1. What is Apache NiFi?
Apache NiFi is a free and open-source
application that automates and manages data flow across systems. It is a secure
and dependable data processing and distribution system that incorporates a
web-based user interface for the purpose of creating, monitoring, and
controlling data flows. It features a highly customizable and changeable data
flow method that allows for real-time data modification.
2. What is the purpose of a NiFi Processor?
The Processor is a critical
component of the NiFi since it is responsible for actually executing the
FlowFile data and assists in producing, transmitting, receiving, converting,
routing, dividing, integrating, and analyzing FlowFile.
3. What actually is a NiFi FlowFile?
A FlowFile is a file that
contains signal, event, or user data that is pushed or generated in the NiFi. A
FlowFile is mostly composed of two components. Its data and attributes.
Attributes are key-value pairs that are associated with a piece of content or
data.
4. Describe MiNiFi
MiNiFi is a project of NiFi
that is intended to enhance the fundamental concepts of NiFi by emphasizing the
gathering of data at its generation source. MiNiFi is meant to operate at the
source, which is why it places a premium on minimal area and resource
utilization.
5. Is it possible for a NiFi Flow file to
contain complex data as well?
Yes, with NiFi, a FlowFile
may include both organized (XML, JSON files) and complex
(graphics) data.
6. What specifically is a Processor Node?
A Processor Node is a shell
all around the Processor that manages the processor's state. The Processor Node
is responsible for maintaining the
Positioning of processors in
the graph.
Processor configuration characteristics.
Scheduling the processor's states.
7. What does the Reporting Task involve?
A Reporting Task is a NiFi
expansion endpoint that is responsible for reporting and analyzing NiFi's inner
statistics in order to transmit the data to other sources or to display status
data straight in the NiFi UI.
8. Is the processor capable of committing or
rolling back the session?
Yes, the processor is the
module that may submit and reverse data via the session. When a Processor
starts rolling back a session, all FlowFiles retrieved during the session are
restored to their prior states. If, on the other hand, the Processor decides to
submit the session, it will update the FlowFile repositories with the necessary
information.
9. What does "Write-Ahead-Log" mean
in the context of FlowFileRepository?
This implies that any changes
made to the FlowFileRepository will
be first logged and checked for consistency. Remain in the logs to avoid data
loss, both before and during data processing, as well as checkpoints on a
frequent basis to facilitate reversal.
10. Does the Reporting Task get access to the
entire contents of the FlowFile?
No, a Reporting Task has no
access to the contents of any specific FlowFile. Rather than that, a Reporting
Task gets accessibility to all Provenance Events, alerts, and metrics
associated with graph components, like Bits of data, read or written.
Apache NiFi Interview Questions For Experienced
11. What use does FlowFileExpiration serve?
It assists in determining
when this FlowFile must be terminated and destroyed after a certain period of
time. Assume you've set FlowFileExpiration to 1 hour. As soon as the FlowFile
is detected in the NiFi platform, the countdown begins. Furthermore, once
FlowFile reaches the connection, it will verify the age of the FlowFile; if it
is older than 1 hour, the FlowFile will be ignored and destroyed.
12. What is the NiFi system's backpressure?
Occasionally, the producer
system outperforms the consumer system. As a result, communications are slower.
Hence, all unprocessed messages (FlowFiles) will stay in the network buffer.
However, you may restrict the magnitude of the network backpressure depending
on the number of FlowFiles or the quantity of the data. If it exceeds the set
limit, the link will return pressure to the producing processor, causing it to
stop running. As a result, no more FlowFiles are created until the backpressure
is removed.
13. Is it possible to alter the settings of a
processor while it is running?
No, the settings of the
processor cannot be altered or modified while it is operating. You must first
halt it and then allow for all FlowFile processing to complete. Then and only
then may you modify the processor's settings.
14. What use does RouteOnAttribute serve?
RouteOnAttribute permits the
system to make congestion control within the flow, allowing certain FlowFiles
to be treated differently than others.
15. What Is The NiFi Template?
A template is a workflow that
may be reused, which you may import and export across many NiFi instances. It
can save a lot of time compared to generating Flow repeatedly. The template is
produced in the form of an XML file.
16. What does the term "Provenance
Data" signify in NiFi?
NiFi maintains a Data
provenance library that contains all information about the FlowFile. As data
continues to flow and is converted, redirected, divided, consolidated, and sent
to various endpoints, all of this metadata is recorded in NiFi's Provenance
Repository. Users can conduct a search for the processing of every single
FlowFile.
17. What is a FlowFile's
"lineageStartDate"?
This FlowFile property
indicates the date and time the FlowFile was added or generated in the NiFi
system. Even if a FlowFile is copied, combined, or divided, a child FlowFile
may be generated. However, the lineageStartDate property will provide the timestamp
for the ancestor FlowFile.
18. How to get data from a FlowFile's
attributes?
Numerous algorithms are
available, including ExtractText, and EvaluateXQuery which can help you get
data from the FlowFile attribute. Furthermore, you may design your own
customized microprocessor to meet the same criteria if no off-the-shelf
processor is provided.
19. What occurs to the ControllerService when
a DataFlow is used to generate a template?
When a template is produced
via DataFlow and if it has an associated ControllerService, a new instance of
the control system service will be generated throughout the import process.
20. What occurs if you save a passcode in a
DataFlow and use it to generate a template?
A password is a very
sensitive piece of information. As a result, when publishing the DataFlow as
templates, the password is removed. Once you export the template into another
NiFi system, whether the same or a different one, you must enter the password once
more.
Apache NiFi FAQs
21. What is bulleting and how does it benefit
NiFi?
While you can review the
archives for anything noteworthy, having notifications come up on the board is
far handier. If a Process records something as a WARNING, a "Bulletin
Indicator" will appear in the Processor. This indication, which resembles
a sticky note, will be displayed for five minutes following the occurrence of
the event. If the bulletin is part of a cluster, it will additionally specify
which network device released it. Furthermore, we may alter the log frequency
at which bulletins are generated
22. What is a NiFi process group?
A process group can assist
you in developing a sub-data stream that users can include in your primary data
flow. The destination address and the input port are used to transmit and
receive information from the process group, respectively.
23. What use does a flow controller serve?
The flow controller is the
project's brain that allocates threads to run modifications and maintains the
scheduling for when modules obtain resources to execute. The Flow Controller
functions as the engine, determining when a thread is assigned to a specific
processor.
24. How Does Nifi Handle Massive Payload
Volumes in a Dataflow?
DataFlow can handle massive
amounts of data. As data flows via NiFi, referred to as a FlowFile, is handed
around, the FlowFile's information is only accessible when necessary.
25. What is the distinction between NiFi's
FlowFile and Content repositories?
The FlowFile Library is where
NiFi stores information about a particular FlowFile that is currently online in
the stream.
The Content Repository stores
the exact bytes of a FlowFile's information.
26. What does "deadlock in
backpressure" imply?
Assume you're using a
processor, such as PublishJMS, to release the information to the target list.
The destination queue, on the other hand, is full, and your FlowFile will be
sent to the failed relationship. And when you retry the unsuccessful FlowFile,
the incoming backpressure linkage becomes full, which might result in a
backpressure stalemate.
27. What is the remedy for the "back
pressure deadlock"?
There are several
alternatives, including
The administrator can
temporarily boost the failed connection's backpressure level.
Another option to explore in this scenario is to have Reporting Tasks monitor
the flow for big queues.
28. How does NiFi ensure the delivery of
messages?
This is accomplished by
implementing an effective permanent write-ahead logging and information
repository.
29. Can you utilize the fixed Ranger setup on
the HDP to work with HDF?
Yes, you may handle HDF with
a single Ranger deployed on the HDP. Nevertheless, the Ranger that comes with
HDP doesn't include NiFi service definition and must be installed manually.
30. Is NiFi capable of functioning as a
master-slave design?
No, starting with NiFi 1.0,
the 0-master principle is taken into account. Furthermore, each unit in the
NiFi network is identical. The Zookeeper service manages the NiFi cluster.
Apache ZooKeeper appoints a single point as the Cluster Administrator, and ZooKeeper
handles redundancy seamlessly.
The Advantages of Apache NiFi are as follows:
- Apache
NiFi offers a web-based User Interface (UI). So that it can run on a web
browser using port and localhost.
- On a
web browser, Apache NiFi uses the HTTPS protocol to ensure secure user
interaction.
- It
supports the SFTP protocol that enables data fetching from remote
machines.
- It
also provides security policies at the process group level, user level,
and other modules.
- NiFi
supports all the devices that run Java.
- It
provides real-time control that eases the movement of data between source
and destination.
- Apache
NiFi supports clustering so that it can work on multiple nodes with the
same flow processing different data, which increases the performance of
data processing.
- NiFi
supports over 188 processors, and a user can create custom plugins to
support various types of data systems.
Disadvantages
of Apache NiFi
The following are the disadvantages of Apache NiFi.
- Apache
NiFi has a state persistence issue in the case of a primary node switch
that makes processors unable to fetch data from source systems.
- While
making any change by the user, the node gets disconnected from the
cluster, and then flow.xml gets invalid. The node cannot connect to the
cluster till the admin copies the .xml file manually from the node.
- To
work with Apache NiFi, you must have good underlying system knowledge.
- It
offers a topic level, and SSL authorization might not be sufficient.
- It is
required to maintain a chain of custody for data.
Apache NiFi is a data flow system based on the concepts of
Flow-based programming. It is developed by the National Security Agency (NSA),
and then in 2015, it became an official part of the Apache Project Suite.
Every 6-8 weeks, Apache NiFi
releases a new update to meet the requirements of the users.
This Apache NiFi tutorial is
designed for beginners and professionals who are willing to learn the basics of
Apache NiFi. It includes several sections that provide core knowledge of how to
work with NiFi.
What is Apache NiFi?
Apache NiFi is a robust,
scalable, and reliable system that is used to process and distribute data. It
is built to automate the transfer of data between systems.
- NiFi offers a
web-based User Interface for creating, monitoring, and controlling data
flows. NiFi stands for Niagara Files which was developed by National
Security Agency (NSA) but now it is maintained by the Apache
foundation.
- Apache NiFi is a
web-based UI platform where we need to define the source, destination, and
processor for data collection, data storage, and data transmission,
respectively.
- Each processor in the
NiFi has relations that are used while connecting one processor to
another.
Why do we use Apache NiFi?
Apache NiFi is open-source;
therefore, it is freely available in the market. It supports several data
formats, such as social feeds, geographical locations, logs, etc.
Apache NiFi supports a wide
variety of protocols such as SFTP, KAFKA, HDFS, etc. which makes this platform
more popular in the IT industry. There are so many reasons to choose Apache
NiFi. They are as follows.
·
Apache NiFi helps
organizations to integrate NiFi with their existing infrastructure.
·
It allows users to make use of Java ecosystem functions and
existing libraries.
·
It provides real-time control that enables the user to manage
the flow of data between any source, processor, and destination.
·
It helps to visualize DataFlow at the enterprise level.
·
It helps to aggregate, transform, route, fetch, listen, split,
and drag-and-drop the data flow.
·
It allows users to start and stop components at individual and
group levels.
·
NiFi enables users to pull the data from various sources to NiFi
and allows them to create flow files.
·
It is designed to scale out in clusters that provide guaranteed
delivery of data.
·
Visualize and monitor
performance, and behavior in the flow bulletin that offers inline and insight
documentation.
Features
of Apache NiFi
The features of Apache NiFi
are as follows:
·
Apache NiFi is a web-based
User Interface that offers a seamless experience of design, monitoring,
control, and feedback.
·
It even provides a data provenance module that helps to track
and monitor data from the source to the destination of the data flow.
·
Developers can create their customized processors and reporting
tasks as per the requirements.
·
It supports troubleshooting and flow optimization.
·
It enables rapid development and testing effectively.
·
It provides content encryption and communication over a secure
protocol.
·
It supports buffering of all queued data and provides an ability
of backpressure as the queues can reach specified limits.
·
Apache NiFi delivers a system
to the user, the user to the system, and multi-tenant authentication security
features.
Apache NiFi Architecture
Apache NiFi Architecture includes a web server,
flow controller, and processor that runs on a Java Virtual Machine (JVM).
It has three repositories such as FlowFile
Repository, Content Repository, and Provenance Repository.
- Web Server
Web Server is used to host the HTTP-based command
and control API.
- Flow Controller
The flow controller is the brain of the operation.
It offers threads for extensions to run and manage the schedule of when the
extensions receive resources to run.
- Extensions
Several types of NiFi extensions are defined in
other documents. Extensions are used to operate and execute within the JVM.
- FlowFile Repository
The FlowFile Repository includes the current state
and attribute of each FlowFile that passes through the data flow of NiFi.
It keeps track of the state that is active in the
flow currently. The standard approach is the continuous Write-Ahead Log which
is located in a described disk partition.
- Content Repository
The Content Repository is used to store all the
data present in the flow files. The default approach is a fairly simple
mechanism that stores blocks of data in the file system.
To reduce the contention on any single volume,
specify more than one file system storage location to get different partitions.
- Provenance Repository
The Provenance Repository is where all the
provenance event data is stored. The repository construct is pluggable to the
default implementation that makes use of one or more physical disk volumes.
Event data is indexed and searchable in each
location.
From the NiFi 1.0 version, a Zero-Leader Clustering pattern is incorporated. Every node in the cluster executes similar tasks on the data but operates on a different set of data.
Apache Zookeeper picks a single node as a Cluster
Coordinator. The Cluster Coordinator is used for connecting and disconnecting
nodes. Also, every cluster has one Primary Node.
Key
concepts of Apache NiFi
The key concepts of Apache NiFi are as follows:
- Flow: Flow is created to connect different
processors to share and modify data that is required from one data source
to another destination.
- Connection: Connection is used to connect the processors that act as a queue
to hold the data in a queue when required. It is also known as a bounded
buffer in Flow-based programming (FBP) terms. It allows several processes
to interact at different rates.
- Processors: The processor is a Java module that is used to either fetch data
from the source system or to be stored in the destination system. Several
processors can be used to add an attribute or modify the content in the
FlowFile. It is responsible for sending, merging, routing, transforming,
processing, creating, splitting, and receiving flow files.
- FlowFile: FlowFile is the basic concept of NiFi that represents a single
object of the data selected from the source system in NiFi. It allows
users to make changes to Flowfile when it moves from the source processor
to the destination. Various events such as Create, Receive, Clone, etc.
that are performed on Flowfile using different processors in a flow.
- Event: An
event represents the modification in Flowfile when traversing by the NiFi
Flow. Such events are monitored in the data provenance.
- Data provenance: Data provenance is a repository that allows users to verify the
data regarding the Flowfile and helps in troubleshooting if any issues
arise while processing the Flow file.
- Process
group: The
process group is a set of processes and their respective connections that
can receive data from the input port and send it through output ports.
The input port is used to get data from the processor, which is not available in the process group. When the Input icon is dragged to the canvas, then it allows adding an Input port to the dataflow.
The output port is used to transfer data to the processor, which is not available in the process group. When the output port icon is dragged into the canvas, then it allows adding an output port.
Process group helps to add process groups in NiFi canvas. When the Process Group icon is dragged into the canvas, it enables to enter the Process Group name, and then it is added to the canvas.
The Funnel is used to send the output of the processor to various processors. Users can drag the Funnel icon into the canvas to add Funnel to the dataflow.
It allows adding a Remote Process Group in the NiFi
canvas.
Template
The template icon is used to add the dataflow template to the NiFi canvas. It helps to reuse the data flow in the same or different instances.
After dragging, it allows users to select the
existing template for the data flow.
Label
These are used to add text on NiFi canvas regarding any component available in the NiFi. It provides colors used by the user to add an aesthetic sense.
Processors
Categorization in Apache NiFi
The following are the process categorization of
Apache NiFi.
- AWS Processors
AWS processors are responsible for communicating
with the Amazon web services system. Such category processors are PutSNS,
FetchS3Object, GetSQS,PutS3Object, etc.
- Attribute Extraction Processors
Attribute Extraction processors are responsible for
extracting, changing, and analyzing FlowFile attributes processing in the NiFi
data flow.
Examples are ExtractText, EvaluateJSONPath,
AttributeToJSON, UpdateAttribute, etc.
- Database Access Processors
The Database Access processors are used to select
or insert data or execute and prepare other SQL statements from the database.
Such processors use the data connection controller
settings of Apache NiFi. Examples are PutSQL, ListDatabaseTables, ExecuteSQL,
PutDatabaseRecord, etc.
- Data Ingestion Processors
The Data Ingestion processors are used to ingest
data into the data flow, such as a starting point of any data flow in Apache
NiFi. Examples are GetFile, GetFTP, GetKAFKA,GetHTTP, etc.
- Data Transformation Processors
Data Transformation processors are used for
altering the content of the FlowFiles.
These can be used to replace the data of the
FlowFile when the user has to send FlowFile as an HTTP format to invoke an HTTP
processor. Examples are JoltTransformJSON ReplaceText, etc.
- HTTP Processors
The HTTP processors work with the HTTP and HTTPS
calls. Examples are InvokeHTTP, ListenHTTP, PostHTTP, etc.
- Routing and Mediation Processors
Routing and Mediation processors are used to route
the FlowFiles to different processors depending on the information in
attributes of the FlowFiles.
It is responsible for controlling the NiFi data
flows. Examples are RouteOnContent, RouteText, RouteOnAttribute, etc.
- Sending Data Processors
Sending Data Processors are the end processors in
the Data flow. It is responsible for storing or sending data to the
destination.
After sending the data, the processor DROP the
FlowFile with a successful relationship. Examples are PutKAFKA, PutFTP,
PutSFTP, PutEmail, etc.
- Splitting and Aggregation Processors
The Splitting and Aggregation processors are used
to split and merge the content available in the Dataflow. Examples are
SplitXML, SplitJSON, SplitContent, MergeContent, etc.
- System Interaction Processors
The system interaction processors are used to run
the process in any operating system. It also runs scripts in various languages
with different systems.
Examples are ExecuteScript, ExecuteStreamCommand,
ExecuteGroovyScript, ExecuteProcess, etc.
1. What is virtual hosting?
Virtual hosting is crucial for many web administrators,
especially those who work for big companies with many websites. An interviewer
might ask you this question to gauge your knowledge of Apache's functions and
business applications. When answering this question, define the term and give
an example of when to use virtual hosting.
Web administrators use access log analysis to gain insights
into a website's performance that they then share with marketing or sales
teams. An interviewer may ask this question to confirm how familiar you are
with the relationship between web development and other functions of a company.
When answering this question, define the concept and give adequate examples.
It is often the responsibility of IT experts to oversee the
smooth running of an organisation's website and resolve server errors. An
interviewer may ask questions to learn how you solve this type of problem. When
answering, explain what a 503 HTTP error means and highlight the procedure to
resolve it.
Writing custom processors helps you perform different
operations to transform flow file content according to specific needs.
Interviewers ask this question to understand your knowledge of using processors
in NiFi. Mention the steps you use to create a custom processor.
Bulletin is a NiFi UI that provides information about
occurrences, allowing developers to avoid going through log messages to find
errors. Interviewers ask this question to understand the potential benefits of
Bulletin. When answering, explain what it means and its benefits to developers.
|
NiFi Term |
FBP Term |
Description |
|
FlowFile |
Information
Packet |
A
FlowFile represents each object moving through the system and for each one,
NiFi keeps track of a map of key/value pair attribute strings and its
associated content of zero or more bytes. |
|
FlowFile
Processor |
Black Box |
Processors
actually perform the work. In [eip] terms
a processor is doing some combination of data Routing, Transformation, or
Mediation between systems. Processors have access to attributes of a given
FlowFile and its content stream. Processors can operate on zero or more
FlowFiles in a given unit of work and either commit that work or rollback. |
|
Connection |
Bounded
Buffer |
Connections
provide the actual linkage between processors. These act as queues and allow
various processes to interact at differing rates. These queues then can be
prioritized dynamically and can have upper bounds on load, which enable back
pressure. |
|
Flow
Controller |
Scheduler |
The
Flow Controller maintains the knowledge of how processes actually connect and
manages the threads and allocations thereof which all processes use. The Flow
Controller acts as the broker facilitating the exchange of FlowFiles between
processors. |
|
Process
Group |
Subnet |
A
Process Group is a specific set of processes and their connections, which can
receive data via input ports and send data out via output ports. In this
manner process groups allow creation of entirely new components simply by
composition of other components. |
You can create a custom processor in NiFi by extending the
AbstractProcessor class and overriding the onTrigger method. In the onTrigger
method, you will need to implement the logic for your processor. You can access
the NiFi FlowFile object to read and write data, and you can also use the NiFi
ProcessContext object to access properties and variables.
11.
What is provenance in the context of NiFi? Why is it important?
Provenance is the history of a given piece of data, and it is
important in NiFi because it allows you to track where data came from and how
it has been processed. This is useful for debugging purposes, as well as for
understanding the data flow through a NiFi system.
12.
What information is captured by NiFi Provenance Repository?
The NiFi Provenance Repository
captures information about the dataflow through NiFi, including the data that
is processed, the NiFi processors that are used, the NiFi connections that are
used, and the NiFi parameters that are used.
14. What is a Connection Queue in NiFi?
A Connection Queue is a queue of FlowFiles that are waiting to
be processed by a downstream connection.
15.
Can you tell me about the process used by NiFi to handle back pressure?
Back pressure is the name given to the process of slowing down
or stopping the flow of data through a system when that system is becoming
overwhelmed. This is done in order to prevent the system from becoming
overloaded and crashing. NiFi uses a back pressure mechanism to automatically
control the flow of data through the system in order to prevent data loss.
16.
Is it possible to run NiFi as a cluster? If yes, then how?
Yes, it is possible to run NiFi
as a cluster. In order to do so, you will need to start up multiple NiFi
instances and then configure them to work together as a cluster. The specifics
of how to do this will vary depending on your particular environment and setup.
FlowFileAttributes are metadata associated with a FlowFile,
while FlowFileContent is the actual data contained in the FlowFile.
You can create a custom processor in NiFi by extending the
AbstractProcessor class and overriding the onTrigger method. In the onTrigger
method, you will need to implement the logic for your processor. You can access
the NiFi FlowFile object to read and write data, and you can also use the NiFi
ProcessContext object to access properties and variables.
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