== Filtering Queries and Aggregations
A natural extension to aggregation scoping is filtering. Because the aggregation
operates in the context of the query scope, any filter applied to the query
will also apply to the aggregation.
[float="true"]
=== Filtered Query
If we want to find all cars over $10,000 and also calculate the average price
for those cars,((("filtering", "serch query results")))((("filtered query")))((("queries", "filtered"))) we can simply use a `filtered` query:
[source,js]
--------------------------------------------------
GET /cars/transactions/_search?search_type=count
{
"query" : {
"filtered": {
"filter": {
"range": {
"price": {
"gte": 10000
}
}
}
}
},
"aggs" : {
"single_avg_price": {
"avg" : { "field" : "price" }
}
}
}
--------------------------------------------------
// SENSE: 300_Aggregations/45_filtering.json
Fundamentally, using a `filtered` query is no different from using a `match`
query, as we discussed in the previous chapter. The query (which happens to include
a filter) returns a certain subset of documents, and the aggregation operates
on those documents.
[float="true"]
=== Filter Bucket
But what if you would like to filter just the aggregation results?((("filtering", "aggregation results, not the query")))((("aggregations", "filtering just aggregations"))) Imagine we
are building the search page for our car dealership. We want to display
search results according to what the user searches for. But we also want
to enrich the page by including the average price of cars (matching the search)
that were sold in the last month.
We can't use simple scoping here, since there are two different criteria. The
search results must match +ford+, but the aggregation results must match +ford+
AND +sold > now - 1M+.
To solve this problem, we can use a special bucket called `filter`.((("filter bucket")))((("buckets", "filter"))) You specify
a filter, and when documents match the filter's criteria, they are added to the
bucket.
Here is the resulting query:
[source,js]
--------------------------------------------------
GET /cars/transactions/_search?search_type=count
{
"query":{
"match": {
"make": "ford"
}
},
"aggs":{
"recent_sales": {
"filter": { <1>
"range": {
"sold": {
"from": "now-1M"
}
}
},
"aggs": {
"average_price":{
"avg": {
"field": "price" <2>
}
}
}
}
}
}
--------------------------------------------------
// SENSE: 300_Aggregations/45_filtering.json
<1> Using the `filter` bucket to apply a filter in addition to the `query` scope.
<2> This `avg` metric will therefore average only docs that are both +ford+ and sold in the last month.
Since the `filter` bucket operates like any other bucket, you are free to nest
other buckets and metrics inside. All nested components will "inherit" the filter.
This allows you to filter selective portions of the aggregation as required.
[float="true"]
=== Post Filter
So far, we have a way to filter both the search results and aggregations (a
`filtered` query), as well as filtering individual portions of the aggregation
(`filter` bucket).
You may be thinking to yourself, "hmm...is there a way to filter _just_ the search
results but not the aggregation?"((("filtering", "search results, not the aggregation")))((("post filter"))) The answer is to use a `post_filter`.
This is a top-level search-request element that accepts a filter. The filter is
applied _after_ the query has executed (hence the +post+ moniker: it runs
_post query_ execution). Because it operates after the query has executed,
it does not affect the query scope--and thus does not affect the aggregations
either.
We can use this behavior to apply additional filters to our search
criteria that don't affect things like categorical facets in your UI. Let's
design another search page for our car dealer. This page will allow the user
to search for a car and filter by color. Color choices are populated via an
aggregation:
[source,js]
--------------------------------------------------
GET /cars/transactions/_search?search_type=count
{
"query": {
"match": {
"make": "ford"
}
},
"post_filter": { <1>
"term" : {
"color" : "green"
}
},
"aggs" : {
"all_colors": {
"terms" : { "field" : "color" }
}
}
}
--------------------------------------------------
// SENSE: 300_Aggregations/45_filtering.json
<1> The `post_filter` element is a +top-level+ element and filters just the search hits.
The `query` portion is finding all +ford+ cars. We are then building a list of
colors with a `terms` aggregation. Because aggregations operate in the query
scope, the list of colors will correspond with the colors that Ford cars are
painted.
Finally, the `post_filter` will filter the search results to show only green
+ford+ cars. This happens _after_ the query is executed, so the aggregations
are unaffected.
This is often important for coherent UIs. Imagine that a user clicks a category in
your UI (for example, green). The expectation is that the search results are filtered,
but _not_ the UI options. If you applied a `filtered` query, the UI would
instantly transform to show _only_ +green+ as an option--not what the user wants!
[WARNING]
.Performance consideration
====
Use a `post_filter` _only_ if you need to differentially filter search results
and aggregations. ((("post filter", "performance and")))Sometimes people will use `post_filter` for regular searches.
Don't do this! The nature of the `post_filter` means it runs _after_ the query,
so any performance benefit of filtering (such as caches) is lost completely.
The `post_filter` should be used only in combination with aggregations, and only
when you need differential filtering.
====
[float="true"]
=== Recap
Choosing the appropriate type of filtering--search hits, aggregations, or
both--often boils down to how you want your user interface to behave. Choose
the appropriate filter (or combinations) depending on how you want to display
results to your user.
- A `filtered` query affects both search results and aggregations.
- A `filter` bucket affects just aggregations.
- A `post_filter` affects just search results.
- Introduction
- 入门
- 是什么
- 安装
- API
- 文档
- 索引
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- 聚合
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- Conclusion
- Language intro
- Intro
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- Conclusion
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- Intro
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- Token normalization
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- Unicode world
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- Intro
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- Intro
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- Intro
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- concepts buckets
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- add metric
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- approx intro
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- percentiles
- sigterms intro
- sigterms
- fielddata
- analyzed vs not
- 地理坐标点
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- 嵌套
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- Parent Child
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- Kagillion shards
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- Multiple indices
- Index per timeframe
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- Scale is not infinite
- Cluster Admin
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- Health
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- Deployment
- hardware
- other
- config
- dont touch
- heap
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- conclusion
- cluster settings
- Post Deployment
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- conclusion