Real Time Spark Project for Beginners: Hadoop, Spark, Docker

Building Real Time Data Pipeline Using Apache Kafka, Apache Spark, Hadoop, PostgreSQL, Django and Flexmonster on Docker

Real Time Spark Project for Beginners: Hadoop, Spark, Docker
Real Time Spark Project for Beginners: Hadoop, Spark, Docker

Real Time Spark Project for Beginners: Hadoop, Spark, Docker free download

Building Real Time Data Pipeline Using Apache Kafka, Apache Spark, Hadoop, PostgreSQL, Django and Flexmonster on Docker

  • In many data centers, different type of servers generate large amount of data(events, Event in this case is status of the server in the data center) in real-time.

  • There is always a need to process these data in real-time and generate insights which will be used by the server/data center monitoring people and they have to track these server's status regularly and find the resolution in case of issues occurring, for better server stability.

  • Since the data is huge and coming in real-time, we need to choose the right architecture with scalable storage and computation frameworks/technologies.

  • Hence we want to build the Real Time Data Pipeline Using Apache Kafka, Apache Spark, Hadoop, PostgreSQL, Django and Flexmonster on Docker to generate insights out of this data.

  • The Spark Project/Data Pipeline is built using Apache Spark with Scala and PySpark on Apache Hadoop Cluster which is on top of Docker.

  • Data Visualization is built using Django Web Framework and Flexmonster.

  • Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance.

    Apache Kafka is a distributed event store and stream-processing platform. It is an open-source system developed by the Apache Software Foundation written in Java and Scala. The project aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds.

    Apache Hadoop is a collection of open-source software utilities that facilitates using a network of many computers to solve problems involving massive amounts of data and computation. It provides a software framework for distributed storage and processing of big data using the MapReduce programming model.

    A NoSQL (originally referring to "non-SQL" or "non-relational") database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases.