Oracle 1z0-1093-25勉強方法、1z0-1093-25独学書籍
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1z0-1093-25独学書籍 & 1z0-1093-25試験問題解説集
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Oracle 1z0-1093-25 認定試験の出題範囲:
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Oracle Cloud Database Services 2025 Professional 認定 1z0-1093-25 試験問題 (Q96-Q101):
質問 # 96
What is the MOST appropriate method for patching an Exadata Database Service infrastructure, including both database and storage servers, to maintain the latest security updates and bug fixes?
正解:B
解説:
B: Automated Patching via OCI Console/API:
* Oracle Cloud Infrastructure offers automated patching tools specifically designed for Exadata Database Service.
* These tools coordinate patching across database and storage servers, ensuring consistency.
* Features include rolling patching to minimize downtime.
* Automation significantly reduces human error and ensures that both database and storage servers are patched efficiently.
Why the other options are incorrect:
* A. Manual patching:Prone to errors and time-consuming, especially for complex Exadata environments.
* C. Default OS auto-update:Insufficient for comprehensive patching of Exadata components.
* D. Ignoring storage servers:Unsafe and could lead to security vulnerabilities.
質問 # 97
You are tasked with monitoring the I/O performance of an Exadata Database Service (ExaDB) using the exadcli utility. You need to retrieve detailed statistics on Smart Flash Cache usage, including read and write operations, at the storage cell level. Which exadcli command will provide the most comprehensive information?
正解:A
解説:
Detailed Flash Cache Monitoring:
The commandexadcli list metricdetail -cell -metricname "flashcache.*"provides acomprehensive overviewof all metrics related toSmart Flash Cache. This includes bothread and write operations, hit ratios, and IOPS statistics.
* Themetricdetailoption retrieves in-depth data, crucial for performance troubleshooting.
* Theflashcache.*wildcard captures all relevant metrics associated with the Flash Cache subsystem.
Why the other options are incorrect:
* A:Limited to current IOPS and throughput, not specifically flash cache.
* C:Too broad, as it includes general cell metrics.
* D:Focuses only on historical read/write IOPS, not comprehensive.
質問 # 98
Which of the following is the recommended approach for migrating a large, mission-critical database from an on-premises Exadata system to Exadata Database Service with minimal downtime?
正解:C
解説:
B: Using Data Guard for physical standby and switchover:
* This method enablesminimal downtimemigration.
* Steps:
* Configure Data Guard to synchronize thestandby databasewith the primary on-premises database.
* Once synchronized, perform aswitchoverto make the standby the new primary.
* Downtime is limited to the switchover duration.
* This approach leveragesreal-time replicationto minimize disruption.
Why the other options are incorrect:
* A. Export/Import with Data Pump:Too time-consuming for large databases.
* C. Full backup and restore:High downtime due to the time required for data transfer and restoration.
* D. Copying via SQL Developer:Not feasible for mission-critical and large databases due to slow transfer speeds.
質問 # 99
What role does the Exadata Storage Server Software play within the Exadata Database Service architecture?
正解:D
解説:
C: Intelligent Storage Capabilities:
* The Exadata Storage Server Software enhances data processing at the storage layer.
* Key features include:
* Smart Scan:Offloads SQL processing to storage.
* Compression:Reduces data size and improves I/O efficiency.
* Encryption:Protects data at rest.
* This software significantly boosts database performance by reducing data transfer to the compute nodes.
Why the other options are incorrect:
* A. VM management:Handled by OCI infrastructure.
* B. OS and management software:Not related to Exadata Storage Server Software.
* D. Load balancing:Handled by Oracle RAC or OCI load balancers.
質問 # 100
How does HeatWave address the challenges of Online Analytical Processing (OLAP) compared to traditional row-based database systems?
正解:E
解説:
HeatWave's Columnar Processing:
HeatWave improves OLAP performance by storing data in acolumnar formatin memory. This format is particularly efficient foranalytical queriesbecause:
* It minimizes the amount of data read by only scanning thenecessary columns.
* Columnar storage supportsvectorized processing, which significantly speeds up aggregation operations.
* Beingin-memory, it eliminates disk I/O bottlenecks, crucial for high-speed analytics.
Why the other options are incorrect:
* A:Indexing is useful, but columnar storage is the primary driver of speed.
* C:Caching improves access times but does not address the fundamental OLAP challenge of processing large datasets.
* D:HeatWave distributes workload usingparallel processing, not simple sharding.
* E:AI-powered indexing is not a core feature of HeatWave.
質問 # 101
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