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Answer: Structured Streaming models new data arriving in a data stream as new rows appended to an unbounded table.
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.
Author: LeetQuiz Editorial Team
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Which statement describes the fundamental programming model employed by Spark Structured Streaming?
A
Structured Streaming leverages the parallel processing of GPUs to achieve highly parallel data throughput.
B
Structured Streaming is implemented as a messaging bus and is derived from Apache Kafka.
C
Structured Streaming relies on a distributed network of nodes that hold incremental state values for cached stages.
D
Structured Streaming models new data arriving in a data stream as new rows appended to an unbounded table.
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