Geo-point and geo-shape types in Elasticsearch - Mini Project: Build & Apply

Geo-point and Geo-shape Types in Elasticsearch

📖 Scenario: You are working on a location-based service that stores places and their areas on a map. You want to use Elasticsearch to store and search these locations efficiently.

🎯 Goal: Build an Elasticsearch index mapping that uses geo_point for storing exact locations and geo_shape for storing areas. Then, add sample documents and query them.

📋 What You'll Learn

Create an index mapping with location as geo_point

Add area field as geo_shape

Index sample documents with both fields

Query documents by location and shape

💡 Why This Matters

🌍 Real World

Location-based apps like delivery services, real estate, or mapping use geo_point and geo_shape to store and search places and areas.

💼 Career

Understanding geo data types in Elasticsearch is important for backend developers and data engineers working on geospatial search and analytics.

1

Create index mapping with geo_point and geo_shape

Create an Elasticsearch index called places with a mapping that has a location field of type geo_point and an area field of type geo_shape.

Elasticsearch

# Create the index mapping with geo_point and geo_shape fields
# Your code here

Need a hint?

Use the PUT method to create the index and define location as geo_point and area as geo_shape in the mappings.

2

Index sample documents with geo_point and geo_shape

Index a document into the places index with location set to latitude 40.7128 and longitude -74.0060, and area set to a polygon shape with coordinates [[[-74.0, 40.7], [-74.0, 40.8], [-73.9, 40.8], [-73.9, 40.7], [-74.0, 40.7]]].

Elasticsearch

PUT /places/_doc/1
{
  "location": {"lat": 0, "lon": 0},
  "area": {
    "type": "polygon",
    "coordinates": []
  }
}
# Replace the values above with the correct latitude, longitude, and polygon coordinates
# Your code here

Need a hint?

Use PUT /places/_doc/1 to add a document. Set location with lat and lon. Define area as a polygon with the given coordinates.

3

Query documents by geo_point location

Write a search query on the places index to find documents where the location is within 5km of latitude 40.7130 and longitude -74.0070 using a geo_distance query.

Elasticsearch

GET /places/_search
{
  "query": {
    "geo_distance": {
      "distance": "5km",
      "location": {
        "lat": 0,
        "lon": 0
      }
    }
  }
}
# Replace lat and lon with 40.7130 and -74.0070
# Your code here

Need a hint?

Use a geo_distance query with distance set to "5km" and location coordinates as given.

4

Query documents by geo_shape area

Write a search query on the places index to find documents where the area intersects with a polygon shape defined by coordinates [[[-74.005, 40.705], [-74.005, 40.715], [-73.995, 40.715], [-73.995, 40.705], [-74.005, 40.705]]].

Elasticsearch

GET /places/_search
{
  "query": {
    "geo_shape": {
      "area": {
        "shape": {
          "type": "polygon",
          "coordinates": []
        },
        "relation": "intersects"
      }
    }
  }
}
# Replace the coordinates array with the polygon coordinates given
# Your code here

Need a hint?

Use a geo_shape query with relation set to "intersects" and the polygon coordinates given.