Apache NiFi processors are the basic blocks of creating a data flow. Every processor has different functionality, which contributes to the creation of output flowfile. Dataflow shown in the image below is fetching file from one directory using GetFile processor and storing it in another directory using PutFile processor.

GetFile

GetFile process is employed to fetch files of a specific format from a specific directory. It also provides other options to user for more control on fetching. We will discuss it in properties section below.

GetFile Settings

Following are the different settings of GetFile processor −

Name

In the Name setting, a user can define any name for the processors either according to the project or by that, which makes the name more meaningful.

Enable

A user can enable or disable the processor using this setting.

Penalty Duration

This setting lets a user to add the penalty time duration, in the event of flowfile failure.

Yield Duration

This setting is employed to specify the yield time for processor. In this duration, the process is not scheduled again.

Bulletin Level

This setting is employed to specify the log level of that processor.

Automatically Terminate Relationships

This has a list of check of all the available relationship of that particular process. By checking the boxes, a user can program processor to terminate the flowfile on that event and do not send it further in the flow.

GetFile Scheduling

These are the following scheduling options offered by the GetFile processor −

Schedule Strategy

You can either schedule the process on time basis by selecting time driven or a specified CRON string by selecting a CRON driver option.

Concurrent Tasks

This option is employed to define the concurrent task schedule for this processor.

Execution

A user can define whether to run the processor in all nodes or only in Primary node by using this option.

Run Schedule

It’s employed to define the time for time driven strategy or CRON expression for CRON driven strategy.

GetFile Properties

GetFile offers multiple properties as shown in the image below raging compulsory properties like Input directory and file filter to optional properties like Path Filter and Maximum file Size. A user can manage file fetching process using these properties.

GetFile Comments

This Section is employed to specify any information about processor.

PutFile

The PutFile processor is employed to store the file from the data flow to a specific location.

PutFile Settings

The PutFile processor has the following settings −

Name

In the Name setting, a user can define any name for the processors either according to the project or by that which makes the name more meaningful.

Enable

A user can enable or disable the processor using this setting.

Penalty Duration

This setting lets a user add the penalty time duration, in the event of flowfile failure.

Yield Duration

This setting is employed to specify the yield time for processor. In this duration, the process does not get scheduled again.

Bulletin Level

This setting is employed to specify the log level of that processor.

Automatically Terminate Relationships

This settings has a list of check of all the available relationship of that particular process. By checking the boxes, user can program processor to terminate the flowfile on that event and do not send it further in the flow.

PutFile Scheduling

These are the following scheduling options offered by the PutFile processor −

Schedule Strategy

You can schedule the process on time basis either by selecting timer driven or a specified CRON string by selecting CRON driver option. There is also an Experimental strategy Event Driven, which will trigger the processor on a specific event.

Concurrent Tasks

This option is employed to define the concurrent task schedule for this processor.

Execution

A user can define whether to run the processor in all nodes or only in primary node by using this option.

Run Schedule

It’s employed to define the time for timer driven strategy or CRON expression for CRON driven strategy.

PutFile Properties

The PutFile processor provides properties like Directory to specify the output directory for the purpose of file transfer and others to manage the transfer as shown in the image below.

PutFile Comments

This Section is employed to specify any information about processor.

So, this brings us to the end of Deep Dive into Apache NiFi User Interface blog. This Tecklearn ‘Deep Dive into Apache NiFi Processors’ 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.

572