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Google Certified Professional Data Engineer Exam Sample Questions (Q111-Q116):

NEW QUESTION # 111
Which Google Cloud Platform service is an alternative to Hadoop with Hive?

A. Cloud Dataflow
B. Cloud Datastore
C. Cloud Bigtable
D. BigQuery

Answer: D

Explanation:
Explanation
Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data summarization, query, and analysis.
Google BigQuery is an enterprise data warehouse.
Reference: https://en.wikipedia.org/wiki/Apache_Hive

NEW QUESTION # 112
You want to create a machine learning model using BigQuery ML and create an endpoint foe hosting the model using Vertex Al. This will enable the processing of continuous streaming data in near-real time from multiple vendors. The data may contain invalid values. What should you do?

A. Create a Pub'Sub topic and send all vendor data to it Connect a Cloud Function to the topic to process the data and store it in BigQuery.
B. Create a new BigOuery dataset and use streaming inserts to land the data from multiple vendors.
Configure your BigQuery ML model to use the "ingestion' dataset as the training data.
C. Use BigQuery streaming inserts to land the data from multiple vendors whore your BigQuery dataset ML model is deployed.
D. Create a Pub/Sub topic and send all vendor data to it Use Dataflow to process and sanitize the Pub/Sub data and stream it to BigQuery.

Answer: D

Explanation:
Dataflow provides a scalable and flexible way to process and clean the incoming data in real-time before loading it into BigQuery.

NEW QUESTION # 113
You have a streaming pipeline that ingests data from Pub/Sub in production. You need to update this streaming pipeline with improved business logic. You need to ensure that the updated pipeline reprocesses the previous two days of delivered Pub/Sub messages. What should you do?
Choose 2 answers

A. Use Pub/Sub Snapshot capture two days before the deployment.
B. Use Pub/Sub Seek with a timestamp.
C. Use the Pub/Sub subscription retain-asked-messages flag.
D. Create a new Pub/Sub subscription two days before the deployment.
E. Use the Pub/Sub subscription clear-retry-policy flag.

Answer: A,B

Explanation:
To update a streaming pipeline with improved business logic and reprocess the previous two days of delivered Pub/Sub messages, you should use Pub/Sub Seek with a timestamp and Pub/Sub Snapshot capture two days before the deployment. Pub/Sub Seek allows you to replay or purge messages in a subscription based on a time or a snapshot. Pub/Sub Snapshot allows you to capture the state of a subscription at a given point in time and replay messages from that point. By using these features, you can ensure that the updated pipeline can process the messages that were delivered in the past two days without losing any data. Reference:
Pub/Sub Seek
Pub/Sub Snapshot

NEW QUESTION # 114
Your analytics team wants to build a simple statistical model to determine which customers are most likely to work with your company again, based on a few different metrics. They want to run the model on Apache Spark, using data housed in Google Cloud Storage, and you have recommended using Google Cloud Dataproc to execute this job. Testing has shown that this workload can run in approximately 30 minutes on a 15-node cluster, outputting the results into Google BigQuery. The plan is to run this workload weekly. How should you optimize the cluster for cost?

A. Use pre-emptible virtual machines (VMs) for the cluster
B. Use SSDs on the worker nodes so that the job can run faster
C. Migrate the workload to Google Cloud Dataflow
D. Use a higher-memory node so that the job runs faster

Answer: C

NEW QUESTION # 115
You need to store and analyze social media postings in Google BigQuery at a rate of 10,000 messages per minute in near real-time. Initially, design the application to use streaming inserts for individual postings. Your application also performs data aggregations right after the streaming inserts. You discover that the queries after streaming inserts do not exhibit strong consistency, and reports from the queries might miss in-flight data. How can you adjust your application design?

A. Load the original message to Google Cloud SQL, and export the table every hour to BigQuery via streaming inserts.
B. Convert the streaming insert code to batch load for individual messages.
C. Re-write the application to load accumulated data every 2 minutes.
D. Estimate the average latency for data availability after streaming inserts, and always run queries after waiting twice as long.

Answer: D

Explanation:
Explanation
The data is first comes to buffer and then written to Storage. If we are running queries in buffer we will face above mentioned issues. If we wait for the bigquery to write the data to storage then we won't face the issue.
So We need to wait till it's written tio storage

NEW QUESTION # 116
......

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Professional-Data-Engineer Exams Training, Valid Professional-Data-Engineer Mock Test

Valid Professional-Data-Engineer Mock Test & Updated Professional-Data-Engineer CBT

Google Certified Professional Data Engineer Exam Sample Questions (Q111-Q116):

Professional-Data-Engineer study materials - Google Professional-Data-Engineer dumps VCE

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