認定するProfessional-Cloud-Database-Engineer問題数 &合格スムーズProfessional-Cloud-Database-Engineer参考書勉強 |権威のあるProfessional-Cloud-Database-Engineer実際試験

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Google Professional-Cloud-Database-Engineerの認定試験を受験するには、最低3年間のデータベース管理またはデータ管理の経験が必要であり、Google Cloud Platformでの最低1年間の経験が必要です。また、SQLおよびデータベース設計原則に強い理解を持っている必要があります。この試験は、多肢選択問題とパフォーマンスベースのシナリオから構成され、2時間で完了する必要があります。

Google Professional-Cloud-Database-Engineer試験に合格するには、候補者は、ビジネス要件を満たすデータベースソリューションを設計および実装する能力を実証する必要があります。この試験では、データベースの問題をトラブルシューティングおよび解決し、データベースソリューションを監視および維持する候補者の能力もテストします。成功した候補者は、Googleクラウド環境で効率的かつ効果的なデータベースソリューションを設計、開発、管理に必要なスキルと知識を備えています。

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Professional-Cloud-Database-Engineer参考書勉強 & Professional-Cloud-Database-Engineer実際試験

Professional-Cloud-Database-Engineerトレーニング資料にはハラーン語は含まれておらず、すべてのページは献身的な熟練した専門家によって書かれています。当社のウェブサイトの専門家は、複雑な概念を簡素化し、例、シミュレーション、および図を追加して、理解しにくいかもしれないことを説明します。そのため、普通の試験官でも難なくすべての学習問題を習得できます。さらに、Professional-Cloud-Database-Engineer受験者は、テストエンジンを使用することで自分自身に利益をもたらし、演習や回答などの多くのテスト問題を取得できます。

Google Professional-Cloud-Database-Engineer 認定試験は、クラウドベースのデータベースソリューションに関連する広範なトピックをカバーしています。この試験は、GCPのデータベースサービスに関する知識と、さまざまなGCPツールやサービスを使用してデータベースを設計、構成、管理する能力をテストするために設計されています。また、この試験は、データベースの設計パターン、データモデリング技術、データベースのセキュリティ、スケーラビリティ、パフォーマンスのためのベストプラクティスに関する知識も重視されます。

Google Cloud Certified - Professional Cloud Database Engineer 認定 Professional-Cloud-Database-Engineer 試験問題 (Q94-Q99):

質問 # 94
Your company uses Bigtable for a user-facing application that displays a low-latency real-time dashboard.
You need to recommend the optimal storage type for this read-intensive database. What should you do?

A. Recommend solid-state drives (SSD).
B. Recommend splitting the Bigtable instance into two instances in order to load balance the concurrent reads.
C. Recommend hard disk drives (HDD).
D. Recommend mixed storage types.

正解：A

解説：
if you plan to store extensive historical data for a large number of remote-sensing devices and then use the data to generate daily reports, the cost savings for HDD storage might justify the performance tradeoff. On the other hand, if you plan to use the data to display a real-time dashboard, it probably would not make sense to use HDD storage-reads would be much more frequent in this case, and reads that are not scans are much slower with HDD storage.

質問 # 95
You have a large Cloud SQL for PostgreSQL instance. The database instance is not mission- critical, and you want to minimize operational costs. What should you do to lower the cost of backups in this environment?

A. Change the storage tier of the automated backups from solid-state drive (SSD) to hard disk drive (HDD).
B. Set the automated backups to occur every other day to lower the frequency of backups.
C. Select a different region to store your backups.
D. Reduce the number of automated backups that are retained to two (2).

正解：D

質問 # 96
Your company is migrating the existing infrastructure for a highly transactional application to Google Cloud. You have several databases in a MySQL database instance and need to decide how to transfer the data to Cloud SQL. You need to minimize the downtime for the migration of your 500 GB instance. What should you do?

A. 1. Create a Cloud SQL for MySQL instance for your databases, and configure Datastream to stream your database changes to Cloud SQL.
2. Select the Backfill historical data check box on your stream configuration to initiate Datastream to backfill any data that is out of sync between the source and destination.
3. Delete your stream when all changes are moved to Cloud SQL for MySQL, and update your application to use the new instance.
B. 1. Use the mysqldump utility to manually initiate a backup of MySQL during the application maintenance window.
2. Move the files to Cloud Storage, and import each database into your Cloud SQL instance.
3. Continue to dump each database until all the databases are migrated.
4. Update your application connections to the new instance.
C. 1. Create migration job using Database Migration Service.
2. Set the migration job type to One-time, and perform this migration during a maintenance window.
3. Stop all write workloads to the source database and initiate the dump. Wait for the dump to be loaded into the Cloud SQL destination database and the destination database to be promoted to the primary database.
4. Update your application connections to the new instance.
D. 1. Create migration job using Database Migration Service.
2. Set the migration job type to Continuous, and allow the databases to complete the full dump phase and start sending data in change data capture (CDC) mode.
3. Wait for the replication delay to minimize, initiate a promotion of the new Cloud SQL instance, and wait for the migration job to complete.
4. Update your application connections to the new instance.

正解：D

質問 # 97
Your customer is running a MySQL database on-premises with read replicas. The nightly incremental backups are expensive and add maintenance overhead. You want to follow Google-recommended practices to migrate the database to Google Cloud, and you need to ensure minimal downtime. What should you do?

A. Create an external replica, and use Cloud SQL to synchronize the data to the replica.
B. Create a Google Kubernetes Engine (GKE) cluster, install MySQL on the cluster, and then import the dump file.
C. Use the mysqldump utility to take a backup of the existing on-premises database, and then import it into Cloud SQL.
D. Create a Compute Engine VM, install MySQL on the VM, and then import the dump file.

正解：A

解説：
https://cloud.google.com/sql/docs/mysql/replication/configure-replication-from-external

質問 # 98
You are building a data warehouse on BigQuery. Sources of data include several MySQL databases located on-premises.
You need to transfer data from these databases into BigQuery for analytics. You want to use a managed solution that has low latency and is easy to set up. What should you do?

A. Use Cloud Data Fusion and scheduled workflows to extract data from MySQL. Transform this data into the appropriate schema, and load this data into your BigQuery database.
B. Use Database Migration Service to replicate data to a Cloud SQL for MySQL instance. Create federated tables in BigQuery on top of the replicated instances to transform and load the data into your BigQuery database.
C. Create extracts from your on-premises databases periodically, and push these extracts to Cloud Storage.
Upload the changes into BigQuery, and merge them with existing tables.
D. Use Datastream to connect to your on-premises database and create a stream. Have Datastream write to Cloud Storage. Then use Dataflow to process the data into BigQuery.

正解：D

質問 # 99
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Professional-Cloud-Database-Engineer参考書勉強: https://www.goshiken.com/Google/Professional-Cloud-Database-Engineer-mondaishu.html

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