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| Section | Weight | Objectives |
|---|---|---|
| AI Features and Capabilities | 30% | - Configure and use AI Vector Search - Implement Select AI for natural language to SQL generation - Use Oracle Machine Learning within Autonomous Database - Apply AI-assisted performance tuning and optimization |
| Autonomous Database Architecture and Provisioning | 25% | - Provision and configure Autonomous Database on dedicated infrastructure - Integrate Autonomous Database with Oracle Cloud Infrastructure services - Describe Autonomous Database architecture and core components - Provision and configure Autonomous Database on shared infrastructure |
| Security, Integration and Data Management | 20% | - Use Autonomous Database tools for development and administration - Configure identity and access management - Load, migrate and integrate data from various sources - Implement data encryption and security controls |
| Database Management and Operations | 25% | - Monitor and manage database performance and resources - Perform patching, upgrades and lifecycle management - Implement backup, recovery and high availability strategies - Configure auto-scaling and storage management |
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質問 # 123
You have a requirement to create an Autonomous Transaction Processing database that can support at least 200 concurrent statements per OCPU as well as parallelism. Which service will you need to connect to?
正解：C
解説：
Full Detailed In-Depth Explanation:
Autonomous Transaction Processing (ATP) offers predefined service levels with varying concurrency and parallelism capabilities:
MEDIUM: Supports up to 50 concurrent statements per OCPU, with no parallelism by default. Unsuitable for the requirement.
TPURGENT: Supports up to 200 concurrent statements per OCPU and enables manual parallelism. This meets both requirements (concurrency ≥ 200 and parallelism), making it the correct choice.
LOW: Supports only 25 concurrent statements per OCPU, with no parallelism. Insufficient for the requirement.
TP: Supports 125 concurrent statements per OCPU, with no parallelism by default. Falls short of the 200 concurrency threshold.
TPURGENT is designed for high-concurrency, time-sensitive workloads, providing the necessary resources and flexibility for parallel query execution, aligning perfectly with the specified needs.
質問 # 124
What REST verb is used to create an Autonomous Database service using REST APIs?
正解：B
解説：
Full Detailed In-Depth Explanation:
REST APIs use HTTP verbs:
A: True. POST creates new resources, such as an Autonomous Database instance.
B: False. GET retrieves data, not creates.
C: False. PUT updates existing resources.
D: False. INSERT is not a REST verb; it’s SQL-specific.
質問 # 125
Which two optimizations are different between Autonomous Data Warehouse and Autonomous Transaction Processing? (Choose two.)
正解：A、B
解説：
Autonomous Data Warehouse (ADW) and Autonomous Transaction Processing (ATP) are optimized for different workloads, reflected in their configurations. The two differing optimizations are:
Memory Usage (A): ADW and ATP allocate memory differently to suit their purposes. ADW prioritizes a larger data cache (part of the SGA) to keep more data in memory, boosting analytical query performance (e.g., aggregations over millions of rows). For example, a SELECT SUM(sales) GROUP BY region runs faster with more cached data. ATP, conversely, balances memory across the SGA and PGA for transactional workloads, emphasizing concurrency and quick row-level operations (e.g., UPDATE orders SET status = 'shipped'). This difference ensures ADW excels at scan-heavy analytics, while ATP handles high-throughput updates.
Data Organization (B): ADW uses a columnar storage format (e.g., Hybrid Columnar Compression) optimized for analytics, storing data by column to speed up aggregations and reduce I/O (e.g., scanning only the sales column for a SUM). ATP uses a row-based format suited for OLTP, enabling fast single-row access and updates (e.g., retrieving or modifying a specific order_id). For instance, inserting a row in ATP is efficient due to row storage, while ADW’s columnar format accelerates SELECT AVG(price) FROM products.
The incorrect options are:
Backup Retention (C): Both ADW and ATP use the same automatic backup system (via Oracle’s Automatic Workload Repository), with a default 60-day retention adjustable by users. There’s no optimization difference here; it’s a shared managed feature.
Undo Management (D): Both databases use Oracle’s Flashback technology for undo (e.g., rolling back transactions or querying past states), with retention periods set similarly. Undo is managed automatically in both, not optimized differently.
These optimizations tailor ADW for analytics and ATP for transactions, despite their shared autonomous foundation.
質問 # 126
A corporation is building a web application to allow its customers to schedule service requests online. There is also a need to run operational reports at times during non-peak hours. The architecture team is debating whether such reports should be run on the OLTP database or in a separate data mart. The DBA Manager does not want to add any more admin responsibility to the team and is looking for a database option that’s low to zero maintenance, but meets their strict performance requirements as well. Which Oracle Cloud Infrastructure database service is appropriate for this scenario?
正解：D
解説：
The scenario requires a low-maintenance, high-performance database for an OLTP web application with occasional reporting. The correct answer is:
ATP using 'tpurgent' and 'high' TNS services to separate connection types (A): Autonomous Transaction Processing (ATP) is ideal here. It’s a fully managed database optimized for OLTP workloads (e.g., scheduling service requests) with zero maintenance overhead—Oracle handles patching, backups, and tuning. ATP supports multiple connection services:
'tpurgent': Prioritizes low-latency, time-critical transactions (e.g., customer scheduling requests), ensuring fast response times for the web app.
'high': Suited for high-concurrency or reporting queries, allowing operational reports to run during non-peak hours without impacting the OLTP workload.
By using these predefined services, the architecture separates transactional and reporting workloads within the same database, meeting performance needs without additional administration. For example, the web app connects via tpurgent for real-time updates, while a reporting tool uses high for batch queries at night, leveraging ATP’s auto-scaling if needed.
The incorrect options are:
Since the application needs to be highly available, it should be deployed on a Kubernetes Cluster (B): This misinterprets the question—it’s about the database service, not the application deployment. Kubernetes is for container orchestration, not a database solution, and adds complexity counter to the low-maintenance goal.
It is best to build a separate data warehouse, and move the OLTP data on a nightly basis (C): While a separate Autonomous Data Warehouse (ADW) could handle reporting, it requires data movement (e.g., via ETL), increasing admin effort and complexity, which the DBA Manager wants to avoid. ATP can handle both workloads with proper service separation.
ADW since operational reporting is a higher priority in this scenario (D): ADW is optimized for analytics, not OLTP. The web app’s transactional needs are primary, with reporting secondary and occasional, making ATP more suitable.
ATP’s self-managing nature and service flexibility make it the best fit.
質問 # 127
Which are the two restrictions for an Always Free Autonomous Database? (Choose two.)
正解：A、B
解説：
The Always Free tier of Autonomous Database has specific limits. The two correct restrictions are:
Maximum of two Always Free Databases per OCI tenancy (B): OCI’s Always Free tier allows up to two free ADB instances per tenancy (e.g., one ATP, one ADW). This limit ensures fair resource distribution across users. For example, you might create FREEATP1 (1 OCPU, 20 GB) and FREEADW1 (1 OCPU, 20 GB) in your tenancy, but a third free instance isn’t permitted—you’d need a paid upgrade. This is tracked by tenancy OCID, visible in the OCI console under “Limits.” Maximum of one OCPU per Database (D): Each Always Free ADB is capped at 1 OCPU, non-scalable, with 20 GB of storage. This restricts compute power (e.g., no auto-scaling to 3x like paid tiers), suitable for small workloads like dev/test apps. For instance, a free ATP instance runs a lightweight app with SELECT * FROM users, but can’t handle heavy concurrency due to the single OCPU.
The incorrect options are:
Supports only ATP as a workload type (A): False. Always Free supports both ATP (transactional) and ADW (warehouse) workload types, giving flexibility for OLTP or analytics (e.g., ATP for a web app, ADW for reports).
Oracle Application Express (APEX) not included (C): False. APEX is included in both free ATP and ADW instances, pre-installed and accessible via the OCI console (e.g., “Development” > “APEX”). You can build apps like a task tracker without extra cost.
These restrictions balance free access with resource constraints, encouraging upgrades for heavier use.
質問 # 128
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