A data engineer is using the following code block as part of a batch ingestion pipeline to read from a composable table: Which of the following changes needs to be made so this code block will work…

The correct answer is E. Replace spark.read with spark.readStream. In Databricks/Spark, spark.read is used for batch reads and returns a static DataFrame. To read from a streaming source (such as a Delta table used as a stream), you must use spark.readStream, which returns a streaming DataFrame and enables the Structured Streaming engine. The…

Submitted by saadiq_pk· Apr 18, 2026Databricks Lakehouse Platform

Question

A data engineer is using the following code block as part of a batch ingestion pipeline to read from a composable table: Which of the following changes needs to be made so this code block will work when the transactions table is a stream source?

Exhibit

Options

AReplace predict with a stream-friendly prediction function
BReplace schema(schema) with option ("maxFilesPerTrigger", 1)
CReplace "transactions" with the path to the location of the Delta table
DReplace format("delta") with format("stream")
EReplace spark.read with spark.readStream

How the community answered

(17 responses)

D
6% (1)
E
94% (16)

Explanation

In Databricks/Spark, spark.read is used for batch reads and returns a static DataFrame. To read from a streaming source (such as a Delta table used as a stream), you must use spark.readStream, which returns a streaming DataFrame and enables the Structured Streaming engine. The format, schema, and table reference remain the same - only the entry point changes from spark.read to spark.readStream.

Topics

#Structured Streaming#Spark API#Batch to Stream Conversion#Data Ingestion

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