Databricks Databricks-Certified-Data-Analyst-Associate Exam With Confidence Using Practice Dumps

The correct answer is C because the task requires creating or replacing a managed table with an explicitly defined schema. In Databricks SQL, column definitions are placed directly after the table name inside parentheses. The USING clause is for specifying a data source format, not for defining columns. Option C correctly uses CREATE OR REPLACE TABLE database_name.table_name (...), which recreates the table if it already exists and creates an empty table with the specified schema.

Official documentation extract used: Databricks CREATE TABLE syntax supports [CREATE OR] REPLACE followed by the table name and a table_specification containing column identifiers and column types.

In Databricks SQL, a subquery is a nested query within a larger SQL query that allows for the retrieval of data without the necessity of creating a table or view. This is particularly useful for simplifying complex queries by breaking them down into more manageable parts. Subqueries can be employed in various clauses such as SELECT, FROM, and WHERE to perform operations like filtering, transforming, and aggregating data on-the-fly. This flexibility enhances query efficiency and readability without the overhead of persisting intermediate results as separate tables or views.

External tables are tables that are defined in the Databricks metastore using the information stored in a cloud object storage location. External tables do not manage the data, but provide a schema and a table name to query the data. To create an external table, you can use the CREATE EXTERNAL TABLE statement and specify the object storage path to the LOCATION clause. For example, to create an external table named ext_table on a Parquet file stored in S3, you can use the following statement:

SQL

CREATE EXTERNAL TABLE ext_table (

col1 INT,

col2 STRING

)

STORED AS PARQUET

LOCATION ' s3://bucket/path/file.parquet '

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 External tables