퍼펙트한 시험대비자료

GCP-DE 최신덤프는 GCP-DE실제시험의 모든 범위를 커버하고 있고 모든 시험유형이 포함되어 있어 시험대비 공부의 완벽한 선택입니다.최신버전 덤프는 Data Engineer시험문제에 근거하여 만들어진 시험준비 공부가이드로서 학원공부 필요없이 덤프공부 만으로도 시험을 한방에 패스할수 있습니다.자격증을 취득하시면 국제적으로 인정받기에 취직이나 승진 혹은 이직에 힘을 가해드립니다.

시험전 20-30시간의 공부시간

자격증을 취득하려면 오랜시간동안 시험공부를 해야 한다고 생각하시는 분들이 많습니다. 하지만 이는 GCP-DE덤프가 아닌 다른 공부방법에 적용되는 보편적인 생각일뿐입니다. GCP-DE덤프를 공부하시는데는 20~30시간만 사용하시면 됩니다.덤프만 있으면 다른 공부자료는 필요하지 않습니다.덤프는 Data Engineer시험문제의 모든 범위와 유형을 포함하고 있어 GCP-DE덤프에 있는 문제와 답만 기억하시면 시험문제가 변경되지 않는다면 합격을 예약한것과 같다고 보시면 됩니다.

구매전 덤프 샘플문제 다운

GCP-DE덤프를 구매하기전에 사이트에서 해당 덤프의 무료샘플을 다운받아 덤프품질을 체크해보실수 있습니다. Data Engineer덤프를 구매하시면 구매일로부터 1년내에 덤프가 업데이트된다면 업데이트된 버전을 무료로 제공해드립니다.만약 GCP-DE덤프를 구매하고 공부한후 GCP-DE시험에서 떨어지면 60일내 주문은 덤프비용 전액을 환불해드려 고객님의 이익을 최대한 보장해드립니다.

우선 시험센터에서 정확한 시험코드를 확인하고 그 코드와 동일한 코드로 되어있는 덤프를 구매하셔서 덤프에 있는 문제와 답을 기억하시면 시험을 쉽게 패스하실수 있습니다. GCP-DE덤프는 가장 최근 기출문제를 기준으로 제작되기에 Data Engineer시험문제가 변경되지 않는한 100%에 가까운 적중율을 보장해 시험에서 패스하는데 가장 좋은 동반자로 되어드릴것입니다.

DOWNLOAD DEMO

최신 Google Cloud Certified GCP-DE 무료샘플문제:

1. You need to choose a database for a new project that has the following requirements:
Fully managed
Able to automatically scale up
Transactionally consistent
Able to scale up to 6 TB
Able to be queried using SQL Which database do you choose?

A) Cloud Bigtable
B) Cloud Spanner
C) Cloud SQL
D) Cloud Datastore

2. You are planning to migrate your current on-premises Apache Hadoop deployment to the cloud. You need to ensure that the deployment is as fault-tolerant and cost-effective as possible for long-running batch jobs. You want to use a managed service. What should you do?

A) Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://
B) Install Hadoop and Spark on a 10-node Compute Engine instance group with preemptible instances.Store data in HDF
C) Use an SSD persistent disk and 50% preemptible worker
D) Change references in scripts from hdfs:// to gs://
E) Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://
F) Change references in scripts from hdfs:// to gs://
G) Use a standard persistent disk and 50% preemptible worker
H) Install the Cloud Storage connector, and store the data in Cloud Storag
I) Deploy a Cloud Dataproc cluste
J) Deploy a Cloud Dataproc cluste
K) Install Hadoop and Spark on a 10-node Compute Engine instance group with standard instance

3. You are integrating one of your internal IT applications and Google BigQuery, so users can query BigQuery from the application's interface. You do not want individual users to authenticate to BigQuery and you do not want to give them access to the dataset. You need to securely access BigQuery from your IT application.
What should you do?

A) Use the service account's private key to access the dataset
B) Integrate with a single sign-on (SSO) platform, and pass each user's credentials along with the query request
C) Create groups for your users and give those groups access to the dataset
D) Create a service account and grant dataset access to that accoun
E) Create a dummy user and grant dataset access to that use
F) Store the username and password for that user in a file on the files system, and use those credentials to access the BigQuery dataset

4. Which row keys are likely to cause a disproportionate number of reads and/or writes on a particular node in a Bigtable cluster (select 2 answers)?

A) A non-sequential numeric ID
B) A sequential numeric ID
C) A stock symbol followed by a timestamp
D) A timestamp followed by a stock symbol

5. You want to migrate an on-premises Hadoop system to Cloud Dataproc. Hive is the primary tool in use, and the data format is Optimized Row Columnar (ORC). All ORC files have been successfully copied to a Cloud Storage bucket. You need to replicate some data to the cluster's local Hadoop Distributed File System (HDFS) to maximize performance. What are two ways to start using Hive in Cloud Dataproc? (Choose two.)

A) Then run the Hadoop utility to copy them do HDF
B) Replicate external Hive tables to the native ones.
C) Leverage BigQuery connector for Hadoop to mount the BigQuery tables as external Hive table
D) Load the ORC files into BigQuer
E) Mount the Hive tables locally.
F) Mount the Hive tables locally.
G) Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to HDF
H) Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to any node of the Dataproc cluste
I) Leverage Cloud Storage connector for Hadoop to mount the ORC files as external Hive table
J) Replicate external Hive tables to the native ones.
K) Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to the master node of the Dataproc cluste
L) Mount the Hive tables from HDFS.

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