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PDE Practice Question: Migrating its on-premises Apache Spark jobs to…
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?
⚠ Common exam trap
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.
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
✓
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.
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.
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