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Google Cloud Certified Professional-Data-Engineer まだ何を待っていますか。

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現在IT技術会社に通勤しているあなたは、GoogleのProfessional-Data-Engineerテスト問題集試験認定を取得しましたか？Professional-Data-Engineerテスト問題集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テスト問題集試験に一発合格したいなら、我々社のGoogleのProfessional-Data-Engineerテスト問題集資料を参考しましょう。また、Professional-Data-Engineerテスト問題集問題集に疑問があると、メールで問い合わせてください。

Google Professional-Data-Engineerテスト問題集試験備考資料の整理を悩んでいますか。

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テスト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テスト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テスト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。

まだどうのようにGoogle　Professional-Data-Engineerテスト問題集資格認定試験にパースすると煩悩していますか。現時点で我々サイトNewValidDumpsを通して、ようやくこの問題を心配することがありませんよ。

Professional-Data-Engineer PDF DEMO:

QUESTION NO: 1
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: 2
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: 3
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: 4
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: 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

CompTIA 220-1101 - 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。 従って、Juniper JN0-664試験資料を勉強する時間が短くてもいいです。 あなたにGoogle　Oracle 1z1-808J試験に関する最新かつ最完備の資料を勉強させ、試験に合格させることだと信じます。 Microsoft MB-230 - いまの市場にとてもよい問題集が探すことは難しいです。 周りの多くの人は全部Google　Google Associate-Cloud-Engineer資格認定試験にパースしまして、彼らはどのようにできましたか。

Updated: May 27, 2022