我々NewValidDumpsはGoogleのProfessional-Data-Engineer独学書籍試験の変化を注目しています。数年以来の試験問題集を研究しています。現在あなたに提供するのは大切なGoogleのProfessional-Data-Engineer独学書籍資料です。 現在IT技術会社に通勤しているあなたは、GoogleのProfessional-Data-Engineer独学書籍試験認定を取得しましたか？Professional-Data-Engineer独学書籍試験認定は給料の増加とジョブのプロモーションに役立ちます。短時間でProfessional-Data-Engineer独学書籍試験に一発合格したいなら、我々社のGoogleのProfessional-Data-Engineer独学書籍資料を参考しましょう。 今まで、弊社のNewValidDumpsのProfessional-Data-Engineer独学書籍問題集はそのスローガンに沿って協力します。

Google Cloud Certified Professional-Data-Engineer それはあなたが夢を実現することを助けられます。

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NewValidDumpsは多くの受験生を助けて彼らにGoogleのProfessional-Data-Engineer独学書籍試験に合格させることができるのは我々専門的なチームがGoogleのProfessional-Data-Engineer独学書籍試験を研究して解答を詳しく分析しますから。試験が更新されているうちに、我々はGoogleのProfessional-Data-Engineer独学書籍試験の資料を更新し続けています。できるだけ100％の通過率を保証使用にしています。

Google Professional-Data-Engineer独学書籍 - 暇の時間を利用して勉強します。

GoogleのProfessional-Data-Engineer独学書籍試験の認定はIT業種で欠くことができない認証です。では、どうやって、最も早い時間でGoogleのProfessional-Data-Engineer独学書籍認定試験に合格するのですか。NewValidDumpsは君にとって最高な選択になっています。NewValidDumpsのGoogleのProfessional-Data-Engineer独学書籍試験トレーニング資料はNewValidDumpsのIT専門家たちが研究して、実践して開発されたものです。その高い正確性は言うまでもありません。もし君はいささかな心配することがあるなら、あなたはうちの商品を購入する前に、NewValidDumpsは無料でサンプルを提供することができます。

多分、Professional-Data-Engineer独学書籍テスト質問の数が伝統的な問題の数倍である。Google　Professional-Data-Engineer独学書籍試験参考書は全ての知識を含めて、全面的です。

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