WARNING: The 2.x versions of Elasticsearch have passed their EOL dates. If you are running a 2.x version, we strongly advise you to upgrade.
This documentation is no longer maintained and may be removed. For the latest information, see the current Elasticsearch documentation.
Lat/Lon Formatsedit
With the location
field defined as a geo_point
, we can proceed to index
documents containing latitude/longitude pairs, which can be formatted as
strings, arrays, or objects:
PUT /attractions/restaurant/1 { "name": "Chipotle Mexican Grill", "location": "40.715, -74.011" } PUT /attractions/restaurant/2 { "name": "Pala Pizza", "location": { "lat": 40.722, "lon": -73.989 } } PUT /attractions/restaurant/3 { "name": "Mini Munchies Pizza", "location": [ -73.983, 40.719 ] }
A string representation, with |
|
An object representation with |
|
An array representation with |
Everybody gets caught at least once: string geo-points are
"latitude,longitude"
, while array geo-points are [longitude,latitude]
—the opposite order!
Originally, both strings and arrays in Elasticsearch used latitude followed by longitude. However, it was decided early on to switch the order for arrays in order to conform with GeoJSON.
The result is a bear trap that captures all unsuspecting users on their journey to full geolocation nirvana.
- Elasticsearch - The Definitive Guide:
- Foreword
- Preface
- Getting Started
- You Know, for Search…
- Installing and Running Elasticsearch
- Talking to Elasticsearch
- Document Oriented
- Finding Your Feet
- Indexing Employee Documents
- Retrieving a Document
- Search Lite
- Search with Query DSL
- More-Complicated Searches
- Full-Text Search
- Phrase Search
- Highlighting Our Searches
- Analytics
- Tutorial Conclusion
- Distributed Nature
- Next Steps
- Life Inside a Cluster
- Data In, Data Out
- What Is a Document?
- Document Metadata
- Indexing a Document
- Retrieving a Document
- Checking Whether a Document Exists
- Updating a Whole Document
- Creating a New Document
- Deleting a Document
- Dealing with Conflicts
- Optimistic Concurrency Control
- Partial Updates to Documents
- Retrieving Multiple Documents
- Cheaper in Bulk
- Distributed Document Store
- Searching—The Basic Tools
- Mapping and Analysis
- Full-Body Search
- Sorting and Relevance
- Distributed Search Execution
- Index Management
- Inside a Shard
- You Know, for Search…
- Search in Depth
- Structured Search
- Full-Text Search
- Multifield Search
- Proximity Matching
- Partial Matching
- Controlling Relevance
- Theory Behind Relevance Scoring
- Lucene’s Practical Scoring Function
- Query-Time Boosting
- Manipulating Relevance with Query Structure
- Not Quite Not
- Ignoring TF/IDF
- function_score Query
- Boosting by Popularity
- Boosting Filtered Subsets
- Random Scoring
- The Closer, The Better
- Understanding the price Clause
- Scoring with Scripts
- Pluggable Similarity Algorithms
- Changing Similarities
- Relevance Tuning Is the Last 10%
- Dealing with Human Language
- Aggregations
- Geolocation
- Modeling Your Data
- Administration, Monitoring, and Deployment