162 lines
4.6 KiB
Plaintext
162 lines
4.6 KiB
Plaintext
[[search-aggregations-pipeline-bucket-script-aggregation]]
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=== Bucket Script Aggregation
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A parent pipeline aggregation which executes a script which can perform per bucket computations on specified metrics
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in the parent multi-bucket aggregation. The specified metric must be numeric and the script must return a numeric value.
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[[bucket-script-agg-syntax]]
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==== Syntax
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A `bucket_script` aggregation looks like this in isolation:
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[source,js]
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--------------------------------------------------
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{
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"bucket_script": {
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"buckets_path": {
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"my_var1": "the_sum", <1>
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"my_var2": "the_value_count"
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},
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"script": "params.my_var1 / params.my_var2"
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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<1> Here, `my_var1` is the name of the variable for this buckets path to use in the script, `the_sum` is the path to
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the metrics to use for that variable.
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[[bucket-script-params]]
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.`bucket_script` 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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|`script` |The script to run for this aggregation. The script can be inline, file or indexed. (see <<modules-scripting>>
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for more details) |Required |
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|`buckets_path` |A map of script variables and their associated path to the buckets we wish to use for the variable
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(see <<buckets-path-syntax>> for more 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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|===
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The following snippet calculates the ratio percentage of t-shirt sales compared to total sales each month:
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[source,console]
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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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"total_sales": {
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"sum": {
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"field": "price"
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}
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},
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"t-shirts": {
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"filter": {
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"term": {
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"type": "t-shirt"
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}
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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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"t-shirt-percentage": {
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"bucket_script": {
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"buckets_path": {
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"tShirtSales": "t-shirts>sales",
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"totalSales": "total_sales"
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},
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"script": "params.tShirtSales / params.totalSales * 100"
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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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// TEST[setup:sales]
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And the following may be the response:
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[source,console-result]
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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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"total_sales": {
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"value": 550.0
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},
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"t-shirts": {
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"doc_count": 1,
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"sales": {
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"value": 200.0
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}
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},
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"t-shirt-percentage": {
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"value": 36.36363636363637
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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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"total_sales": {
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"value": 60.0
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},
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"t-shirts": {
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"doc_count": 1,
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"sales": {
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"value": 10.0
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}
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},
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"t-shirt-percentage": {
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"value": 16.666666666666664
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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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"total_sales": {
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"value": 375.0
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},
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"t-shirts": {
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"doc_count": 1,
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"sales": {
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"value": 175.0
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}
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},
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"t-shirt-percentage": {
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"value": 46.666666666666664
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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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// 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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