Courseiva
← PDE
Full test
Question 437 of 499
Building and operationalizing data processing systems →hardMultiple ChoiceObjective-mapped

Quick Answer

The answer is that the user-provided record ID for deduplication in BigQuery’s streaming inserts is not being set for all messages. This is the most likely reason duplicate rows appear because BigQuery’s streaming buffer relies on these record IDs to identify and discard duplicate inserts during retries or redeliveries from Pub/Sub; when a record ID is missing, BigQuery treats each insert as a new row, even if the underlying message is identical. On the Google Professional Data Engineer exam, this scenario tests your understanding of exactly-once semantics in Dataflow and the critical role of insertId in BigQuery’s deduplication mechanism—a common trap is assuming that enabling exactly-once in Dataflow alone guarantees deduplication in BigQuery. Remember the memory tip: “No ID, no dedup—BigQuery treats every stream as fresh.”

PDE Practice Question: Building and operationalizing data processing systems

This PDE practice question tests your understanding of building and operationalizing data processing systems. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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's Dataflow pipeline uses the PubSubIO source to read messages and writes to BigQuery via the BigQueryIO sink. The pipeline is running in Streaming mode with exactly-once semantics enabled. Occasionally, duplicate rows appear in BigQuery. What is the most likely reason?

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.

Question 1hardmultiple choice
Full question →

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 user-provided record ID for deduplication in BigQuery's streaming inserts is not being set for all messages, leading to duplicate rows.

In Dataflow streaming pipelines with exactly-once semantics, BigQuery's streaming inserts use user-provided record IDs for deduplication. If the record ID is not set for all messages, BigQuery cannot identify duplicates, and retries or redeliveries from Pub/Sub can result in duplicate rows. This is the most common cause of duplicates in this scenario.

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 user-provided record ID for deduplication in BigQuery's streaming inserts is not being set for all messages, leading to duplicate rows.

    Why this is correct

    BigQueryIO uses insertId for deduplication; if it's missing or inconsistent, duplicates can occur.

    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.

  • ✗

    The pipeline is using the WriteResult method with WRITE_APPEND in batch mode, which can cause duplicates if retries happen.

    Why it's wrong here

    In streaming mode, BigQueryIO uses streaming inserts by default, not batch.

  • ✗

    The pipeline is experiencing the 'dataflow streaming log processing' bug, causing duplicate logs to be written.

    Why it's wrong here

    This is not a known bug; Dataflow handles duplicates internally.

  • ✗

    The PubSubIO source is configured with a dead-letter queue and messages are being redelivered without proper deduplication.

    Why it's wrong here

    Dead-letter queues prevent redelivery; if configured correctly, duplicates should not occur.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Google Cloud often tests the misconception that exactly-once semantics in Dataflow automatically deduplicates at the sink, but in reality, BigQuery requires explicit user-provided record IDs for deduplication during streaming inserts.

Detailed technical explanation

How to think about this question

BigQuery streaming inserts use the `insertId` field for best-effort deduplication within a 1-minute window. If the `insertId` is missing or not unique per message, BigQuery may accept duplicate rows when the same message is delivered multiple times due to Pub/Sub's at-least-once delivery. Dataflow's exactly-once sink (BigQueryIO with `withCreateDisposition(CreateDisposition.CREATE_NEVER)`) does not automatically generate these IDs; the user must set them via `withMethod(StandardStreamingWrite)` and `withIdAttribute()` or by providing a custom `ValueProvider`.

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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

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.

Related practice questions

Related PDE practice-question pages

Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.

Designing data processing systems practice questions

Practise PDE questions linked to Designing data processing systems.

Building and operationalizing data processing systems practice questions

Practise PDE questions linked to Building and operationalizing data processing systems.

Operationalizing machine learning models practice questions

Practise PDE questions linked to Operationalizing machine learning models.

Ensuring solution quality practice questions

Practise PDE questions linked to Ensuring solution quality.

PDE fundamentals practice questions

Practise PDE questions linked to PDE fundamentals.

PDE scenario practice questions

Practise PDE questions linked to PDE scenario.

PDE troubleshooting practice questions

Practise PDE questions linked to PDE troubleshooting.

Practice this exam

Start a free PDE practice session

Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.

10 questions20 questions30 questions50 questionsTimed 30
PDE practice-test guide →Study guide →Browse all practice tests

FAQ

Questions learners often ask

What does this PDE question test?

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 user-provided record ID for deduplication in BigQuery's streaming inserts is not being set for all messages, leading to duplicate rows. — In Dataflow streaming pipelines with exactly-once semantics, BigQuery's streaming inserts use user-provided record IDs for deduplication. If the record ID is not set for all messages, BigQuery cannot identify duplicates, and retries or redeliveries from Pub/Sub can result in duplicate rows. This is the most common cause of duplicates in this scenario.

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.

About these practice questions

Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →

How Courseiva writes practice questions · Editorial policy

Last reviewed: Jun 30, 2026

Question Discussion

Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.

Loading comments…

Sign in to join the discussion.

This PDE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PDE exam.