mirror of https://github.com/apache/druid.git
193 lines
6.5 KiB
Markdown
193 lines
6.5 KiB
Markdown
---
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id: searchquery
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title: "Search queries"
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sidebar_label: "Search"
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---
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~ Licensed to the Apache Software Foundation (ASF) under one
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~ or more contributor license agreements. See the NOTICE file
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> Apache Druid supports two query languages: [Druid SQL](sql.md) and [native queries](querying.md).
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> This document describes a query
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> type that is only available in the native language.
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A search query returns dimension values that match the search specification.
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```json
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{
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"queryType": "search",
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"dataSource": "sample_datasource",
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"granularity": "day",
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"searchDimensions": [
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"dim1",
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"dim2"
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],
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"query": {
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"type": "insensitive_contains",
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"value": "Ke"
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},
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"sort" : {
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"type": "lexicographic"
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},
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"intervals": [
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"2013-01-01T00:00:00.000/2013-01-03T00:00:00.000"
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]
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}
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```
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There are several main parts to a search query:
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|property|description|required?|
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|--------|-----------|---------|
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|queryType|This String should always be "search"; this is the first thing Apache Druid looks at to figure out how to interpret the query.|yes|
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|dataSource|A String or Object defining the data source to query, very similar to a table in a relational database. See [DataSource](../querying/datasource.md) for more information.|yes|
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|granularity|Defines the granularity of the query. See [Granularities](../querying/granularities.md).|no (default to `all`)|
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|filter|See [Filters](../querying/filters.md).|no|
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|limit| Defines the maximum number per Historical process (parsed as int) of search results to return. |no (default to 1000)|
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|intervals|A JSON Object representing ISO-8601 Intervals. This defines the time ranges to run the query over.|yes|
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|searchDimensions|The dimensions to run the search over. Excluding this means the search is run over all dimensions.|no|
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|query|See [SearchQuerySpec](#searchqueryspec).|yes|
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|sort|An object specifying how the results of the search should be sorted.<br/>Possible types are "lexicographic" (the default sort), "alphanumeric", "strlen", and "numeric".<br/>See [Sorting Orders](./sorting-orders.md) for more details.|no|
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|context|See [Context](../querying/query-context.md)|no|
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The format of the result is:
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```json
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[
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{
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"timestamp": "2013-01-01T00:00:00.000Z",
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"result": [
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{
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"dimension": "dim1",
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"value": "Ke$ha",
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"count": 3
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},
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{
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"dimension": "dim2",
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"value": "Ke$haForPresident",
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"count": 1
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}
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]
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},
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{
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"timestamp": "2013-01-02T00:00:00.000Z",
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"result": [
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{
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"dimension": "dim1",
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"value": "SomethingThatContainsKe",
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"count": 1
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},
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{
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"dimension": "dim2",
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"value": "SomethingElseThatContainsKe",
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"count": 2
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}
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]
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}
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]
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```
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### Implementation details
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#### Strategies
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Search queries can be executed using two different strategies. The default strategy is determined by the
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"druid.query.search.searchStrategy" runtime property on the Broker. This can be overridden using "searchStrategy" in the
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query context. If neither the context field nor the property is set, the "useIndexes" strategy will be used.
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- "useIndexes" strategy, the default, first categorizes search dimensions into two groups according to their support for
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bitmap indexes. And then, it applies index-only and cursor-based execution plans to the group of dimensions supporting
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bitmaps and others, respectively. The index-only plan uses only indexes for search query processing. For each dimension,
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it reads the bitmap index for each dimension value, evaluates the search predicate, and finally checks the time interval
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and filter predicates. For the cursor-based execution plan, please refer to the "cursorOnly" strategy. The index-only
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plan shows low performance for the search dimensions of large cardinality which means most values of search dimensions
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are unique.
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- "cursorOnly" strategy generates a cursor-based execution plan. This plan creates a cursor which reads a row from a
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queryableIndexSegment, and then evaluates search predicates. If some filters support bitmap indexes, the cursor can read
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only the rows which satisfy those filters, thereby saving I/O cost. However, it might be slow with filters of low selectivity.
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- "auto" strategy uses a cost-based planner for choosing an optimal search strategy. It estimates the cost of index-only
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and cursor-based execution plans, and chooses the optimal one. Currently, it is not enabled by default due to the overhead
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of cost estimation.
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## Server configuration
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The following runtime properties apply:
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|Property|Description|Default|
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|--------|-----------|-------|
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|`druid.query.search.searchStrategy`|Default search query strategy.|useIndexes|
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## Query context
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The following query context parameters apply:
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|Property|Description|
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|--------|-----------|
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|`searchStrategy`|Overrides the value of `druid.query.search.searchStrategy` for this query.|
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## SearchQuerySpec
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### `insensitive_contains`
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If any part of a dimension value contains the value specified in this search query spec, regardless of case, a "match" occurs. The grammar is:
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```json
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{
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"type" : "insensitive_contains",
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"value" : "some_value"
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}
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```
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### `fragment`
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If any part of a dimension value contains all of the values specified in this search query spec, regardless of case by default, a "match" occurs. The grammar is:
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```json
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{
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"type" : "fragment",
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"case_sensitive" : false,
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"values" : ["fragment1", "fragment2"]
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}
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```
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### `contains`
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If any part of a dimension value contains the value specified in this search query spec, a "match" occurs. The grammar is:
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```json
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{
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"type" : "contains",
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"case_sensitive" : true,
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"value" : "some_value"
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}
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```
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### `regex`
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If any part of a dimension value contains the pattern specified in this search query spec, a "match" occurs. The grammar is:
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```json
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{
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"type" : "regex",
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"pattern" : "some_pattern"
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}
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```
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