OmgzlookのGoogleのProfessional-Data-Engineer受験記試験トレーニング資料は最高のトレーニング資料です。IT職員としてのあなたは切迫感を感じましたか。Omgzlookを選んだら、成功への扉を開きます。 あなたはGoogleのProfessional-Data-Engineer受験記資格認定のために、他人より多くの時間をかかるんですか？OmgzlookのProfessional-Data-Engineer受験記問題集を紹介させてください。Professional-Data-Engineer受験記は専門家たちが長年の経験で研究分析した勉強資料です。 IT技術の急速な発展につれて、IT認証試験の問題は常に変更されています。
Google Cloud Certified Professional-Data-Engineer できるだけ100％の通過率を保証使用にしています。
Google Cloud Certified Professional-Data-Engineer受験記 - Google Certified Professional Data Engineer Exam しかし必ずしも大量の時間とエネルギーで復習しなくて、弊社が丹精にできあがった問題集を使って、試験なんて問題ではありません。 ただ、社会に入るIT卒業生たちは自分能力の不足で、Professional-Data-Engineer 資格復習テキスト試験向けの仕事を探すのを悩んでいますか？それでは、弊社のGoogleのProfessional-Data-Engineer 資格復習テキスト練習問題を選んで実用能力を速く高め、自分を充実させます。その結果、自信になる自己は面接のときに、面接官のいろいろな質問を気軽に回答できて、順調にProfessional-Data-Engineer 資格復習テキスト向けの会社に入ります。
GoogleのProfessional-Data-Engineer受験記認定試験は競争が激しい今のIT業界中でいよいよ人気があって、受験者が増え一方で難度が低くなくて結局専門知識と情報技術能力の要求が高い試験なので、普通の人がGoogle認証試験に合格するのが必要な時間とエネルギーをかからなければなりません。
Google Professional-Data-Engineer受験記 - 例外がないです。
GoogleのProfessional-Data-Engineer受験記の認定試験に合格すれば、就職機会が多くなります。この試験に合格すれば君の専門知識がとても強いを証明し得ます。GoogleのProfessional-Data-Engineer受験記の認定試験は君の実力を考察するテストでございます。
これは前例のない真実かつ正確なものです。受験生のあなたが首尾よく試験に合格することを助けるように、当社のITエリートの団体はずっと探っています。
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