https://github.com/lixun910/mrweights

https://github.com/lixun910/mrweights

Last synced: about 1 month ago
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• Host: GitHub
• URL: https://github.com/lixun910/mrweights
• Owner: lixun910
• Created: 2014-11-04T08:58:43.000Z (about 10 years ago)
• Default Branch: master
• Last Pushed: 2015-05-13T20:29:54.000Z (over 9 years ago)
• Last Synced: 2023-08-07T09:12:14.030Z (over 1 year ago)
• Language: Python
• Size: 164 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
A MapReduce Algorithm to Create Contiguity Weights for Spatial Analysis of Big Data

=========

[convert_shp_splitable.py]: 

converting ESRI shapefile to the format used by Hadoop

[new_mapper_v1.py]:

map program for creating Queen Contiguity Weights

map Python script used by Hadoop Stream Pipline

[new_merge_v1.py]:

reduce program for creating Queen Contiguity Weights

reduce Python script used by Hadoop Stream Pipline

[gal_mapper.py]:

map program for creating GAL file from Hadoop Queen Contiguity Weights creation

map Python script used by Hadoop Stream Pipline

[gal_reducer.py]

reduce program for creating GAL file from Hadoop Queen Contiguity Weights creation

map Python script used by Hadoop Stream Pipline

[gen_wheader.sh]

used to insert a header to the result (GAL file) of gal_reducer.py

## References ##

* Xun Li, Wenwen Li, Luc Anselin, Sergio Rey and Julia Koschinsky. [A MapReduce algorithm to create contiguity weights for spatial analysis of big data](http://www.public.asu.edu/~xunli/p50-li.pdf).

  Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial '14), p50-53, Dallas Texas USA, 2014.

```bibtex

@inproceedings{Li:2014:MAC:2676536.2676543,

 author = {Li, Xun and Li, Wenwen and Anselin, Luc and Rey, Sergio and Koschinsky, Julia},

 title = {A MapReduce Algorithm to Create Contiguity Weights for Spatial Analysis of Big Data},

 booktitle = {Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data},

 series = {BigSpatial '14},

 year = {2014},

 isbn = {978-1-4503-3132-6},

 location = {Dallas, Texas},

 pages = {50--53},

 numpages = {4},

 url = {http://doi.acm.org/10.1145/2676536.2676543},

 doi = {10.1145/2676536.2676543},

 acmid = {2676543},

 publisher = {ACM},

 address = {New York, NY, USA},

 keywords = {big data, mapreduce, spatial weights},

} 

```