Apache is a web-based platform that can be accessed by a user using web UI. The NiFi UI is very interactive and gives a wide variety of information about NiFi. As shown within the image below, a user can access information about the subsequent 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

Components of Apache NiFi

Apache NiFi UI has the subsequent components −

Processors

User can drag the process icon on the canvas and select the desired processor for the data flow in NiFi.

Input port

Below icon is dragged to canvas to add the input port into any data flow.

Input port is employed to get data from the processor, which is not present in that process group.

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After dragging this icon, NiFi asks to enter the name of the Input port and then it is added to the NiFi canvas.

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Output port

The below icon is dragged to canvas to add the output port into any data flow.

The output port is employed to transfer data to the processor, which is not present in that process group.

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After dragging this icon, NiFi asks to enter the name of the Output port and then it is added to the NiFi canvas.

Process Group

A user uses below icon to add process group within the NiFi canvas.

After dragging this icon, NiFi asks to enter the name of the Process Group and then it is added to the NiFi canvas.

Remote Process Group

This is employed to add Remote process group in NiFi canvas.

Funnel

Funnel is employed to transfer the output of a processor to multiple processors. User can use the below icon to add the funnel in a NiFi data flow.

Template

This icon is employed to add a data flow template to NiFi canvas. This helps to reuse the data flow within the same or different NiFi instances.

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After dragging, a user can select the templates already added within the NiFi.

Label

These are employed to add text on NiFi canvas about any component present in NiFi. It offers a range of colors employed by a user to add aesthetic sense.

So, this brings us to the end of Deep Dive into Apache NiFi User Interface blog. This Tecklearn ‘Deep Dive into Apache NiFi User Interface’ helps you with commonly asked questions if you are looking out for a job in Apache NiFi and Big Data Domain.

If you wish to learn Apache NiFi and build a career in Apache NiFi or Big Data domain, then check out our interactive, Apace NiFi Training, that comes with 24*7 support to guide you throughout your learning period. Please find the link for course details:

https://www.tecklearn.com/course/apache-nifi-training/

Apache NiFi Training

About the Course

Tecklearn Apache NiFi Training makes you an expert in Cluster integration and the challenges associated, Usefulness of Automation, Apache NiFi configuration challenges and etc. Apache NiFi that helps you master various aspects of automating dataflow, managing flow of information between systems, streaming analytics, the concepts of data lake and constructs, various methods of data ingestion and real-world Apache NiFi projects .Transforming the databases is becoming a challenge for many organizations and thus they often look for those who have certification in Apache NiFi to help them in automating the flow of data between the systems.

Why Should you take Apache NiFi Training?

The Average Salary for Apache NiFi Developers is $96,578 per year. – paysa.com
Micron, Macquarie Telecom Group , Dovestech, Payoff, Flexilogix , Hashmap Inc. & many other MNC’s worldwide use Ansible across industries.
Apache NiFi is an open source software for automating and managing the flow of data between systems. It is a powerful and reliable system to process and distribute data. It provides a web-based User Interface for creating, monitoring, & controlling data flows.

What you will Learn in this Course?

Overview of Apache NiFi and its capabilities

Understanding the Apache NiFi
Apache NiFi most interesting features and capabilities

High Level Overview of Key Apache NiFi Features

Key features categories: Flow management, Ease of use, Security, Extensible architecture and Flexible scaling model

Advantages of Apache NiFi over other traditional ETL tools

Features of NiFi which make it different form traditional ETL tool and gives NiFi an edge over them

Apache NiFi as a Data Ingestion Tool

Introduction to Apache NiFi for data ingestion
Apache NiFi Processor : Data ingestion tools available for transferring , importing , loading and processing of data

Data Lake Concepts and Constructs (Big Data & Hadoop Environment)

Concept of data lake and its attributes
Support for colocation of data in various formats and overcoming the problem of data silos

Apache NiFi capabilities in Big Data and Hadoop Environment

Introduction to NiFi processors which sync with data lake and Hadoop ecosystem
An overview of the various components of the Hadoop ecosystem and data lake

Installation Requirements and Cluster Integration

Apache NiFi installation requirements and cluster integration
Successfully running Apache NiFi and addition of processor to NiFi
Working with attributes and Process of scaling up and down
Hands On

Apache NiFi Core Concepts

Apache NiFi fundamental concepts
Overview of FlowFile, Flow Controller ,FlowFile Processor, and their attributes
Functions in dataflow

Architecture of Apache NiFi

Architecture of Apache NiFi
Various components including FlowFile Repository, Content Repository, Provenance Repository and web-based user interface
Hands On

Performance Expectation and Characteristics of NiFi

How to utilize maximization of resources is particularly strong with respect to CPU and disk
Understand the best practices and configuration tips

Queuing and Buffering Data

Buffering of Data in Apache NiFi
Concept of queuing, recovery and latency
Working with controller services and directed graphs
Data transformation and routing
Processor connection, addition and configuration
Hands On

Database Connection with Apache NiFi

Apache NiFi Connection with database
Data Splitting, Transforming and Aggregation
Monitoring of NiFi and process of data egress
Reporting and Data lineage
Expression language and Administration of Apache NiFi
Hands On

Apache NiFi Configuration Best Practices

Apache NiFi configuration Best Practices
ZooKeeper access, properties, custom properties and encryption
Guidelines for developers
Security of Data in Hadoop and NiFi Kerberos interface
Hands On

Apache NiFi Project

Apache NiFi Installation
Configuration and Deployment of toolbar
Building a dataflow using NiFi
Creating, importing and exporting various templates to construct a dataflow
Deploying Real-time ingestion and Batch ingestion in NiFi
Hands On

Got a question for us? Please mention it in the comments section and we will get back to you.

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