Omgzlook의 Google Professional-Data-Engineer최신기출자료덤프를 구매하기전 우선 pdf버전 덤프샘플을 다운받아 덤프문제를 공부해보시면Omgzlook덤프품질에 신뢰가 느껴질것입니다. Omgzlook의 Google Professional-Data-Engineer최신기출자료덤프가 고객님의 시험패스테 조금이나마 도움이 되신다면 행복으로 느끼겠습니다. 다른 덤프들과 같이Google인증 Professional-Data-Engineer최신기출자료덤프 적중율과 패스율은 100% 보장해드립니다. Google인증 Professional-Data-Engineer최신기출자료시험에 도전하려는 분들은Omgzlook 의Google인증 Professional-Data-Engineer최신기출자료덤프로 시험을 준비할것이죠? 네트웨크시대인 지금 인터넷에 검색하면 수많은Google인증 Professional-Data-Engineer최신기출자료시험공부자료가 검색되는데 그중에서도Omgzlook에서 출시한 Google인증 Professional-Data-Engineer최신기출자료덤프가 가장 높은 인지도를 지니고 있습니다.
Google인증 Professional-Data-Engineer최신기출자료시험을 패스하는 방법은 많고도 많습니다.
국제공인자격증을 취득하여 IT업계에서 자신만의 자리를 잡고 싶으신가요? 자격증이 수없이 많은데Google Professional-Data-Engineer - Google Certified Professional Data Engineer Exam최신기출자료 시험패스부터 시작해보실가요? 100%합격가능한 Google Professional-Data-Engineer - Google Certified Professional Data Engineer Exam최신기출자료덤프는Google Professional-Data-Engineer - Google Certified Professional Data Engineer Exam최신기출자료시험문제의 기출문제와 예상문제로 되어있는 퍼펙트한 모음문제집으로서 시험패스율이 100%에 가깝습니다. Google 인증Professional-Data-Engineer 자격증문제 인증시험패스는 아주 어렵습니다. 자기에 맞는 현명한 학습자료 선택은 성공의 지름길을 내딛는 첫발입니다.
Omgzlook는 응시자에게 있어서 시간이 정말 소중하다는 것을 잘 알고 있으므로 Google Professional-Data-Engineer최신기출자료덤프를 자주 업데이트 하고, 오래 되고 더 이상 사용 하지 않는 문제들은 바로 삭제해버리며 새로운 최신 문제들을 추가 합니다. 이는 응시자가 확실하고도 빠르게Google Professional-Data-Engineer최신기출자료덤프를 마스터하고Google Professional-Data-Engineer최신기출자료시험을 패스할수 있도록 하는 또 하나의 보장입니다.
Google Professional-Data-Engineer최신기출자료 - Omgzlook는 아주 믿을만하고 서비스 또한 만족스러운 사이트입니다.
관심있는 인증시험과목Google Professional-Data-Engineer최신기출자료덤프의 무료샘플을 원하신다면 덤프구매사이트의 PDF Version Demo 버튼을 클릭하고 메일주소를 입력하시면 바로 다운받아Google Professional-Data-Engineer최신기출자료덤프의 일부분 문제를 체험해 보실수 있습니다. PDF버전외에 온라인버전과 테스트엔버전 Demo도 다운받아 보실수 있습니다.
Omgzlook의 덤프선택으로Google Professional-Data-Engineer최신기출자료인증시험에 응시한다는 것 즉 성공과 멀지 않았습니다. 여러분의 성공을 빕니다.
Professional-Data-Engineer PDF DEMO:
QUESTION NO: 1
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: 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
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 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
QUESTION NO: 5
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
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Updated: May 27, 2022