Google PCA Practice Question: Analyze and optimize technical and business processes
A company runs a streaming data pipeline using Dataflow to process real-time data and insert into BigQuery. Recently, workers are frequently failing with out-of-memory errors and the pipeline latency is increasing. What should they do to resolve the issue?
⚠ Common exam trap
Google Cloud often tests the misconception that scaling up resources (more memory or more workers) is the primary fix for streaming pipeline memory issues, when the real solution is to offload state management using Streaming Engine.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable Dataflow Streaming Engine
Dataflow Streaming Engine offloads the streaming data processing state and shuffle data from worker memory to a backend service, reducing memory pressure on workers. This directly addresses out-of-memory errors and latency increases without requiring manual scaling or machine type changes. It is the recommended solution for streaming pipelines experiencing memory bottlenecks.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the worker machine type and memory
Why it's wrong here
This may temporarily mitigate but does not eliminate memory issues; Streaming Engine is more effective.
- ✗
Use Cloud Pub/Sub for buffering and then load into BigQuery in batches
Why it's wrong here
This changes the architecture significantly and may introduce additional latency.
- ✗
Enable autoscaling and increase the maximum number of workers
Why it's wrong here
More workers do not fix per-worker memory issues.
- ✓
Enable Dataflow Streaming Engine
Why this is correct
Streaming Engine moves state to a backend service, reducing memory usage per worker.
Visual reference
Go deeper
Related to this question
Learn chapter
Virtual Machine Instances in Compute Engine
Key term
Service
A service is a software component or system that performs a specific function and is available to be used by other programs or users over a network.
Key term
Dataflow
Dataflow is a Google Cloud managed service that processes and transforms data in real-time or batch mode using Apache Beam pipelines.
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