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Edge to ai analytics from edge to cloud with efficient movement of machine data

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This is my talk from DataWorks Summit Barcelona at 2pm on Thursday March 21, 2019.

https://dataworkssummit.com/barcelona-2019/session/edge-to-ai-analytics-from-edge-to-cloud-with-efficient-movement-of-machine-data/

Timothy Spann
Senior Solutions Engineer
Cloudera, formerly Hortonworks, Pivotal.

It shows how to run AI on edge devices, in NiFi flows and in CDSW.

Published in: Data & Analytics
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Edge to ai analytics from edge to cloud with efficient movement of machine data

  1. 1. Edge to AI: Analytics from Edge to Cloud with Efficient Movement of Machine Data TIMOTHY SPANN Senior Solutions Engineer Cloudera
  2. 2. 2 © Cloudera, Inc. All rights reserved. DISCLAIMER DA The information in this document is proprietary to Cloudera. No part of this document may be reproduced, copied or transmitted in any form for any purpose without the express prior written permission of Cloudera. This document is a preliminary version and not subject to your license agreement or any other agreement with Cloudera. This document contains only intended strategies, developments and functionalities of Cloudera products and is not intended to be binding upon Cloudera to any particular course of business, product strategy and/or development. Please note that this document is subject to change and may be changed by Cloudera at any time without notice. Cloudera assumes no responsibility for errors or omissions in this document. Cloudera does not warrant the accuracy or completeness of the information, text, graphics, links or other items contained within this material. This document is provided without a warranty of any kind, either express or implied, including but not limited to the implied warranties of merchantability, fitness for a particular purpose or non-infringement. Cloudera shall have no liability for damages of any kind including without limitation direct, special, indirect or consequential damages that may result from the use of these materials. The limitation shall not apply in cases of gross negligence.
  3. 3. @PaaSDev
  4. 4. @PaaSDev Hadoop {Submarine} Project: Running deep learning workloads on YARN , Tim Spann (Cloudera)
  5. 5. @PaaSDev
  6. 6. @PaaSDev
  7. 7. @PaaSDev IoT Edge Processing with Apache NiFi MiNiFi and Multiple Deep Learning Libraries
  8. 8. 8© Cloudera, Inc. All rights reserved.
  9. 9. 9 © Cloudera, Inc. All rights reserved. INDUSTRIALIZED AI REQUIRES LARGER DATA PLATFORM Streaming Ingest Batch Ingest Machine Learning Tools BI Tools and SQL Editors Data Products DATA, METADATA, SECURITY, GOVERNANCE, WORKLOAD MANAGEMENT MACHINE LEARNING DATA ENGINEERING DATA WAREHOUSE OPERATIONAL DATABASE
  10. 10. 10© Cloudera, Inc. All rights reserved. MACHINE LEARNING PHASES Where to Connect to Apache NiFi
  11. 11. Speed of Data Model Training Model Scoring Use Case Batch Batch Batch Batch Reporting, Analytics, Applications Online DS Applications/ Interactive Dashboards Streaming In-stream Streaming Applications Incremental/Online In-stream Streaming Applications Training, Scoring and Monitoring
  12. 12. 13© Cloudera, Inc. All rights reserved.
  13. 13. 14 © Cloudera, Inc. All rights reserved. ACCELERATED DEEP LEARNING WITH GPUS Multi-tenant GPU support on-premises or cloud • Extend CDSW to deep learning • Schedule & share GPU resources • Train on GPUs, deploy on CPUs • Works on-premises or cloud CDSW GPUCPU CDH CPU CDH CPU single-node training distributed training, scoring “Our data scientists want GPUs, but we need multi-tenancy. If they go to the cloud on their own, it’s expensive and we lose governance.” GPU On CDH coming in C6
  14. 14. 15 © Cloudera, Inc. All rights reserved. INTRODUCING MODELS Machine learning models as one-click microservices (REST APIs) Model APIs made easy! 1. Choose Python/R file, e.g. score.py 2. Choose function, e.g. forecast f = open('model.pk', 'rb') model = pickle.load(f) def forecast(data): return model.predict(data) 3. Choose resources
  15. 15. 16© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCH Select a Project, Create a Session, Load Libraries and Data CLOUDERA DATA SCIENCE WORKBENCH
  16. 16. 17© Cloudera, Inc. All rights reserved. Load a File and Run It CLOUDERA DATA SCIENCE WORKBENCH
  17. 17. 18© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCH Install Python Libraries for Python 2 or Python 3 CLOUDERA DATA SCIENCE WORKBENCH
  18. 18. 19© Cloudera, Inc. All rights reserved. Test your function with an argument CLOUDERA DATA SCIENCE WORKBENCH
  19. 19. 20© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCH Create a model from that file and function CLOUDERA DATA SCIENCE WORKBENCH
  20. 20. 21© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHList All The Models CLOUDERA DATA SCIENCE WORKBENCH
  21. 21. 22© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHDeploy the Model CLOUDERA DATA SCIENCE WORKBENCH
  22. 22. 23© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHCheckout The Build CLOUDERA DATA SCIENCE WORKBENCH
  23. 23. 24© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHTest the Model CLOUDERA DATA SCIENCE WORKBENCH
  24. 24. 25© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHValidate the Model Results CLOUDERA DATA SCIENCE WORKBENCH
  25. 25. 26© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHMonitor The Running Models CLOUDERA DATA SCIENCE WORKBENCH
  26. 26. 27© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHInvoke the Model From Apache NiFi In Flow CLOUDERA DATA SCIENCE WORKBENCH
  27. 27. 28© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHQuery Results of Classification in Flow { "class1": "cat", "cpu": 38.3, "end": "1549672761.1262221", "host": "gluoncv-apache-mxnet-29-50-7fb5cfc5b9-sx6dg", "memory": 14.9, "pct1": "98.15670800000001", "shape": "(1, 3, 566, 512)", "systemtime": "02/09/2019 00:39:21", "te": "3.380652666091919" } CLOUDERA DATA-IN-MOTION (APACHE NIFI)
  28. 28. 29© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHIntegrating Calls to CDSW Jobs CLOUDERA DATA-IN-MOTION (APACHE NIFI)
  29. 29. 30© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHPySpark Job for HDFS Storage CLOUDERA DATA SCIENCE WORKBENCH
  30. 30. 31© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHPySpark Job Receiving REST API CLOUDERA DATA SCIENCE WORKBENCH
  31. 31. 32© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHNiFi Job Integration CLOUDERA DATA SCIENCE WORKBENCH
  32. 32. 33© Cloudera, Inc. All rights reserved. CLOUDERA DATA SCIENCE WORKBENCHDisplay Data CLOUDERA DATA SCIENCE WORKBENCH

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