A data engineer is attempting to drop a Spark SQL table my_table and runs the following command: DROP TABLE IF EXISTS my_table; After running this command, the engineer notices that the data files…

The correct answer is A. The table was managed. In Spark SQL and Databricks, there are two types of tables: managed and external. For a managed (internal) table, Spark controls both the metadata in the metastore and the underlying data files. When you DROP a managed table, Spark deletes both the metadata and the actual data…

Submitted by tom_us· Apr 18, 2026Data Management

Question

A data engineer is attempting to drop a Spark SQL table my_table and runs the following command: DROP TABLE IF EXISTS my_table; After running this command, the engineer notices that the data files and metadata files have been deleted from the file system. Which of the following describes why all of these files were deleted?

Options

AThe table was managed
BThe table's data was smaller than 10 GB
CThe table's data was larger than 10 GB
DThe table was external
EThe table did not have a location

How the community answered

(26 responses)

A
92% (24)
C
4% (1)
E
4% (1)

Explanation

In Spark SQL and Databricks, there are two types of tables: managed and external. For a managed (internal) table, Spark controls both the metadata in the metastore and the underlying data files. When you DROP a managed table, Spark deletes both the metadata and the actual data files from storage. For an external table, only the metadata is removed - the data files remain intact. Because both data and metadata were deleted after DROP TABLE, the table must have been managed.

Topics

#Spark SQL#Table Management#Managed Tables

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