時間が経つとともに、我々はインタネット時代に生活します。この時代にはIT資格認証を取得するは重要になります。それでは、Professional-Data-Engineer資料勉強試験に参加しよう人々は弊社Goldmile-InfobizのProfessional-Data-Engineer資料勉強問題集を選らんで勉強して、一発合格して、GoogleIT資格証明書を受け取れます。 それも受験生たちが実践を通して証明したことです。インターネットで高品質かつ最新のGoogleのProfessional-Data-Engineer資料勉強の試験の資料を提供していると言うサイトがたくさんあります。 無事試験に合格しました。
Professional-Data-Engineer資料勉強試験は難しいです。
GoogleのProfessional-Data-Engineer - Google Certified Professional Data Engineer Exam資料勉強試験に受かるのはあなたが自分をIT業種にアピールする方法の一つです。 Google Professional-Data-Engineer 日本語版参考資料試験の合格のために、Goldmile-Infobizを選択してください。Goldmile-InfobizはGoogleのProfessional-Data-Engineer 日本語版参考資料「Google Certified Professional Data Engineer Exam」試験に関する完全な資料を唯一のサービスを提供するサイトでございます。
そうだったら、Goldmile-Infobizを利用したください。GoogleのProfessional-Data-Engineer資料勉強認定試験に受かることを悩んでいたら、Goldmile-Infobizを選びましょう。Goldmile-InfobizのGoogleのProfessional-Data-Engineer資料勉強試験トレーニング資料は間違いなく最高のトレーニング資料ですから、それを選ぶことはあなたにとって最高の選択です。
Google Professional-Data-Engineer資料勉強 - これは試験に合格する最速のショートカットです。
Goldmile-Infobizを選択したら、成功が遠くではありません。Goldmile-Infobizが提供するGoogleのProfessional-Data-Engineer資料勉強認証試験問題集が君の試験に合格させます。テストの時に有効なツルが必要でございます。
そうだったら、下記のものを読んでください。いまProfessional-Data-Engineer資料勉強試験に合格するショートカットを教えてあげますから。
Professional-Data-Engineer PDF DEMO:
QUESTION NO: 1
You are building a model to make clothing recommendations. You know a user's fashion preference is likely to change over time, so you build a data pipeline to stream new data back to the model as it becomes available.
How should you use this data to train the model?
A. Continuously retrain the model on just the new data.
B. Continuously retrain the model on a combination of existing data and the new data.
C. Train on the new data while using the existing data as your test set.
D. Train on the existing data while using the new data as your test set.
Answer: C
QUESTION NO: 2
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: 3
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: 4
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: 5
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
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Updated: May 27, 2022