Exam Professional Data Engineer topic 1 question 282 discussion

It should B, Storage Write API has "3 GB per second throughput in multi-regions; 300 MB per second in regions"

- BigQuery Storage Write API: This API is designed for high-throughput, low-latency writing of data into BigQuery. It also provides tools to prevent data duplication, which is essential for exactly-once delivery semantics. - Regional Table: Choosing a regional location for the BigQuery table could potentially provide better performance and lower latency, as it would be closer to the Dataflow job if they are in the same region.

Why A is correct: BigQuery Storage Write API: Supports exactly-once semantics (deduplication via stream offsets). Designed for high-throughput streaming ingestion (scales much better than the legacy Streaming Insert API). Can handle your throughput requirement of 1.5 GB/s. Regional table: Required for exactly-once delivery guarantees with the Storage Write API.

3 GB per second throughput in multi-regions; 300 MB per second in regions

Go With (B) Not (A), Max throughput for regional currently only 300 MB/s as for the dcos

Honestly, I think exam topic should do better job. the answers only make more mislead.

You need a write latency of 1.5 GBs per second. Given the high throughput requirement, a regional BigQuery table (Option A) is generally preferred over a multi-regional table due to potentially lower write latency in multi-region. Simple.

As per GCP document multi-region meets the troughput requirement.

It’s A

A. Implement the BigQuery Storage Write API and guarantee that the target BigQuery table is regional. Here's the breakdown: Why Option A is Superior Exactly-Once Delivery: The BigQuery Storage Write API intrinsically supports exactly-once delivery using stream offsets. This guarantees that each message is written to BigQuery exactly one time, even in the case of retries due to the lack of native exactly-once support in your message bus. High Throughput: The Storage Write API is optimized for high-throughput scenarios. It can handle the expected ingestion throughput of 1.5 GB per second. Regional Tables: Using a regional BigQuery table aligns with best practices when utilizing the Storage Write API, as it helps to minimize latency and reduce potential cross-region communication costs.

- BigQuery Storage Write API: This API is designed for high-throughput, low-latency writing of data into BigQuery. It also provides tools to prevent data duplication, which is essential for exactly-once delivery semantics. - The multiregional table ensures that your data is highly available and can be streamed into BigQuery across multiple regions. It is better suited for high-throughput and low-latency workloads, as it provides distributed write capabilities that can handle large data volumes, such as the 1.5 GB per second you expect to stream.

https://cloud.google.com/bigquery/docs/streaming-data-into-bigquery For new projects, we recommend using the BigQuery Storage Write API instead of the tabledata.insertAll method. The Storage Write API has lower pricing and more robust features, including exactly-once delivery semantics https://cloud.google.com/bigquery/docs/write-api#advantages

B is correct. When aiming for exactly-once delivery in a Dataflow streaming job, the key is to use the BigQuery Storage Write API, as it provides the capability to handle large-scale data ingestion with the correct semantics, including exactly-once delivery.

3 GB per second throughput in multi-regions; 300 MB per second in regions https://cloud.google.com/bigquery/quotas#write-api-limits

streamed into BigQuery with exactly-once delivery semantics >>> Storage Write API ingestion throughput into BigQuery to be about 1.5 GB per second >>> multiregional (check throughput rate here >>> https://cloud.google.com/bigquery/quotas#write-api-limits)

- Choosing a regional target BigQuery table ensures that data is stored redundantly in a single region, providing high availability and durability.

According to this documentation, its B https://cloud.google.com/bigquery/quotas#write-api-limits