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Professional-Data-Engineer日本語受験攻略 & Professional-Data-Engineer日本語版問題集 - Professional-Data-Engineer受験内容 - Royalholidayclubbed
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どの版でもGoogleのProfessional-Data-Engineer日本語受験攻略試験の復習資料は効果的なのを保証します。あなたはどのような方式で試験を準備するのが好きですか。PDF、オンライン問題集または模擬試験ソフトですか。 我々は心からあなたが首尾よく試験に合格することを願っています。あなたに便利なオンラインサービスを提供して、Google Professional-Data-Engineer日本語受験攻略試験問題についての全ての質問を解決して差し上げます。 全日でのオンライン係員、GoogleのProfessional-Data-Engineer日本語受験攻略試験資料のデモ、豊富なバーション、GoogleのProfessional-Data-Engineer日本語受験攻略試験資料を購入した後の無料更新、試験に失敗した後の全額の返金…これら全部は我々Royalholidayclubbedが信頼される理由です。
Google Cloud Certified Professional-Data-Engineer 「信仰は偉大な感情で、創造の力になれます。
弊社のProfessional-Data-Engineer - Google Certified Professional Data Engineer Exam日本語受験攻略試験問題集によって、あなたの心と精神の満足度を向上させながら、勉強した後Professional-Data-Engineer - Google Certified Professional Data Engineer Exam日本語受験攻略試験資格認定書を受け取って努力する人生はすばらしいことであると認識られます。 あなたの夢は何ですか。あなたのキャリアでいくつかの輝かしい業績を行うことを望まないのですか。
Google Professional-Data-Engineer日本語受験攻略試験問題集を購買してから、一年間の無料更新を楽しみにしています。あなたにGoogle Professional-Data-Engineer日本語受験攻略試験に関する最新かつ最完備の資料を勉強させ、試験に合格させることだと信じます。もしあなたはProfessional-Data-Engineer日本語受験攻略試験に合格しなかったら、全額返金のことを承諾します。
Google Professional-Data-Engineer日本語受験攻略 - 試験に失敗したら、全額で返金する承諾があります。
Royalholidayclubbedは最高な品質で最速なスピードでGoogleのProfessional-Data-Engineer日本語受験攻略認定試験の資料を更新するサイトでございます。もしかすると君はほかのサイトもGoogleのProfessional-Data-Engineer日本語受験攻略認証試験に関する資料があるのを見つけた、比較したらRoyalholidayclubbedが提供したのがいちばん全面的で品質が最高なことがわかりました。
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。
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
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
QUESTION NO: 5
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
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Updated: May 27, 2022
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