Pointer variable in COBOL is a special type of variable. In this post I am sharing what is pointer variable, how to initialize and use them.
What are pointers
Another extension of the USAGE clause is to define data items that contain addresses of data or procedures.
POINTER is a four-byte data item that holds the address of another data item. PROCEDURE-POINTER is a four- or eight-byte data item (depending on the operating system) that contains the address of a program-entry point.
Rules for Pointer Variables
- A POINTER data item cannot have a PICTURE clause.
- The figurative constant NULL (or NULLS) can be used to initialise POINTER and PROCEDURE-POINTER data. No other literal value can be assigned to POINTER data.
In addition to the new data types, vendors implement special registers for use with address data:
ADDRESS OF a register that exists for each record (level 01 or 77) in the Linkage Section of the Data Division. The contents are the address of the data item, for example, ADDRESS OF record.
LENGTH OF a register that contains the length in bytes of the named data item, for example, LENGTH OF identifier.
POINTER variable you cannot use in a MOVE statement. They are manipulated by an extension of the SET statement that assigns them values.
SET identifier-1 TO ADDRESS OF identifier-2
where identifier-1 is a POINTER data item and identifer-2 is any data item in the Working-Storage Section or Linkage Section.
- POINTER data items can be used in relation conditions (to test for equality) and as arguments in a CALL statement.
- PROCEDURE-POINTER data items can be used as the object of a CALL statement.
-
Databricks Lakebase vs. Lakehouse vs. Data Warehouse: What’s the Difference?
Confused by Databricks Lakebase, Lakehouse, and traditional Data Warehouses? Here is a complete comparison of OLTP vs. OLAP architectures, key use cases, and when to use each.
-
Why Databricks Genie Ontology is the “Brain” Your Enterprise AI Was Missing
Ever wondered how AI assistants accurately answer business questions? Learn how Databricks Genie Ontology acts as a smart “translator” between raw data and AI.
-
PySpark + Delta Lake / Apache Iceberg: Building Modern Lakehouse Data Pipelines
Introduction Traditional data warehouses were designed for structured data and fixed schemas. Modern businesses generate massive amounts of data from applications, IoT devices, APIs, logs, and transactions. To handle this scale, organizations are adopting the Lakehouse Architecture, which combines the flexibility of data lakes with the reliability of data warehouses. Two major technologies powering modern…



