* Refresh query docs. Larger changes: - New doc: querying/datasource.md describes the various kinds of datasources you can use, and has examples for both SQL and native. - New doc: querying/query-execution.md describes how native queries are executed at a high level. It doesn't go into the details of specific query engines or how queries run at a per-segment level. But I think it would be good to add or link that content here in the future. - Refreshed doc: querying/sql.md updated to refer to joins, reformatted a bit, added a new "Query translation" section that explains how queries are translated from SQL to native, and removed configuration details (moved to configuration/index.md). - Refreshed doc: querying/joins.md updated to refer to join datasources. Smaller changes: - Add helpful banners to the top of query documentation pages telling people whether a given page describes SQL, native, or both. - Add SQL metrics to operations/metrics.md. - Add some color and cross-links in various places. - Add native query component docs to the sidebar, and renamed them so they look nicer. - Remove Select query from the sidebar. - Fix Broker SQL configs in configuration/index.md. Remove them from querying/sql.md. - Combined querying/searchquery.md and querying/searchqueryspec.md. * Updates. * Fix numbering. * Fix glitches. * Add new words to spellcheck file. * Assorted changes. * Further adjustments. * Add missing punctuation.
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id | title | sidebar_label |
---|---|---|
searchquery | Search queries | Search |
Apache Druid supports two query languages: Druid SQL and native queries. This document describes a query type that is only available in the native language.
A search query returns dimension values that match the search specification.
{
"queryType": "search",
"dataSource": "sample_datasource",
"granularity": "day",
"searchDimensions": [
"dim1",
"dim2"
],
"query": {
"type": "insensitive_contains",
"value": "Ke"
},
"sort" : {
"type": "lexicographic"
},
"intervals": [
"2013-01-01T00:00:00.000/2013-01-03T00:00:00.000"
]
}
There are several main parts to a search query:
property | description | required? |
---|---|---|
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 |
dataSource | A String or Object defining the data source to query, very similar to a table in a relational database. See DataSource for more information. | yes |
granularity | Defines the granularity of the query. See Granularities. | yes |
filter | See Filters. | no |
limit | Defines the maximum number per Historical process (parsed as int) of search results to return. | no (default to 1000) |
intervals | A JSON Object representing ISO-8601 Intervals. This defines the time ranges to run the query over. | yes |
searchDimensions | The dimensions to run the search over. Excluding this means the search is run over all dimensions. | no |
query | See SearchQuerySpec. | yes |
sort | An object specifying how the results of the search should be sorted. Possible types are "lexicographic" (the default sort), "alphanumeric", "strlen", and "numeric". See Sorting Orders for more details. |
no |
context | See Context | no |
The format of the result is:
[
{
"timestamp": "2013-01-01T00:00:00.000Z",
"result": [
{
"dimension": "dim1",
"value": "Ke$ha",
"count": 3
},
{
"dimension": "dim2",
"value": "Ke$haForPresident",
"count": 1
}
]
},
{
"timestamp": "2013-01-02T00:00:00.000Z",
"result": [
{
"dimension": "dim1",
"value": "SomethingThatContainsKe",
"count": 1
},
{
"dimension": "dim2",
"value": "SomethingElseThatContainsKe",
"count": 2
}
]
}
]
Implementation details
Strategies
Search queries can be executed using two different strategies. The default strategy is determined by the "druid.query.search.searchStrategy" runtime property on the Broker. This can be overridden using "searchStrategy" in the query context. If neither the context field nor the property is set, the "useIndexes" strategy will be used.
-
"useIndexes" strategy, the default, first categorizes search dimensions into two groups according to their support for bitmap indexes. And then, it applies index-only and cursor-based execution plans to the group of dimensions supporting bitmaps and others, respectively. The index-only plan uses only indexes for search query processing. For each dimension, it reads the bitmap index for each dimension value, evaluates the search predicate, and finally checks the time interval and filter predicates. For the cursor-based execution plan, please refer to the "cursorOnly" strategy. The index-only plan shows low performance for the search dimensions of large cardinality which means most values of search dimensions are unique.
-
"cursorOnly" strategy generates a cursor-based execution plan. This plan creates a cursor which reads a row from a queryableIndexSegment, and then evaluates search predicates. If some filters support bitmap indexes, the cursor can read only the rows which satisfy those filters, thereby saving I/O cost. However, it might be slow with filters of low selectivity.
-
"auto" strategy uses a cost-based planner for choosing an optimal search strategy. It estimates the cost of index-only and cursor-based execution plans, and chooses the optimal one. Currently, it is not enabled by default due to the overhead of cost estimation.
Server configuration
The following runtime properties apply:
Property | Description | Default |
---|---|---|
druid.query.search.searchStrategy |
Default search query strategy. | useIndexes |
Query context
The following query context parameters apply:
Property | Description |
---|---|
searchStrategy |
Overrides the value of druid.query.search.searchStrategy for this query. |
SearchQuerySpec
insensitive_contains
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:
{
"type" : "insensitive_contains",
"value" : "some_value"
}
fragment
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:
{
"type" : "fragment",
"case_sensitive" : false,
"values" : ["fragment1", "fragment2"]
}
contains
If any part of a dimension value contains the value specified in this search query spec, a "match" occurs. The grammar is:
{
"type" : "contains",
"case_sensitive" : true,
"value" : "some_value"
}
regex
If any part of a dimension value contains the pattern specified in this search query spec, a "match" occurs. The grammar is:
{
"type" : "regex",
"pattern" : "some_pattern"
}