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Persists the DataFrame with the default storage level (MEMORY_AND_DISK_DESER).
Syntax
cache()
Returns
DataFrame: Cached DataFrame.
Notes
The default storage level has changed to MEMORY_AND_DISK_DESER to match Scala in 3.0.
Cached data is shared across all Spark sessions on the cluster.
Examples
:::note Serverless compatibility
Databricks recommends moving away from DataFrame.cache() as it is not compatible with Databricks serverless compute architecture. Materialize intermediate results to a Delta table instead.
:::
df = spark.range(1)
df.cache()
# DataFrame[id: bigint]
df.explain()
# == Physical Plan ==
# InMemoryTableScan ...