PDE Ingesting and Processing the Data Practice Question
You need to ingest data from a Cloud Storage bucket into BigQuery. The data is in Avro format and you want to minimize the time to insight. Which method should you use?
⚠ Common exam trap
The trap here is overengineering the solution by choosing a pipeline or streaming service when a simple load job is sufficient and more efficient for batch Avro ingestion.
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
✓
Use the BigQuery Load job with the Avro source format and enable autodetect schema.
The BigQuery Load job natively supports Avro and can automatically detect the schema from the Avro file's embedded schema. This makes it the fastest and simplest way to ingest Avro data from Cloud Storage, minimizing time to insight. Other methods like Dataflow, Streaming API, or Cloud Data Fusion add unnecessary complexity, latency, or cost for a straightforward batch load.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Cloud Data Fusion to read the Avro files and load them into BigQuery.
Why it's wrong here
Cloud Data Fusion is a managed ETL service that can read Avro and write to BigQuery, but it is overkill for a simple load. It introduces additional setup, cost, and potential latency. For straightforward ingestion without transformation, a native BigQuery load job is faster and requires less configuration. Data Fusion is more suitable for complex pipelines with multiple sources and transformations.
- ✗
Use the BigQuery Streaming API to stream the Avro records from Cloud Storage.
Why it's wrong here
The BigQuery Streaming API is designed for real-time, row-by-row inserts, not for bulk loading from files. Streaming Avro records from Cloud Storage would require a program to read and stream each record, which is inefficient and incurs higher costs. It also does not provide the same throughput as a load job. This method is not appropriate for batch ingestion of Avro files.
- ✗
Use a Dataflow pipeline to read the Avro files and write to BigQuery.
Why it's wrong here
While Dataflow can read Avro and write to BigQuery, it adds unnecessary complexity and latency for a simple load. Dataflow is better suited for transformations or streaming. For straightforward ingestion of Avro files without transformation, a direct load job is faster and more cost-effective. Using Dataflow would increase the time to insight due to pipeline setup and execution overhead.
- ✓
Use the BigQuery Load job with the Avro source format and enable autodetect schema.
Why this is correct
Loading Avro files directly into BigQuery using a load job is the fastest and simplest method for batch ingestion. Avro is a supported format, and autodetect can infer the schema from the Avro file's embedded schema, eliminating manual schema definition. This approach minimizes time to insight because it avoids intermediate processing steps. It is ideal for one-time or scheduled batch loads from Cloud Storage.
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Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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