Professional-Data-Engineer熱門考古題介紹

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Professional-Data-Engineer PDF DEMO:

QUESTION NO: 1
For the best possible performance, what is the recommended zone for your Compute Engine instance and Cloud Bigtable instance?
A. Have both the Compute Engine instance and the Cloud Bigtable instance to be in different zones.
B. Have the Compute Engine instance in the furthest zone from the Cloud Bigtable instance.
C. Have the Cloud Bigtable instance to be in the same zone as all of the consumers of your data.
D. Have both the Compute Engine instance and the Cloud Bigtable instance to be in the same zone.
Answer: D
Explanation
It is recommended to create your Compute Engine instance in the same zone as your Cloud Bigtable instance for the best possible performance, If it's not possible to create a instance in the same zone, you should create your instance in another zone within the same region. For example, if your Cloud
Bigtable instance is located in us-central1-b, you could create your instance in us-central1-f. This change may result in several milliseconds of additional latency for each Cloud Bigtable request.
It is recommended to avoid creating your Compute Engine instance in a different region from your
Cloud Bigtable instance, which can add hundreds of milliseconds of latency to each Cloud Bigtable request.
Reference: https://cloud.google.com/bigtable/docs/creating-compute-instance

QUESTION NO: 2
You have an Apache Kafka Cluster on-prem with topics containing web application logs. You need to replicate the data to Google Cloud for analysis in BigQuery and Cloud Storage. The preferred replication method is mirroring to avoid deployment of Kafka Connect plugins.
What should you do?
A. Deploy the PubSub Kafka connector to your on-prem Kafka cluster and configure PubSub as a Sink connector. Use a Dataflow job to read fron PubSub and write to GCS.
B. Deploy a Kafka cluster on GCE VM Instances. Configure your on-prem cluster to mirror your topics to the cluster running in GCE. Use a Dataproc cluster or Dataflow job to read from Kafka and write to
GCS.
C. Deploy the PubSub Kafka connector to your on-prem Kafka cluster and configure PubSub as a
Source connector. Use a Dataflow job to read fron PubSub and write to GCS.
D. Deploy a Kafka cluster on GCE VM Instances with the PubSub Kafka connector configured as a Sink connector. Use a Dataproc cluster or Dataflow job to read from Kafka and write to GCS.
Answer: B

QUESTION NO: 3
Which Google Cloud Platform service is an alternative to Hadoop with Hive?
A. Cloud Datastore
B. Cloud Bigtable
C. BigQuery
D. Cloud Dataflow
Answer: C
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

QUESTION NO: 4
You want to use Google Stackdriver Logging to monitor Google BigQuery usage. You need an instant notification to be sent to your monitoring tool when new data is appended to a certain table using an insert job, but you do not want to receive notifications for other tables. What should you do?
A. Using the Stackdriver API, create a project sink with advanced log filter to export to Pub/Sub, and subscribe to the topic from your monitoring tool.
B. In the Stackdriver logging admin interface, enable a log sink export to Google Cloud Pub/Sub, and subscribe to the topic from your monitoring tool.
C. In the Stackdriver logging admin interface, and enable a log sink export to BigQuery.
D. Make a call to the Stackdriver API to list all logs, and apply an advanced filter.
Answer: C

QUESTION NO: 5
You need to create a near real-time inventory dashboard that reads the main inventory tables in your BigQuery data warehouse. Historical inventory data is stored as inventory balances by item and location. You have several thousand updates to inventory every hour. You want to maximize performance of the dashboard and ensure that the data is accurate. What should you do?
A. Use the BigQuery streaming the stream changes into a daily inventory movement table. Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.
B. Use the BigQuery bulk loader to batch load inventory changes into a daily inventory movement table.
Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.
C. Leverage BigQuery UPDATE statements to update the inventory balances as they are changing.
D. Partition the inventory balance table by item to reduce the amount of data scanned with each inventory update.
Answer: C

Shobhadoshi Google的EMC D-NWR-DY-01考試認證培訓資料是幫助每個IT人士實現自己人生宏偉目標的最好的方式方法,它包括了試題及答案,並且和真實的考試題目不相上下,真的是所謂稱得上是最好的別無二選的培訓資料。 Shobhadoshi網站在通過VMware 3V0-21.23資格認證考試的考生中有著良好的口碑。 Google的SAP C_HRHFC_2411考試認證將會從遙不可及變得綽手可得。 他們一直致力于為考生提供最好的學習資料,以確保您獲得的是最有價值的Google Microsoft SC-200考古題。 Scaled Agile SAFe-Agilist - 它可以讓你得到事半功倍的結果。

Updated: May 27, 2022

Professional-Data-Engineer熱門考古題,Professional-Data-Engineer考題套裝 - Google Professional-Data-Engineer考題資源

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考試編碼:Professional-Data-Engineer
考試名稱:Google Certified Professional Data Engineer Exam
更新時間:2025-06-07
問題數量:380題
Google Professional-Data-Engineer 最新考證

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軟體引擎

考試編碼:Professional-Data-Engineer
考試名稱:Google Certified Professional Data Engineer Exam
更新時間:2025-06-07
問題數量:380題
Google 最新 Professional-Data-Engineer 試題

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在線測試引擎

考試編碼:Professional-Data-Engineer
考試名稱:Google Certified Professional Data Engineer Exam
更新時間:2025-06-07
問題數量:380題
Google Professional-Data-Engineer 熱門證照

  下載免費試用


 

最新 Professional-Data-Engineer 考古題

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