Professional-Data-Engineer試験番号 - Professional-Data-Engineer模擬試験サンプル、Google Certified Professional-Data-Engineer Exam - Royalholidayclubbed

 

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この問題集は最近更新されたもので、実際試験で出題される可能性がある問題をすべて含んでいて、あなたが一回で成功することを保証できますから。この問題集は信じられないほどの良い成果を見せます。試験に失敗すればRoyalholidayclubbedは全額返金のことができますから、ご安心に問題集を利用してください。 そうしたらあなたはRoyalholidayclubbedが用意した問題集にもっと自信があります。早くRoyalholidayclubbedの問題集を君の手に入れましょう。 RoyalholidayclubbedのGoogleのProfessional-Data-Engineer試験番号を利用した大勢の人々によると、GoogleのProfessional-Data-Engineer試験番号試験の合格率は100パーセントに達したのです。

Google Cloud Certified Professional-Data-Engineer できるだけ100%の通過率を保証使用にしています。

Google Cloud Certified Professional-Data-Engineer試験番号 - Google Certified Professional Data Engineer Exam あなたにとても良い指導を確保できて、試験に合格するのを助けって、Royalholidayclubbedからすぐにあなたの通行証をとります。 ただ、社会に入るIT卒業生たちは自分能力の不足で、Professional-Data-Engineer 受験料試験向けの仕事を探すのを悩んでいますか?それでは、弊社のGoogleのProfessional-Data-Engineer 受験料練習問題を選んで実用能力を速く高め、自分を充実させます。その結果、自信になる自己は面接のときに、面接官のいろいろな質問を気軽に回答できて、順調にProfessional-Data-Engineer 受験料向けの会社に入ります。

RoyalholidayclubbedはきみのIT夢に向かって力になりますよ。GoogleのProfessional-Data-Engineer試験番号の認証そんなに人気があって、Royalholidayclubbedも君の試験に合格するために全力で助けてあげて、またあなたを一年の無料なサービスの更新を提供します。明日の成功のためにRoyalholidayclubbedを選らばましょう。

Google Professional-Data-Engineer試験番号 - 君の夢は1歩更に近くなります。

GoogleのProfessional-Data-Engineer試験番号の認定試験に合格すれば、就職機会が多くなります。この試験に合格すれば君の専門知識がとても強いを証明し得ます。GoogleのProfessional-Data-Engineer試験番号の認定試験は君の実力を考察するテストでございます。

ところが、GoogleのProfessional-Data-Engineer試験番号の試験にどうやって合格しますか。心配することはないですよ、ヘルプがあなたの手元にありますから。

Professional-Data-Engineer PDF DEMO:

QUESTION NO: 1
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: 2
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: 3
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: 4
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

QUESTION NO: 5
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

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Updated: May 27, 2022

 

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