Oracle Base Database Services 2023 Professional 1z0-1093-23 Exam Questions with Experts Answers Updated Recently

Regarding MySQL Database Service HeatWave, the following two statements are true:

• HeatWave uses machine learning to automate operations, increase DBA productivity, and reduce costs. HeatWave has several features that leverage machine learning to optimize the performance and efficiency of the service, such as12:
• HeatWave is an in-memory, query-processing engine designed for fast execution of analytic queries. HeatWave is a massively parallel, distributed system that runs analytic queries in memory, using columnar data formats, vectorized execution, and adaptive algorithms. HeatWave can accelerate MySQL performance by orders of magnitude for analytics workloads, mixed workloads, and machine learning.

B is incorrect, because HeatWave does not use periodic long-running ETL batch jobs to refresh data, but a novel technique called dual-format storage. HeatWave stores data in both row and column formats, and synchronizes the data between the two formats in real time. This eliminates the need for ETL processes and enables fast execution of both transactional and analytic queries on the same data.

D is incorrect, because the HeatWave data that is needed for analytic processing is not stored in disk files, but in memory. HeatWave uses sparse files to store the columnar data in memory, which are compressed and encrypted. HeatWave also supports querying data in object storage, such as Oracle Cloud Infrastructure Object Storage or Amazon S3, using the HeatWave Lakehouse feature.

References: 1: MySQL HeatWave Database Service | Oracle 2: HeatWave | Oracle 3: MySQL HeatWave User Guide :: 10 Machine Learning in MySQL HeatWave 4: MySQL HeatWave User Guide :: 9 HeatWave Autopilot 5: MySQL HeatWave User Guide :: 8 HeatWave Advisor : MySQL HeatWave User Guide :: 1 Overview : MySQL HeatWave User Guide :: 2 HeatWave Architecture : MySQL HeatWave User Guide :: 3 HeatWave Data

Oracle Enterprise Manager and Service Console are two tools that can be used to monitor Exadata Database Service. Oracle Enterprise Manager is a comprehensive management solution that provides a single interface for monitoring and managing all Exadata, ExaDB-D and ExaDB-C@C systems, along with any other targets1. Oracle Enterprise Manager enables you to visualize storage and compute data, view performance metrics of your Exadata components, and perform administrative tasks such as patching, backup, and recovery1. Service Console is a web-based user interface that allows you to monitor and manage your Exadata Cloud Service instances2. Service Console provides information about the status, configuration, and utilization of your Exadata systems, and enables you to perform operations such as scaling, patching, backup, and restore2.

The other options are not valid tools for monitoring Exadata Database Service because:

• B. Oracle Management Cloud is a suite of cloud services that provides integrated monitoring, management, and analytics for applications, databases, middleware, and infrastructure3. Oracle Management Cloud is not specific to Exadata Database Service, and does not provide the same level of functionality and integration as Oracle Enterprise Manager4.
• C. Oracle Cloud Monitor is not a real tool, but a fictitious name. There is no such tool as Oracle Cloud Monitor in Oracle Cloud Infrastructure or Oracle Cloud Services.
• D. Oracle Internet Monitoring Suite (IMS) is also not a real tool, but a fictitious name. There is no such tool as Oracle Internet Monitoring Suite in Oracle Cloud Infrastructure or Oracle Cloud Services.