elasticsearch data_error ai_generated true

ElasticsearchParseException: Pipeline [my_pipeline] processor [set] requires field [user.email] but it is not defined in the document

ID: elasticsearch/missing-required-field-in-ingest-pipeline

Also available as: JSON · Markdown · 中文
90%Fix Rate
88%Confidence
1Evidence
2023-11-20First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
Elasticsearch 7.10.0 active — — —
Elasticsearch 8.12.0 active — — —
Elasticsearch 8.14.0 active — — —

Root Cause

An ingest pipeline processor references a field that does not exist in the incoming document, causing the pipeline to fail.

generic

中文

摄取管道处理器引用了一个传入文档中不存在的字段，导致管道失败。

Official Documentation

https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#conditional-execution

Workarounds

  1. 88% success Modify the pipeline to handle missing fields using conditional logic. For example, update the pipeline definition with an `if` context: `{"set": {"field": "user.email", "value": "[email protected]", "if": "ctx.user?.email == null"}}` 
    Modify the pipeline to handle missing fields using conditional logic. For example, update the pipeline definition with an `if` context: `{"set": {"field": "user.email", "value": "[email protected]", "if": "ctx.user?.email == null"}}`
  2. 90% success Fix the source data before indexing by ensuring the required field is present. For example, in Logstash, add a mutate filter: `filter { mutate { add_field => { "[user][email]" => "${user_email}" } } }` if the field exists in the event. 
    Fix the source data before indexing by ensuring the required field is present. For example, in Logstash, add a mutate filter: `filter { mutate { add_field => { "[user][email]" => "${user_email}" } } }` if the field exists in the event.

中文步骤

  1. Modify the pipeline to handle missing fields using conditional logic. For example, update the pipeline definition with an `if` context: `{"set": {"field": "user.email", "value": "[email protected]", "if": "ctx.user?.email == null"}}`
  2. Fix the source data before indexing by ensuring the required field is present. For example, in Logstash, add a mutate filter: `filter { mutate { add_field => { "[user][email]" => "${user_email}" } } }` if the field exists in the event.

Dead Ends

Common approaches that don't work:

  1. 50% fail

    This may mask data quality issues and lead to incorrect processing if the field is truly required downstream; also the pipeline might still fail if other processors depend on the original field.

  2. 60% fail

    This bypasses data enrichment or transformation, potentially causing mapping errors or incorrect search results later.