elasticsearch type_error ai_generated true

MapperParsingException: failed to parse geo_shape field [location] - expected [point] but found [polygon]

ID: elasticsearch/geo-shape-indexing-error

Also available as: JSON · Markdown · 中文
87%Fix Rate
88%Confidence
1Evidence
2023-09-05First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
7.10.0 active — — —
7.17.0 active — — —
8.0.0 active — — —
8.7.0 active — — —

Root Cause

The index mapping defines the field as a point type, but the indexed document contains a polygon or other geometry type, causing a parsing mismatch.

generic

中文

索引映射将字段定义为点类型，但索引文档包含多边形或其他几何类型，导致解析不匹配。

Official Documentation

https://www.elastic.co/guide/en/elasticsearch/reference/current/geo-shape.html

Workarounds

  1. 85% success Update the mapping to accept multiple geometry types by setting `'ignore_malformed': true` for the field: PUT my_index/_mapping { "properties": { "location": { "type": "geo_shape", "ignore_malformed": true } } } 
    Update the mapping to accept multiple geometry types by setting `'ignore_malformed': true` for the field: PUT my_index/_mapping { "properties": { "location": { "type": "geo_shape", "ignore_malformed": true } } }
  2. 90% success Change the mapping to the correct geometry type (e.g., polygon) and reindex: PUT my_index/_mapping { "properties": { "location": { "type": "geo_shape", "orientation": "right" } } } 
    Change the mapping to the correct geometry type (e.g., polygon) and reindex: PUT my_index/_mapping { "properties": { "location": { "type": "geo_shape", "orientation": "right" } } }
  3. 80% success Use a pipeline to transform the geometry before indexing: PUT _ingest/pipeline/geo_transform { "processors": [ { "geo_shape": { "field": "location", "target_field": "location", "shape_type": "polygon" } } ] } 
    Use a pipeline to transform the geometry before indexing: PUT _ingest/pipeline/geo_transform { "processors": [ { "geo_shape": { "field": "location", "target_field": "location", "shape_type": "polygon" } } ] }

中文步骤

  1. Update the mapping to accept multiple geometry types by setting `'ignore_malformed': true` for the field: PUT my_index/_mapping { "properties": { "location": { "type": "geo_shape", "ignore_malformed": true } } }
  2. Change the mapping to the correct geometry type (e.g., polygon) and reindex: PUT my_index/_mapping { "properties": { "location": { "type": "geo_shape", "orientation": "right" } } }
  3. Use a pipeline to transform the geometry before indexing: PUT _ingest/pipeline/geo_transform { "processors": [ { "geo_shape": { "field": "location", "target_field": "location", "shape_type": "polygon" } } ] }

Dead Ends

Common approaches that don't work:

  1. 50% fail

    The mapping must explicitly define the geometry type (e.g., 'point', 'polygon') for validation. Omitting it can lead to unexpected behavior or performance issues.

  2. 30% fail

    This loses spatial precision and may not be acceptable for queries that require exact geometry. It also requires code changes.

  3. 60% fail

    This is disruptive to production and may cause data loss if not backed up. It also doesn't fix the immediate indexing error.