Tag: Geodatabase

Geocoding Improvements and Deprecations in ArcGIS Desktop 10.5 and ArcGIS Pro 1.4

DeprecationLocatorsGeodatabaseStyleImprovements

With almost every new release of ArcGIS Desktop and ArcGIS for Server, there are changes that aim to improve software quality and performance; sometimes, these changes require you to update your workflows. The improvements and deprecations made for geocoding in ArcMap 10.5 and ArcGIS … Continue reading

Posted in Analysis & Geoprocessing, ArcGIS for Server, ArcGIS Pro, ArcMap | Tagged , , , , , , , , , , , , , , , | Leave a comment

PerfQAnalyzer (PQA): Build 172 now available for download for 10.4

PQA

The Performance Engineering team at Esri is excited to release a new build of PerfQAnalyzer (PQA), build 172. This build further exposes the Workspace and FeatureClass using EditCommand script command; allowing the user to gather performance metrics for opening a database … Continue reading

Posted in Analysis & Geoprocessing, ArcMap, Editing, Mapping, Uncategorized | Tagged , , , , , , , , , , | 3 Comments

Pro 1.1: Why Do I Need to Click “Download?”

Pictometry 3D Scene

On Friday, July 17th, many ArcGIS Pro users saw a small window pop up on their computer screen. It announced to them, and to the world that a new version of Pro is available to download. I often find myself … Continue reading

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New Spatial Aggregation Tutorial for GIS Tools for Hadoop

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The Big Data team is excited to offer a new tutorial on spatial aggregation (sometimes called spatial binning). Spatial aggregation is extremely useful in summarizing big data to gain a meaningful snapshot of patterns in your data. Spatial aggregation works … Continue reading

Posted in Geodata | Tagged , , , , , , | 2 Comments

Course Change for the Arc Marine Data Model

ArcMarine_sml

As mentioned in a prior blog post and presentation, there have been discussions about the development of a new, improved version of the 2007 Arc Marine Data Model (also known as the “Marine Data Model”). This was an action item … Continue reading

Posted in Analysis & Geoprocessing, Hydro, Oceans & Maritime | Tagged , , , , , , , , , , | Leave a comment

Setting up a small budget Hadoop Cluster for Big Data Analysis

At the 2014 Esri User Conference, the Big Data team gave several presentations, including two technical workshops entitled: ‘Big Data and Analytics: The Fundamentals’ and ‘Big Data and Analytics with ArcGIS’. We presented our open source GIS Tools for Hadoop (shared on GitHub), as well as some research that we’re currently pursuing (exciting things to come!). We gave demos using both our open source tools as well as the prototype tools being currently researched.

For the demos (source data consisted of > 170 million data points that represent all the taxi cab trips in New York City in 2013), we ran all of our analytics on a Hadoop cluster back in Redlands. A twenty node cluster may seem like a big investment (and it can be); but, it doesn’t have to be. Enter the DREDD cluster… Continue reading

Posted in Geodata | Tagged , , , | 8 Comments

Big Data ST_Geometry Queries up to 20X Faster in Hive

The Big Data development team at Esri is excited to announce a major performance speedup in ST_Geometry for Hive, which is part of Esri’s open-source Spatial Framework for Hadoop.  The amount of performance gain depends on the type of spatial query run and on the size of the table in Hive.  The biggest gain comes with relational operations such as ST_Contains and ST_Overlaps.  In general, the performance gain will be greater with larger tables — exactly where it helps the most.

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Posted in Geodata | Tagged , , , , , , | 1 Comment

ST_Geometry Aggregate Functions for Hive in Spatial Framework for Hadoop

We are pleased to announce that the ST_Geometry aggregate functions are now available for Hive, in the Spatial Framework for Hadoop. The aggregate functions can be used to perform a convex-hull, intersection, or union operation on geometries from multiple records of a dataset.

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Posted in Geodata | Tagged , , , , , , | 1 Comment

Vehicle Trip Discovery with GIS Tools for Hadoop

An interesting task in highway management is to study potential impact of driver carpooling, based on an analysis of automatically collected automobile GPS position data. To identify potential enhancements to carpool participation, we set out to study places that have the highest numbers of trips with similar origin and destination locations. The source data for this experiment consists of nearly 40 million vehicle position records assembled from a single day of GPS-collected vehicle positions. The position data consists of longitude and latitude along with date, time, and speed. We used the Hadoop MapReduce framework for distributed parallel computation, considering its capability for analyzing larger data sets. Continue reading

Posted in Geodata | Tagged , , , , | 7 Comments

The Geodatabase Team at the 2013 Esri User Conference

The 2013 Esri International User Conference starts next week down at the San Diego Convention Center. There will be 15,000 attendees eager to learn and to see our path towards the future of GIS. Hopefully you’re one of them!

The Geodatabase Team will be down there giving technical sessions and demo theater presentations. We’ll be available to answer your questions and discuss what projects you’re working on too, so come visit us in the convention’s showcase area.

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Posted in Developer, Geodata | Tagged , , , , | 2 Comments