A data engineer has joined an existing project and they see the following query in the project repository: CREATE STREAMING LIVE TABLE loyal_customers AS SELECT customer_id - FROM…

The correct answer is C. The customers table is a streaming live table. In Delta Live Tables SQL, the STREAM() function wraps a LIVE table reference to indicate that the source table should be read as a stream - processing only new or changed records incrementally rather than reprocessing the entire table on each run. The STREAM() function is…

Submitted by haru.x· Apr 18, 2026ELT with Spark SQL and Python

Question

A data engineer has joined an existing project and they see the following query in the project repository: CREATE STREAMING LIVE TABLE loyal_customers AS SELECT customer_id - FROM STREAM(LIVE.customers) WHERE loyalty_level = 'high'; Which of the following describes why the STREAM function is included in the query?

Options

AThe STREAM function is not needed and will cause an error.
BThe table being created is a live table.
CThe customers table is a streaming live table.
DThe customers table is a reference to a Structured Streaming query on a PySpark DataFrame.
EThe data in the customers table has been updated since its last run.

How the community answered

(23 responses)

A
4% (1)
C
91% (21)
D
4% (1)

Explanation

In Delta Live Tables SQL, the STREAM() function wraps a LIVE table reference to indicate that the source table should be read as a stream - processing only new or changed records incrementally rather than reprocessing the entire table on each run. The STREAM() function is required specifically when the source (LIVE.customers) is itself defined as a STREAMING LIVE TABLE. If customers were a standard batch LIVE TABLE, the STREAM() wrapper would not be appropriate. The function does not relate to PySpark DataFrames (option D) - it is purely a DLT SQL construct. It is not an error (option A), nor is it triggered by data updates since last run in the way option E implies.

Topics

#Delta Live Tables (DLT)#Streaming ETL#SQL#Streaming Sources

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