この問題集の合格率は高いので、多くのお客様からProfessional-Data-Engineer学習体験談問題集への好評をもらいました。Professional-Data-Engineer学習体験談問題集のカーバー率が高いので、勉強した問題は試験に出ることが多いです。だから、弊社の提供するProfessional-Data-Engineer学習体験談問題集を暗記すれば、きっと試験に合格できます。 Omgzlookだけ全面と高品質の問題集があるのではOmgzlookの専門家チームが彼らの長年のIT知識と豊富な経験で研究してしました。そして、Omgzlookに多くの受験生の歓迎されます。 Omgzlookは同業の中でそんなに良い地位を取るの原因は弊社のかなり正確な試験の練習問題と解答そえに迅速の更新で、このようにとても良い成績がとられています。
Google Cloud Certified Professional-Data-Engineer 試験に失敗したら、全額で返金いたします。
Google Cloud Certified Professional-Data-Engineer学習体験談 - Google Certified Professional Data Engineer Exam どんな業界で自分に良い昇進機会があると希望する職人がとても多いと思って、IT業界にも例外ではありません。 君が後悔しないようにもっと少ないお金を使って大きな良い成果を取得するためにOmgzlookを選択してください。Omgzlookはまた一年間に無料なサービスを更新いたします。
Omgzlookの専門家チームが君の需要を満たすために自分の経験と知識を利用してGoogleのProfessional-Data-Engineer学習体験談認定試験対策模擬テスト問題集が研究しました。模擬テスト問題集と真実の試験問題がよく似ています。一目でわかる最新の出題傾向でわかりやすい解説と充実の補充問題があります。
Google Professional-Data-Engineer学習体験談 - 我々のデモから感じられます。
現在IT技術会社に通勤しているあなたは、GoogleのProfessional-Data-Engineer学習体験談試験認定を取得しましたか？Professional-Data-Engineer学習体験談試験認定は給料の増加とジョブのプロモーションに役立ちます。短時間でProfessional-Data-Engineer学習体験談試験に一発合格したいなら、我々社のGoogleのProfessional-Data-Engineer学習体験談資料を参考しましょう。また、Professional-Data-Engineer学習体験談問題集に疑問があると、メールで問い合わせてください。
GoogleのProfessional-Data-Engineer学習体験談試験にリラクスで合格するのも可能性があります。我々Omgzlookの提供するGoogleのProfessional-Data-Engineer学習体験談試験のソフトを利用した多くのお客様はこのような感じがあります。
Professional-Data-Engineer PDF DEMO:
QUESTION NO: 1
MJTelco is building a custom interface to share data. They have these requirements:
* They need to do aggregations over their petabyte-scale datasets.
* They need to scan specific time range rows with a very fast response time (milliseconds).
Which combination of Google Cloud Platform products should you recommend?
A. Cloud Datastore and Cloud Bigtable
B. Cloud Bigtable and Cloud SQL
C. BigQuery and Cloud Bigtable
D. BigQuery and Cloud Storage
Answer: C
QUESTION NO: 2
You have Cloud Functions written in Node.js that pull messages from Cloud Pub/Sub and send the data to BigQuery. You observe that the message processing rate on the Pub/Sub topic is orders of magnitude higher than anticipated, but there is no error logged in Stackdriver Log Viewer. What are the two most likely causes of this problem? Choose 2 answers.
A. Publisher throughput quota is too small.
B. The subscriber code cannot keep up with the messages.
C. The subscriber code does not acknowledge the messages that it pulls.
D. Error handling in the subscriber code is not handling run-time errors properly.
E. Total outstanding messages exceed the 10-MB maximum.
Answer: B,D
QUESTION NO: 3
You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do?
A. Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery
B. Store the data in a file in a regional Google Cloud Storage bucket. Use Cloud Dataflow to query
BigQuery and combine the data programmatically with the data stored in Google Cloud Storage.
C. Store the data in Google Cloud Datastore. Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore
D. Load the data every 30 minutes into a new partitioned table in BigQuery.
Answer: D
QUESTION NO: 4
Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)?
A. A Dataproc cluster cannot have only preemptible workers.
B. Preemptible workers cannot store data.
C. Preemptible workers cannot use persistent disk.
D. If a preemptible worker is reclaimed, then a replacement worker must be added manually.
Answer: A,B
Explanation
The following rules will apply when you use preemptible workers with a Cloud Dataproc cluster:
Processing only-Since preemptibles can be reclaimed at any time, preemptible workers do not store data.
Preemptibles added to a Cloud Dataproc cluster only function as processing nodes.
No preemptible-only clusters-To ensure clusters do not lose all workers, Cloud Dataproc cannot create preemptible-only clusters.
Persistent disk size-As a default, all preemptible workers are created with the smaller of 100GB or the primary worker boot disk size. This disk space is used for local caching of data and is not available through HDFS.
The managed group automatically re-adds workers lost due to reclamation as capacity permits.
Reference: https://cloud.google.com/dataproc/docs/concepts/preemptible-vms
QUESTION NO: 5
Your company is using WHILECARD tables to query data across multiple tables with similar names. The SQL statement is currently failing with the following error:
# Syntax error : Expected end of statement but got "-" at [4:11]
SELECT age
FROM
bigquery-public-data.noaa_gsod.gsod
WHERE
age != 99
AND_TABLE_SUFFIX = '1929'
ORDER BY
age DESC
Which table name will make the SQL statement work correctly?
A. 'bigquery-public-data.noaa_gsod.gsod*`
B. 'bigquery-public-data.noaa_gsod.gsod'*
C. 'bigquery-public-data.noaa_gsod.gsod'
D. bigquery-public-data.noaa_gsod.gsod*
Answer: A
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Updated: May 27, 2022