Date nanoseconds field type

This data type is an addition to the date data type. However there is an important distinction between the two. The existing date data type stores dates in millisecond resolution. The date_nanos data type stores dates in nanosecond resolution, which limits its range of dates from roughly 1970 to 2262, as dates are still stored as a long representing nanoseconds since the epoch.

Queries on nanoseconds are internally converted to range queries on this long representation, and the result of aggregations and stored fields is converted back to a string depending on the date format that is associated with the field.

Date formats can be customised, but if no format is specified then it uses the default:

"strict_date_optional_time_nanos||epoch_millis"

For instance:

PUT my-index-000001
{
  "mappings": {
    "properties": {
      "date": {
        "type": "date_nanos"
      }
    }
  }
}
PUT my-index-000001/_bulk?refresh
{ "index" : { "_id" : "1" } }
{ "date": "2015-01-01" }
{ "index" : { "_id" : "2" } }
{ "date": "2015-01-01T12:10:30.123456789Z" }
{ "index" : { "_id" : "3" } }
{ "date": 1420070400000 }
GET my-index-000001/_search
{
  "sort": { "date": "asc"},
  "runtime_mappings": {
    "date_has_nanos": {
      "type": "boolean",
      "script": "emit(doc['date'].value.nano != 0)"
    }
  },
  "fields": [
    {
      "field": "date",
      "format": "strict_date_optional_time_nanos"
    },
    {
      "field": "date_has_nanos"
    }
  ]
}

1. The date field uses the default format.
2. This document uses a plain date.
3. This document includes a time.
4. This document uses milliseconds-since-the-epoch.
5. Note that the sort values that are returned are all in nanoseconds-since-the-epoch.
6. Use .nano in scripts to return the nanosecond component of the date.
7. You can specify the format when fetching data using the fields parameter. Use strict_date_optional_time_nanos or you’ll get a rounded result.

You can also specify multiple date formats separated by ||. The same mapping parameters than with the date field can be used.

Aggregations are still on millisecond resolution, even when using a date_nanos field. This limitation also affects transforms.

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Synthetic source may sort date_nanos field values. For example:

PUT idx
{
  "settings": {
    "index": {
      "mapping": {
        "source": {
          "mode": "synthetic"
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "date": { "type": "date_nanos" }
    }
  }
}
PUT idx/_doc/1
{
  "date": ["2015-01-01T12:10:30.000Z", "2014-01-01T12:10:30.000Z"]
}

Will become:

{
  "date": ["2014-01-01T12:10:30.000Z", "2015-01-01T12:10:30.000Z"]
}