Point-in-time recovery in DB2 typically involves restoring the database to a consistent state prior to the corruption incident. This requires performing a full database backup, restoring it to a different location, and applying transaction logs up to the desired point in time to achieve consistency. 

DB2 handles SQL injection attacks by sanitizing user inputs before executing SQL queries. SQL injection is a common technique used by attackers to manipulate database queries by inserting malicious SQL code into input fields. By sanitizing inputs, DB2 ensures that any potentially harmful characters or commands are escaped or removed, thus preventing the injection of unauthorized SQL code. This approach helps to mitigate the risk of SQL injection attacks and safeguard the integrity and security of the database. 

Dynamic SQL statement caching in DB2 refers to the process of storing frequently executed SQL statements in a cache memory. This feature improves performance as the database engine doesn't need to recompile these statements every time they are executed. Furthermore, it indirectly enhances security by reducing the exposure of SQL statements to potential attackers. Since the cached statements are already compiled and optimized, there is less risk of attackers exploiting vulnerabilities in the compilation process to execute malicious code or gain unauthorized access to the database. 

A materialized view in DB2 is a database object that contains the results of a query and is physically stored on disk, allowing for faster query performance. Unlike regular views, which are virtual and only stored as a predefined query, materialized views are materialized or precomputed and updated automatically when the underlying data changes, ensuring data consistency. 

Log shipping in disaster recovery ensures that changes made to the primary DB2 database are replicated to a standby database in real-time or near real-time. This replication allows for point-in-time recovery by applying transaction logs to the standby database, ensuring minimal data loss in the event of a disaster. 

Data compression in DB2 can improve database performance by reducing the amount of data that needs to be stored, transferred, and processed. With smaller data footprints, compression can lead to faster query execution times, reduced I/O operations, and improved memory utilization, resulting in overall performance enhancements. However, the impact of compression on performance may vary depending on factors such as the compression algorithm used, data characteristics, and workload patterns. Properly configured compression strategies can effectively balance storage savings with performance considerations in DB2 environments. 

Visual Explain assists in identifying potential bottlenecks in query execution by highlighting high-cost operations. By visually representing the query execution plan, it makes it easier to identify operations that are resource-intensive or time-consuming, thus allowing for optimization of the query for better performance. 

In a distributed DB2 environment, several considerations need to be made when using views. Network latency can impact performance, so optimizing network connectivity is crucial. Data consistency across distributed systems is essential to ensure accurate results. Security concerns such as data encryption and access control must be addressed to prevent unauthorized access to sensitive information. Considering all these factors is essential for efficient and secure operations in a distributed DB2 environment. 

A Foreign Key Constraint establishes a relationship between two tables, ensuring referential integrity by enforcing that values in one table must exist in another table's specified column. This constraint maintains the integrity of the relationship between tables. 

Database Services in DB2 architecture primarily handle data storage management tasks such as organizing data on disk, managing buffer pools, and allocating storage space efficiently to optimize performance and resource utilization.