2013-09-16 17:49:36 -04:00
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---
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2013-09-26 19:22:28 -04:00
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layout: doc_page
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2013-09-16 17:49:36 -04:00
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---
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2013-09-13 18:20:39 -04:00
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A search query returns dimension values that match the search specification.
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<code>{
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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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</code>
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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 Druid looks at to figure out how to interpret the query|yes|
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|dataSource|A String defining the data source to query, very similar to a table in a relational database|yes|
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|granularity|Defines the granularity of the query. See [Granularities](Granularities.html)|yes|
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|filter|See [Filters](Filters.html)|no|
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2013-09-13 18:20:39 -04:00
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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.html).|yes|
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|sort|How the results of the search should sorted. Two possible types here are "lexicographic" and "strlen".|yes|
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|context|An additional JSON Object which can be used to specify certain flags.|no|
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The format of the result is:
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<code>[
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{
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"timestamp": "2012-01-01T00:00:00.000Z",
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"result": [
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{
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"dimension": "dim1",
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"value": "Ke$ha"
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},
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{
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"dimension": "dim2",
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"value": "Ke$haForPresident"
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}
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]
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},
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{
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"timestamp": "2012-01-02T00:00:00.000Z",
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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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},
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{
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"dimension": "dim2",
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"value": "SomethingElseThatContainsKe"
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}
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]
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}
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]
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</code>
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