我々Omgzlookは最も速いパースする方法をあげるし、PDF版、ソフト版、オンライン版の三つ種類版を提供します。PDF版、ソフト版、オンライン版は各自のメリットがあるので、あなたは自分の好きにするし、我々OmgzlookのGoogle Professional-Data-Engineer試験対策問題集デモを参考して選択できます。どんな版でも、Google Professional-Data-Engineer試験対策試験に合格するのには成功への助力です。 Omgzlookはずっと君のために最も正確なGoogleのProfessional-Data-Engineer試験対策「Google Certified Professional Data Engineer Exam」試験に関する資料を提供して、君が安心に選択することができます。君はオンラインで無料な練習問題をダウンロードできて、１００％で試験に合格しましょう。 激しく変化する世界に対応し、私たちのProfessional-Data-Engineer試験対策試験資料のガイドで、あなたの長所を発揮することができます。
Google Cloud Certified Professional-Data-Engineer 夢を持ったら実現するために頑張ってください。
Google Cloud Certified Professional-Data-Engineer試験対策 - Google Certified Professional Data Engineer Exam いまの市場にとてもよい問題集が探すことは難しいです。 最近、GoogleのProfessional-Data-Engineer トレーニング費用試験は非常に人気のある認定試験です。あなたもこの試験の認定資格を取得したいのですか。
Omgzlookで、あなたは一番良い準備資料を見つけられます。その資料は練習問題と解答に含まれています。弊社の資料があなたに練習を実践に移すチャンスを差し上げ、あなたはぜひGoogleのProfessional-Data-Engineer試験対策試験に合格して自分の目標を達成できます。
Google Professional-Data-Engineer試験対策 - 自分がやっていることに満足していますか。
暇な時間だけでGoogleのProfessional-Data-Engineer試験対策試験に合格したいのですか。我々の提供するPDF版のGoogleのProfessional-Data-Engineer試験対策試験の資料はあなたにいつでもどこでも読めさせます。我々もオンライン版とソフト版を提供します。すべては豊富な内容があって各自のメリットを持っています。あなたは各バーションのGoogleのProfessional-Data-Engineer試験対策試験の資料をダウンロードしてみることができ、あなたに一番ふさわしいバーションを見つけることができます。
実際にはそれは全く不要です。IT認定試験はあなたの思い通りに神秘的なものではありません。
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
Your startup has never implemented a formal security policy. Currently, everyone in the company has access to the datasets stored in Google BigQuery. Teams have freedom to use the service as they see fit, and they have not documented their use cases. You have been asked to secure the data warehouse. You need to discover what everyone is doing. What should you do first?
A. Use the Google Cloud Billing API to see what account the warehouse is being billed to.
B. Use Stackdriver Monitoring to see the usage of BigQuery query slots.
C. Get the identity and access management IIAM) policy of each table
D. Use Google Stackdriver Audit Logs to review data access.
Answer: B
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Updated: May 27, 2022