Indexing

Creating Indexes

Enhanced Definition

Indexing, in the mainframe context, refers to the process of creating and maintaining a specialized data structure that provides a fast access path to records within a larger dataset or database table. It functions as a lookup mechanism, mapping specific key values to the physical location of the corresponding data, thereby significantly accelerating data retrieval operations.

Key Characteristics

- Accelerated Data Access: The primary purpose is to reduce the time required to locate specific data records, avoiding full table or file scans.
- Separate Data Structure: An index is a distinct object from the base data, typically organized as a B-tree or similar tree-like structure for efficient searching, insertion, and deletion.
- Overhead for Modifications: While improving read performance, indexes introduce overhead during data modification (INSERT, UPDATE, DELETE) as the index structure must also be updated to reflect changes.
- Types of Indexes: Includes primary indexes (often clustered, determining physical order or direct access), secondary indexes (providing alternative access paths), and unique indexes (enforcing uniqueness of values).
- Managed by System: In database systems like DB2 or IMS, indexes are automatically maintained by the DBMS; for VSAM KSDS, the access method manages the index component.
- Storage Consumption: Indexes require additional storage space on DASD (Direct Access Storage Device) separate from the base data.

Use Cases

- Database Query Optimization: Essential for speeding up SELECT statements in DB2, IMS, or other mainframe databases, particularly for queries involving WHERE, JOIN, ORDER BY, and GROUP BY clauses.
- VSAM KSDS (Key-Sequenced Data Set): The core mechanism for direct and sequential access in KSDS files, where the index component maps control intervals to data records.
- Online Transaction Processing (OLTP): Crucial for ensuring fast response times in CICS transactions that frequently access specific records based on key values.
- Batch Reporting and Updates: Optimizing lookups in large master files during batch processing for report generation or data synchronization.
- Enforcing Uniqueness and Referential Integrity: Used in DB2 to enforce primary key constraints and efficiently support foreign key lookups, ensuring data consistency.

Related Concepts

Indexing is fundamental to the performance of DB2 for z/OS, IMS DB, and VSAM KSDS. It directly influences the access path chosen by database optimizers for SQL or DL/I calls, impacting CPU consumption and I/O operations. Indexes are closely tied to data integrity by enforcing uniqueness and are a critical component of efficient storage management on DASD, as they consume space and affect I/O patterns.

Best Practices:

Strategic Indexing: Create indexes on columns frequently used in WHERE clauses, JOIN conditions, ORDER BY clauses, and GROUP BY clauses.
Avoid Over-Indexing: Too many indexes can degrade performance for INSERT, UPDATE, and DELETE operations and consume excessive storage; regularly review and remove unused indexes.
Monitor and Reorganize: Use utilities like DB2 RUNSTATS to monitor index usage and fragmentation. Periodically reorganize (rebuild) indexes to improve efficiency and reduce I/O after significant data changes.
Consider Clustering Indexes: For tables with frequent range scans or sequential access, a clustering index can significantly improve performance by physically ordering data rows according to the index key.
Choose Appropriate Columns: Index columns with high cardinality (many unique values) for better selectivity, and consider composite indexes for multi-column searches.