April 5, 2018 IoT Fusion 2018 Conference in Philadelphia, PA hosted by Chariot Solutions. This talk is about Apache NiFi, MiniFi, Python, Deep Learning, NVidia Jetson TX1, Raspberry Pi, Apache MXNet, TensorFlow and how to run things at the edge and process in your big data center. http://iotfusion.net/session/ https://github.com/tspannhw/IoTFusion2018Talk

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Enterprise IIoT Edge Processing
#iotfusion

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© Hortonworks, Inc. 2011-2018. All rights reserved. | Hortonworks confidential and proprietary information.
Enterprise IIoT Edge Processing
Timothy Spann, Solutions Engineer
Hortonworks @PaaSDev

3. 3 © Hortonworks Inc. 2011–2018. All rights reserved.
Disclaimer
• This document may contain product features and technology directions that are under
development, may be under development in the future or may ultimately not be
developed.
• Technical feasibility, market demand, user feedback, and the Apache Software
Foundation community development process can all effect timing and final delivery.
• This document’s description of these features and technology directions does not
represent a contractual commitment, promise or obligation from Hortonworks to deliver
these features in any generally available product.
• Product features and technology directions are subject to change, and must not be
included in contracts, purchase orders, or sales agreements of any kind.
• Since this document contains an outline of general product development plans,
customers should not rely upon it when making a purchase decision.

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Agenda
• Overview
• Architecture
• Ingest
• Deep Learning
• Examples
• Questions
https://community.hortonworks.com/articles/183151/enterprise-iiot-edge-processing-with-apache-nifi-m.html

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IIoT
Multiple devices, protocols, frameworks, languages, data types, sensors and networks
Protocols
• MQTT
• HTTPS / SSL (REST/JSON)
• OPC UA
• CoAP
• AMQP
• LoRA
• Cellular
• JSON
• XML
• CSV
• Raw Text
• Images (JPEG, PNG)
• Raw Data Streams
• PDF
Data Types Sensors
• Cameras
• Temperature/Humidity
• IR
• Proximity
• Motion Sensors
• GPS
Protocols
• NVidia Jetson TX1
• Raspberry Pi
• Arduino
• TS-7800 V2
• ESP8266
• DragonBoard 410c
• BeagleBone Black
• NanoPi Duo

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Data Ingestion: Optimize Analytics with Content Based Routing

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Hortonworks DataFlow Manages Data in Motion
Core
InfrastructureSources
à Constrained
à High-latency
à Localized context
à Hybrid – cloud / on-premises
à Low-latency
à Global context
Regional
Infrastructure

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What do we want to do?
q MiniFi ingests camera images and sensor data
q MiniFi executes Apache MXNet and TensorFlow at the edge
q Run Apache MXNet and TensorFlow for Object Detection and Image
Recognition
q Apache NiFi stores images, metadata and enriched data in Hadoop
q Apache OpenNLP and Apache Tika for textual data

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Data in
Motion
Data at
Rest
Deep Historical
Analysis
DATA C E NTE R
Stream Analytics
Edge
Data
Data in
Motion
Deep
Learning
C LO UD Edge
Data
Edge
Analytics
Data at
Rest
Transformational Applications Require Connected Data

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The New Way of Business Is Fueled by Data
• Connected customers,
vehicles, devices
• Socially crowd-sourced
requirements
• Digital design and
analysis
• Digital prototypes and
tests
• Connected factories,
sensors, devices
• Human-robotic
interaction
• 3D-printing on
demand
• Connected trucks,
inventory
• Location, traffic,
weather-aware
distribution
• Real-time inventory
visibility
• Dynamic rerouting
• Connected customers,
devices
• Omni- channel
demand sensing
• Real-time
recommendations
• Connected assets
• Remote service
monitoring & delivery
• Predictive maintenance
• OTA updates
MANUFACTURING DISTRIBUTION MARKETING/SALES SERVICEDEVELOPMENT

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Aggregate all data from sensors, drones, logs, geo-location devices, images,
machines and social feeds.
Collect: Bring Together
Mediate point-to-point and bi-directional data flows, delivering data
reliably to Apache HBase, Apache Hive, HDFS, Slack and Email.
Conduct: Mediate the Data Flow
Parse, filter, join, transform, fork, query, sort, dissect; enrich with weather,
location, Apache OpenNLP, TensorFlow and Apache MXNet.
Curate: Gain Insights

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“Innovation happens best not in
isolation but in collaboration”
T H E
I N N O V A T I O N
A D V A N T A G E
P R O P R I E T A R Y A P P R O A C H
T I M E
INNOVATION
O P E N
C O M M U N I T Y

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IIoT Processing
Data Acquisition
Edge Processing
Real Time Stream Analytics
Rapid Application Development
IoT
ANALYTICS
CLOUD
Acquire Move
Routing
&
Filtering
Deliver Parse Analysis
Aggregation
Modeling

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Streaming Analytics
Manager
Part of MiniFi C++ Agent
Detect metadata and data
Extract metadata and data
Content Analysis
Deep Learning Framework
Complex Event Processing
Joining DataSets for Streaming Analytics
Open Source Components
Enabling Record Processing
Schema Management

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Streaming Analytics
Manager
Run everywhere
Orchestration
Queueing
Simple Event Processing
Deep Learning Framework
Entity Resolution
Natural Language Processing
Open Source Components
Edge Ingest
Data Buffering
Device Integration

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HDF Data-In-Motion Platform – with HDF 3.1 GA Release

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HDF 3.1 for Big Data Engineers
Multiple users, frameworks, languages, data sources & clusters
BIG DATA ENGINEER
• Experience in ETL
• Coding skills in Scala,
Python, Java
• Experience with Apache
Hadoop
• Knowledge of tools such
Hive, Flume or Pig
• Knowledge of SQL
• Expert in ETL (Eating, Ties
and Laziness)
• Social Media Maven
• Deep SME in Buzzwords
• No Coding skills
• Interest in Pig and Falcon
CAT AI
• Will Drive your Car
• Will Fix Your Code
• Will Not Be Discussed
Today
• Will Not Finish This Talk For
Me, This Time

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Edge Intelligence with Apache MiNiFi
à Guaranteed delivery
à Data buffering
‒ Backpressure
‒ Pressure release
à Prioritized queuing
à Flow specific QoS
‒ Latency vs. throughput
‒ Loss tolerance
à Data provenance
à Recovery / recording a rolling log
of fine-grained history
à Designed for extension
Different from Apache NiFi
à Design and Deploy
à Warm re-deploys
Key Features

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NiFi Site-to-Site (S2S)
• Guaranteed delivery
• 2-way SSL Encryption
• Built-in proxy capabilities
NiFi JVM
REST API
NiFi
Framework
Proc CS
Report
TaskS2S
API
Extension API
NiFi/MiNiFi/App JVM
S2S Client Libraries
Proxy
Socket protocol: TCP
HTTP(S) protocol

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Improved Operational Efficiency
MiNiFi C++ Agent
C++ Agent
C++ Agent
C++ Agent
There are many configuration options for MiNiFi
C++, all dependent on the use case, they may
help with:
• Minimizing memory footprint
• Lowering CPU consumption
• Reducing size on disk
• Battery monitoring
• USB Camera, PCAP, Kafka, MQTT, and
TensorFlow processors and extensions
https://community.hortonworks.com/articles/167193/building-and-
running-minifi-cpp-in-orangepi-zero.html
https://www.parisi.io/index.php/2018/01/19/batteries-not-
included/

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Why Apache NiFi?
• Guaranteed delivery
• Data buffering
- Backpressure
- Pressure release
• Prioritized queuing
• Flow specific QoS
- Latency vs. throughput
- Loss tolerance
• Data provenance
• Supports push and pull
models
• Hundreds of processors
• Visual command and
control
• Over a fifty sources
• Flow templates
• Pluggable/multi-role
security
• Designed for extension
• Clustering
• Version Control

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FlowFiles are like HTTP data
HTTP Data FlowFile
HTTP/1.1 200 OK
Date: Sun, 10 Oct 2010 23:26:07 GMT
Server: Apache/2.2.8 (CentOS) OpenSSL/0.9.8g
Last-Modified: Sun, 26 Sep 2010 22:04:35 GMT
ETag: "45b6-834-49130cc1182c0"
Accept-Ranges: bytes
Content-Length: 13
Connection: close
Content-Type: text/html
Hello world!
Standard FlowFile Attributes
Key: 'entryDate’ Value: 'Fri Jun 17 17:15:04 EDT 2016'
Key: 'lineageStartDate’ Value: 'Fri Jun 17 17:15:04 EDT 2016'
Key: 'fileSize’ Value: '23609'
FlowFile Attribute Map Content
Key: 'filename’ Value: '15650246997242'
Key: 'path’ Value: './’
Binary Content *
Header
Content

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Visual Command and Control
• Drag and drop processors to build a flow
• Start, stop, and configure components in real time
• View errors and corresponding error messages
• View statistics and health of data flow
• Create templates of common processor & connections

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Provenance/Lineage

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Increased Developer Productivity
Apache NiFi Registry
NiFi (PROD)
MiNiFi
MiNiFi
MiNiFi
MiNiFi
MiNiFi
MiNiFi
MiNiFi
NiFi Registry API
Persistence Other services Other services
NiFi (QA)
NiFi (Dev)
Register DeployDeploy
à NiFi Registry
• Repository of versioned flows
• Portability
• Support multiple registries and
interactions between them
• Design and deploy mechanism

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http://mxnet.incubator.apache.org/
• Cloud ready
• Experienced team (XGBoost)
• AWS, Microsoft, NVIDIA, Baidu, Intel backing
• Apache Incubator Project
• Run distributed on YARN
• In my early tests, faster than TensorFlow.
• Runs on Raspberry PI, Nvidia Jetson TX1
and other constrained devices
• Great documentation
• Gluon
• Great Python Interaction
• Model Server Available
• ONNX Support
• Now in Version 1.1!
• Great Model Zoo
https://mxnet.incubator.apache.org/how_to/cloud.html
https://github.com/apache/incubator-mxnet/tree/1.1.0/example
https://community.hortonworks.com/articles/176932/apache-deep-learning-101-using-apache-mxnet-on-the.html

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Deep Learning Architecture
HDP Node X
Node
Manager
Datanode
HBase
Region
HDP Node Y
Node
Manager
Datanode
HBase
Region
HDF Node
Apache NiFi
Zookeeper
Apache Spark
MLib
Apache Spark
MLib
GPU Node
Neural Network
Apache Spark
MLib
Apache Spark
MLib
Pipeline
GPU Node
Neural Network
Pipeline
MiNiFi Java
Agent
MiNiFi C++
Agent
HDF Node
Apache NiFi
Zookeeper
Apache Livy

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Why TensorFlow?
• Google
• Multiple platform
support
• Hadoop integration
• Spark integration
• Keras
• Large Community
• Python and Java APIs
• GPU Support
• Mobile Support
• Inception v3
• Clustering
• Fully functional demos
• Open Source
• Apache Licensed
• Large Model Library
• Buzz
• Extensive Documentation
• Raspberry Pi Support

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TensorFlow Running on Edge Nodes (MiniFi)

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TensorFlow Java Processor in Apache NiFi
https://community.hortonworks.com/content/kbentry/116803/building-a-custom-processor-in-
apache-nifi-12-for.html
https://github.com/tspannhw/nifi-tensorflow-processor
https://community.hortonworks.com/articles/178498/integrating-tensorflow-16-
image-labelling-with-hdf.html

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Apache MXNet Running on Edge Nodes (MiniFi)
https://community.hortonworks.com/articles/176932/apache-
deep-learning-101-using-apache-mxnet-on-the.html
https://github.com/tspannhw/rpi-mxnet-movidius-minifi
https://community.hortonworks.com/articles/183151/enterprise-iiot-edge-processing-with-
apache-nifi-m.html

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Edge Analytics with NVidia Jetson TX1 Running Apache MXNet (MiniFi)
https://community.hortonworks.com/articles/146704/edge-analytics-with-nvidia-jetson-tx1-running-apac.html

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Using Apache MXNet on The Edge with Sensors and Intel Movidius
(MiniFi)
https://community.hortonworks.com/articles/176932/apache-deep-learning-101-using-apache-mxnet-on-
the.html

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Questions?

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Contact
https://github.com/tspannhw/ApacheDeepLearning101
https://community.hortonworks.com/users/9304/tspann.html
https://dzone.com/users/297029/bunkertor.html
https://www.meetup.com/futureofdata-princeton/
https://twitter.com/PaaSDev
https://community.hortonworks.com/articles/155435/using-the-new-mxnet-model-server.html
• https://github.com/tspannhw/IoTFusion2018Talk

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