In DB2, a view represents a virtual table that does not store data physically but rather provides a logical representation of data stored in one or more underlying tables. Queries against views are processed by fetching data from the underlying tables based on the view's definition. 

Eclipse is commonly used alongside IBM Data Studio for developing and managing DB2 databases. IBM Data Studio is built on top of the Eclipse platform, providing a seamless integration of development tools specifically tailored for working with DB2 databases. 

The SQL statement used to create a user-defined function in DB2 is "CREATE FUNCTION". This statement allows developers to define custom functions tailored to specific requirements. 

DB2 primarily uses a hash key for data distribution in partitioning. This involves hashing the data using a hash function and distributing it across partitions based on the result of the hash function. 

DB2 provides built-in functions specifically designed for querying and manipulating semi-structured data types such as XML and JSON. These functions enable developers to perform various operations on semi-structured data stored in DB2 databases, such as extracting values, navigating hierarchical structures, and transforming data formats. 

The primary objective of normalization in DB2 is to minimize redundancy by organizing data efficiently. Reducing redundancy helps improve data integrity, save storage space, and ensure consistency in the database. 

When designing triggers in DB2, it's crucial to consider various factors to avoid performance issues. One such factor is the frequency of trigger execution. Triggers that fire frequently can impact database performance, especially if they involve complex logic or operations on large data sets. The complexity of trigger logic is another consideration. Complex triggers may require more CPU and memory resources, leading to performance degradation. Additionally, the size of the affected data set can impact trigger performance, as triggers must process all affected rows. Therefore, it's essential to carefully analyze these factors and optimize trigger design to minimize performance overhead in a DB2 environment. 

The DB2 Command Line Processor (CLP) offers batch capabilities for executing SQL commands and scripts. It allows users to run SQL commands and scripts in batch mode, enabling automation and efficient execution of tasks without the need for manual intervention. 

The MAX() function retrieves the largest value from a specified column in a table. On the other hand, the MIN() function retrieves the smallest value from a specified column. Both functions are aggregate functions commonly used in SQL queries to perform calculations on sets of values. The key difference lies in the values they retrieve based on the specified column. 

Clustering in DB2 is primarily used for optimizing query performance. It involves physically storing related rows together on disk to minimize disk I/O operations and improve the efficiency of data retrieval during queries.