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Google Cloud Certified Professional-Data-Engineer 弊社の商品が好きなのは弊社のたのしいです。

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あなたは新しい旅を始めることができ、人生の輝かしい実績を実現することができます。他の人の成功を見上げるよりも、自分の成功への努力をしたほうがよいです。ShobhadoshiのGoogleのProfessional-Data-Engineer専門知識訓練試験トレーニング資料はあなたの成功への第一歩です。

それはShobhadoshiのGoogle Professional-Data-Engineer専門知識訓練問題集です。

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ショートカットを選択し、テクニックを使用するのはより良く成功できるからです。Professional-Data-Engineer専門知識訓練認定試験に一発合格できる保障を得たいなら、Shobhadoshi のProfessional-Data-Engineer専門知識訓練問題集はあなたにとってユニークな、しかも最良の選択です。

Professional-Data-Engineer PDF DEMO:

QUESTION NO: 1
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: 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
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: 4
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: 5
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

Microsoft GH-300 - 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。 Adobe AD0-E727 - もし学習教材は問題があれば、或いは試験に不合格になる場合は、全額返金することを保証いたします。 ShobhadoshiのGoogleのPMI PMI-RMP試験トレーニング資料を手に入れたら、我々は一年間の無料更新サービスを提供します。 Shobhadoshiの GoogleのGoogle Professional-Data-Engineer試験トレーニング資料を手に入れるなら、君が他の人の一半の努力で、同じGoogleのGoogle Professional-Data-Engineer認定試験を簡単に合格できます。 Cisco 300-745 - Shobhadoshiを選んだら、成功への扉を開きます。

Updated: May 27, 2022