IT인증시험문제는 수시로 변경됩니다. 이 점을 해결하기 위해Shobhadoshi의Google인증 Professional-Data-Engineer시험유효자료덤프도 시험변경에 따라 업데이트하도록 최선을 다하고 있습니다.시험문제 변경에 초점을 맞추어 업데이트를 진행한후 업데이트된Google인증 Professional-Data-Engineer시험유효자료덤프를 1년간 무료로 업데이트서비스를 드립니다. 더욱 안전한 지불을 위해 저희 사이트의 모든 덤프는paypal을 통해 지불을 완성하게 되어있습니다. Paypal을 거쳐서 지불하면 저희측에서Google Professional-Data-Engineer시험유효자료덤프를 보내드리지 않을시 paypal에 환불신청하실수 있습니다. 고득점으로 패스하시면 지인분들께 추천도 해주실거죠?

Google Cloud Certified Professional-Data-Engineer IT인증시험은 국제적으로 인정받는 자격증을 취득하는 과정이라 난이도가 아주 높습니다.

Google Professional-Data-Engineer - Google Certified Professional Data Engineer Exam시험유효자료인증시험을 패스하여 자격증을 취득하면 보다 쉽고 빠르게 승진할수 있고 연봉인상에도 많은 도움을 얻을수 있습니다. IT업계 취업 준비생이라면 국제적으로도 승인받는 IT인증자격증 정도는 몇개 취득해야 하지 않을가 싶습니다. Google인증 Professional-Data-Engineer Dumps시험을 통과하여 인기 자격증을 취득하시면 취업경쟁율이 제고되어 취업이 쉬워집니다.

만약Shobhadoshi를 선택하였다면 여러분은 반은 성공한 것입니다. 여러분은 아주 빠르게 안전하게 또 쉽게Google Professional-Data-Engineer시험유효자료인증시험 자격증을 취득하실 수 있습니다. 우리Shobhadoshi에서 제공되는 모든 덤프들은 모두 100%보장 도를 자랑하며 그리고 우리는 일년무료 업데이트를 제공합니다.

Google인증 Google Professional-Data-Engineer시험유효자료덤프는 기출문제와 예상문제로 되어있어 시험패스는 시간문제뿐입니다.

Shobhadoshi의Google Professional-Data-Engineer시험유효자료인증시험의 자료 메뉴에는Google Professional-Data-Engineer시험유효자료인증시험실기와Google Professional-Data-Engineer시험유효자료인증시험 문제집으로 나누어져 있습니다.우리 사이트에서 관련된 학습가이드를 만나보실 수 있습니다. 우리 Shobhadoshi의Google Professional-Data-Engineer시험유효자료인증시험자료를 자세히 보시면 제일 알맞고 보장도가 높으며 또한 제일 전면적인 것을 느끼게 될 것입니다.

Shobhadoshi의 Google인증 Professional-Data-Engineer시험유효자료덤프의 무료샘플을 이미 체험해보셨죠? Shobhadoshi의 Google인증 Professional-Data-Engineer시험유효자료덤프에 단번에 신뢰가 생겨 남은 문제도 공부해보고 싶지 않나요? Shobhadoshi는 고객님들의 시험부담을 덜어드리기 위해 가벼운 가격으로 덤프를 제공해드립니다. Shobhadoshi의 Google인증 Professional-Data-Engineer시험유효자료로 시험패스하다 더욱 넓고 좋은곳으로 고고싱 하세요.

Professional-Data-Engineer PDF DEMO:

QUESTION NO: 1
You have Cloud Functions written in Node.js that pull messages from Cloud Pub/Sub and send the data to BigQuery. You observe that the message processing rate on the Pub/Sub topic is orders of magnitude higher than anticipated, but there is no error logged in Stackdriver Log Viewer. What are the two most likely causes of this problem? Choose 2 answers.
A. Publisher throughput quota is too small.
B. The subscriber code cannot keep up with the messages.
C. The subscriber code does not acknowledge the messages that it pulls.
D. Error handling in the subscriber code is not handling run-time errors properly.
E. Total outstanding messages exceed the 10-MB maximum.
Answer: B,D

QUESTION NO: 2
MJTelco is building a custom interface to share data. They have these requirements:
* They need to do aggregations over their petabyte-scale datasets.
* They need to scan specific time range rows with a very fast response time (milliseconds).
Which combination of Google Cloud Platform products should you recommend?
A. Cloud Datastore and Cloud Bigtable
B. Cloud Bigtable and Cloud SQL
C. BigQuery and Cloud Bigtable
D. BigQuery and Cloud Storage
Answer: C

QUESTION NO: 3
You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do?
A. Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery
B. Store the data in a file in a regional Google Cloud Storage bucket. Use Cloud Dataflow to query
BigQuery and combine the data programmatically with the data stored in Google Cloud Storage.
C. Store the data in Google Cloud Datastore. Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore
D. Load the data every 30 minutes into a new partitioned table in BigQuery.
Answer: D

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 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

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Updated: May 27, 2022