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Oracle 1z0-915-1 Exam Syllabus Topics:

Topic
Details

Topic 1

Inbound Replication: For database administrators and replication experts, this section of the exam covers setting up and troubleshoot inbound replication and creating channels.

Topic 2

MySQL HeatWave Configurations: For database administrators and performance tuning specialists, this part of the exam covers creating custom configurations, comparing configurations, describing the effects of changing dynamic and non-dynamic variables, and updating a DB system configuration.

Topic 3

MySQL HeatWave Service: For database administrators, cloud architects, and DevOps engineers, this section of the exam covers identifying key features and benefits, describing MySQL HeatWave architecture, defining MySQL HeatWave terminology, and identifying MySQL HeatWave limitations.

Topic 4

Describe the architecture of the HeatWave cluster, adding a HeatWave cluster to a DB system, and determine whether a query is offloaded to HeatWave cluster for execution.

Topic 5

Data Migrations: For data migration specialists and database administrators, this part of the exam covers creating a DB system with data import, importing data into a DB system, and exporting data from MySQL servers and DB systems.

Topic 6

Read Replicas: For database architects and replication specialists, this domain of the exam covers creating and managing read replicas, describing the read replica load balancer, connecting to a read replica, etc.

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Oracle MySQL HeatWave Implementation Associate Rel 1 Sample Questions (Q61-Q66):

NEW QUESTION # 61
There are more than 10 concurrent users running queries on the DB system. The airport_geo table has been loaded successfully into a HeatWave cluster.
You want to run this query:
SELECT DISTINCT country FROM airport_geo ORDER BY country;
How do you determine whether the query is offloaded to the HeatWave cluster for execution?

A. Query the rpd_tables table in performance_schema.
B. View the Query Execution Plan of the query by running EXPLAIN.
C. Check the value of the rapid_query_offload_count global status variable.
D. Check the value of the hw_data_scanned global status variable.

Answer: C

Explanation:
To determine whether a query is offloaded to the HeatWave cluster for execution,check the value of the rapid_query_offload_countglobal status variable(Answer B).
* rapid_query_offload_count: This variable indicates the number of queries that have been offloaded to the HeatWave cluster. By checking its value before and after running the query, you can determine if the query was offloaded.
Steps:
* Connect to the MySQL DB system.
* RunSHOW GLOBAL STATUS LIKE 'rapid_query_offload_count';before and after executing the query to see if the count increases, indicating offloading.
References:
* MySQL HeatWave Documentation
* Monitoring HeatWave Status Variables

NEW QUESTION # 62
A DB system has been deleted successfully. Which two operations are allowed on the deleted DB system?
(Choose two.)

A. Create a manual backup.
B. Restore the DB system from an existing manual backup.
C. View the API call logs on the Audit page.
D. View the metrics.
E. Change the storage size.

Answer: B,C

Explanation:
When a DB system has been successfully deleted, the following operations are allowed:
* Restore the DB system from an existing manual backup(Answer C): Even after the DB system is deleted, you can restore it from any existing manual backups. This allows you to recover the data and configuration from a point-in-time backup.
* View the API call logs on the Audit page(Answer E): You can view the API call logs related to the deleted DB system on the Audit page. These logs provide a record of actions taken on the DB system, including the deletion event.
References:
* OCI Backup and Restore Documentation
* OCI Audit Documentation

NEW QUESTION # 63
How can you determine the uptime of a DB system?

A. By querying performance_schema.global_status from a connected MySQL client
B. By checking the DB system details in the OCI Web console
C. By executing mysql db-system get --db-system-id with OCI CLI
D. By using the Audit section in Logging information in the OCI Web console

Answer: B

Explanation:
You can determine the uptime of a DB system bychecking the DB system details in the OCI Web console(Answer B). The console provides information on the system status, including the uptime since the last start.
Steps:
* Log in to the OCI Web console.
* Navigate to the MySQL DB system.
* View the details page of the DB system, where the uptime information is displayed.
References:
* OCI Console Documentation
* Monitoring DB System Uptime

NEW QUESTION # 64
Which two are available when creating a new MySQL DB system in OCI Console? (Choose two.)

A. Lakehouse
B. Read replica
C. HeatWave cluster
D. Standalone server
E. High availability

Answer: D,E

Explanation:
When creating a new MySQL DB system in the OCI Console, you have the following options:
* High availability(Answer A): This option allows you to create a DB system that can automatically fail over to a standby instance in case of hardware or software failure, ensuring minimal downtime.
* Standalone server(Answer C): This option lets you create a DB system with a single instance, suitable for workloads that do not require high availability or read replicas.
References:
* OCI MySQL Database Service Documentation
* MySQL High Availability

NEW QUESTION # 65
You want to train a model that predicts sales based on the available data the company holds.
This is an excerpt of thesalestable:

Which command trains the model?

A. CALL sys.ML_TRAIN('ml_data.sales', 'Sales', JSON_OBJECT('task', 'anomaly_detection'),
@model);
B. CALL sys.mML_TRAIN('ml_data.sales', 'Sales', JSON_OBJECT('task', 'forecasting'), @model);
C. CALL sys.ML_TRAIN('ml_data.sales', 'Sales', JSON_OBJECT('task', 'regression'), @model);
D. CALL sys.ML_TRAIN('ml_data.sales', 'Sales', JSON_OBJECT('task', 'classification'), @model);

Answer: C

Explanation:
To train a model that predicts sales, the appropriate machine learning task would be regression, as it involves predicting a continuous value (sales) based on the given data. The command to train such a model is:
D:CALL sys.ML_TRAIN('ml_data.sales', 'Sales', JSON_OBJECT('task', 'regression'), @model); This command calls theML_TRAINprocedure on theml_data.salestable, withSalesas the target variable, specifying the task as regression.

NEW QUESTION # 66
......

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