現在、認証試験に合格したいのならOmgzlook のGoogleのProfessional-Data-Engineer日本語版復習指南トレーニング資料を利用してください。さあ、最新のOmgzlook のGoogleのProfessional-Data-Engineer日本語版復習指南問題集にショッピングカートに入れましょう。あなたに予想外の良い効果を見せられますから。 そうしたらあなたはOmgzlookが用意した問題集にもっと自信があります。早くOmgzlookの問題集を君の手に入れましょう。 Professional-Data-Engineer日本語版復習指南認定試験の目標が変更されば、Omgzlookが提供した勉強資料も変化に追従して内容を変えます。
Google Cloud Certified Professional-Data-Engineer Omgzlookには専門的なエリート団体があります。
Google Cloud Certified Professional-Data-Engineer日本語版復習指南 - Google Certified Professional Data Engineer Exam 当社の製品を利用したら、一年間の無料更新サービスを提供します。 試験の目標が変わる限り、あるいは我々の勉強資料が変わる限り、すぐに更新して差し上げます。あなたのニーズをよく知っていていますから、あなたに試験に合格する自信を与えます。
順調にIT認定試験に合格したいなら、Omgzlookはあなたの唯一の選択です。Omgzlookに提供されている資料はIT認定試験に対して10年過ぎの経験を持っているプロフェッショナルによって研究と実践を通じて作成し出されたものです。Omgzlookは最新かつ最も正確な試験Professional-Data-Engineer日本語版復習指南問題集を用意しておきます。
Google Professional-Data-Engineer日本語版復習指南 - 不思議を思っていますか。
IT技術の急速な発展につれて、IT認証試験の問題は常に変更されています。したがって、OmgzlookのProfessional-Data-Engineer日本語版復習指南問題集も絶えずに更新されています。それに、Omgzlookの教材を購入すれば、Omgzlookは一年間の無料アップデート・サービスを提供してあげます。問題が更新される限り、Omgzlookは直ちに最新版のProfessional-Data-Engineer日本語版復習指南資料を送ってあげます。そうすると、あなたがいつでも最新バージョンの資料を持っていることが保証されます。Omgzlookはあなたが試験に合格するのを助けることができるだけでなく、あなたは最新の知識を学ぶのを助けることもできます。このような素晴らしい資料をぜひ見逃さないでください。
それはもちろんOmgzlookのProfessional-Data-Engineer日本語版復習指南問題集ですよ。Professional-Data-Engineer日本語版復習指南試験の準備をするとき、がむしゃらにITに関連する知識を学ぶのは望ましくない勉強法です。
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 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: 3
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: 4
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: 5
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
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Updated: May 27, 2022