pyspark.sql.Catalog.isCached#
- Catalog.isCached(tableName)[source]#
- Returns true if the table is currently cached in-memory. - New in version 2.0.0. - Parameters
- tableNamestr
- name of the table to get. - Changed in version 3.4.0: Allow - tableNameto be qualified with catalog name.
 
- Returns
- bool
 
 - Examples - >>> _ = 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")