Partitioning a table in DB2 can enhance database scalability. By partitioning a large table into smaller, manageable partitions, DB2 can distribute data storage and processing across multiple servers, improving overall system scalability. 

Auditing in DB2 involves tracking and logging database activity to monitor user actions, changes to data, and system events. This process helps in identifying security breaches, detecting unauthorized access, and ensuring compliance with regulatory requirements. By recording database activities, auditing provides a comprehensive trail of actions performed within the database, facilitating forensic analysis and investigation in case of security incidents. It plays a crucial role in ensuring the integrity, confidentiality, and availability of data in DB2 environments. 

DB2 offers automatic database tuning features that analyze database performance and automatically adjust configuration parameters to optimize performance. This helps in identifying and resolving performance bottlenecks without manual intervention, improving overall efficiency. 

In DB2, a cursor is primarily used to process result sets. Cursors allow fetching and processing individual rows from a result set returned by a SQL query. They enable iterative processing of query results, facilitating row-by-row operations within application programs. 

DB2 is a robust relational database management system (RDBMS) known for its support across various platforms, including mainframes, distributed systems, and cloud. It offers advanced features like high availability, disaster recovery, and security mechanisms to protect data integrity and confidentiality. 

Different versions of DB2 introduce new features and enhancements that may affect the compatibility of existing applications. For instance, upgrading to a newer version may offer improved performance optimizations, but it could also require modifications to existing code to leverage new features effectively. Therefore, understanding the impact of version upgrades on application compatibility is essential for ensuring a smooth transition and optimal performance. 

The First Normal Form (1NF) ensures that there are no repeating groups in a table by ensuring that each column contains atomic values, and each column has a unique name. This is the fundamental level of normalization in DB2. 

Locking in DB2 serves the purpose of preventing concurrent transactions from accessing the same data concurrently, ensuring data integrity and consistency. This helps in avoiding situations such as dirty reads and conflicting updates, thereby maintaining the accuracy and reliability of the data. It ensures that only one transaction can modify data at a time, preventing inconsistencies. 

Indexing contributes to query optimization in DB2 by organizing data in a structured way, allowing the database engine to efficiently locate and retrieve data, thereby improving query performance. It helps in reducing the number of rows scanned during query execution, resulting in faster response times. 

User-defined functions in DB2 can encapsulate procedural logic for reuse in queries. This means that developers can implement custom logic within functions to perform specific operations, such as calculations, data transformations, or validations, and then reuse these functions in various SQL queries, enhancing code readability and maintainability. 

Materialized Views are a common technique used in denormalization. They are precomputed views stored on disk, which can greatly improve query performance by reducing the need for joins and calculations. 

Too many indexes on a table in DB2 can lead to increased maintenance overhead. This is because each index needs to be updated whenever there are changes to the table data, which can impact performance.