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Google Cloud Certified Professional-Data-Engineer しかし、あまりにも心配する必要はありません。

Google Cloud Certified Professional-Data-Engineer問題数 - Google Certified Professional Data Engineer Exam 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 復習時間認定試験に関連する知識を学んで自分のスキルを向上させ、Professional-Data-Engineer 復習時間認証資格を通して他人の認可を得たいですか。Googleの認定試験はあなたが自分自身のレベルを高めることができます。

きみはGoogleのProfessional-Data-Engineer問題数認定テストに合格するためにたくさんのルートを選択肢があります。Shobhadoshiは君のために良い訓練ツールを提供し、君のGoogle認証試に高品質の参考資料を提供しいたします。あなたの全部な需要を満たすためにいつも頑張ります。

Google Professional-Data-Engineer問題数 - 常々、時間とお金ばかり効果がないです。

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我々の提供する問題集を体験してから、あなたはGoogleのProfessional-Data-Engineer問題数試験に合格できる自信を持っています。IT業界で働いている多くの人はGoogleのProfessional-Data-Engineer問題数試験の準備が大変だと知っています。

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 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

試験の準備をするためにShobhadoshiのGoogleのACAMS CAMS-JP試験トレーニング資料を買うのは冒険的行為と思ったとしたら、あなたの人生の全てが冒険なことになります。 ほかの人がインタネットでゲームを遊んでいるとき、あなたはオンラインでGoogleのPegasystems PEGACPLSA24V1の問題集をすることができます。 真剣にShobhadoshiのGoogle GIAC GEIR問題集を勉強する限り、受験したい試験に楽に合格することができるということです。 このように、客様は我々のMicrosoft AZ-800問題集を手に入れて勉強したら、試験に合格できるかのを心配することはありません。 VMware 6V0-21.25 - がむしゃらに試験に関連する知識を勉強しているのですか。

Updated: May 27, 2022