129 lines
3.8 KiB
Plaintext
129 lines
3.8 KiB
Plaintext
[[search-aggregations-pipeline-extended-stats-bucket-aggregation]]
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=== Extended Stats Bucket Aggregation
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A sibling pipeline aggregation which calculates a variety of stats across all bucket of a specified metric in a sibling aggregation.
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The specified metric must be numeric and the sibling aggregation must be a multi-bucket aggregation.
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This aggregation provides a few more statistics (sum of squares, standard deviation, etc) compared to the `stats_bucket` aggregation.
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==== Syntax
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A `extended_stats_bucket` aggregation looks like this in isolation:
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[source,js]
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--------------------------------------------------
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{
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"extended_stats_bucket": {
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"buckets_path": "the_sum"
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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[[extended-stats-bucket-params]]
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.`extended_stats_bucket` Parameters
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[options="header"]
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|===
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|Parameter Name |Description |Required |Default Value
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|`buckets_path` |The path to the buckets we wish to calculate stats for (see <<buckets-path-syntax>> for more
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details) |Required |
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|`gap_policy` |The policy to apply when gaps are found in the data (see <<gap-policy>> for more
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details)|Optional | `skip`
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|`format` |format to apply to the output value of this aggregation |Optional | `null`
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|`sigma` |The number of standard deviations above/below the mean to display |Optional | 2
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|===
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The following snippet calculates the extended stats for monthly `sales` bucket:
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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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"size": 0,
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"aggs" : {
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"sales_per_month" : {
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"date_histogram" : {
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"field" : "date",
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"calendar_interval" : "month"
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},
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"aggs": {
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"sales": {
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"sum": {
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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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"stats_monthly_sales": {
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"extended_stats_bucket": {
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"buckets_path": "sales_per_month>sales" <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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// CONSOLE
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// TEST[setup:sales]
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<1> `bucket_paths` instructs this `extended_stats_bucket` aggregation that we want the calculate stats for the `sales` aggregation in the
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`sales_per_month` date histogram.
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And the following may be the response:
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[source,js]
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--------------------------------------------------
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{
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"took": 11,
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"timed_out": false,
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"_shards": ...,
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"hits": ...,
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"aggregations": {
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"sales_per_month": {
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"buckets": [
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{
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"key_as_string": "2015/01/01 00:00:00",
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"key": 1420070400000,
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"doc_count": 3,
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"sales": {
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"value": 550.0
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}
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},
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{
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"key_as_string": "2015/02/01 00:00:00",
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"key": 1422748800000,
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"doc_count": 2,
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"sales": {
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"value": 60.0
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}
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},
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{
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"key_as_string": "2015/03/01 00:00:00",
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"key": 1425168000000,
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"doc_count": 2,
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"sales": {
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"value": 375.0
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}
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}
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]
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},
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"stats_monthly_sales": {
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"count": 3,
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"min": 60.0,
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"max": 550.0,
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"avg": 328.3333333333333,
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"sum": 985.0,
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"sum_of_squares": 446725.0,
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"variance": 41105.55555555556,
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"std_deviation": 202.74505063146563,
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"std_deviation_bounds": {
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"upper": 733.8234345962646,
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"lower": -77.15676792959795
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}
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}
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}
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}
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--------------------------------------------------
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// TESTRESPONSE[s/"took": 11/"took": $body.took/]
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// TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
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// TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]
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