Professional-Data-Engineer題庫資訊，Google Professional-Data-Engineer證照資訊 & Google Certified Professional-Data-Engineer Exam - Royalholidayclubbed

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通過Google Professional-Data-Engineer題庫資訊的認證考試可以提高你的IT職業技能。

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Royalholidayclubbed是一個能為很多參加Google Professional-Data-Engineer題庫資訊認證考試的IT行業專業人士提供相關輔導資料來幫助他們拿到Google Professional-Data-Engineer題庫資訊認證證書的網站。Royalholidayclubbed提供的學習資料是由Royalholidayclubbed的資深專家的豐富的行業經驗和專業知識研究出來的的，品質是很好，更新速度也非常快。並且我們提供的練習題是和真正的考試題目很接近的，幾乎是一樣的。

Google Professional-Data-Engineer題庫資訊 - 只要你用了它你就會發現，這一切都是真的。

Royalholidayclubbed為通過Professional-Data-Engineer題庫資訊考試提供最完整有效的方案，幫祝廣大考生在考試中獲得更多的優勢。確保你只獲得最新的和最有效的Google Professional-Data-Engineer題庫資訊考古題，我們也希望客戶能隨時隨地的訪問，于是有了多個版本的題庫資料。PDF版的題庫方便你閱讀，為你真實地再現Professional-Data-Engineer題庫資訊考試題目，軟件版本的題庫作為一個測試引擎，可以幫你模擬真實的Professional-Data-Engineer題庫資訊考試環境，為考生做好充足的考前準備。通過Google Professional-Data-Engineer題庫資訊考試不再是夢想，我們的考古題就可以確保你成功。

通過Professional-Data-Engineer題庫資訊認證考試好像是一件很難的事情。已經報名參加考試的你，現在正在煩惱應該怎麼準備考試嗎？如果是這樣的話，請看下面的內容，我現在告訴你通過Professional-Data-Engineer題庫資訊考試的捷徑。

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
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: 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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