2013-11-24 06:13:08 -05:00
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[[search-aggregations-metrics-min-aggregation]]
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2014-05-12 19:35:58 -04:00
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=== Min Aggregation
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2013-11-24 06:13:08 -05:00
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2017-01-20 15:26:53 -05:00
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A `single-value` metrics aggregation that keeps track and returns the minimum
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value among numeric values extracted from the aggregated documents. These
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values can be extracted either from specific numeric fields in the documents,
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or be generated by a provided script.
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2016-11-28 04:34:43 -05:00
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NOTE: The `min` and `max` aggregation operate on the `double` representation of
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the data. As a consequence, the result may be approximate when running on longs
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whose absolute value is greater than +2^53+.
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2014-01-17 11:20:05 -05:00
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Computing the min price value across all documents:
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2013-11-24 06:13:08 -05:00
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[source,js]
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--------------------------------------------------
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POST /sales/_search?size=0
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{
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"aggs" : {
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"min_price" : { "min" : { "field" : "price" } }
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}
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}
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--------------------------------------------------
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// CONSOLE
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// TEST[setup:sales]
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Response:
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[source,js]
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--------------------------------------------------
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{
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...
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"aggregations": {
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"min_price": {
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"value": 10.0
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}
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}
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}
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--------------------------------------------------
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// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
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2017-01-20 15:26:53 -05:00
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As can be seen, the name of the aggregation (`min_price` above) also serves as
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the key by which the aggregation result can be retrieved from the returned
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response.
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==== Script
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2017-01-20 15:26:53 -05:00
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The `min` aggregation can also calculate the maximum of a script. The example
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below computes the minimum price:
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[source,js]
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--------------------------------------------------
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POST /sales/_search
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{
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"aggs" : {
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"min_price" : {
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"min" : {
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"script" : {
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"source" : "doc.price.value"
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}
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}
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}
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2013-11-24 06:13:08 -05:00
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}
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}
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--------------------------------------------------
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2017-01-20 15:26:53 -05:00
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// CONSOLE
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// TEST[setup:sales]
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2017-01-20 15:26:53 -05:00
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This will use the <<modules-scripting-painless, Painless>> scripting language
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and no script parameters. To use a stored script use the following syntax:
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[source,js]
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--------------------------------------------------
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POST /sales/_search
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2015-05-12 05:37:22 -04:00
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{
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"aggs" : {
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"min_price" : {
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"min" : {
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"script" : {
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"id": "my_script",
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"params": {
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"field": "price"
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}
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}
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}
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}
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}
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}
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--------------------------------------------------
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// CONSOLE
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// TEST[setup:sales,stored_example_script]
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==== Value Script
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2017-01-20 15:26:53 -05:00
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Let's say that the prices of the documents in our index are in USD, but we
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would like to compute the min in EURO (and for the sake of this example, let's
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say the conversion rate is 1.2). We can use a value script to apply the
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conversion rate to every value before it is aggregated:
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2013-11-24 06:13:08 -05:00
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[source,js]
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--------------------------------------------------
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POST /sales/_search
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{
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"aggs" : {
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"min_price_in_euros" : {
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"min" : {
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"field" : "price",
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"script" : {
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"source" : "_value * params.conversion_rate",
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"params" : {
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"conversion_rate" : 1.2
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}
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2013-11-24 06:13:08 -05:00
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}
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}
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}
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}
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}
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2014-08-27 22:56:59 -04:00
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--------------------------------------------------
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2017-01-20 15:26:53 -05:00
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// CONSOLE
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// TEST[setup:sales]
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2015-05-07 10:46:40 -04:00
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==== Missing value
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2017-01-20 15:26:53 -05:00
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The `missing` parameter defines how documents that are missing a value should
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be treated. By default they will be ignored but it is also possible to treat
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them as if they had a value.
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2015-05-07 10:46:40 -04:00
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[source,js]
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--------------------------------------------------
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2017-01-20 15:26:53 -05:00
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POST /sales/_search
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2015-05-07 10:46:40 -04:00
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{
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"aggs" : {
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"grade_min" : {
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"min" : {
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"field" : "grade",
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"missing": 10 <1>
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}
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}
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}
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}
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--------------------------------------------------
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2017-01-20 15:26:53 -05:00
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// CONSOLE
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// TEST[setup:sales]
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2015-05-07 10:46:40 -04:00
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<1> Documents without a value in the `grade` field will fall into the same
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bucket as documents that have the value `10`.
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