2019-10-01 10:58:44 -04:00
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[[search-aggregations-bucket-range-field-note]]
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=== Subtleties of bucketing range fields
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==== Documents are counted for each bucket they land in
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Since a range represents multiple values, running a bucket aggregation over a
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range field can result in the same document landing in multiple buckets. This
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can lead to surprising behavior, such as the sum of bucket counts being higher
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than the number of matched documents. For example, consider the following
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index:
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[source, console]
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--------------------------------------------------
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PUT range_index
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{
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"settings": {
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"number_of_shards": 2
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},
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"mappings": {
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"properties": {
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"expected_attendees": {
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"type": "integer_range"
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},
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"time_frame": {
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"type": "date_range",
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"format": "yyyy-MM-dd||epoch_millis"
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}
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}
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}
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}
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PUT range_index/_doc/1?refresh
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{
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"expected_attendees" : {
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"gte" : 10,
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"lte" : 20
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},
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"time_frame" : {
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"gte" : "2019-10-28",
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"lte" : "2019-11-04"
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}
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}
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--------------------------------------------------
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// TESTSETUP
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The range is wider than the interval in the following aggregation, and thus the
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document will land in multiple buckets.
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[source, console]
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--------------------------------------------------
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POST /range_index/_search?size=0
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{
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2020-07-20 15:59:00 -04:00
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"aggs": {
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"range_histo": {
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"histogram": {
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"field": "expected_attendees",
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"interval": 5
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}
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2019-10-01 10:58:44 -04:00
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}
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2020-07-20 15:59:00 -04:00
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}
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2019-10-01 10:58:44 -04:00
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}
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--------------------------------------------------
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Since the interval is `5` (and the offset is `0` by default), we expect buckets `10`,
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`15`, and `20`. Our range document will fall in all three of these buckets.
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[source, console-result]
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--------------------------------------------------
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{
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...
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"aggregations" : {
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"range_histo" : {
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"buckets" : [
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{
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"key" : 10.0,
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"doc_count" : 1
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},
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{
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"key" : 15.0,
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"doc_count" : 1
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},
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{
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"key" : 20.0,
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"doc_count" : 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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--------------------------------------------------
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// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
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A document cannot exist partially in a bucket; For example, the above document
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cannot count as one-third in each of the above three buckets. In this example,
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since the document's range landed in multiple buckets, the full value of that
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document would also be counted in any sub-aggregations for each bucket as well.
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==== Query bounds are not aggregation filters
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Another unexpected behavior can arise when a query is used to filter on the
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field being aggregated. In this case, a document could match the query but
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still have one or both of the endpoints of the range outside the query.
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Consider the following aggregation on the above document:
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[source, console]
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--------------------------------------------------
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POST /range_index/_search?size=0
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{
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2020-07-20 15:59:00 -04:00
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"query": {
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"range": {
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"time_frame": {
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"gte": "2019-11-01",
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"format": "yyyy-MM-dd"
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2019-10-01 10:58:44 -04:00
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}
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}
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2020-07-20 15:59:00 -04:00
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},
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"aggs": {
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"november_data": {
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"date_histogram": {
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"field": "time_frame",
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"calendar_interval": "day",
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"format": "yyyy-MM-dd"
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}
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}
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}
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2019-10-01 10:58:44 -04:00
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}
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--------------------------------------------------
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Even though the query only considers days in November, the aggregation
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generates 8 buckets (4 in October, 4 in November) because the aggregation is
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calculated over the ranges of all matching documents.
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[source, console-result]
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--------------------------------------------------
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{
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...
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"aggregations" : {
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"november_data" : {
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"buckets" : [
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2019-10-04 17:21:17 -04:00
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{
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"key_as_string" : "2019-10-28",
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2019-10-01 10:58:44 -04:00
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"key" : 1572220800000,
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"doc_count" : 1
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},
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{
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2019-10-04 17:21:17 -04:00
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"key_as_string" : "2019-10-29",
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2019-10-01 10:58:44 -04:00
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"key" : 1572307200000,
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"doc_count" : 1
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},
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{
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2019-10-04 17:21:17 -04:00
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"key_as_string" : "2019-10-30",
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2019-10-01 10:58:44 -04:00
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"key" : 1572393600000,
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"doc_count" : 1
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},
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{
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2019-10-04 17:21:17 -04:00
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"key_as_string" : "2019-10-31",
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2019-10-01 10:58:44 -04:00
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"key" : 1572480000000,
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"doc_count" : 1
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},
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{
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2019-10-04 17:21:17 -04:00
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"key_as_string" : "2019-11-01",
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2019-10-01 10:58:44 -04:00
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"key" : 1572566400000,
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"doc_count" : 1
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},
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{
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2019-10-04 17:21:17 -04:00
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"key_as_string" : "2019-11-02",
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2019-10-01 10:58:44 -04:00
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"key" : 1572652800000,
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"doc_count" : 1
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},
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{
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2019-10-04 17:21:17 -04:00
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"key_as_string" : "2019-11-03",
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2019-10-01 10:58:44 -04:00
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"key" : 1572739200000,
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"doc_count" : 1
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},
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{
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2019-10-04 17:21:17 -04:00
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"key_as_string" : "2019-11-04",
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2019-10-01 10:58:44 -04:00
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"key" : 1572825600000,
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"doc_count" : 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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--------------------------------------------------
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// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
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Depending on the use case, a `CONTAINS` query could limit the documents to only
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those that fall entirely in the queried range. In this example, the one
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document would not be included and the aggregation would be empty. Filtering
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the buckets after the aggregation is also an option, for use cases where the
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document should be counted but the out of bounds data can be safely ignored.
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