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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
:::note 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.
:::
_ = 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")