Professional-Data-Engineer資格認定 & Google Certified Professional-Data-Engineer Exam復習教材 - Royalholidayclubbed

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あなたはインターネットでGoogleのProfessional-Data-Engineer資格認定認証試験の練習問題と解答の試用版を無料でダウンロードしてください。そうしたらあなたはRoyalholidayclubbedが用意した問題集にもっと自信があります。早くRoyalholidayclubbedの問題集を君の手に入れましょう。しかし、成功には方法がありますよ。正確な選択をしたら、そんなに苦労しなくても成功することもできます。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Royalholidayclubbedを選択してください。

Google Cloud Certified Professional-Data-Engineer しかも、昇進と高給も実現できます。

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Royalholidayclubbedには専門的なエリート団体があります。認証専門家や技術者及び全面的な言語天才がずっと最新のGoogleのProfessional-Data-Engineer資格認定試験を研究していますから、GoogleのProfessional-Data-Engineer資格認定認定試験に受かりたかったら、Royalholidayclubbedのサイトをクッリクしてください。あなたに成功に近づいて、夢の楽園に一歩一歩進めさせられます。

Google Professional-Data-Engineer資格認定認定試験の準備を完了したのですか。

人生にはあまりにも多くの変化および未知の誘惑がありますから、まだ若いときに自分自身のために強固な基盤を築くべきです。あなた準備しましたか。RoyalholidayclubbedのGoogleのProfessional-Data-Engineer資格認定試験トレーニング資料は最高のトレーニング資料です。IT職員としてのあなたは切迫感を感じましたか。Royalholidayclubbedを選んだら、成功への扉を開きます。頑張ってください。

私たちのIT専門家は受験生のために、最新的なGoogleのProfessional-Data-Engineer資格認定問題集を提供します。うちの学習教材の高い正確性は言うまでもありません。

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
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: 3
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: 4
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: 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

by RHC.

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