Databricks Certified Data Engineer - Associate
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A data engineer has a Python variable table_name that they would like to use in a SQL query. They want to construct a Python code block that will run the query using table_name. They have the following incomplete code block:
____(f"SELECT customer_id, spend FROM {table_name}")
____(f"SELECT customer_id, spend FROM {table_name}")
What can be used to fill in the blank to successfully complete the task?
Real Exam
Community
KKeng
A
spark.delta.sql
B
spark.sql
C
spark.table
D
dbutils.sql
Explanation:
Explanation
The correct answer is B. spark.sql.
Why this is correct:
spark.sql()is the standard method in PySpark for executing SQL queries in Databricks.- It allows you to pass SQL query strings as arguments, including formatted strings with Python variables.
- The syntax
spark.sql(f"SELECT customer_id, spend FROM {table_name}")will properly execute the SQL query with the table name variable substituted.
Why other options are incorrect:
- A.
spark.delta.sql: This method doesn't exist in PySpark. Delta Lake operations are typically done throughspark.sql()or specific DeltaTable APIs. - C.
spark.table: This method is used to create a DataFrame from a table name (e.g.,spark.table(table_name)), not to execute SQL queries. - D.
dbutils.sql:dbutilsis a Databricks utility module, butdbutils.sqldoesn't exist. SQL execution is handled throughspark.sql().
Key Points:
- In Databricks notebooks, you can seamlessly mix Python and SQL using
spark.sql() - The method supports Python f-strings for dynamic query construction
- Results are returned as DataFrames that can be further processed in Python
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