used to execute two long running tasks in parallel, so as to reduce their overall execution time.

While we can create threads for this purpose, an additional benefit of using Observables is that it provides a convenient way of collecting the results of the parallel tasks. With threads, this can get pretty complicated. Let’s consider a situation where we have a consumer class that depends on the result of two or more expensive independent tasks.

public class Producer1 {
  public List<Integer> produce() {
    List<Integer> list = new ArrayList<Integer>();
    
    for(int i=0; i<5; i++) {
      System.out.println("Producer1 - " + i);
      try {
        Thread.sleep(1000);
      } catch(Exception e) {}
      list.add(i);
    }
    return list;
  }
}

public class Producer2 {
  public List<Integer> produce() {
    List<Integer> list = new ArrayList<Integer>();
    
    for(int i=0; i<5; i++) {
      System.out.println("Producer2 - " + i);
      try {
        Thread.sleep(1000);
      } catch(Exception e) {}
      list.add(i);
    }
    return list;
  }
}

Aspect oriented programming (AOP) is a way of separating the business login in your code from cross cutting concerns. What is a cross cutting concern?

Analogy time. A typical house has different rooms that have designated functions. We keep our stuff in the rooms where they make sense. The living room is an unlikely location for a dishwasher and a bathtub belongs in the bathroom. But the electric circuit runs throughout the house because it is not tied to the functionality of any specific room. Thus, the electric circuit is a cross-cutting concern.

Recently I have been trying to learn different memory profiling tools to monitor Java applications. I have looked into the command line tools that are shipped as part of JDK like jstat, jps, jvisualvm etc. Licensed tools like Yourkit provide wholesome information about a running JVM including memory usage, CPU time, thread count etc. Running a java application with -verbose:gc option prints memory usage of each generation after every garbage collection event.

In a relational database, the relationships between two tables are defined by foreign keys. Typically, one table has a column that contains the primary key of another table’s row. In JPA, we deal with entity objects that are Java representations of database tables. So we need a different way for establishing relationship between two entities. JPA entity relationships define how these entities refer to each other.

For the purpose of this article, I will work with JPA 2.0 and a table structure as following.

CREATE TABLE team(team_id NUMBER, name VARCHAR2(20));
INSERT INTO team(team_id, name) VALUES(1, 'india');
INSERT INTO team(team_id, name) VALUES(2, 'australia');
INSERT INTO team(team_id, name) VALUES(3, 'england');


CREATE TABLE player(player_id NUMBER, name VARCHAR2(50), team_id NUMBER, age NUMBER, role VARCHAR2(20));
INSERT INTO player(player_id, name, team_id, age, role) VALUES(1, 'sachin', 1, 42, 'batsman');
INSERT INTO player(player_id, name, team_id, age, role) VALUES(2, 'dhoni', 1, 34, 'wicketkeeper');
INSERT INTO player(player_id, name, team_id, age, role) VALUES(3, 'clarke', 2, 38, 'batsman');
INSERT INTO player(player_id, name, team_id, age, role) VALUES(4, 'rogers', 2, 40, 'batsman');
INSERT INTO player(player_id, name, team_id, age, role) VALUES(5, 'cook', 3, 31, 'batsman');
INSERT INTO player(player_id, name, team_id, age, role) VALUES(6, 'root', 3, 26, 'batsman');

CREATE TABLE player_stat(player_stat_id NUMBER, player_id NUMBER, runs NUMBER, wickets NUMBER);
INSERT INTO player_stat(player_stat_id, player_id, runs, wickets) VALUES(10, 1, 10000, 300);
INSERT INTO player_stat(player_stat_id, player_id, runs, wickets) VALUES(20, 2, 5000, 10);
INSERT INTO player_stat(player_stat_id, player_id, runs, wickets) VALUES(30, 3, 7000, 100);
INSERT INTO player_stat(player_stat_id, player_id, runs, wickets) VALUES(40, 4, 2000, 0);
INSERT INTO player_stat(player_stat_id, player_id, runs, wickets) VALUES(50, 5, 9000, 0);

jdb (Java Debugger) is a simple command-line debugger for Java classes that is provided as part of the JDK tools and utilities.

jdb is based on a server-client model. While debugging, you have one JVM where the code is executed and another JVM where debugger runs. Either VMs can act as the server. There are two ways to start the debugger. You can directly fire up the debugger by giving the main class name with the jdb command.

In a microservices environment we can run multiple instances of a service for resilience and scalability. In a cloud environment these instances can go up and down arbitrarily. So we need some kind of service discovery mechanism to keep track of running instances. When a service A needs to call a service B, it asks for the address of any running instance of service B from the service discovery. The service discovery can also load balance the incoming requests. In this post I demonstrate how to setup a service discovery environment with Netflix Eureka. When ever a service instance spins up, it registers itself with Eureka and sends regular heartbeats to confirm its availability.

From the official documentation,

Spring Cloud Config provides server and client-side support for externalized configuration in a distributed system. With the Config Server you have a central place to manage external properties for applications across all environments.

Steps to configure config server

a. Create a new Gradle project for the config server. In https://start.spring.io/, select the starters for config server.

b. In your project, navigate to src/main/resources. Rename the automatically generated application.properties file to bootstrap.yml.

Gradle is a popular build tool to manage Java projects. Gradle’s build scripts are written in Groovy. The design of Gradle is aimed to be used as a language, not as a rigid framework. In this article, I want to give some basic idea about what a Gradle build script is composed of and some of the features provided by Gradle.

Gradle is based upon two basic concepts: projects and tasks. A project can be your application or a library that might be used by a different project. A project doesn’t have to be something that you build, it could be something to be performed, like deploying an application. A task represents a particular piece of work that is done in a build process, like compiling some classes or running unit tests.