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}")
Which of the following can be used to fill in the blank to successfully complete the task?
Real Exam
Community
KKeng
A
spark.delta.sql
B
spark.delta.table
C
spark.table
D
dbutils.sql
E
spark.sql
Explanation:
The correct answer is spark.sql because:
spark.sql()is the primary method in PySpark for executing SQL queries in Databricks.- The code block shows an f-string that constructs a SQL query with the
table_namevariable interpolated. - The syntax should be:
spark.sql(f"SELECT customer_id, spend FROM {table_name}")
Why other options are incorrect:
- A. spark.delta.sql: This method doesn't exist in the Databricks/Spark API.
- B. spark.delta.table: This is used for Delta table operations, not for executing SQL queries.
- C. spark.table: This method is used to create a DataFrame from a table, not to execute SQL queries.
- D. dbutils.sql:
dbutilsdoesn't have a.sqlmethod; SQL execution is done throughspark.sql().
Key Concept: In Databricks, spark.sql() is the standard way to execute SQL queries from Python code, and it supports string interpolation using f-strings or other string formatting methods.
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