Professional-Data-Engineer学習体験談、Professional-Data-Engineer資格取得講座 - Google Professional-Data-Engineer過去問 - Royalholidayclubbed

Name: Google Professional-Data-Engineer
Brand: Google
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Google Cloud Certified Professional-Data-Engineer どうするか全然分からないですか。

努力すれば報われますなので、Google　Professional-Data-Engineer - Google Certified Professional Data Engineer Exam学習体験談資格認定を取得して自分の生活状況を改善できます。受験生の皆さんを試験に合格させることを旨とするだけでなく、皆さんに最高のサービスを提供することも目標としています。Royalholidayclubbedはあなたが完全に信頼できるウェブサイトです。

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Google Professional-Data-Engineer学習体験談 - きっと君に失望させないと信じています。

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我々は受験生の皆様により高いスピードを持っているかつ効率的なサービスを提供することにずっと力を尽くしていますから、あなたが貴重な時間を節約することに助けを差し上げます。Royalholidayclubbed GoogleのProfessional-Data-Engineer学習体験談試験問題集はあなたに問題と解答に含まれている大量なテストガイドを提供しています。

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 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: 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

励ましだけであなたの試験への自信を高めるのは不可能だと知っていますから、我々は効果的なソフトを提供してあなたにGoogleのSAP C_S4TM_2023試験に合格させます。 Royalholidayclubbedが提供したGoogleのFortinet FCP_ZCS_AD-7.4トレーニング資料を利用したら、GoogleのFortinet FCP_ZCS_AD-7.4認定試験に受かることはたやすくなります。我々のウェブサイトであなたはGoogleのSnowflake DEA-C02試験のソフトを購入できます。 Google Professional-Cloud-DevOps-Engineer-JPN - あなたが自分のキャリアでの異なる条件で自身の利点を発揮することを助けられます。 GoogleのThe Open Group OGEA-101資格認定証明書を持つ人は会社のリーダーからご格別のお引き立てを賜ったり、仕事の昇進をたやすくなったりしています。

Updated: May 27, 2022

by RHC.

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