Geo-point and geo-shape types in Elasticsearch - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this geo-point query?

Given the following Elasticsearch query, what will be the number of hits returned if the index contains documents with geo-points at (40, -70), (41, -71), and (39, -69)?

Elasticsearch

{
  "query": {
    "geo_distance": {
      "distance": "100km",
      "location": {
        "lat": 40,
        "lon": -70
      }
    }
  }
}

A 0

B 2

C 3

D 1

💡 Hint

Think about which points fall within 100km radius of (40, -70).

Only the point at (40, -70) is within 100km of the center point. The points at (41, -71) and (39, -69) are approximately 140km away.

🧠 Conceptual

intermediate

Which geo-shape type represents a polygon with holes?

In Elasticsearch geo-shape types, which of the following correctly represents a polygon with holes inside it?

A A MultiPoint with points inside the polygon area

B A LineString with multiple segments forming a closed loop

C A Polygon with multiple linear rings, where the first ring is the outer boundary and subsequent rings are holes

D A Point with a radius representing the hole

💡 Hint

Think about how polygons with holes are defined in geojson format.

Polygons with holes are defined by multiple linear rings: the first is the outer boundary, others are holes inside.

🔧 Debug

advanced

Why does this geo_shape query fail?

This geo_shape query returns an error. What is the cause?

Elasticsearch

{
  "query": {
    "geo_shape": {
      "location": {
        "shape": {
          "type": "circle",
          "coordinates": [-70, 40],
          "radius": "100km"
        },
        "relation": "intersects"
      }
    }
  }
}

A Elasticsearch does not support 'circle' type in geo_shape queries

B The coordinates are in wrong order; should be [lat, lon]

C The radius value must be a number, not a string

D The relation 'intersects' is invalid for geo_shape queries

💡 Hint

Check the supported geo_shape types in Elasticsearch.

Elasticsearch geo_shape does not support 'circle' type; it supports types like Point, Polygon, MultiPolygon, etc.

📝 Syntax

advanced

Identify the syntax error in this geo-point mapping

Which option contains the correct syntax for defining a geo_point field in an Elasticsearch mapping?

A "location": { "type": "geo_point" }

B "location": { "geo_point": true }

C "location": { "type": "geo-point" }

D "location": { "type": "point_geo" }

💡 Hint

Check the exact spelling of the geo_point type.

The correct type name is 'geo_point' without hyphen or other variations.

🚀 Application

expert

How many shapes are indexed with this geo_shape document?

Given this document indexed in Elasticsearch with a geo_shape field 'area': { "area": { "type": "geometrycollection", "geometries": [ { "type": "point", "coordinates": [100.0, 0.0] }, { "type": "linestring", "coordinates": [[101.0, 0.0], [102.0, 1.0]] }, { "type": "polygon", "coordinates": [[[100.0, 0.0], [101.0, 0.0], [101.0, 1.0], [100.0, 1.0], [100.0, 0.0]]] } ] } } How many individual shapes does this geo_shape field contain?

A 0

B 3

C 1

D 4

💡 Hint

Count each geometry inside the GeometryCollection.

A GeometryCollection contains multiple geometries; here there are 3: a point, a linestring, and a polygon.

Practice

1.

What is the main difference between geo_point and geo_shape types in Elasticsearch?

easy

A. geo_point stores a single location; geo_shape stores complex shapes like polygons.

B. geo_point stores polygons; geo_shape stores single points.

C. geo_point is used for text data; geo_shape is used for numbers.

D. geo_point stores multiple points; geo_shape stores only lines.

Solution

1. Step 1: Understand geo_point type

   geo_point stores a single geographic location using latitude and longitude coordinates.

2. Step 2: Understand geo_shape type

   geo_shape stores complex geographic shapes such as polygons, lines, or multi-points.

3. Final Answer:

   geo_point stores a single location; geo_shape stores complex shapes like polygons. -> Option A

4. Quick Check:

   Single point vs complex shape = C [OK]

Hint: Remember: point = one spot, shape = many spots connected [OK]

Common Mistakes:

• Confusing points with polygons
• Thinking geo_point stores multiple points
• Mixing data types with geo types

2.

Which of the following is the correct way to define a geo_point field in an Elasticsearch mapping?

{
  "properties": {
    "location": {
      "type": "?"
    }
  }
}

easy

A. "geo_shape"

B. "geo_point"

C. "point_geo"

D. "location_point"

Solution

1. Step 1: Recall Elasticsearch geo types

   Elasticsearch uses "geo_point" as the type name for single geographic points.

2. Step 2: Match the correct type in mapping

   The mapping must specify "type": "geo_point" to store latitude and longitude.

3. Final Answer:

   "geo_point" -> Option B

4. Quick Check:

   Mapping type for point = "geo_point" [OK]

Hint: Use exact type names: geo_point for points [OK]

Common Mistakes:

• Using incorrect type names like geo_shape for points
• Typos in type string
• Confusing field name with type

3.

Given this Elasticsearch document indexed with a geo_point field location:

{ "location": { "lat": 40.7128, "lon": -74.0060 } }

Which query will correctly find documents within 10km of this point?

medium

A. { "range": { "location": { "gte": "10km" } } }

B. { "geo_shape": { "location": { "shape": { "type": "point", "coordinates": [40.7128, -74.0060] }, "relation": "within" } } }

C. { "term": { "location": "40.7128,-74.0060" } }

D. { "geo_distance": { "distance": "10km", "location": { "lat": 40.7128, "lon": -74.0060 } } }

Solution

1. Step 1: Identify correct query type for geo_point

   For geo_point, geo_distance query finds documents within a distance from a point.

2. Step 2: Check query syntax and parameters

   { "geo_distance": { "distance": "10km", "location": { "lat": 40.7128, "lon": -74.0060 } } } uses geo_distance with correct distance and point coordinates.

3. Final Answer:

   { "geo_distance": { "distance": "10km", "location": { "lat": 40.7128, "lon": -74.0060 } } } -> Option D

4. Quick Check:

   geo_distance query = { "geo_distance": { "distance": "10km", "location": { "lat": 40.7128, "lon": -74.0060 } } } [OK]

Hint: Use geo_distance for points, geo_shape for polygons [OK]

Common Mistakes:

• Using geo_shape query on geo_point field
• Wrong coordinate order in geo_shape
• Using term or range queries for geo data

4.

What is wrong with this Elasticsearch mapping for a geo_shape field named area?

{
  "properties": {
    "area": {
      "type": "geo_point"
    }
  }
}

The data to be stored is a polygon shape.

medium

A. The type should be geo_shape to store polygons.

B. The field name area is invalid for geo data.

C. The mapping must include coordinates property.

D. The type geo_point supports polygons by default.

Solution

1. Step 1: Check field type for polygon data

   Polygons require geo_shape type, not geo_point.

2. Step 2: Identify mapping error

   Mapping uses geo_point which only supports single points, so it cannot store polygons.

3. Final Answer:

   The type should be geo_shape to store polygons. -> Option A

4. Quick Check:

   Polygon needs geo_shape type = D [OK]

Hint: Polygons need geo_shape, not geo_point [OK]

Common Mistakes:

• Using geo_point for polygon shapes
• Assuming field name affects type
• Adding coordinates in mapping instead of data

5.

You want to store a city boundary as a polygon and find all points inside it. Which Elasticsearch setup is correct?

{
  "mappings": {
    "properties": {
      "city_boundary": { "type": "?" },
      "user_location": { "type": "?" }
    }
  }
}

Choose the correct types for city_boundary and user_location.

hard

A. "geo_shape" for both city_boundary and user_location

B. "geo_point" for city_boundary and "geo_shape" for user_location

C. "geo_shape" for city_boundary and "geo_point" for user_location

D. "geo_point" for both city_boundary and user_location

Solution

1. Step 1: Determine type for city boundary polygon

   City boundary is a polygon, so it requires geo_shape type.

2. Step 2: Determine type for user location point

   User location is a single point, so it requires geo_point type.

3. Step 3: Match types to fields

   Assign geo_shape to city_boundary and geo_point to user_location.

4. Final Answer:

   "geo_shape" for city_boundary and "geo_point" for user_location -> Option C

5. Quick Check:

   Polygon = geo_shape, Point = geo_point [OK]

Hint: Polygon needs geo_shape; point needs geo_point [OK]

Common Mistakes:

• Swapping types between polygon and point
• Using geo_point for polygons
• Using geo_shape for single points unnecessarily