[[search-aggregations-bucket-autodatehistogram-aggregation]]
=== Auto-interval Date Histogram Aggregation

A multi-bucket aggregation similar to the <<search-aggregations-bucket-datehistogram-aggregation>> except 
instead of providing an interval to use as the width of each bucket, a target number of buckets is provided
indicating the number of buckets needed and the interval of the buckets is automatically chosen to best achieve
that target. The number of buckets returned will always be less than or equal to this target number.

The buckets field is optional, and will default to 10 buckets if not specified.

Requesting a target of 10 buckets.

[source,js]
--------------------------------------------------
POST /sales/_search?size=0
{
    "aggs" : {
        "sales_over_time" : {
            "auto_date_histogram" : {
                "field" : "date",
                "buckets" : 10
            }
        }
    }
}
--------------------------------------------------
// CONSOLE
// TEST[setup:sales]

==== Keys

Internally, a date is represented as a 64 bit number representing a timestamp
in milliseconds-since-the-epoch. These timestamps are returned as the bucket
++key++s. The `key_as_string` is the same timestamp converted to a formatted
date string using the format specified with the `format` parameter:

TIP: If no `format` is specified, then it will use the first date
<<mapping-date-format,format>> specified in the field mapping.

[source,js]
--------------------------------------------------
POST /sales/_search?size=0
{
    "aggs" : {
        "sales_over_time" : {
            "auto_date_histogram" : {
                "field" : "date",
                "buckets" : 5,
                "format" : "yyyy-MM-dd" <1>
            }
        }
    }
}
--------------------------------------------------
// CONSOLE
// TEST[setup:sales]

<1> Supports expressive date <<date-format-pattern,format pattern>>

Response:

[source,js]
--------------------------------------------------
{
    ...
    "aggregations": {
        "sales_over_time": {
            "buckets": [
                {
                    "key_as_string": "2015-01-01",
                    "key": 1420070400000,
                    "doc_count": 3
                },
                {
                    "key_as_string": "2015-02-01",
                    "key": 1422748800000,
                    "doc_count": 2
                },
                {
                    "key_as_string": "2015-03-01",
                    "key": 1425168000000,
                    "doc_count": 2
                }
            ],
            "interval": "1M"
        }
    }
}
--------------------------------------------------
// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]

=== Intervals

The interval of the returned buckets is selected based on the data collected by the 
aggregation so that the number of buckets returned is less than or equal to the number 
requested. The possible intervals returned are:

[horizontal]
seconds::      In multiples of 1, 5, 10 and 30
minutes::      In multiples of 1, 5, 10 and 30
hours::        In multiples of 1, 3 and 12
days::         In multiples of 1, and 7
months::       In multiples of 1, and 3
years::        In multiples of 1, 5, 10, 20, 50 and 100

In the worst case, where the number of daily buckets are too many for the requested 
number of buckets, the number of buckets returned will be 1/7th of the number of 
buckets requested.

==== Time Zone

Date-times are stored in Elasticsearch in UTC.  By default, all bucketing and
rounding is also done in UTC. The `time_zone` parameter can be used to indicate
that bucketing should use a different time zone.

Time zones may either be specified as an ISO 8601 UTC offset (e.g. `+01:00` or
`-08:00`)  or as a timezone id, an identifier used in the TZ database like
`America/Los_Angeles`.

Consider the following example:

[source,js]
---------------------------------
PUT my_index/log/1?refresh
{
  "date": "2015-10-01T00:30:00Z"
}

PUT my_index/log/2?refresh
{
  "date": "2015-10-01T01:30:00Z"
}

PUT my_index/log/3?refresh
{
  "date": "2015-10-01T02:30:00Z"
}

GET my_index/_search?size=0
{
  "aggs": {
    "by_day": {
      "auto_date_histogram": {
        "field":     "date",
        "buckets" : 3
      }
    }
  }
}
---------------------------------
// CONSOLE

UTC is used if no time zone is specified, three 1-hour buckets are returned 
starting at midnight UTC on 1 October 2015:

[source,js]
---------------------------------
{
  ...
  "aggregations": {
    "by_day": {
      "buckets": [
        {
          "key_as_string": "2015-10-01T00:00:00.000Z",
          "key": 1443657600000,
          "doc_count": 1
        },
        {
          "key_as_string": "2015-10-01T01:00:00.000Z",
          "key": 1443661200000,
          "doc_count": 1
        },
        {
          "key_as_string": "2015-10-01T02:00:00.000Z",
          "key": 1443664800000,
          "doc_count": 1
        }
      ],
      "interval": "1h"
    }
  }
}
---------------------------------
// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]

If a `time_zone` of `-01:00` is specified, then midnight starts at one hour before
midnight UTC:

[source,js]
---------------------------------
GET my_index/_search?size=0
{
  "aggs": {
    "by_day": {
      "auto_date_histogram": {
        "field":     "date",
        "buckets" : 3,
        "time_zone": "-01:00"
      }
    }
  }
}
---------------------------------
// CONSOLE
// TEST[continued]


Now three 1-hour buckets are still returned but the first bucket starts at 
11:00pm on 30 September 2015 since that is the local time for the bucket in 
the specified time zone.

[source,js]
---------------------------------
{
  ...
  "aggregations": {
    "by_day": {
      "buckets": [
        {
          "key_as_string": "2015-09-30T23:00:00.000-01:00", <1>
          "key": 1443657600000,
          "doc_count": 1
        },
        {
          "key_as_string": "2015-10-01T00:00:00.000-01:00",
          "key": 1443661200000,
          "doc_count": 1
        },
        {
          "key_as_string": "2015-10-01T01:00:00.000-01:00",
          "key": 1443664800000,
          "doc_count": 1
        }
      ],
      "interval": "1h"
    }
  }
}
---------------------------------
// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]

<1> The `key_as_string` value represents midnight on each day
    in the specified time zone.

WARNING: When using time zones that follow DST (daylight savings time) changes,
buckets close to the moment when those changes happen can have slightly different
sizes than neighbouring buckets.
For example, consider a DST start in the `CET` time zone: on 27 March 2016 at 2am,
clocks were turned forward 1 hour to 3am local time. If the result of the aggregation 
was daily buckets, the bucket covering that day will only hold data for 23 hours 
instead of the usual 24 hours for other buckets. The same is true for shorter intervals 
like e.g. 12h. Here, we will have only a 11h bucket on the morning of 27 March when the 
DST shift happens.

==== Scripts

Like with the normal <<search-aggregations-bucket-datehistogram-aggregation, `date_histogram`>>, both document level 
scripts and value level scripts are supported. This aggregation does not however, support the `min_doc_count`, 
`extended_bounds` and `order` parameters.  

==== Missing value

The `missing` parameter defines how documents that are missing a value should be treated.
By default they will be ignored but it is also possible to treat them as if they
had a value.

[source,js]
--------------------------------------------------
POST /sales/_search?size=0
{
    "aggs" : {
        "sale_date" : {
             "auto_date_histogram" : {
                 "field" : "date",
                 "buckets": 10,
                 "missing": "2000/01/01" <1>
             }
         }
    }
}
--------------------------------------------------
// CONSOLE
// TEST[setup:sales]

<1> Documents without a value in the `publish_date` field will fall into the same bucket as documents that have the value `2000-01-01`.

