An Early Look at Performing Big Data Geo Analytics for Feature and Tabular Datasets

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1 FedGIS Conference February 24 25, 2016 Washington, DC An Early Look at Performing Big Data Geo Analytics for Feature and Tabular Datasets Erik Hoel and Sarah Ambrose

2 ArcGIS 2016 Feature Analytics and Big Data Processing: What s Coming in 2016

3 What is Feature Geo Analytics? ArcGIS has a new way of processing spatiotemporal data that is designed for big data by leveraging distributed analytics and storage Works with your existing GIS data and tabular data Designed to perform both spatial and temporal analysis Uses familiar workflows to complete complex analyses

4 Feature Geo Analytics Feature Geo Analytics adds to existing ArcGIS analysis capabilities Geoprocessing Feature Geo Analytics Web GIS Layers Portal Distributed analytics and storage more new extends

5 Solve New Problems Run analytics: against data that is too big for a single desktop machine - tens of millions of 911 calls accumulated over years - billions of observations of ship movements ingested through GeoEvent designed to gain insight into both spatial and temporal patterns against massive collections in a scalable manner and meet time constraints months weeks days hours minutes

6 Rich Collection of Analysis Tools Summarize Data Aggregate Points Summarize Nearby Summarize Within Reconstruct Tracks Join Features Find Locations Find Existing Locations Find Similar Locations Aggregate Points Summarize Nearby Summarize Within Find Existing Locations Find Similar Locations Analyze Patterns Calculate Density Find Hot Spots Create Space Time Cube Use Proximity Create Buffers Manage Data Extract Data Calculate Density Find Hot Spots Create Buffers Extract Data * Temporally aware tools

7 Familiar and Simple Interfaces Easy to get started, available out of the box Simple user experience - Simplified analysis Web UX through Portal - Familiar tool box and ribbon experience through Pro Great developer interfaces - Python developer experience through Pro - Develop quickly and share through Python notebooks - Familiar REST API

8 Feature Geo Analytics and Your Data Use your own big data sources - Easily attach folders located locally on a disk or a file share - Multiple files can be recognized as a single Geo Analytics dataset - Attach big data stores Use your GIS data - Works with layers already in your Web GIS

9 Geo Analytics Architectural Overview New Web GIS Layers Feature Geo Analytics can power systems that need to execute analysis in a distributed and scalable environment. It is designed for analysts, researchers, and developers. Web GIS Layers Server Cluster Portal Use your Web GIS layers through Pro, Portal, Python Notebooks, or the REST API Files Files Shapefiles Delimited Files Enterprise Big Data Stores Relational Data Store Spatiotemporal Data Store Un-Managed Data Managed Data

10 ArcGIS 2016 Feature Geo Analytics: Analytic Details

11 Analytical Overview Analysis capabilities patterned from ArcGIS Online Spatial Analysis Tools useful for big data with an emphasis on: - Spatiotemporal analysis - Summarization and aggregation Instant Interval

12 Aggregation and Summarization Spatial Joins Space-time slices

13 Time Slicing Three parameters to define a time slice: - Interval (time in a slice) - Step (frequency of slice) - Reference time (alignment) Step Interval Reference time Examples: - Hourly slices Interval: 1 hour - Every 12 th hour Interval: 1 hour Step: 12 hours - Every Monday Interval: 1 day Step: 1 week Reference: Some Monday

14 Demo Find Hotspots NYC Taxi Data - 3 years of yellow cab data - Taxi pickup locations with time - 3 x 12 CSVs = 72 GB million pickup locations

15 Aggregation and Summarization (cont.) Spatiotemporal joins Target Features Join Features Intermediate Result Final Result

16 Temporal Relationships on Intervals

17 Demo Join Features Earthquake dataset - 2 million points - ~100 years Volcano eruptions dataset points - ~100 years Not big data per se, but illustrative

18 Aggregation and Summarization (cont.) Points into Bins

19 Aggregation Polygons vs Cells Aggregation By Polygons Aggregation By Cells

20 Aggregation and Summarization (cont.) Reconstruct Tracks - Summarize time-enabled points into tracks

21 Demo Construct Tracts Hurricane dataset - 120,000 points, ~100 years - Each point has: - Serial number - Location - Date - Wind speed and pressure attributes - Problems? - Difficult to visualize that many points - Difficult to visualize hurricane path

22 Geo Analytics Performance Aggregate by Cell 16 nodes in the cluster - 4 cores per node (commodity desktops) - 14 GB RAM per node Buffer Polygons (NYC Blocks) 40K Points (NYC Taxi) 170M Aggregate by Polygon

23 Geo Analytics Performance 16 nodes in the cluster - 4 cores per node (commodity desktops) - 14 GB RAM per node Aggregate 4 billion points into polygons - 52 polygons (states) 12 minutes - 11 million polygons (census blocks) 1.2 hours 4 billion points x 11 million polygons 200K x more polygons 6 x more time

24 Geo Analytics Performance 18 nodes in the cluster - 8 cores per node (commodity desktops) - 24 GB RAM per node Spatiotemporal attribute join of 1 billion points (the plenary financial dataset) - 1 km radius - 1 hour time window - target:destination_id = join:destination_id (i.e., transactions to the same bank) 1.0 hour, including all I/O to ArcGIS Spatiotemporal Data Store

25 Why will I want to use Geo Analytics? Helps you get big jobs done faster Makes big data easier to use and easier to share Parallelizes and focuses on space and time analysis for massive dataset processing Feature Geo Analytics are out of the box and ready to use within your ArcGIS system - familiar and simple interfaces - faster prototyping, R&D, and insight into your data Lets you see the big data picture in a clearer and more meaningful way

26 Don t forget to complete your digital session survey Download the Esri Events app

27 GIS Solutions Expo, Hall A Wednesday, 12:30 p.m. 6:30 p.m. Welcome Social, 5:15 p.m. 6:30 p.m. Thursday, 10:45 a.m. 4:00 p.m. Exhibitors Hands-on Learning Lab Demo Theaters Esri Showcase

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