Solving the "Failed to Parse Date Field" Error in Elasticsearch

Elasticsearch is a powerful, open-source search and analytics engine that allows for complex queries on large volumes of data. However, like any sophisticated software, it can sometimes throw errors that might stump developers. One such common error is the "Failed to parse date field" error. This error can be particularly frustrating because date fields are often crucial for sorting, filtering, and aggregating data. In this post, we'll dive into what causes this error and how to fix it.

Understanding the Error

The "Failed to parse date field" error occurs when Elasticsearch encounters a date format it does not recognize or when the date format does not match the format specified in the mapping. Elasticsearch uses a strict date parsing system, which means that if the date format in your data doesn't exactly match the expected format, you will run into this error.

Common Causes

  1. Mismatched Date Formats: The most common cause is a mismatch between the date format in your data and the date format specified in your index mapping.
  2. Incorrect Date Format in Mapping: Sometimes, the date format specified in the mapping is incorrect or too restrictive.
  3. Invalid Dates: Occasionally, the data itself might contain invalid dates or date formats that Elasticsearch cannot parse.

How to Fix It

Adjusting the Date Format in Mapping

First, ensure that the date format in your index mapping matches the format of the dates in your data. Elasticsearch supports multiple date formats in a single field, which can be useful if your data contains dates in different formats.

Here's an example of how to specify multiple date formats in your mapping:

  "mappings": {
    "properties": {
      "date": { 
        "type": "date",
        "format": "yyyy-MM-dd||epoch_millis"

In this example, Elasticsearch will recognize dates in the "yyyy-MM-dd" format as well as dates expressed in milliseconds since the epoch.

Using the Date Processor in Ingest Pipelines

If modifying the mapping is not an option or if your data contains dates in various unpredictable formats, you can use an ingest pipeline with a date processor to parse dates dynamically.

Here's how you can define an ingest pipeline with a date processor:

  "description": "Parse dates from different formats",
  "processors": [
      "date": {
        "field": "date",
        "formats": ["yyyy-MM-dd", "dd-MM-yyyy"]

This pipeline attempts to parse dates from the specified formats and can be adjusted to include any format present in your data.

Fallback Strategies

In cases where dates might be in a completely unpredictable format or might sometimes be invalid, consider using a script to process your data before indexing or within an ingest pipeline to either fix the date formats or to set a default/fallback date.


The "Failed to parse date field" error in Elasticsearch is a common issue that usually stems from a mismatch between the expected and actual date formats. By ensuring your index mappings are correctly configured to handle the date formats in your data or by using ingest pipelines to dynamically process dates, you can resolve this error. Remember, handling dates correctly is crucial for taking full advantage of Elasticsearch's powerful search and analytics capabilities.