Professional-Data-Engineer試験攻略、Google Professional-Data-Engineer学習指導 - Google Certified Professional-Data-Engineer Exam - Royalholidayclubbed

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でも、受かることが難しいですから、トレーニングツールを利用するのを勧めます。トレーニング資料を選びたいのなら、RoyalholidayclubbedのGoogleのProfessional-Data-Engineer試験攻略試験トレーニング資料は最高の選択です。この資料の成功率が１００パーセントに達して、あなたが試験に合格することを保証します。 RoyalholidayclubbedのGoogleのProfessional-Data-Engineer試験攻略試験問題資料は質が良くて値段が安い製品です。我々は低い価格と高品質の模擬問題で受験生の皆様に捧げています。 RoyalholidayclubbedのGoogleのProfessional-Data-Engineer試験攻略試験トレーニング資料は信頼できるもので、１００パーセントの合格率を保証します。

Google Cloud Certified Professional-Data-Engineer 成功の楽園にどうやって行きますか。

Google Cloud Certified Professional-Data-Engineer試験攻略 - Google Certified Professional Data Engineer Exam 」とゴーリキーは述べました。それに、万一の場合、問題集を利用してからやはり試験に失敗すれば、Royalholidayclubbedは全額返金のことを約束します。こうすれば、まだ何を心配しているのですか。

さて、はやく試験を申し込みましょう。Royalholidayclubbedはあなたを助けることができますから、心配する必要がないですよ。あなたの夢は何ですか。

Google Professional-Data-Engineer試験攻略 - まだ何を待っていますか。

RoyalholidayclubbedのGoogleのProfessional-Data-Engineer試験攻略試験トレーニング資料は豊富な経験を持っているIT専門家が研究したものです。君がGoogleのProfessional-Data-Engineer試験攻略問題集を購入したら、私たちは一年間で無料更新サービスを提供することができます。もしGoogleのProfessional-Data-Engineer試験攻略問題集は問題があれば、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。

自分自身のIT技能を増強したいか。一回だけでGoogleのProfessional-Data-Engineer試験攻略認定試験に合格したいか。

Professional-Data-Engineer PDF DEMO:

QUESTION NO: 1
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: 2
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: 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
Your startup has never implemented a formal security policy. Currently, everyone in the company has access to the datasets stored in Google BigQuery. Teams have freedom to use the service as they see fit, and they have not documented their use cases. You have been asked to secure the data warehouse. You need to discover what everyone is doing. What should you do first?
A. Use the Google Cloud Billing API to see what account the warehouse is being billed to.
B. Use Stackdriver Monitoring to see the usage of BigQuery query slots.
C. Get the identity and access management IIAM) policy of each table
D. Use Google Stackdriver Audit Logs to review data access.
Answer: B

QUESTION NO: 5
You need to create a near real-time inventory dashboard that reads the main inventory tables in your BigQuery data warehouse. Historical inventory data is stored as inventory balances by item and location. You have several thousand updates to inventory every hour. You want to maximize performance of the dashboard and ensure that the data is accurate. What should you do?
A. Use the BigQuery streaming the stream changes into a daily inventory movement table. Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.
B. Use the BigQuery bulk loader to batch load inventory changes into a daily inventory movement table.
Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.
C. Leverage BigQuery UPDATE statements to update the inventory balances as they are changing.
D. Partition the inventory balance table by item to reduce the amount of data scanned with each inventory update.
Answer: C

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Updated: May 27, 2022

by RHC.

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