- A
BigQueryExecuteQuery
This component executes a SQL query and writes results to a destination table.
- B
BigQueryExportData
Why wrong: This component exports data from a table to GCS, not execute a query.
- C
BigQueryQueryJobOp
Why wrong: This is not a standard component name in the GCPC library.
- D
BigqueryRunQuery
Why wrong: Not a standard component name; the correct naming convention is BigQueryExecuteQuery.
Question 114 of 1,000
PMLE Automating and Orchestrating ML Pipelines Practice Question
This PMLE practice question tests your understanding of automating and orchestrating ml pipelines. 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.
An ML engineer is building a pipeline that includes a step to run a BigQuery query and pass the results to the next step. They want to use a pre-built Google Cloud Pipeline Component for BigQuery. Which component should they use to execute a query and output the results to a destination table?
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
✓
BigQueryExecuteQuery
The correct component is BigQueryExecuteQuery because it is the pre-built Google Cloud Pipeline Component (from the `google-cloud-pipeline-components` package) specifically designed to run a BigQuery SQL query and write the results to a destination table. It returns a `DatasetArtifact` or `Table` artifact that can be passed to downstream pipeline steps, fulfilling the requirement of outputting results to a destination table.
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.
- ✓
BigQueryExecuteQuery
Why this is correct
This component executes a SQL query and writes results to a destination table.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
BigQueryExportData
Why it's wrong here
This component exports data from a table to GCS, not execute a query.
- ✗
BigQueryQueryJobOp
Why it's wrong here
This is not a standard component name in the GCPC library.
- ✗
BigqueryRunQuery
Why it's wrong here
Not a standard component name; the correct naming convention is BigQueryExecuteQuery.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse the generic BigQuery client method `query()` or the legacy `BigQueryQueryJobOp` with the official pipeline component `BigQueryExecuteQuery`, which is the only one that properly integrates with Kubeflow Pipelines artifact passing and is the recommended approach in the PMLE exam domain.
Detailed technical explanation
How to think about this question
Under the hood, `BigQueryExecuteQuery` creates a BigQuery job via the `jobs.insert` API with a query configuration that includes a `destinationTable` parameter. The component leverages the `google-cloud-pipeline-components` library to wrap the job into a Kubeflow Pipelines `ContainerOp`, automatically handling artifact metadata (e.g., table schema, row count) so downstream steps can consume the table as an input. A subtle behavior is that if no destination table is specified, the component writes results to a temporary anonymous table, which is not suitable for persistent downstream consumption.
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.
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Automating and Orchestrating ML Pipelines — study guide chapter
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FAQ
Questions learners often ask
What does this PMLE question test?
Automating and Orchestrating ML Pipelines — This question tests Automating and Orchestrating ML Pipelines — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: BigQueryExecuteQuery — The correct component is BigQueryExecuteQuery because it is the pre-built Google Cloud Pipeline Component (from the `google-cloud-pipeline-components` package) specifically designed to run a BigQuery SQL query and write the results to a destination table. It returns a `DatasetArtifact` or `Table` artifact that can be passed to downstream pipeline steps, fulfilling the requirement of outputting results to a destination table.
What should I do if I get this PMLE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
This PMLE 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 PMLE exam.
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