Apache is a web-based platform that can be accessed by a user using a web interface. The NiFi UI is very interactive and provides a wide variety of information about NiFi. Once the NiFi has been started successfully, UI will bring you up to speed on how to create and monitor the dataflows. Users can drag and drop components in NiFi.

As shown in the image below, a user can access information about the following attributes −

  • Active Threads
  • Total queued data
  • Transmitting Remote Process Groups
  • Not Transmitting Remote Process Groups
  • Running Components
  • Stopped Components
  • Invalid Components
  • Disabled Components
  • Up to date Versioned Process Groups
  • Locally modified Versioned Process Groups
  • Stale Versioned Process Groups
  • Locally modified and Stale Versioned Process Groups
  • Sync failure Versioned Process Groups

    As shown in the image below, the user interface of Apache NiFi is as follows:

    Apache NiFi UI Components

    There are following components of Apache NiFi, which are listed under the component section of the toolbar -

    Processors

    Processors are basic blocks that are used for creating a data flow. Apache NiFi has several processors, where each processor has different functionality. Users can drag and drop the processor icon on the canvas to add the processor and then select the desired processor to create the dataflow.

    Drag the process icon on the canvas that will open an Add Processor window. Choose the desired processor you needed for the data flow in Apache NiFi.

    To know more about the processor, right-click on it and go to Usage. This will bring up the documentation for the processor. It provides information like what a processor does, properties that need to be configured, and the relationship with the processor.

    Input Port

    An input port is used for getting data from the processor, which is not present in that process group. The input port can be dragged on the canvas by clicking on the icon given below.

    To add an input port to any data flow, drag the icon onto the canvas.

    After dragging the icon onto the canvas, NiFi asks you to enter the name for the input port. Provide the name of the input port and click on the Add button.

    Related Articles and Resources

    Apache Spark Tutorial

    This Apache Spark tutorial explains what Apache Spark is, including the installation process and writing Spark applications with examples:We believe that learning the basics and …

    Apache Spark Features

    Developed in the AMPLab of the University of California, Berkeley, Apache Spark was developed for high speed, ease of use, and more in-depth analysis. Though …

    Apache Nifi Introduction

    Apache NiFi is a free and open-source data integration tool that enables users to automate the flow of data between disparate systems. It was created …

    Apache Nifi Architecture

    Apache NiFi has a processor, flow controller, and web server that execute on the JVM machine. Additionally, it also includes three repositories, as shown in …

    Apache Nifi Installation

    Prerequisites:Make sure your computer has the following components installed before installing Apache Nifi:Java 8 or later must be installed and added to the PATH environment …

    Apache Nifi Getting Started

    Go to the "bin" folder inside the extracted folder, i.e., apache-nifi/bin. Click on the "run-nifi" batch file and run it to start NiFi.The run-nifi.bat file …

    Machine Learning Tutorial

    What is Machine LearningMachine learning is a subset of artificial intelligence (AI) that entails developing algorithms that allow computers to learn from and improve on …

    Machine Learning Steps

    Machine learning's ultimate goal is to create algorithms that automatically assist a system in gathering data and using that data to learn more. Systems are …

    Applications Of Machine Learning

    Machine learning has a wide range of applications across various industries. Some of the popular applications of machine learning include:Image and speech recognition: Machine learning …

    Data Analytics And Machine Learning: Key Differences

    Data Analytics and Machine Learning are two mighty forces that rule supreme in the quick-moving world of data science. Like enigmatic twins, they have similarities …

    Trusted by digital leaders and practitioners from 100+ International Organizations