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Google Certified Professional Data Engineer Exam Sample Questions (Q53-Q58):
NEW QUESTION # 53
You want to use a BigQuery table as a data sink. In which writing mode(s) can you use BigQuery as a sink?
- A. Both batch and streaming
- B. Only streaming
- C. Only batch
- D. BigQuery cannot be used as a sink
Answer: A
Explanation:
When you apply a BigQueryIO.Write transform in batch mode to write to a single table, Dataflow invokes a BigQuery load job. When you apply a BigQueryIO.Write transform in streaming mode or in batch mode using a function to specify the destination table, Dataflow uses BigQuery's streaming inserts
NEW QUESTION # 54
You are choosing a NoSQL database to handle telemetry data submitted from millions of Internet-of-Things (IoT) devices. The volume of data is growing at 100 TB per year, and each data entry has about 100 attributes. The data processing pipeline does not require atomicity, consistency, isolation, and durability (ACID). However, high availability and low latency are required.
You need to analyze the data by querying against individual fields. Which three databases meet your requirements? (Choose three.)
- A. MongoDB
- B. HDFS with Hive
- C. Redis
- D. Cassandra
- E. MySQL
- F. HBase
Answer: A,B,F
Explanation:
Explanation:
NEW QUESTION # 55
You work for a mid-sized enterprise that needs to move its operational system transaction data from an on-premises database to GCP. The database is about 20 TB in size. Which database should you choose?
- A. Cloud Spanner
- B. Cloud Bigtable
- C. Cloud SQL
- D. Cloud Datastore
Answer: C
NEW QUESTION # 56
Which Java SDK class can you use to run your Dataflow programs locally?
- A. LocalPipelineRunner
- B. DirectPipelineRunner
- C. MachineRunner
- D. LocalRunner
Answer: B
Explanation:
Explanation
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
NEW QUESTION # 57
You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on non- key columns. What should you do?
- A. Use Cloud Spanner for storage. Add secondary indexes to support query patterns.
- B. Use Cloud Spanner for storage. Use Cloud Dataflow to transform data to support query patterns.
- C. Use Cloud SQL for storage. Add secondary indexes to support query patterns.
- D. Use Cloud SQL for storage. Use Cloud Dataflow to transform data to support query patterns.
Answer: B
Explanation:
Explanation/Reference: https://cloud.google.com/solutions/data-lifecycle-cloud-platform
NEW QUESTION # 58
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