The correct answer is that the jobs use the Cloud Storage connector instead of HDFS, causing network latency. This performance degradation occurs because Cloud Storage is an object store accessed over the network, while HDFS on local SSDs provides data locality and much faster I/O for shuffle-heavy Spark workloads. On the Google Professional Data Engineer exam, this question tests your understanding of how Dataproc performance differs between Cloud Storage and HDFS, particularly for jobs migrated from on-premises environments. A common trap is assuming that local SSDs automatically speed up all operations, but they only benefit HDFS; the Cloud Storage connector still incurs network round trips for every read and write. To remember this, think of the “locality vs. latency” tradeoff: local SSDs with HDFS give you locality, while Cloud Storage trades that for durability and scalability at the cost of network latency.
PDE Practice Question: Building and operationalizing data processing systems
This PDE practice question tests your understanding of building and operationalizing data processing systems. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is migrating its on-premises Apache Spark jobs to Dataproc. The jobs read from and write to Cloud Storage. After migration, the jobs are slower than expected. The Dataproc cluster uses standard worker machines with local SSDs. What is the most likely cause of the performance degradation?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The jobs use the Cloud Storage connector instead of HDFS, causing network latency.
D is correct because the performance degradation is most likely due to network latency when using the Cloud Storage connector instead of HDFS. Cloud Storage is an object store accessed over the network, while HDFS leverages local SSDs for data locality and faster I/O. In Dataproc, jobs that read/write to Cloud Storage incur higher latency compared to using HDFS on local SSDs, especially for shuffle-heavy Spark workloads.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
The Spark shuffle service is not enabled on the cluster.
Why it's wrong here
Shuffle service affects intermediate data, not final read/write.
✗
The local SSDs are not mounted or are misconfigured.
Why it's wrong here
Dataproc automatically mounts local SSDs; misconfiguration is unlikely.
✗
The Cloud Storage connector is not using the gRPC protocol.
Why it's wrong here
gRPC improves performance but is not the primary cause of slowdown.
✓
The jobs use the Cloud Storage connector instead of HDFS, causing network latency.
Why this is correct
Reading from Cloud Storage over network is slower than local HDFS reads.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that local SSDs or connector protocols are the bottleneck, when the real issue is the inherent latency of using a remote object store (Cloud Storage) versus a distributed filesystem (HDFS) with data locality.
Detailed technical explanation
How to think about this question
Under the hood, the Cloud Storage connector uses HTTP/1.1 with chunked transfer encoding for reads and writes, which introduces higher per-request overhead compared to HDFS's block-based local I/O. In a real-world scenario, a Spark job that performs heavy shuffling (e.g., aggregations or joins) will suffer more because intermediate data is written to Cloud Storage over the network, whereas HDFS would write to local SSDs with near-zero network latency. The gRPC protocol (option C) can reduce latency by using HTTP/2 and multiplexing, but it does not eliminate the fundamental network round-trip time to Cloud Storage.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Building and operationalizing data processing systems — This question tests Building and operationalizing data processing systems — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The jobs use the Cloud Storage connector instead of HDFS, causing network latency. — D is correct because the performance degradation is most likely due to network latency when using the Cloud Storage connector instead of HDFS. Cloud Storage is an object store accessed over the network, while HDFS leverages local SSDs for data locality and faster I/O. In Dataproc, jobs that read/write to Cloud Storage incur higher latency compared to using HDFS on local SSDs, especially for shuffle-heavy Spark workloads.
What should I do if I get this PDE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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