Professional-Data-Engineer試験問題集 & Google Certified Professional-Data-Engineer Exam復習内容 - Royalholidayclubbed

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それはRoyalholidayclubbedが受験生の注目を浴びる理由です。受験生の皆様は我々を信じて、依頼しています。これもRoyalholidayclubbedが実力を体現する点です。真剣にRoyalholidayclubbedのGoogle Professional-Data-Engineer試験問題集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。IT認定試験の中でどんな試験を受けても、RoyalholidayclubbedのProfessional-Data-Engineer試験問題集試験参考資料はあなたに大きなヘルプを与えることができます。 RoyalholidayclubbedにはIT専門家が組み立てられた団体があります。

Google Cloud Certified Professional-Data-Engineer IT認定試験には多くの種類があります。

無料デモはあなたに安心で購入して、購入した後1年間の無料GoogleのProfessional-Data-Engineer - Google Certified Professional Data Engineer Exam試験問題集試験の更新はあなたに安心で試験を準備することができます、あなたは確実に購入を休ませることができます私たちのソフトウェアを試してみてください。学歴はただ踏み台だけで、あなたの地位を確保できる礎は実力です。IT職員としているあなたがどうやって自分自身の実力を養うのですか。

我々の承諾だけでなく、お客様に最も全面的で最高のサービスを提供します。GoogleのProfessional-Data-Engineer試験問題集の購入の前にあなたの無料の試しから、購入の後での一年間の無料更新まで我々はあなたのGoogleのProfessional-Data-Engineer試験問題集試験に一番信頼できるヘルプを提供します。GoogleのProfessional-Data-Engineer試験問題集試験に失敗しても、我々はあなたの経済損失を減少するために全額で返金します。

Google Professional-Data-Engineer試験問題集 - ここには、私たちは君の需要に応じます。

社会と経済の発展につれて、多くの人はIT技術を勉強します。なぜならば、IT職員にとって、GoogleのProfessional-Data-Engineer試験問題集資格証明書があるのは肝心な指標であると言えます。自分の能力を証明するために、Professional-Data-Engineer試験問題集試験に合格するのは不可欠なことです。弊社のProfessional-Data-Engineer試験問題集真題を入手して、試験に合格する可能性が大きくなります。

Royalholidayclubbedは君のもっと輝い将来に助けられます。簡単にGoogleのProfessional-Data-Engineer試験問題集認定試験に合格したいか。

Professional-Data-Engineer PDF DEMO:

QUESTION NO: 1
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: 2
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: 3
You have a query that filters a BigQuery table using a WHERE clause on timestamp and ID columns. By using bq query - -dry_run you learn that the query triggers a full scan of the table, even though the filter on timestamp and ID select a tiny fraction of the overall data. You want to reduce the amount of data scanned by BigQuery with minimal changes to existing SQL queries. What should you do?
A. Recreate the table with a partitioning column and clustering column.
B. Create a separate table for each I
C. Use the LIMIT keyword to reduce the number of rows returned.
D. Use the bq query - -maximum_bytes_billed flag to restrict the number of bytes billed.
Answer: C

QUESTION NO: 4
You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:
* The user profile: What the user likes and doesn't like to eat
* The user account information: Name, address, preferred meal times
* The order information: When orders are made, from where, to whom
The database will be used to store all the transactional data of the product. You want to optimize the data schema. Which Google Cloud Platform product should you use?
A. BigQuery
B. Cloud Datastore
C. Cloud SQL
D. Cloud Bigtable
Answer: A

QUESTION NO: 5
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

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Updated: May 27, 2022

by RHC.

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