Nóta
Aðgangur að þessari síðu krefst heimildar. Þú getur prófað aðskrá þig inn eða breyta skráasöfnum.
Aðgangur að þessari síðu krefst heimildar. Þú getur prófað að breyta skráasöfnum.
Caches the specified table in-memory or with given storage level. Default MEMORY_AND_DISK.
Syntax
cacheTable(tableName: str, storageLevel: StorageLevel = None)
Parameters
| Parameter | Type | Description |
|---|---|---|
tableName |
str | Name of the table to get. Can be qualified with catalog name. |
storageLevel |
StorageLevel, optional |
Storage level to set for persistence. |
Notes
Cached data is shared across all Spark sessions on the cluster.
Examples
_ = spark.sql("DROP TABLE IF EXISTS tbl1")
_ = spark.sql("CREATE TABLE tbl1 (name STRING, age INT) USING parquet")
spark.catalog.cacheTable("tbl1")
# or
spark.catalog.cacheTable("tbl1", StorageLevel.OFF_HEAP)
# Throw an analysis exception when the table does not exist.
spark.catalog.cacheTable("not_existing_table")
# Traceback (most recent call last):
# ...
# AnalysisException: ...
# Using the fully qualified name for the table.
spark.catalog.cacheTable("spark_catalog.default.tbl1")
spark.catalog.uncacheTable("tbl1")
_ = spark.sql("DROP TABLE tbl1")