| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127 | [[search-aggregations-metrics-stats-aggregation]]=== Stats AggregationA `multi-value` metrics aggregation that computes stats over numeric values extracted from the aggregated documents. These values can be extracted either from specific numeric fields in the documents, or be generated by a provided script.The stats that are returned consist of: `min`, `max`, `sum`, `count` and `avg`.Assuming the data consists of documents representing exams grades (between 0 and 100) of students[source,js]--------------------------------------------------{    "aggs" : {        "grades_stats" : { "stats" : { "field" : "grade" } }    }}--------------------------------------------------The above aggregation computes the grades statistics over all documents. The aggregation type is `stats` and the `field` setting defines the numeric field of the documents the stats will be computed on. The above will return the following:[source,js]--------------------------------------------------{    ...    "aggregations": {        "grades_stats": {            "count": 6,            "min": 60,            "max": 98,            "avg": 78.5,            "sum": 471        }    }}--------------------------------------------------The name of the aggregation (`grades_stats` above) also serves as the key by which the aggregation result can be retrieved from the returned response.==== ScriptComputing the grades stats based on a script:[source,js]--------------------------------------------------{    ...,    "aggs" : {        "grades_stats" : { "stats" : { "script" : "doc['grade'].value" } }    }}--------------------------------------------------This will interpret the `script` parameter as an `inline` script with the default script language and no script parameters. To use a file script use the following syntax:[source,js]--------------------------------------------------{    ...,    "aggs" : {        "grades_stats" : {            "stats" : {                 "script" : {                    "file": "my_script",                    "params" : {                        "field" : "grade"                    }                }            }        }    }}--------------------------------------------------TIP: for indexed scripts replace the `file` parameter with an `id` parameter.===== Value ScriptIt turned out that the exam was way above the level of the students and a grade correction needs to be applied. We can use a value script to get the new stats:[source,js]--------------------------------------------------{    "aggs" : {        ...        "aggs" : {            "grades_stats" : {                "stats" : {                    "field" : "grade",                    "script" :                         "inline": "_value * correction",                        "params" : {                            "correction" : 1.2                        }                    }                }            }        }    }}--------------------------------------------------==== Missing valueThe `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 theyhad a value.[source,js]--------------------------------------------------{    "aggs" : {        "grades_stats" : {            "stats" : {                "field" : "grade",                "missing": 0 <1>            }        }    }}--------------------------------------------------<1> Documents without a value in the `grade` field will fall into the same bucket as documents that have the value `0`.
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