Free Professional-Data-Engineer Exam Braindumps

- (Exam Topic 5)
Cloud Dataproc is a managed Apache Hadoop and Apache service.

1. A. Blaze
2. B. Spark
3. C. Fire
4. D. Ignite

Correct Answer: B
Cloud Dataproc is a managed Apache Spark and Apache Hadoop service that lets you use open source data tools for batch processing, querying, streaming, and machine learning.
Reference: https://cloud.google.com/dataproc/docs/

- (Exam Topic 5)
Which Java SDK class can you use to run your Dataflow programs locally?

1. A. LocalRunner
2. B. DirectPipelineRunner
3. C. MachineRunner
4. D. LocalPipelineRunner

Correct Answer: B
DirectPipelineRunner allows you to execute operations in the pipeline directly, without any optimization. Useful for small local execution and tests
Reference:
https://cloud.google.com/dataflow/java-sdk/JavaDoc/com/google/cloud/dataflow/sdk/runners/DirectPipelineRun

- (Exam Topic 6)
You are building an application to share financial market data with consumers, who will receive data feeds. Data is collected from the markets in real time. Consumers will receive the data in the following ways:
Real-time event stream
ANSI SQL access to real-time stream and historical data
Batch historical exports
Which solution should you use?

1. A. Cloud Dataflow, Cloud SQL, Cloud Spanner
2. B. Cloud Pub/Sub, Cloud Storage, BigQuery
3. C. Cloud Dataproc, Cloud Dataflow, BigQuery
4. D. Cloud Pub/Sub, Cloud Dataproc, Cloud SQL

Correct Answer: A

- (Exam Topic 6)
You are running a pipeline in Cloud Dataflow that receives messages from a Cloud Pub/Sub topic and writes the results to a BigQuery dataset in the EU. Currently, your pipeline is located in europe-west4 and has a maximum of 3 workers, instance type n1-standard-1. You notice that during peak periods, your pipeline is struggling to process records in a timely fashion, when all 3 workers are at maximum CPU utilization. Which two actions can you take to increase performance of your pipeline? (Choose two.)

1. A. Increase the number of max workers
2. B. Use a larger instance type for your Cloud Dataflow workers
3. C. Change the zone of your Cloud Dataflow pipeline to run in us-central1
4. D. Create a temporary table in Cloud Bigtable that will act as a buffer for new dat
5. E. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Bigtable to BigQuery
6. F. Create a temporary table in Cloud Spanner that will act as a buffer for new dat
7. G. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Spanner to BigQuery

Correct Answer: BE

- (Exam Topic 6)
You are designing a data processing pipeline. The pipeline must be able to scale automatically as load increases. Messages must be processed at least once, and must be ordered within windows of 1 hour. How should you design the solution?

1. A. Use Apache Kafka for message ingestion and use Cloud Dataproc for streaming analysis.
2. B. Use Apache Kafka for message ingestion and use Cloud Dataflow for streaming analysis.
3. C. Use Cloud Pub/Sub for message ingestion and Cloud Dataproc for streaming analysis.
4. D. Use Cloud Pub/Sub for message ingestion and Cloud Dataflow for streaming analysis.

Correct Answer: C