Free 1Z0-515 Exam Dumps Preview

Explanation:
The Oracle Exadata Database Machine brings database performance to a whole new level, but have you ever wondered what exactly makes it so fast? Several components of the Oracle Exadata Database Machine, such as Oracle Database 11g Release 2; Oracle Exadata's Smart Flash Cache, Hybrid
Columnar Compression, and SmartScan features; and InfiniBand interconnect, help deliver high performance. One of the key technologies that supports this performance is the storage index, which is not a regular database index. Storage indexes reside in the memory of the storage servers--also called storage cells--and significantly reduce unnecessary I/O by excluding irrelevant database blocks in the storage cells.

Oracle Exadata I/O and Smart Scan Storage in Oracle Exadata changes query processing so that not all blocks have to go to the database server for that server to determine which rows might satisfy a query. Oracle Exadata's Smart Scan feature enables certain types of query processing to be done in the storage cell. With Smart Scan technology, the database nodes send query details to the storage cells via a protocol known as iDB (Intelligent Database).
With this information, the storage cells can take over a large portion of the data-intensive query processing. Oracle Exadata storage cells can search storage disks with added intelligence about the query and send only the relevant bytes, not all the database blocks, to the database nodes--hence the term smart scan.

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Explanation:
Oracle Database Resource Management (DRM) provides tools that allow any Oracle DBA to manage a database server's CPU resources effectively for application user groups and during different resource demand periods.

DRM consists of four basic components: *Resource Consumer Groups (not A). A resource consumer group is a collection of users with similar requirements for resource consumption. Users can be assigned to more than one resource consumer group, but each user's active session can only be assigned to one resource consumer group at a time.
*Resource Plans (not C). In its simplest form, a resource plan describes the resources allocated to one or more resource consumer group(s).
*Resource Plan Directives (not B). Resource plan directives allocate resources among the resource consumer groups in the resource plan. Essentially, directives connect resource consumer groups or subplans to their resource plans.
* SYSTEM_PLAN. Oracle supplies an initial, default resource plan named SYSTEM_PLAN. This plan implements a CPU utilization resource allocation method to divide and prioritize CPU resources to three resource consumer groups

Explanation:
All metadata for cubes and dimensions is stored in the Oracle database.

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Explanation:
The RESULT_CACHE_MODE initialization parameter determines the SQL query result cache mode. The parameter specifies when a ResultCache operator is spliced into a query's execution plan. The parameter accepts the following values: FORCE
The ResultCache operator is added to the root of all SELECT statements, if that is possible. However, if the statement contains a NO_RESULT_CACHE hint, then the hint takes precedence over the parameter setting.
MANUAL
The ResultCache operator is added, only if you use the RESULT_CACHE hint in the SQL query.

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Explanation:
A data warehouse is a relational database that is designed for query and analysis rather than for transaction processing. It usually contains historical data derived from transaction data, but it can include data from other sources. It separates analysis workload from transaction workload and enables an organization to consolidate data from several sources.

Explanation:
GOTOs cannot be used within the Oracle Data Integrator.
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Explanation:

Substring functions are not analytic.

Explanation:
Advanced Compression features in Oracle Database 11g include:
* Online Transaction Processing (OLTP) Table Compression: This breakthrough compression feature compresses table data during all types of data manipulation operations, including conventional INSERT or UPDATE. OLTP Table Compression leverages a sophisticated and intelligent algorithm that minimizes compression overhead during write operations, thereby making it viable for highly transactional workloads

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Explanation:
Interval Partitioning was introduced in 11g, interval partitions are extensions to range partitioning. These provide automation for equi-sized range partitions. Partitions are created as metadata and only the start partition is made persistent. The additional segments are allocated as the data arrives. The additional partitions and local indexes are automatically created.
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Explanation:

Without any redundancy (high performance is the only goal) you can use 100% of the disk space to data.

With disk mirroring (with lower performance) you can use 50% of the disk space to data.

Explanation:
The Metadata Dependency Manager (MDM) enables you to plan your project by previewing the impact of the changes or future changes for "what-if" analysis. When you plan to introduce changes to your source systems, you can gauge the impact of that change on your warehouse design. If changes have already been introduced, then you can plan the time required to update your ETL design and rebuild your data warehouse.

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