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* Refactor metric aggregation section Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Update _query-dsl/aggregations/metric/matrix-stats.md Co-authored-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> * Update _query-dsl/aggregations/metric/extended-stats.md Co-authored-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> --------- Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> Co-authored-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com>
60 lines
1.3 KiB
Markdown
60 lines
1.3 KiB
Markdown
---
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layout: default
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title: Date histogram
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parent: Bucket aggregations
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grand_parent: Aggregations
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nav_order: 20
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---
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# Date histogram aggregations
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The `date_histogram` aggregation uses [date math]({{site.url}}{{site.baseurl}}/opensearch/supported-field-types/date/#date-math) to generate histograms for time-series data.
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For example, you can find how many hits your website gets per month:
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```json
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GET opensearch_dashboards_sample_data_logs/_search
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{
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"size": 0,
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"aggs": {
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"logs_per_month": {
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"date_histogram": {
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"field": "@timestamp",
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"interval": "month"
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}
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}
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}
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}
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```
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{% include copy-curl.html %}
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#### Example response
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```json
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...
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"aggregations" : {
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"logs_per_month" : {
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"buckets" : [
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{
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"key_as_string" : "2020-10-01T00:00:00.000Z",
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"key" : 1601510400000,
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"doc_count" : 1635
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},
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{
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"key_as_string" : "2020-11-01T00:00:00.000Z",
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"key" : 1604188800000,
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"doc_count" : 6844
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},
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{
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"key_as_string" : "2020-12-01T00:00:00.000Z",
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"key" : 1606780800000,
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"doc_count" : 5595
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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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The response has three months worth of logs. If you graph these values, you can see the peak and valleys of the request traffic to your website month over month.
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