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更新するProfessional-Cloud-Database-Engineer復習範囲 &合格スムーズProfessional-Cloud-Database-Engineer資格試験 |正確的なProfessional-Cloud-Database-Engineer復習テキスト

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お客様に最も信頼性の高いバックアップを提供するという信念から当社のProfessional-Cloud-Database-Engineer試験問題を作成し、優れた結果により、試験受験者の機能に対する心を捉えました。 Professional-Cloud-Database-Engineer練習資料は、3つのバージョンに分類できます。これらのバージョンの使用はすべて、彼らに受け入れられています。これらのバージョンのProfessional-Cloud-Database-Engineer模擬練習には大きな格差はありませんが、能力を強化し、レビュープロセスをスピードアップして試験に関する知識を習得するのに役立ちます。そのため、レビュープロセスは妨げられません。

Google Professional-Cloud-Database-Engineer試験に備えるために、候補者はGoogle Cloudデータベースサービスでの実務経験を持つことが勧められます。また、データベースの概念や原則に強い理解を持ち、データベース管理ツールや技術の経験も必要です。Google Cloudは、オンラインコース、練習問題、学習ガイドなど、試験に備えるための複数のトレーニングコースとリソースを提供しています。

Google Professional-Cloud-Database-Enginer認定試験は、Google Cloudプラットフォームでデータベースの管理と設計を担当する専門家のスキルと知識をテストするように設計されています。この認定は、Google Cloud Technologyの使用に関する専門知識を実証した個人を認識しているGoogle Cloud認定プログラムの一部です。

>> Professional-Cloud-Database-Engineer復習範囲 <<

Professional-Cloud-Database-Engineer資格試験、Professional-Cloud-Database-Engineer復習テキスト

あなたはまだ何を待っているのですか。機会が一回だけありますよ。いまGoogleのProfessional-Cloud-Database-Engineer試験問題のフルバージョンを取ることができます。Pass4Testというサイトをクッリクしたらあなたの願いを果たせます。あなたが最も良いGoogleのProfessional-Cloud-Database-Engineer試験トレーニング資料を見つけましたから、Pass4Testの問題と解答を安心に利用してください。きっと試験に合格しますよ。

この試験は、GCPデータベースの操作経験があり、データベース設計の原則、データモデリング、およびデータベースセキュリティに精通している個人を対象としています。候補者は、Java、Python、GoなどのSQLおよびプログラミング言語の経験があると予想されます。認定試験は、GCPでデータベースソリューションを設計、実装、および管理する候補者の能力をテストする複数選択の質問と実用的なシナリオで構成されています。成功した候補者は、Google Cloud Certified -Professional Cloud Database Engineer認定を受け取ります。これは、GCPデータベースエンジニアリングの分野での専門知識のデモンストレーションとして認識されています。

Google Cloud Certified - Professional Cloud Database Engineer 認定 Professional-Cloud-Database-Engineer 試験問題 (Q113-Q118):

質問 # 113
You work in the logistics department. Your data analysis team needs daily extracts from Cloud SQL for MySQL to train a machine learning model. The model will be used to optimize next-day routes. You need to export the data in CSV format. You want to follow Google-recommended practices. What should you do?

A. Use Cloud Composer to execute a select * from table(s) query and export results.
B. Use Cloud Scheduler to trigger a Cloud Function that will run a select * from table(s) query to call the cloudsql.instances.export API.
C. Use Cloud Scheduler to trigger a Cloud Function through Pub/Sub to call the cloudsql.instances.export API.
D. Use Cloud Composer to orchestrate an export by calling the cloudsql.instances.export API.

正解：C

解説：
https://cloud.google.com/blog/topics/developers-practitioners/scheduling-cloud-sql-exports-using-cloud-functions-and-cloud-scheduler

質問 # 114
You are the database administrator of a Cloud SQL for PostgreSQL instance that has pgaudit disabled. Users are complaining that their queries are taking longer to execute and performance has degraded over the past few months. You need to collect and analyze query performance data to help identity slow-running queries.
What should you do?

A. View Cloud SQL operations to view historical query information.
B. White a Logs Explorer query to identify database queries with high execution times.
C. Review application logs to identify database calls.
D. Use the Query Insights dashboard to identify high execution times.

正解：D

解説：
A Cloud SQL instance configured for HA is also called a regional instance and has a primary and secondary zone within the configured region. Within a regional instance, the configuration is made up of a primary instance and a standby instance. Through synchronous replication to each zone's persistent disk, all writes made to the primary instance are replicated to disks in both zones before a transaction is reported as committed. In the event of an instance or zone failure, the standby instance becomes the new primary instance. Users are then rerouted to the new primary instance. This process is called a failover.

質問 # 115
Your application uses Cloud SQL for MySQL. Your users run reports on data that relies on near-real time; however, the additional analytics caused excessive load on the primary database. You created a read replica for the analytics workloads, but now your users are complaining about the lag in data changes and that their reports are still slow. You need to improve the report performance and shorten the lag in data replication without making changes to the current reports. Which two approaches should you implement? (Choose two.)

A. Disable replication on the primary instance, and set the flag for parallel replication on the primary instance. Re-enable replication and optimize performance by setting flags on the read replica.
B. Disable replication on the read replica, and set the flag for parallel replication on the read replica. Re-enable replication and optimize performance by setting flags on the primary instance.
C. Move your analytics workloads to BigQuery, and set up a streaming pipeline to move data and update BigQuery.
D. Create additional read replicas, and partition your analytics users to use different read replicas.
E. Create secondary indexes on the replica.

正解：C、D

質問 # 116
Your application uses Cloud SQL for MySQL. Your users run reports on data that relies on near-real time; however, the additional analytics caused excessive load on the primary database. You created a read replica for the analytics workloads, but now your users are complaining about the lag in data changes and that their reports are still slow. You need to improve the report performance and shorten the lag in data replication without making changes to the current reports. Which two approaches should you implement? (Choose two.)

A. Disable replication on the read replica, and set the flag for parallel replication on the read replica. Re-enable replication and optimize performance by setting flags on the primary instance.
B. Move your analytics workloads to BigQuery, and set up a streaming pipeline to move data and update BigQuery.
C. Disable replication on the primary instance, and set the flag for parallel replication on the primary instance. Re-enable replication and optimize performance by setting flags on the read replica.
D. Create additional read replicas, and partition your analytics users to use different read replicas.
E. Create secondary indexes on the replica.

正解：A、D

解説：
Replication lag and slow report performance. E is eliminated because using BigQuery would mean changes to the current reports. Report slowness could be the result of poor indexing or just too much read load (or both!). Since excessive load is mentioned in the question, creating additional read replicas and spreading the analytics workload around makes B correct and eliminates A as a way to speed up reporting. That leaves the replication problem. Cloud SQL enables single threaded replication by default, so it stands to reason enabling parallel replication would help the lag. To do that you disable replication on the replica (not the primary), set flags on the replica and optionally set flags on the primary instance to optimize performance for parallel replication. That makes C correct and D incorrect. https://cloud.google.com/sql/docs/mysql/replication/manage-replicas#configuring-parallel-replication

質問 # 117
You have a non-critical business application running on Google Kubernetes Engine (GKE) in the app-dev VPC. You have created an AllayDB cluster with private Service Access (PSA) and no public IP address in the db-dev VPC. You want your application to securely connect to AllowDB in a cost-effective way. What should you do?

A. Connect by using the private IP address of the AlloyDB cluster directly from the application.
B. Set up a high availability VPN between the app-dev and db-dev VPCs. Connect the application directly to AlloyDB.
C. Install a SOCKS proxy in a VM in the db-dev VPC. Install AlloyDB Auth Proxy in your GKE cluster, and connect to the AlloyDB cluster through the SOCKS server and port.
D. Connect by using AlloyDB Auth Proxy installed in the GKE cluster.

正解：A

質問 # 118
......

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