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| Certification Vendor: | Google Cloud |
|---|---|
| Exam Name: | Google Cloud Professional Data Engineer Exam |
| Exam Number: | Professional-Data-Engineer |
| Real Exam Qty: | 40 - 50 |
| Certificate Validity Period: | 2 years |
| Related Certifications: | Google Cloud Professional Data Analyst Google Cloud Associate Cloud Engineer Google Cloud Professional Cloud Architect |
| Exam Format: | Multiple select, Multiple choice |
| Passing Score: | 700 / 1000 |
| Exam Duration: | 120 minutes |
| Available Languages: | Japanese, English |
| Exam Price: | USD 200 (plus tax where applicable) |
| Recommended Training: | Google Cloud Professional Data Engineer Learning Path Official Exam Guide |
| Exam Registration: | Google Cloud Certification Registration |
| Sample Questions: | Google Professional-Data-Engineer Sample Questions |
| Exam Way: | Online-proctored or onsite-proctored |
| Pre Condition: | No mandatory prerequisites; recommended 3+ years industry experience, including 1+ year designing and managing Google Cloud data solutions |
| Official Syllabus URL: | https://cloud.google.com/learn/certification/data-engineer |
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Google Professional-Data-Engineer Certification is a valuable certification that can help professionals advance their careers in the field of data engineering. Google Certified Professional Data Engineer Exam certification demonstrates to employers that a candidate has the skills and knowledge needed to design and build data processing systems on Google Cloud Platform. It also shows that a candidate is committed to staying up-to-date with the latest technology trends and developments in the field of data engineering.
NEW QUESTION # 278
Which of the following IAM roles does your Compute Engine account require to be able to run pipeline jobs?
Answer: D
Explanation:
The dataflow.worker role provides the permissions necessary for a Compute Engine service account to execute work units for a Dataflow pipeline Reference:
https://cloud.google.com/dataflow/access-control
NEW QUESTION # 279
Which action can a Cloud Dataproc Viewer perform?
Answer: A
Explanation:
A Cloud Dataproc Viewer is limited in its actions based on its role. A viewer can only list clusters, get cluster details, list jobs, get job details, list operations, and get operation details.
NEW QUESTION # 280
You work for a manufacturing plant that batches application log files together into a single log file once a
day at 2:00 AM. You have written a Google Cloud Dataflow job to process that log file. You need to make
sure the log file in processed once per day as inexpensively as possible. What should you do?
Answer: A
NEW QUESTION # 281
A live TV show asks viewers to cast votes using their mobile phones. The event generates a large volume of data during a 3 minute period. You are in charge of the Voting restructure* and must ensure that the platform can handle the load and Hal all votes are processed. You must display partial results write voting is open. After voting doses you need to count the votes exactly once white optimizing cost. What should you do?
Answer: A
Explanation:
D Create a Cloud SQL for PostgreSQL database with high availability (HA) configuration and multiple read replicas
NEW QUESTION # 282
You are troubleshooting your Dataflow pipeline that processes data from Cloud Storage to BigQuery. You have discovered that the Dataflow worker nodes cannot communicate with one another Your networking team relies on Google Cloud network tags to define firewall rules You need to identify the issue while following Google-recommended networking security practices. What should you do?
Answer: A
Explanation:
Dataflow worker nodes need to communicate with each other and with the Dataflow service on TCP ports
12345 and 12346. These ports are used for data shuffling and streaming engine communication. By default, Dataflow assigns a network tag called dataflow to the worker nodes, and creates a firewall rule that allows traffic on these ports for the dataflow network tag. However, if you use a custom network tag for your Dataflow pipeline, you need to create a firewall rule that allows traffic on these ports for your custom network tag. Otherwise, the worker nodes will not be able to communicate with each other and the Dataflow service, and the pipeline will fail.
Therefore, the best way to identify the issue is to determine whether there is a firewall rule set to allow traffic on TCP ports 12345 and 12346 for the Dataflow network tag. If there is no such firewall rule, or if the firewall rule does not match the network tag used by your Dataflow pipeline, you need to create or update the firewall rule accordingly.
Option A is not a good solution, as determining whether your Dataflow pipeline has a custom network tag set does not tell you whether there is a firewall rule that allows traffic on the required ports for that network tag.
You need to check the firewall rule as well.
Option C is not a good solution, as determining whether your Dataflow pipeline is deployed with the external IP address option enabled does not tell you whether there is a firewall rule that allows traffic on the required ports for the Dataflow network tag. The external IP address option determines whether the worker nodes can access resources on the public internet, but it does not affect the internal communication between the worker nodes and the Dataflow service.
Option D is not a good solution, as determining whether there is a firewall rule set to allow traffic on TCP ports 12345 and 12346 on the subnet used by Dataflow workers does not tell you whether the firewall rule applies to the Dataflow network tag. The firewall rule should be based on the network tag, not the subnet, as the network tag is more specific and secure. References: Dataflow network tags | Cloud Dataflow | Google Cloud, Dataflow firewall rules | Cloud Dataflow | Google Cloud, Dataflow network configuration | Cloud Dataflow | Google Cloud, Dataflow Streaming Engine | Cloud Dataflow | Google Cloud.
NEW QUESTION # 283
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