Deep Learning on Apache Spark
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The document discusses deep learning using BigDL on Apache Spark, defining key concepts and applications such as computer vision and speech recognition. It highlights BigDL's capabilities as a distributed deep learning library integrated with Spark, contrasting it with other frameworks like TensorFlow and Caffe. Additionally, it describes the Qubole platform's features for managing big data workloads, emphasizing automation and scalability.
Deep Learning on Apache Spark
- 1. Deep Learning On Spark Using BigDL on Qubole Dash Desai Technology Evangelist @iamontheinet
- 3. Copyright 2017 © Qubole What is Machine Learning? Gives ‘computers the ability to learn without being explicitly programmed’ - Wikipedia
- 4. Copyright 2017 © Qubole What is Deep Learning? Form of ML that uses a model of computing— inspired by the structure of the brain
- 5. Copyright 2017 © Qubole Deep Learning Applications Computer Vision / Image Recognition / Object Detection Speech Recognition / Natural Language Processing (NLP) Recommendation Systems (Products, Matchmaking, etc.) Prediction (Stock Market, Healthcare, etc.) Anomaly Detection (Cybersecurity, etc.)
- 6. Copyright 2017 © Qubole What is Apache Spark? A fast and general-purpose engine for large-scale, distributed data processing MLlib Spark’s scalable machine learning library High-quality algorithms; 100x faster than MapReduce Usable in Java, Scala, Python, and R
- 7. Copyright 2017 © Qubole Deep Learning: On Apache Spark
- 8. Copyright 2017 © Qubole Deep Learning: Other Popular Non-Spark Options TensorFlow* (Google) • Natively distributed out-of-the-box Keras • Naturally runs on distributed frameworks/back-ends • Theano, MXNet (CMU, MIT, NYU), TensorFlow, CNTK (Microsoft) *Not to be confused with TensorFlow On Spark (TFOS) by Yahoo
- 9. BigDL
- 10. Copyright 2017 © Qubole What is BigDL? Distributed deep learning library for Apache Spark Open sourced by Intel (in Dec 2016) Feature parity with DL frameworks such as Caffe, Torch Integrates with Spark ML pipeline and Spark Streaming Supports Model snapshots Intel MKL (Math Kernel Library); multi-threading within each Spark task
- 11. Copyright 2017 © Qubole Cont… Includes 100+ Layers (highest level building block in DL) Includes 20+ Loss functions (help with model fitting) Optimization methods include SGD, Adagard, LBFGS Numeric computing via Tensor & high level neural networks Scaling: synchronous mini-batch SGD and all-reduce communication on Spark What is BigDL?
- 12. Copyright 2017 © Qubole BigDL vs TensorFrames TensorFrames — can call TF from individual partitions of a DataFrame or an RDD (in PySpark)… However, since TF is not natively integrated with Spark, it does not support distributed deep learning such as for model training or fine tuning.
- 13. Copyright 2017 © Qubole BigDL vs TensorFlow on Spark (TFOS), Caffe TensorFlow on Spark* (TFOS) and Caffe on Spark — use Spark executors to launch TF or Caffe instances on the cluster… However, model training, predictions, etc. are performed outside of Spark across multiple TF or Caffe instances… • Run as standalone jobs outside of the pipeline • Very fine-grained/limited interaction with analytics pipeline *Not to be confused with natively distributed TensorFlow by Google
- 14. Copyright 2017 © Qubole How Does BigDL Work
- 15. Copyright 2017 © Qubole Distributed Deep Learning: Two Methods
- 16. Copyright 2017 © Qubole Distributed Deep Learning: BigDL
- 17. <Insert Demo Here >> YAY!/>
- 18. Copyright 2017 © Qubole Demo: Recognize Handwritten Digits On Use Model Train On Dataset … with everything running on … … … … to recognize handwritten digits …
- 19. Data Science on Qubole
- 20. 00Copyright 2017 © Qubole Qubole Qubole automates, controls and orchestrates all big data workloads including Data Science so that you can optimize for performance, cost and scale. Built for Anyone Who Uses Data Analysts Data Scientists Data Engineers Data Admins A Single Platform for Any Use Case ETL & Reporting Ad Hoc Queries Machine Learning Streaming Vertical Apps Open Source Engines, Optimized for the Cloud Cloud-Native, Cloud-Optimized, Cloud-Agnostics
- 21. Copyright 2017 © Qubole Data Science on Qubole
- 22. Copyright 2017 © Qubole Data Science on Qubole
- 23. Copyright 2017 © Qubole Cluster LifeCycle Management on Qubole Note: Available on Apache Spark, Hadoop, and Presto as a service on Qubole Auto-scaling Clusters • Policy-driven • One-time setup; Runtime modifications • Work load aware upscaling and downscaling • No wasted resources results in lowered TCO Heterogeneous Clusters • Mix-and-match instance types • On-Demand and Spot instances (on AWS)
- 24. 00Copyright 2017 © Qubole Qubole: High-level View User Access Qubole Tier Customer’s Azure Account QUBOLE UI VIA BROWSER SDK ODBC EPHEMERAL WEB TIER WEB SERVERS Default Hive Metastore RDS–Qubole User, Account Configurations (Encrypted credentials) Encrypted Result Cache (Optional) Custom Hive Metastore (Optional) Other RDS Encrypted HDFS Slave Encrypted HDFS Slave Master Ephemeral Cluster, Managed by Qubole Data Flow within Customer’s CloudRESTAPI (HTTPS)
- 25. Thank you! Dash Desai Technology Evangelist @iamontheinet Getting Started Install BigDL on Qubole + Demo App: http://bit.ly/deep_learning_bigdl_qubole BigDL: https://github.com/intel-analytics/BigDL