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Answer: Exceptions in worker code
The most likely cause of the errors you're experiencing in Dataflow, particularly if they are related to a particular DoFn, is 'B. Exceptions in worker code.' When a Dataflow job processes a few elements successfully before failing, it suggests that the overall job setup, permissions, and pipeline graph are likely correct, as the job was able to start and initially process data. However, if it fails during execution and the errors are associated with a specific DoFn, this points towards issues in the code that executes within the workers. This could include runtime exceptions in the code logic of the DoFn, issues handling specific data elements, or resource constraints. Refer to the Dataflow monitoring interface for stack traces and error messages for further details.
Author: LeetQuiz Editorial Team
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You have initiated a new batch job using Google Dataflow, a fully-managed service for stream and batch processing. The job successfully starts and processes a few elements but then unexpectedly fails and shuts down. Upon examining the Dataflow monitoring interface, you observe error messages associated with a specific DoFn (a function applied on each element in a PCollection) within your data processing pipeline. What is the most probable cause of these errors?
A
Job validation
B
Exceptions in worker code
C
Graph or pipeline construction
D
Insufficient permissions
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