isCached

Returns true if the table is currently cached in-memory.

Syntax

isCached(tableName: str)

Parameters

Parameter	Type	Description
tableName	str	Name of the table to get. Can be qualified with catalog name.

Returns

bool

Examples

Serverless compatibility

Databricks recommends moving away from spark.catalog.cacheTable as it is not compatible with Databricks serverless compute architecture. Remove explicit caching calls (serverless auto-tunes; materialize to Delta if expensive) instead.

Python

_ = spark.sql("DROP TABLE IF EXISTS tbl1")
_ = spark.sql("CREATE TABLE tbl1 (name STRING, age INT) USING parquet")
spark.catalog.cacheTable("tbl1")
spark.catalog.isCached("tbl1")
# True

# Throw an analysis exception when the table does not exist.
spark.catalog.isCached("not_existing_table")
# Traceback (most recent call last):
#     ...
# AnalysisException: ...

# Using the fully qualified name for the table.
spark.catalog.isCached("spark_catalog.default.tbl1")
# True
spark.catalog.uncacheTable("tbl1")
_ = spark.sql("DROP TABLE tbl1")