Omgzlookの試験問題集を手にすると、どのような試験でも問題ではありません。GoogleのProfessional-Data-Engineer日本語版受験参考書認定試験を除いて、最近非常に人気がある試験はまたGoogle、Cisco、IBM、SAPなどの様々な認定試験があります。しかし、もしProfessional-Data-Engineer日本語版受験参考書認証資格を取りたいなら、OmgzlookのProfessional-Data-Engineer日本語版受験参考書問題集はあなたを願望を達成させることができます。 OmgzlookのITエリートたちは彼らの専門的な目で、最新的なGoogleのProfessional-Data-Engineer日本語版受験参考書試験トレーニング資料に注目していて、うちのGoogleのProfessional-Data-Engineer日本語版受験参考書問題集の高い正確性を保証するのです。もし君はいささかな心配することがあるなら、あなたはうちの商品を購入する前に、Omgzlookは無料でサンプルを提供することができます。 こんな保障がありますから、心配する必要は全然ないですよ。
GoogleのProfessional-Data-Engineer日本語版受験参考書試験に合格することができます。
我々Professional-Data-Engineer - Google Certified Professional Data Engineer Exam日本語版受験参考書問題集の通過率は高いので、90％の合格率を保証します。 しかし、我々Omgzlookチームは力を尽くしてあなたのGoogleのProfessional-Data-Engineer 専門トレーリング試験を準備する圧力を減少して規範的な模擬問題と理解しやすい解答分析はあなたにGoogleのProfessional-Data-Engineer 専門トレーリング試験に合格するコツを把握させます。試験に失敗したら、あなたのGoogleのProfessional-Data-Engineer 専門トレーリング試験の成績書を提供して確認してから我々はすべての費用をあなたに払い戻します。
それで、我々社の無料のGoogle Professional-Data-Engineer日本語版受験参考書デモを参考して、あなたに相応しい問題集を入手します。暇の時間を利用して勉強します。努力すれば報われますなので、Google Professional-Data-Engineer日本語版受験参考書資格認定を取得して自分の生活状況を改善できます。
GoogleのGoogle Professional-Data-Engineer日本語版受験参考書試験のほかの認証試験も大切なのです。
多分、Professional-Data-Engineer日本語版受験参考書テスト質問の数が伝統的な問題の数倍である。Google Professional-Data-Engineer日本語版受験参考書試験参考書は全ての知識を含めて、全面的です。そして、Professional-Data-Engineer日本語版受験参考書試験参考書の問題は本当の試験問題とだいたい同じことであるとわかります。Professional-Data-Engineer日本語版受験参考書試験参考書があれば,ほかの試験参考書を勉強する必要がないです。
時間が経つとともに、我々はインタネット時代に生活します。この時代にはIT資格認証を取得するは重要になります。
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 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