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Professional-Data-Engineer資格参考書、Professional-Data-Engineer試験時間 - Google Professional-Data-Engineer合格体験記 - Royalholidayclubbed
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GoogleのProfessional-Data-Engineer資格参考書試験に合格するのは説得力を持っています。我々ができるのはあなたにより速くGoogleのProfessional-Data-Engineer資格参考書試験に合格させます。数年間の発展で我々Royalholidayclubbedはもっと多くの資源と経験を得ています。 RoyalholidayclubbedのProfessional-Data-Engineer資格参考書問題集の合格率が100%に達することも数え切れない受験生に証明された事実です。もし試験の準備をするために大変を感じているとしたら、ぜひRoyalholidayclubbedのProfessional-Data-Engineer資格参考書問題集を見逃さないでください。 大方の人は成功への近道がないとよく言われますけど、IT人材にとって、私達のProfessional-Data-Engineer資格参考書問題集はあなたの成功へショートカットです。
Google Cloud Certified Professional-Data-Engineer Royalholidayclubbedは君にとってベストな選択になります。
我々Royalholidayclubbed提供するProfessional-Data-Engineer - Google Certified Professional Data Engineer Exam資格参考書問題集を通して、試験に迅速的にパースする技をファンドできます。 うちのGoogleのProfessional-Data-Engineer 学習体験談試験トレーニング資料を購入する前に、Royalholidayclubbedのサイトで、一部分のフリーな試験問題と解答をダンロードでき、試用してみます。君がうちの学習教材を購入した後、私たちは一年間で無料更新サービスを提供することができます。
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Google Professional-Data-Engineer資格参考書 - 我々の誠意を信じてください。
現在の社会で、Professional-Data-Engineer資格参考書試験に参加する人がますます多くなる傾向があります。市場の巨大な練習材料からProfessional-Data-Engineer資格参考書の学習教材を手に入れようとする人も増えています。 私たちのProfessional-Data-Engineer資格参考書試験問題を利用し、ほかの資料が克服できない障害を克服できます。 多くの受験者は、私たちのProfessional-Data-Engineer資格参考書練習試験をすることに特権を感じています。 そして、私たちのウェブサイトは、市場でのとても有名で、インターネット上で簡単に見つけられます。
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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
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