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Copy file name to clipboardExpand all lines: articles/stream-analytics/stream-analytics-use-reference-data.md
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Reference data (also known as a lookup table) is a finite data set that is static or slowly changing in nature, used to perform a lookup or to augment your data streams. For example, in an IoT scenario, you could store metadata about sensors (which don’t change often) in reference data and join it with real time IoT data streams. Azure Stream Analytics loads reference data in memory to achieve low latency stream processing. To make use of reference data in your Azure Stream Analytics job, you will generally use a [Reference Data Join](https://docs.microsoft.com/stream-analytics-query/reference-data-join-azure-stream-analytics) in your query.
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## Example
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If a commercial vehicle is registered with the Toll Company, they can pass through the toll booth without being stopped for inspection. We will use a commercial vehicle registration lookup table to identify all commercial vehicles with expired registration.
Stream Analytics supports Azure Blob storage and Azure SQL Database as the storage layer for Reference Data. You can also transform and/or copy reference data to Blob storage from Azure Data Factory to use [any number of cloud-based and on-premises data stores](../data-factory/copy-activity-overview.md).
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## Azure Blob storage
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Increasing number of Streaming Units of a job beyond 6 does not increase the maximum supported size of reference data.
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Support for compression is not available for reference data.
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Support for compression is not available for reference data.
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## Joining multiple reference datasets in a job
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You can join only one stream input with one reference data input in a single step of your query. However, you can join multiple reference datasets by breaking down your query into multiple steps. An example is shown below.
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```SQL
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With Step1 as (
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--JOIN input stream with reference data to get 'Desc'
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