Cloud architectures for data science
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Data Science covers the complete workflow from defining a question, finding the most suitable data source, identifying the right tools and finally presenting the best possible answer in a clear, engaging manner. But it all starts with having access to the data. In these slides I will walk your through some examples of how to collect, store and access data in the Cloud with the use of different APIs.
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Cloud architectures for data science
- 1. @MargrietGr Margriet Groenendijk, PhD Developer Advocate for IBM Cloud Data Services O’Reilly Software Architecture Conference San Francisco 16 November 2016 Cloud Architectures for Data Science
- 2. @MargrietGr About me • Developer Advocate at IBM Cloud Data Services, UK •Data science •Python, Spark, R, Cloudant, dashDB • Research Fellow at University of Exeter, UK •Worked with very large observational datasets and the output of global scale climate models • PhD at Vrije Universiteit Amsterdam, the Netherlands •Explored large observational datasets of carbon uptake by forests
- 3. @MargrietGr A Brief History of Data Science • Computer Science • Data Technology • Visualization • Mathematics • Statistics http://www.datascienceassn.org/content/history-data-science
- 10. @MargrietGr 2016
- 11. @MargrietGr https://blog.rjmetrics.com/2015/10/05/how-many-data-scientists-are-there/ How many Data Scientists are there?
- 15. @MargrietGr Data Engineers Data Scientists Business Analysts App Developers Data Science is a Team Effort Data
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- 20. @MargrietGr Collect Data APIs Open Data Maps Web Scraping Time Series
- 21. @MargrietGr Store Data Object Store - binary files Relational database Document store - json
- 25. @MargrietGr The Spark Stack from Karau et al.: Learning Spark
- 26. @MargrietGr RDDs : Resilient Distributed Datasets • Data does not have to fit on a single machine • Data is separated into partitions • Creation of RDDs •Load an external dataset •Distribute a collection of objects • Transformations construct a new RDD from a previous one (lazy!) • Actions compute a result based on an RDD
- 27. @MargrietGr Run Spark locally in a Python notebook https://www.continuum.io/downloads http://spark.apache.org/downloads.html Create a new kernel to use in a Jupyter notebook
- 28. @MargrietGr Jupyter Notebooks! • Server-client application to edit and run notebook documents via a web browser • Cells with: •Code •Figures and tables •Rich text elements • Different kernels: Python, R, Scala, Spark In the Cloud:
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- 34. @MargrietGr Define Question What will the weather be next weekend? https://unsplash.com/search/autumn?photo=LSF8WGtQmn8 https://unsplash.com/search/rain?photo=19tQv51x4-A
- 36. @MargrietGr Explore Data Python packages • requests and json •API credentials and latitude/longitude of San Francisco •json data returned • pandas, numpy and datetime •convert json to pandas DataFrame (table with multiple indices) •add time as index
- 37. @MargrietGr Weather forecast for San Francisco https://developer.ibm.com/ clouddataservices/2016/10/06/ your-own-weather-forecast-in-a- python-notebook/ Visualize Data Python packages • pandas - rolling mean • matplotlib • Basemap
- 38. @MargrietGr Weather map - example for UK https:// developer.ibm.com/ clouddataservices/ 2016/10/06/your-own- weather-forecast-in-a- python-notebook/ Python packages • matplotlib • Basemap • itertools • urllib
- 39. @MargrietGr Run as a daily cron job cloudant
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- 43. @MargrietGr Weather, Twitter and Sentiment • Where to find the data? • Where to store the data? • Where to analyse the data? • Quick tools to explore
- 45. @MargrietGr Add sentiment - example
- 46. @MargrietGr • watson tone analyser Emotion Language style Social propensities Analyze how you are coming across to others
- 47. @MargrietGr Simpler Workflow Weather Company Data crontab -e 0 23 * * * /path/to/file/do_something.sh python do_something.py Tweets Weather Sentiment Watson Tone Analyser Insights for Twitter Cloudant NoSQL
- 49. @MargrietGr PixieDust: an Open Source Library that simplifies and improves Jupyter Python Notebooks • PackageManager • Visualizations • Cloud Integration • Scala Bridge • Extensibility • Embedded Apps https://developer.ibm.com/clouddataservices/2016/10/11/pixiedust-magic-for- python-notebook/ @DTAIEB55
- 50. @MargrietGr Install Spark packages or plain jars in your Notebook Python kernel without the need to modify configuration file Uses the GraphFrame Python APIs Install GraphFrames Spark Package
- 51. @MargrietGr One simple API: display() Call the Options dialog Panning/Zooming options Performance statistics
- 52. @MargrietGr Easily export your data to csv, json, html, etc. locally on your laptop or into a cloud-based service like Cloudant or Object Storage
- 53. @MargrietGr Scala Bridge Define a Python variable Use the Python var in Scala Define a Scala variable Use the Scala var in Python
- 54. @MargrietGr Easily extend PixieDust to create your own visualizations using HTML/CSS/JavaScript Customized Visualization for GraphFrame Graphs
- 55. @MargrietGr Encapsulate your analytics into compelling User Interfaces better suited for Line of Business Users
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- 58. @MargrietGr • Mission: To explore, understand and explain the origin and nature of life in the universe • Origins: Started in 1959 by two physicists at Cornell • NASA became interested in 1970, started working with SETI in 1988, funding cut in 1993 SETI@IBMCloud http://www.seti.org/node/861
- 59. @MargrietGr • The Allen Telescope Array •198 million radio events detected in the last decade •400,000 candidate signals identified •5TB data generated in 10 hours • No modern analysis or machine learning has been performed on this data • 5 TB of special observations on IBM Object Store SETI@IBMCloud - the Data https://github.com/ibm-cds-labs/ibmseti/
- 60. @MargrietGr Public Spark@SETI 4 TB of SETI Data stored in Object Storage Web API provides Bluemix users access to download SETI data Object Storage Web API Spark Object Storage Public Spark@SETI Bluemix Account My Bluemix Account Spark using Jupyter Notebook and IBM SETI Python Library Goal: Amateur scientists/data scientists download and analyze SETI data
- 61. @MargrietGr IBM Watson Data Platform • Data Science Experience • Watson Data Platform • Machine Learning • Sign up for beta: http://datascience.ibm.com/features#machinelearning
- 62. @MargrietGr Data Science in the Cloud • Flexible and quick to iterate, play and explore data • APIs •Streaming data •Cloud databases •Watson • Scaling up - add storage or Spark kernels • Easy collaboration and presentation •Store Data •Share your analyses in notebooks • Some useful packages: pandas, pyspark, requests, matplotlib, cloudant • Notebooks can be extended! PixieDust
- 63. @MargrietGr https://developer.ibm.com/clouddataservices/author/ mgroenen/ Thanks! Slides will be here: http://www.slideshare.net/MargrietGroenendijk