NewValidDumpsのGoogleのProfessional-Data-Engineer模擬対策試験トレーニング資料を利用して気楽に試験に合格しました。それはコストパフォーマンスが非常に高い資料ですから、もしあなたも私と同じIT夢を持っていたら、NewValidDumpsのGoogleのProfessional-Data-Engineer模擬対策試験トレーニング資料を利用してください。それはあなたが夢を実現することを助けられます。 その理由でこの試験はますます重視されるになります。NewValidDumps GoogleのProfessional-Data-Engineer模擬対策試験トレーニング資料はあなたが上記の念願を実現することを助けられるのです。 最近、GoogleのProfessional-Data-Engineer模擬対策試験は非常に人気のある認定試験です。

Google Cloud Certified Professional-Data-Engineer どんな困難にあっても、諦めないです。

現在、GoogleのProfessional-Data-Engineer - Google Certified Professional Data Engineer Exam模擬対策認定試験に受かりたいIT専門人員がたくさんいます。 おそらく、君たちは私たちのProfessional-Data-Engineer 更新版試験資料について何も知らないかもしれません。でも、私たちのProfessional-Data-Engineer 更新版試験資料のデモをダウンロードしてみると、全部わかるようになります。

NewValidDumpsは優れたIT情報のソースを提供するサイトです。NewValidDumpsで、あなたの試験のためのテクニックと勉強資料を見つけることができます。NewValidDumpsのGoogleのProfessional-Data-Engineer模擬対策試験トレーニング資料は豊富な知識と経験を持っているIT専門家に研究された成果で、正確度がとても高いです。

Google Professional-Data-Engineer模擬対策認定試験に合格することは難しいようですね。

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NewValidDumpsは君にとってベストな選択になります。ここには、私たちは君の需要に応じます。

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