Databricks Certified Data Engineer - Professional

Get started today

Ultimate access to all questions.

Explanation:

Structured Streaming models data streams as a continuously appended table. New data arriving in the stream is treated as new rows being added to an unbounded table, allowing batch-like query operations to apply incrementally. This abstraction aligns with the DataFrame/Dataset API in Spark.

A is incorrect because Spark does not rely on GPU parallelism; it uses distributed CPU clusters.
B is false as Structured Streaming is part of Apache Spark, not derived from Kafka.
C inaccurately describes state management; while stateful processing exists, it's not the core programming model.
D correctly captures the foundational concept of treating streams as unbounded tables.

Explanation:

A is incorrect because Spark does not rely on GPU parallelism; it uses distributed CPU clusters.
B is false as Structured Streaming is part of Apache Spark, not derived from Kafka.
C inaccurately describes state management; while stateful processing exists, it's not the core programming model.
D correctly captures the foundational concept of treating streams as unbounded tables.

Comments (0)

No comments yet.

Which statement describes the fundamental programming model employed by Spark Structured Streaming?

Exam-Like

Structured Streaming leverages the parallel processing of GPUs to achieve highly parallel data throughput.

8.8%

Structured Streaming is implemented as a messaging bus and is derived from Apache Kafka.

8.8%

Structured Streaming relies on a distributed network of nodes that hold incremental state values for cached stages.

14.2%

Structured Streaming models new data arriving in a data stream as new rows appended to an unbounded table.

68.1%