mirror of https://github.com/apache/druid.git
43 lines
2.2 KiB
Markdown
43 lines
2.2 KiB
Markdown
---
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id: joins
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title: "Joins"
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---
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Apache Druid has two features related to joining of data:
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1. [Join](datasource.md#join) operators. These are available using a [join datasource](datasource.md#join) in native
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queries, or using the [JOIN operator](sql.md) in Druid SQL. Refer to the
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[join datasource](datasource.md#join) documentation for information about how joins work in Druid native queries,
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or the [multi-stage query join documentation](../multi-stage-query/reference.md#joins) for information about how joins
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work in multi-stage query tasks.
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2. [Query-time lookups](lookups.md), simple key-to-value mappings. These are preloaded on all servers that are involved
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in queries and can be accessed with or without an explicit join operator. Refer to the [lookups](lookups.md)
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documentation for more details.
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Whenever possible, for best performance it is good to avoid joins at query time. Often this can be accomplished by
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joining data before it is loaded into Druid. However, there are situations where joins or lookups are the best solution
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available despite the performance overhead, including:
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- The fact-to-dimension (star and snowflake schema) case: you need to change dimension values after initial ingestion,
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and aren't able to reingest to do this. In this case, you can use lookups for your dimension tables.
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- Your workload requires joins or filters on subqueries.
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