CACHE TABLE
Applies to: Databricks Runtime
Caches contents of a table or output of a query with the given storage level in Apache Spark cache. If a query is cached, then a temp view is created for this query. This reduces scanning of the original files in future queries.
Syntax
CACHE [ LAZY ] TABLE table_name
[ OPTIONS ( 'storageLevel' [ = ] value ) ] [ [ AS ] query ]
See Disk cache vs. Spark cache for the differences between disk caching and the Apache Spark cache.
Parameters
LAZY
Only cache the table when it is first used, instead of immediately.
-
Identifies the Delta table or view to cache. The name must not include a temporal specification. If the table cannot be found Azure Databricks raises a TABLE_OR_VIEW_NOT_FOUND error.
OPTIONS ( 'storageLevel' [ = ] value )
OPTIONS
clause withstorageLevel
key and value pair. A warning is issued when a key other thanstorageLevel
is used. The valid options forstorageLevel
are:NONE
DISK_ONLY
DISK_ONLY_2
MEMORY_ONLY
MEMORY_ONLY_2
MEMORY_ONLY_SER
MEMORY_ONLY_SER_2
MEMORY_AND_DISK
MEMORY_AND_DISK_2
MEMORY_AND_DISK_SER
MEMORY_AND_DISK_SER_2
OFF_HEAP
An Exception is thrown when an invalid value is set for
storageLevel
. IfstorageLevel
is not explicitly set usingOPTIONS
clause, the defaultstorageLevel
is set toMEMORY_AND_DISK
.query
A query that produces the rows to be cached. It can be in one of following formats:
- A
SELECT
statement - A
TABLE
statement - A
FROM
statement
- A
Examples
> CACHE TABLE testCache OPTIONS ('storageLevel' 'DISK_ONLY') SELECT * FROM testData;