Dataflow with Apache NiFi
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This document provides an overview of Apache NiFi and dataflow. It begins with an introduction to the challenges of moving data effectively within and between systems. It then discusses Apache NiFi's key features for addressing these challenges, including guaranteed delivery, data buffering, prioritized queuing, and data provenance. The document outlines NiFi's architecture and components like repositories and extension points. It also previews a live demo and invites attendees to further discuss Apache NiFi at a Birds of a Feather session.
![7 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Why is moving data effectively hard?
à Standards
à Formats
à “Exactly Once” Delivery
à Protocols
à Veracity of Information
à Validity of Information
à Ensuring Security
à Overcoming Security
à Compliance
à Schemas
à Consumers Change
à Credential Management
à “That [person|team|group]”
à Network
à “Exactly Once” Delivery](https://image.slidesharecdn.com/2017-170412150251/85/Dataflow-with-Apache-NiFi-7-320.jpg)
![10 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Why is moving data effectively hard when scoped internally?
à Standards
à Formats
à “Exactly Once” Delivery
à Protocols
à Veracity of Information
à Validity of Information
à Ensuring Security
à Overcoming Security
à Compliance
à Schemas
à Consumers Change
à Credential Management
à “That [person|team|group]”
à Network
à “Exactly Once” Delivery](https://image.slidesharecdn.com/2017-170412150251/85/Dataflow-with-Apache-NiFi-10-320.jpg)
![12 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Why is moving data effectively hard when scoped globally?
à Standards
à Formats
à “Exactly Once” Delivery
à Protocols
à Veracity of Information
à Validity of Information
à Ensuring Security
à Overcoming Security
à Compliance
à Schemas
à Consumers Change
à Credential Management
à “That [person|team|group]”
à Network
à “Exactly Once” Delivery](https://image.slidesharecdn.com/2017-170412150251/85/Dataflow-with-Apache-NiFi-12-320.jpg)
Dataflow with Apache NiFi
- 1. Dataflow with Apache NiFi Aldrin Piri - @aldrinpiri Apache NiFi Crash Course DataWorks Summit 2017 – Munich 6 April 2017
- 2. 2 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Key: 'Apache NiFi’ Value: 'PMC Member' Key: 'Work’ Value: ’Sr. Member of Technical Staff @ Hortonworks' Key: 'Working with NiFi Since’ Value: '2010’
- 5. 5 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Let’s Connect A to B Producers A.K.A Things Anything AND Everything Internet! Consumers • User • Storage • System • …More Things
- 7. 7 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Why is moving data effectively hard? à Standards à Formats à “Exactly Once” Delivery à Protocols à Veracity of Information à Validity of Information à Ensuring Security à Overcoming Security à Compliance à Schemas à Consumers Change à Credential Management à “That [person|team|group]” à Network à “Exactly Once” Delivery
- 8. 8 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Let’s Connect Lots of As to Bs to As to Cs to Bs to Δs to Cs to ϕs Let’s consider the needs of a courier service Physical Store Gateway Server Mobile Devices Registers Server Cluster Distribution Center Core Data Center at HQ Server Cluster On Delivery Routes Trucks Deliverers Delivery Truck: Creative Stall, https://thenounproject.com/creativestall/ Deliverer: Rigo Peter, https://thenounproject.com/rigo/ Cash Register: Sergey Patutin, https://thenounproject.com/bdesign.by/ Hand Scanner: Eric Pearson, https://thenounproject.com/epearson001/
- 9. 9 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Great! I am collecting all this data! Let’s use it! Finding our needles in the haystack Physical Store Gateway Server Mobile Devices Registers Server Cluster Distribution Center Kafka Core Data Center at HQ Server Cluster Others Storm / Spark / Flink / Apex Kafka Storm / Spark / Flink / Apex On Delivery Routes Trucks Deliverers Delivery Truck: Creative Stall, https://thenounproject.com/creativestall/ Deliverer: Rigo Peter, https://thenounproject.com/rigo/ Cash Register: Sergey Patutin, https://thenounproject.com/bdesign.by/ Hand Scanner: Eric Pearson, https://thenounproject.com/epearson001/
- 10. 10 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Why is moving data effectively hard when scoped internally? à Standards à Formats à “Exactly Once” Delivery à Protocols à Veracity of Information à Validity of Information à Ensuring Security à Overcoming Security à Compliance à Schemas à Consumers Change à Credential Management à “That [person|team|group]” à Network à “Exactly Once” Delivery
- 11. 11 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Let’s Connect Lots of As to Bs to As to Cs to Bs to Δs to Cs to ϕs Oh, that courier service is global
- 12. 12 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Why is moving data effectively hard when scoped globally? à Standards à Formats à “Exactly Once” Delivery à Protocols à Veracity of Information à Validity of Information à Ensuring Security à Overcoming Security à Compliance à Schemas à Consumers Change à Credential Management à “That [person|team|group]” à Network à “Exactly Once” Delivery
- 13. 13 © Hortonworks Inc. 2011 – 2016. All Rights Reserved The Unassuming Line: A Case Study We’ve seen a few lines show up in the wild thus far Internet! Inter- & Intra- connections in our global courier enterprise Spotlight: Arthur Lacôte, https://thenounproject.com/turo/
- 14. 14 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Dataflow Line Anatomy 101 Let’s dissect what this line typically represents Fig 1. Lineus Worldwidewebus. Common Name: Internet! Script or Application Script or Application Data Data Disparate Transport Mechanisms
- 15. 15 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Dataflow Line Anatomy 201 Sometimes that transport is just more lines Fig 1. Lineus Worldwidewebus. Common Name: Internet! Script or Application Script or Application Line Inception Data Data
- 16. 16 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Dataflow Line Anatomy 301 But those lines could also have components… Fig 1. Lineus Worldwidewebus. Common Name: Internet!
- 18. 18 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Apache NiFi Key Features • Guaranteed delivery • Data buffering - Backpressure - Pressure release • Prioritized queuing • Flow specific QoS - Latency vs. throughput - Loss tolerance • Data provenance • Supports push and pull models • Recovery/recording a rolling log of fine- grained history • Visual command and control • Flow templates • Pluggable/multi-role security • Designed for extension • Clustering
- 19. 19 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Apache NiFi Subproject: MiNiFi à Let me get the key parts of NiFi close to where data begins and provide bidrectional communication à NiFi lives in the data center. Give it an enterprise server or a cluster of them. à MiNiFi lives as close to where data is born and is a guest on that device or system
- 20. 20 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Let’s revisit our courier service from the perspective of NiFi Physical Store Gateway Server Mobile Devices Registers Server Cluster Distribution Center Kafka Core Data Center at HQ Server Cluster Others Storm / Spark / Flink / Apex Kafka Storm / Spark / Flink / Apex On Delivery Routes Trucks Deliverers Delivery Truck: Creative Stall, https://thenounproject.com/creativestall/ Deliverer: Rigo Peter, https://thenounproject.com/rigo/ Cash Register: Sergey Patutin, https://thenounproject.com/bdesign.by/ Hand Scanner: Eric Pearson, https://thenounproject.com/epearson001/ Client Libraries Client Libraries MiNiFi MiNiFi NiFi NiFi NiFi NiFi NiFi NiFi Client Libraries
- 21. 21 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Apache NiFi Managed Dataflow SOURCES REGIONAL INFRASTRUCTURE CORE INFRASTRUCTURE
- 22. 22 © Hortonworks Inc. 2011 – 2016. All Rights Reserved NiFi is based on 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.
- 23. 23 © Hortonworks Inc. 2011 – 2016. All Rights Reserved FlowFiles & Data Agnosticism à NiFi is data agnostic! à But, NiFi was designed understanding that users can care about specifics and provides tooling to interact with specific formats, protocols, etc. ISO 8601 - http://xkcd.com/1179/ Robustness principle Be conservative in what you do, be liberal in what you accept from others“
- 24. 24 © Hortonworks Inc. 2011 – 2016. All Rights Reserved 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
- 26. 26 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Extension / Integration Points NiFi Term Description Flow File Processor Push/Pull behavior. Custom UI Reporting Task Used to push data from NiFi to some external service (metrics, provenance, etc..) Controller Service Used to enable reusable components / shared services throughout the flow REST API Allows clients to connect to pull information, change behavior, etc.. © Hortonworks Inc. 2011 – 2016. All Rights ReservedX Architecture OS/Host JVM Flow Controller Web Server Processor 1 Extension N FlowFile Repository Content Repository Provenance Repository Local Storage Standalone Cluster
- 27. 27 © Hortonworks Inc. 2011 – 2016. All Rights Reserved NiFi Architecture – Repositories - Pass by reference FlowFile Content Provenance F1à C1 C1 P1à F1 Excerpt of demo flow… What’s happening inside the repositories… BEFORE AFTER F2à C1 C1 P3à F2 – Clone (F1) F1à C1 P2à F1 – Route P1à F1 – Create
- 28. 28 © Hortonworks Inc. 2011 – 2016. All Rights Reserved NiFi Architecture – Repositories – Copy on Write FlowFile Content Provenance F1à C1 C1 P1à F1 - CREATE Excerpt of demo flow… What’s happening inside the repositories… BEFORE AFTER F1à C1 F1.1à C2 C2 (encrypted) C1 (plaintext) P2à F1.1 - MODIFY P1à F1 - CREATE
- 31. 31 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Why NiFi? à Moving data is multifaceted in its challenges and these are present in different contexts at varying scopes – Think of our courier example and organizations like it: inter vs intra, domestically, internationally à Provide common tooling and extensions that are commonly needed but be flexible for extension – Leverage existing libraries and expansive Java ecosystem for functionality – Allow organizations to integrate with their existing infrastructure à Empower folks managing your infrastructure to make changes and reason about issues that are occurring – Data Provenance to show context and data’s journey – User Interface/Experience a key component
- 32. 32 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Learn more and join us! Apache NiFi site http://nifi.apache.org Subproject MiNiFi site http://nifi.apache.org/minifi/ Subscribe to and collaborate at [email protected] [email protected] Submit Ideas or Issues https://issues.apache.org/jira/browse/NIFI Follow us on Twitter @apachenifi
- 33. 33 © Hortonworks Inc. 2011 – 2016. All Rights Reserved Our Lab for Today à We will be exploring some examples to work through creating a dataflow with Apache NiFi à Use Case: An urban planning board is evaluating the need for a new highway, dependent on current traffic patterns, particularly as other roadwork initiatives are under way. Integrating live data poses a problem because traffic analysis has traditionally been done using historical, aggregated traffic counts. To improve traffic analysis, the city planner wants to leverage real-time data to get a deeper understanding of traffic patterns. NiFi was selected for for this real-time data integration. à Labs are available at http://tinyurl.com/nificrashcourse