Beyond Messaging Enterprise Dataflow powered by Apache NiFi

Beyond Messaging
Enterprise Dataflow powered by Apache NiFi
© Hortonworks Inc. 2011 – 2015. All Rights Reserved
Aldrin Piri
19 January 2016

About me
Senior Member of Technical Staff
Project Management Committee and Committer
@aldrinpiri

Simplistic View of Enterprise Data Flow
The Data Flow Thing
Process and
Analyze Data
Acquire Data
Store Data

Global interactions with customers, business partners, and things
spanning different volume, velocity, bandwidth, and latency needs
Realistic View of Data Flow

Meeting Edge Requirements
GATHER
DELIVER
PRIORITIZE
Track from the edge Through to the datacenter
Small Footprints
operate with very little power
Limited Bandwidth
can create high latency
Data Availability
exceeds transmission bandwidth
Data Must Be Secured
throughout its journey

• Remote sensor delivery (Internet of Things - IoT)
• Intra-site / Inter-site / global distribution (Enterprise)
• Ingest for driving analytics (Big Data)
• Data Processing (Simple Event Processing)
Where do we find data flow?

Basics of Connecting Systems
For every connection,
these must agree:
1. Protocol
2. Format
3. Schema
4. Priority
5. Size of event
6. Frequency of event
7. Authorization access
8. Relevance
P1
Producer
C1
Consumer

• Messaging addresses only a small subset of the problem space
• Needed to understand the big picture
• Needed the ability to make immediate changes
• Must maintain chain of custody for data
• Rigorous security and compliance requirements
Challenges of dataflow in the enterprise

Great options including:
• Kafka
• ActiveMQ
• Tibco
Let us consider the perfect messaging system for this talk:
• It has zero latency
• It has perfect data durability
• It supports unlimited consumers and producers
Messaging Systems as Dataflow

“But my system needs…”
• A different format and/or schema
• To use a different protocol
• The highest priority information first
• Large objects (event batches) / Small Objects (streams)
• Authorization to the data level
• Only interested in a subset of data on a topic
• Data needs to be enriched/sanitized before it arrives
Dataflow as a messaging problem

Using Messaging
Only a subset agree
using messaging
1. Protocol
2. Format
3. Schema
4. Priority
5. Size of event
6. Frequency of event
7. Authorization access
8. Relevance
P1
CN
C1
Messaging
More issues to consider:
• How do you know what the data flow looks like?
• How is it managed?
• How is it working – today, yesterday?

• Add new systems to handle the protocol differences
• Add new systems to convert the data
• Add new systems to reorder the data
• Add new systems to filter the unauthorized data
• Add new topics to represent ‘stages of the flow’
Which leads to latency, complexity, and limited retention
Ultimately, the operations teams who handle data at flow boundaries become
responsible for managing.
How these issues are typically solved

Real-time Data Flow
It’s not just how quickly you
move data – it’s about how
quickly you can change behavior
and seize new opportunities

Introducing Apache NiFi
• Guaranteed delivery
• Data buffering
- Backpressure
- Pressure release
• Prioritized queuing
• Flow specific QoS
- Latency vs. throughput
- Loss tolerance
• Data provenance
• Recovery/recording
a rolling log of fine-
grained history
• Visual command and
control
• Flow templates
• Pluggable/multi-role
security
• Designed for extension
• Clustering

November 2014
NiFi is donated to the Apache Software Foundation
(ASF) through NSA’s Technology Transfer Program
and enters ASF’s incubator.
2006
NiagaraFiles (NiFi) was first incepted by Joe Witt at
the National Security Agency (NSA)
A Brief History
July 2015
NiFi reaches ASF top-level project status

Flow Based Programming (FBP)
FBP Term NiFi Term Description
Information
Packet
FlowFile Each object moving through the system.
Black Box FlowFile
Processor
Performs the work, doing some combination of data routing,
transformation, or mediation between systems.
Bounded
Buffer
Connection The linkage between processors, acting as queues and allowing various
processes to interact at differing rates.
Scheduler Flow
Controller
Maintains the knowledge of how processes are connected, and manages
the threads and allocations thereof which all processes use.
Subnet Process
Group
A set of processes and their connections, which can receive and send
data via ports. A process group allows creation of entirely new
component simply by composition of its components.

OS/Host
JVM
Flow Controller
Web Server
Processor 1 Extension N
FlowFile
Repository
Content
Repository
Provenance
Repository
Local Storage
OS/Host
JVM
Flow Controller
Web Server
FlowFile
Repository
Content
Repository
Provenance
Repository
Local Storage
Architecture
OS/Host
JVM
NiFi Cluster Manager – Request Replicator
Web Server
Master
NiFi Cluster
Manager (NCM)
OS/Host
JVM
Flow Controller
Web Server
FlowFile
Repository
Content
Repository
Provenance
Repository
Local Storage
Slaves
NiFi Nodes

Live Demonstration

Learn more and join us!
Apache NiFi site
http://nifi.apache.org
Subscribe to and collaborate at
dev@nifi.apache.org
users@nifi.apache.org
Submit Ideas or Issues
https://issues.apache.org/jira/browse/NIFI
Follow us on Twitter
@apachenifi

Thank you!

Beyond Messaging Enterprise Dataflow powered by Apache NiFi

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