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Professional-Data-Engineer日本語学習内容 & Professional-Data-Engineer試験解説、Professional-Data-Engineer資料勉強 - Royalholidayclubbed
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Google Cloud Certified Professional-Data-Engineer 常々、時間とお金ばかり効果がないです。
Google Cloud Certified Professional-Data-Engineer日本語学習内容 - Google Certified Professional Data Engineer Exam Royalholidayclubbedの商品はIT業界中で高品質で低価格で君の試験のために専門に研究したものでございます。 できるだけ100％の通過率を保証使用にしています。Royalholidayclubbedは多くの受験生を助けて彼らにGoogleのProfessional-Data-Engineer 受験対策試験に合格させることができるのは我々専門的なチームがGoogleのProfessional-Data-Engineer 受験対策試験を研究して解答を詳しく分析しますから。
現在の社会の中で優秀なIT人材が揃て、競争も自ずからとても大きくなって、だから多くの方はITに関する試験に参加してIT業界での地位のために奮闘しています。Professional-Data-Engineer日本語学習内容はGoogleの一つ重要な認証試験で多くのIT専門スタッフが認証される重要な試験です。
Google Professional-Data-Engineer日本語学習内容 - 暇の時間を利用して勉強します。
あなたはIT職員ですか。今年で一番人気があるIT認証試験に申し込みましたか。もし「はい」と答えてくれたら、あなたはラッキですよ。RoyalholidayclubbedのGoogleのProfessional-Data-Engineer日本語学習内容トレーニング資料はあなたが１００パーセント試験に合格することを保証しますから。これは絶対に真実なことです。IT業種でより高いレベルに行きたいのなら、Royalholidayclubbedを選ぶのは間違いなく選択です。当社のトレーニング資料はあなたが全てのIT認証試験に合格することを助けます。しかも値段が手頃です。信じないことはしないでください。Royalholidayclubbedを利用したら分かります。
多分、Professional-Data-Engineer日本語学習内容テスト質問の数が伝統的な問題の数倍である。Google Professional-Data-Engineer日本語学習内容試験参考書は全ての知識を含めて、全面的です。
Professional-Data-Engineer PDF DEMO:
QUESTION NO: 1
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: 2
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: 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
Your company is using WHILECARD tables to query data across multiple tables with similar names. The SQL statement is currently failing with the following error:
# Syntax error : Expected end of statement but got "-" at [4:11]
SELECT age
FROM
bigquery-public-data.noaa_gsod.gsod
WHERE
age != 99
AND_TABLE_SUFFIX = '1929'
ORDER BY
age DESC
Which table name will make the SQL statement work correctly?
A. 'bigquery-public-data.noaa_gsod.gsod*`
B. 'bigquery-public-data.noaa_gsod.gsod'*
C. 'bigquery-public-data.noaa_gsod.gsod'
D. bigquery-public-data.noaa_gsod.gsod*
Answer: A
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Updated: May 27, 2022
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