Reading Time: 3 minutes From our previous blog on the basics of http4s, we are familiar with http4s library and what all makes it a go-to solution to develop a Scala based Http service. The library provides out-of-box support for creating http routes, servers and clients. Using this, we can easily develop a self-contained http4s dependent app. Demo with http4s In our demo, we will try creating a basic Continue Reading
Reading Time: 3 minutes Our previous blog on http4s gives us an introduction to the library to create HTTP routes, servers and clients. Using the library’s support for various libraries like Ember, Blaze, we can create any type of server and/or client. The library also provides for other libraries for easy encoding/decoding of request and response body using circe, scala-xml, and fs2-data. Ultimately, the heart of the library lies Continue Reading
Reading Time: 3 minutes http4s is Scala’s answer to Java’s servlets. Apart from being a minimal, idiomatic Scala interface for HTTP services, it has a range of impressive features as well: HttpRoutes[F] – Heart of http4s The http4s library is based on the concepts of Request and Response. A request is mapped to a response through a set of function of type Request => Response. These functions are routes, Continue Reading
Reading Time: 5 minutes Apache Cassandra has made its mark in the world of NoSQL Databases. Its features like Partitioning, Clustering, and Ring topology make it unique.
Reading Time: 7 minutes KNIME can be used to develop customised components of Supply Chain Management, from Inventory plan to forecast solutions.
Reading Time: 8 minutes Writing a clean code that nobody mocks is a little difficult, but by cultivating a habit, following best practices, it is not impossible to achieve.
Reading Time: 4 minutes Joins in Apache Spark are fundamental transformations, but if you are not familiar with their internal algorithm, they can become too expensive.
Reading Time: 4 minutes Knime taps into the power of Apache Kafka’s pub-sub mechanism by introducing Kafka extension. It adds nodes to connect, read and publish to Kafka cluster.
Reading Time: 4 minutes Spark provides two shared variables in distributed computing which are accessible to all the nodes in a spark cluster – broadcast variables & Accumulators.
Reading Time: 5 minutes Linear Regression is perhaps one of the most well known and well -understood algorithms in Statistics and Machine Learning. It tries to find a relationship between the independent and dependent continuous variables by determining a linear equation of the form Y = b0 + b1*x1 + b2*x2 + ….. Here, the x values represent the independent variables, b values are the coefficients of the independent Continue Reading
Reading Time: 5 minutes Knime provides access to various file formats without worrying about the coding behind it. The user just needs to drag and drop an appropriate access node.
Reading Time: 4 minutes Morpheus brings the world of Graph Processing to Spark. It’s Property Graph Model and Cypher language allows easy inclusion of Graph into Spark pipelines
Reading Time: 4 minutes NumPy’s built-in methods and concepts like vectorization, broadcasting and indexing allows you to focus on answering questions from your data and not about how to code those solutions. NumPy handles most of that for you.
