Oracle 11g New Features_15 March

The optimizer can choose to share plans based on the use of bind variables because bind variables allow for the reuse of execution plans for different SQL statements that have the same structure but different values. This can improve performance by avoiding the need to generate a new execution plan each time a similar SQL statement is executed. By using bind variables, the optimizer can identify and share execution plans among different SQL statements, resulting in better query performance and resource utilization.

The best place to restrict access to sensitive data stored in an application shared by global users is the database. By implementing access controls and security measures at the database level, you can ensure that only authorized users have the necessary permissions to access and manipulate the data. This approach provides a centralized and robust solution, as it protects the data regardless of the client or application being used. Restricting access at the client or application level may not be as effective, as it can be bypassed or exploited by knowledgeable users.

In OLTP (Online Transaction Processing), the most preferred normalization form is 3NF (Third Normal Form). This form minimizes data redundancy and ensures that each column in a table is dependent only on the primary key. It eliminates transitive dependencies, where a non-key attribute depends on another non-key attribute. By organizing data in 3NF, it becomes easier to maintain data integrity, improve data consistency, and optimize query performance in transactional systems.

DDL operations require a Table Exclusive lock because these operations involve making structural changes to the database schema, such as creating or dropping tables, altering table structures, or modifying indexes. A Table Exclusive lock ensures that no other transactions can read or modify the table while the DDL operation is in progress, preventing any potential conflicts or inconsistencies in the database.

The Private SQL Area is not a part of the System Global Area (SGA). The SGA is a shared memory region in the Oracle database that contains data and control information for the database instance. It includes the Shared Pool, which stores shared SQL and PL/SQL statements, the Java Pool, which stores Java objects and code, and the Redo Log Buffer, which stores redo log records. The Private SQL Area, on the other hand, is a part of the Program Global Area (PGA), which is a memory region specific to each server process and stores private SQL and PL/SQL statements.

During DML operations in Oracle, data integrity is ensured through locks. Locks are used to prevent concurrent access to the same data by multiple transactions, ensuring that only one transaction can modify the data at a time. This helps to prevent data inconsistencies and maintain the integrity of the data.

After table compression, the indexes will be impacted. Table compression reduces the size of the table by eliminating unused space and compressing the data. This can affect the indexes because the compressed data may not be organized in the same way as before, leading to changes in the index structure. As a result, the indexes may need to be rebuilt or reorganized to reflect the new compressed table.

All of these options can be used to achieve the goal of clearing the huge amount of log generated by the database code. A chron job on the server can be scheduled to run at specific intervals and execute a script or command to clear the logs. A database job can be created within the database management system to perform the log clearing task. And an autosys job, which is a job scheduling and management tool, can also be utilized to automate the log clearing process. Therefore, all of these options are valid and effective ways to achieve the desired outcome.

During any database operation, DBMS fetches information from memory. This is because memory, also known as RAM (Random Access Memory), provides faster access to data compared to disk or logs. When a database operation is executed, the required data is loaded into memory from disk or logs, and the DBMS performs the necessary operations on the data in memory. This allows for quicker retrieval and manipulation of data, improving the overall performance of the database system.

When partitioning is implemented on a table, the update operation will be impacted. Partitioning involves dividing a large table into smaller, more manageable partitions based on certain criteria such as range, list, or hash. This allows for improved performance and easier management of data. However, when a table is partitioned, the update operation may be affected because it may require updating data across multiple partitions, which can be more time-consuming and complex compared to updating data in a non-partitioned table.

Tables and partitions are both types of segments in Oracle. Tables are the basic unit of data storage in a database, where data is organized in rows and columns. Partitions, on the other hand, are a way to divide a large table into smaller, more manageable pieces. Each partition is treated as a separate segment, allowing for better performance and easier maintenance. Both tables and partitions play a crucial role in storing and managing data in Oracle databases.

To tune an application means to optimize its performance. Modifying database parameters may improve the performance of the database, but it does not directly address the application itself. Tuning the query can enhance the efficiency of retrieving data from the database, but it still does not encompass the entire application. Therefore, the best way to tune an application is to specifically optimize and fine-tune the application code and logic, ensuring that it runs efficiently and effectively.

The use of virtual columns does not go against the principles of transitive dependency related to normalization. Transitive dependency occurs when a non-key attribute depends on another non-key attribute through a key attribute. Virtual columns are computed columns that are not physically stored in the database but are dynamically generated based on other columns. They do not introduce any new dependencies and do not violate normalization principles. Therefore, the statement is false.

The Oracle optimizer determines execution plans based on the filter criteria and the expected result set. It analyzes the query's filter conditions and the desired outcome to determine the most efficient way to retrieve the required data. By considering the filter criteria and expected result set, the optimizer can choose the appropriate indexes, join methods, and access paths to optimize the query execution. This helps improve the performance of the query and minimize the response time.