Combiner

Enhanced Definition

In the mainframe context, a "Combiner" refers to a utility function or process designed to consolidate multiple input datasets or data streams into a single, unified output dataset. This consolidation can involve merging records based on specific key fields, or simply concatenating datasets sequentially. It is a fundamental operation in batch processing for data aggregation and preparation.

Key Characteristics

- Multiple Inputs: Accepts two or more input datasets, which can be sequential files, partitioned dataset members, or even data from other processes.
- Single Output: Produces a single output dataset, which can then be used as input for subsequent processing steps.
- Merging Capability: Often includes sophisticated logic to merge records from pre-sorted input files based on one or more key fields, typically handled by sort/merge utilities like DFSORT or SYNCSORT.
- Concatenation Capability: Can simply append the contents of multiple input datasets one after another, treating them as a single logical file.
- Data Transformation: Many combiner utilities also offer capabilities to select, reformat, summarize, or manipulate records during the combination process (e.g., using INREC, OUTREC, SUM statements).
- High Performance: Optimized for processing very large volumes of data efficiently, a critical requirement in z/OS environments.

Use Cases

- Consolidating Reports: Combining daily transaction logs or summary reports from various applications or departments into a single, comprehensive report file for end-of-period processing.
- Master File Updates: Merging a sorted master file with a sorted transaction (update) file to produce a new, updated master file in batch processing.
- Data Aggregation: Combining sales data from different regional branches into a single dataset for enterprise-wide analysis or loading into a data warehouse.
- Preparing Database Loads: Collecting and combining data from multiple flat files into a single input file formatted for a DB2 or IMS database load utility.
- JCL DD Concatenation: Using JCL to logically combine multiple sequential datasets under a single DDNAME so that a program reads them as one continuous stream.

Related Concepts

The concept of a Combiner is intrinsically linked to Sort/Merge Utilities (e.g., DFSORT, SYNCSORT, ICETOOL), which are the primary tools providing this functionality on z/OS. It is a core component of Batch Processing workflows, enabling data preparation and transformation. JCL DD concatenation provides a basic form of combining inputs at the dataset level, allowing programs to process multiple physical files as a single logical unit. Combiners are often part of larger ETL (Extract, Transform, Load) processes, where data from various sources is combined, cleaned, and prepared for loading into target systems.

Best Practices:

Pre-sort for Merges: When performing a keyed merge, ensure all input files are sorted in the correct sequence by the merge key *before* invoking the combiner utility to guarantee correct output and optimal performance.
Consistent Data Formats: Verify that input datasets have compatible record formats and data types, especially for fields involved in merging or transformation, to avoid data integrity issues.
Resource Allocation: Provide sufficient SORTWK space and memory (via REGION parameter in JCL or utility-specific options) for large volumes of data to prevent abends and ensure efficient processing.
Error Handling and Logging: Implement robust error checking within the utility (e.g., OPTION STOPAFT=n for DFSORT) and review job logs (SYSOUT, SYSPRINT) for any warnings or errors during the combination process.
Documentation: Clearly document the purpose of the combination, the source of each input dataset, the merge/concatenation logic, and the expected structure of the output dataset for maintainability and troubleshooting.