Java

Spring Beans in Java

Java, spring boot, ,

Reading Time: 2 minutes Spring IoC container is the core of the Spring Framework.In spring-based applications, objects live inside a spring containerThe container instantiate the objects, wires them together and manages their complete life cycle from creation till destruction.These objects in the Spring IoC container are referred to as beans. What is Inversion Of Control(IoC)? IoC simply means giving control to spring container to create and instantiate the spring beans Let`s say you want to Continue Reading

Lambda Expressions: An Introduction in Java 8

Java, Tech Blogs,

Reading Time: 2 minutes Lambda expressions were one of the new features that was introduced in Java 8. They help clean up verbose code by providing a concise and local way to reduce redundancy by keeping code short and self-explanatory. In addition to saving code, Java’s lambda expressions are important in functional programming. They allow developers to write in a functional style by acting as functions without belonging to Continue Reading

Getting started with GraphQL

API's, Functional Programming, GraphQL, Java, java11, Tech Blogs, , , ,

Reading Time: 2 minutes The world is a stage where all of us are artists. Constant learning is the foundation of success. So, here we are going to learn about a query language introduced by Facebook back in 2015, which is GraphQL. In this blog, we will cover the basics of GraphQL. Overview GraphQL is a query language(that’s what QL stands for) for your API and a server-side runtime Continue Reading

Why to use Java9 when I have Java8?

Java, Tech Blogs, ,

Reading Time: 3 minutes The concept of JPMS i.e. Java Platform Module System came in Java 9. Its development was first started in 2005 and finally in 2017, this concept came under the project named Jigsaw. Until Java 8, we used jar files for packaging and bundling the application, but from Java 9 onward, we will be using modules for that. Modularity is the basic rule of good software Continue Reading

Flink: Union operator on Multiple Streams

Apache Flink, Big Data and Fast Data, Flink, Java, Streaming, Streaming Solutions, , , , , , ,

Reading Time: 3 minutes Apache Flink offers rich sources of API and operators which makes Flink application developers productive in terms of dealing with the multiple data streams. Flink provides many multi streams operations like Union, Join, and so on. In this blog, we will explore the Union operator in Flink that can combine two or more data streams together. We know in real-time we can have multiple data streams from different sources Continue Reading

Flink: Implementing the Session window.

Apache Flink, Big Data and Fast Data, Flink, Java, Streaming, Streaming Solutions, , , , , ,

Reading Time: 3 minutes In the previous blogs, we learned about Tumbling, Sliding, and Count windows in Flink. There is one another useful way to window the data which Flink offers i.e, Session window. So in this blog, we will explore the Session window in detail with an example. In the real world, all the work that we do online- Visiting a website, Clicking around the website, do online Continue Reading

Flink: Implementing the Count Window

Apache Flink, Big Data and Fast Data, Flink, Functional Programming, Java, , , , ,

Reading Time: 3 minutes In the blog, we learned about Tumbling and Sliding windows which is based on time. In this blog, we are going to learn to define Flink’s windows on other properties i.e Count window. As the name suggests, count window is evaluated when the number of records received, hits the threshold. Count window set the window size based on how many entities exist within that window. For example, if we fixed the count Continue Reading

Flink: Time Windows based on Processing Time

Apache Flink, Big Data and Fast Data, Flink, Java, ML, AI and Data Engineering, , , , , , , ,

Reading Time: 4 minutes In the previous blog, we talked about Flink’s windows operator, a heart of processing infinite streams. Generally in Flink, after specifying that the stream is keyed or non keyed, the next step is to define a window assigner. The window assigner defines how elements are assigned to windows. Flink provides some useful predefined window assigners like Tumbling windows, Sliding windows, Session windows, Count windows, and Continue Reading

Spark SQL in Delta Lake 0.7.0

Apache Spark, Big Data and Fast Data, Java, SQL, , , , ,

Reading Time: 3 minutes Nowadays Delta lake is a buzz word in the Big Data world, especially among the spark developers because it relegates lots of issues found in the Big Data domain. Delta Lake is an open-source storage layer that brings reliability to data lakes. Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing. It is evolving day by day and adds cool features in its every release. Continue Reading

Basic Anatomy of a Flink Program

Apache Flink, Big Data and Fast Data, Flink, Java, , , , , , ,

Reading Time: 3 minutes Hi Folks! Hope you all are safe in the COVID-19 pandemic and learning new tools and tech while staying at home. I also have just started learning a very prominent Big Data framework for stream processing which is  Flink. Flink is a distributed framework and based on the streaming first principle, means it is a real streaming processing engine and implements batch processing as a special case. In Continue Reading

Bulkhead with Resilience4j

Functional Programming, Java, Microservices, Scala, Tech Blogs, ,

Reading Time: 3 minutes Resilience4j is a lightweight fault tolerance library, inspired by netflix Hystrix. It is kind of replacement of Hystrix because Hystrix is not in active development, instead in maintenance mode. It means they won’t review issue, merge pull requests and release new versions.

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