A flowfile is a basic processing entity in Apache NiFi. It contains data contents and attributes, which are employed by NiFi processors to process data. The file content normally contains the data fetched from source systems. The most common attributes of an Apache NiFi FlowFile are −

2.1 2

UUID

This stands for Universally Unique Identifier, which is a unique identity of a flowfile generated by NiFi.

Filename

This attribute contains the filename of that flowfile and it should not contain any directory structure.

File Size

It contains the size of an Apache NiFi FlowFile.

mime.type

It specifies the MIME Type of this FlowFile.

path

This attribute contains the relative path of a file to which a flowfile belongs and does not contain the file name.

Apache NiFi – Queues

The Apache NiFi data flow connection has a queuing system to handle the large amount of data inflow. These queues can handle very large amount of FlowFiles to let the processor process them serially.

2.2 1

The queue in the above image has 1 flowfile transferred through success relationship. A user can check the flowfile by selecting the List queue option in the drop down list. In case of any overload or error, a user can also clear the queue by selecting the empty queue option and then the user can restart the flow to get those files again in the data flow.

2.3 1

The list of flowfiles in a queue, consist of position, UUID, Filename, File size, Queue Duration, and Lineage Duration. A user can see all the attributes and content of a flowfile by clicking the info icon present at the first column of the flowfile list.

Apache NiFi – Process Groups

In Apache NiFi, a user can maintain different data flows in different process groups. These groups can be based on different projects or the organizations, which Apache NiFi instance supports.

2.5

The fourth symbol in the menu at the top of the NiFi UI as shown in the above picture is employed to add a process group in the NiFi canvas. The process group named “Tutorialspoint.com_ProcessGroup” contains a data flow with four processors currently in stop stage as you can see in the above picture. Process groups can be created in hierarchical manner to manage the data flows in better structure, which is easy to understand.

In the footer of NiFi UI, you can see the process groups and can go back to the top of the process group a user is currently present in.

To see the full list of process groups present in NiFi, a user can go to the summary by using the menu present in the left top side of the NiFi UI. In summary, there is process groups tab where all the process groups are listed with parameters like Version State, Transferred/Size, In/Size, Read/Write, Out/Size, etc. as shown in the below picture.

Apache NiFi – Labels

Apache NiFi offers labels to enable a developer to write information about the components present in the NiFI canvas. The leftmost icon in the top menu of NiFi UI is employed to add the label in NiFi canvas.

A developer can change the color of the label and the size of the text with a right-click on the label and choose the appropriate option from the menu.

2.8

So, this brings us to the end of Deep Dive into Apache NiFi User Interface blog. This Tecklearn ‘Deep Dive into Apache NiFi Flow Files , Queues , Process Groups and Labels’ 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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