This is a Demo of using Spatial Search feature in ElasticSearch
This project is build using grunt, to get started read here
Once grunt
is installed cd
to AroundMe and run grunt
, however for convinince index.js
in build folder is also checked in.
You will need to install ElasticSearch, read about installing it here, also install marvel plugin for configuration and testing.
The data used here is from Geofabrik.
I have used points.shp file from the Great-Britain shape file download, but you can use any other country as well.
To extract the data,I wrote a quick python script using pyshp
you can easily install it by typing sudo easy_install pyshp
.
Before running the script you will have to create an Index and add schema to it.
Assuming that elastic search is running, you can issue a command from marvel.
PUT /places
{
"mappings": {
"place": {
"properties": {
"id": {"type": "double"},
"name": {"type": "string"},
"type": {"type": "string"},
"location": {"type": "geo_point"}
}
}
}
}
Modify the path in script below to the source file, "points" in this case and run the script.
import shapefile
import urllib2
import json
sf = shapefile.Reader("points")
sr = sf.shapeRecords()
for r in sr:
try :
if r.record[2].strip() and r.record[3].strip():
req = urllib2.Request('https://localhost:9200/places/place/')
req.add_header('Content-Type', 'application/json')
data = {'id': r.record[0].strip(),'name':r.record[2].strip(),'type':r.record[3].strip(),'location':{'lat':r.shape.points[0][1],'lon':r.shape.points[0][0]}}
response = urllib2.urlopen(req, json.dumps(data))
print r.record[2]
except Exception,e:
print e
#print "ERROR ",r.record[0],r.record[2],r.record[3] , r.shape.points[0][0], r.shape.points[0][1]
pass
The script inserts all records which have a valid name
and type column
into index.
GET places/_count
GET places/_search
{
"sort" : [
{
"_geo_distance" : {
"location" : {
"lat": 51.5286416,
"lon": -0.10159870000006777
},
"order" : "asc",
"unit" : "km"
}
}
],
"query": {
"filtered" : {
"query" : {
"match_all" : {}
},
"filter" : {
"geo_distance" : {
"distance" : "20km",
"location" : {
"lat": 51.5286416,
"lon": -0.10159870000006777
}
}
}
}
}
}
GET places / _search ? size = 100 & from = 0 {
"sort": [{
"_geo_distance": {
"location": {
"lat": 51.5286416,
"lon": -0.10159870000006777
},
"order": "asc",
"unit": "km"
}
}],
"query": {
"filtered": {
"query": {
"bool": {
"should": [{
"term": {
"type": "pub"
}
}]
}
},
"filter": {
"geo_distance": {
"distance": "1km",
"location": {
"lat": 51.5286416,
"lon": -0.10159870000006777
}
}
}
}
}
}
Final step is to configure a proxy to server html and to route ajax requests to localhost9200.
In this case the server in use is nginx, below is the minimal configuration, The localhost:80
is mapped to server contents of AroundMe folder
and the proxy is mapped to route requests /elastic
to localhost:9200
server {
listen 80;
server_name localhost;
#charset koi8-r;
#access_log logs/host.access.log main;
location / {
root /Users/varunpant/Documents/Github/AroundMe;
index index.html index.htm;
}
location /elastic/ {
proxy_pass https://localhost:9200/;
}
#error_page 404 /404.html;
# redirect server error pages to the static page /50x.html
#
error_page 500 502 503 504 /50x.html;
location = /50x.html {
root html;
}
}
Once configured restart the server and browse to localhost
:)
I hope you find it useful.
If you like or use this project somewhere please contact me at [email protected].