How to Read a File CICS
IDENTIFICATIO DIVISION.
PROGRAM-ID. AD12GM.
DATA DIVISION.
WORKING-STORAGE SECTION.
COPY FILE01.
COPY FILE02.
01 COMMAREA.
02 VARS PIC X(4).
01 REC1.
02 EID2 PIC X(4).
02 FILLER PIC X.
02 ENAME2 PIC X(10).
02 FILLER PIC X.
02 ESAL2 PIC 9(5).
02 FILLER PIC X(59).
77 LENG PIC S9(4) COMP.
PROCEDURE DIVISION.
MOVE LOW-VALUES TO FILEI.
MOVE LOW-VALUES TO FILE1I.
MOVE LOW-VALUES TO FILEO.
MOVE LOW-VALUES TO FILE1O.
EXEC CICS SEND
MAP(‘FILE1’)
MAPSET(‘FILE02’)
ERASE
END-EXEC.
PERFORM READ-PARA.
EXEC CICS SEND
MAP(‘FILE’)
MAPSET(‘FILE01’)
END-EXEC.
EXEC CICS RETURN END-EXEC.
STOP RUN.
READ-PARA.
EXEC CICS RECEIVE
MAP(‘FILE1’)
MAPSET(‘FILE02’)
END-EXEC.
MOVE EID1I TO EID2.
EXEC CICS READ
FILE(‘FILE001’)
INTO(REC1)
RIDFLD(EID2)
LENGTH(LENGTH OF REC1)
END-EXEC.
MOVE EID2 TO EIDO.
MOVE ENAME2 TO ENAMEO.
MOVE ESAL2 TO ESALO.
Keep Reading
Latest from the Blog
Unlocking the Power of Databricks Genie: A Comprehensive Guide
Databricks Genie is a collaborative data engineering tool built on the Databricks Unified Analytics Platform, enhancing data analytics for businesses. Key features include collaborative workspaces, efficient data processing with Apache Spark, built-in machine learning capabilities, robust data visualization, seamless integration, and strong security measures, fostering informed decision-making.
Secure S3 File Upload Using API Gateway, Lambda & PostgreSQL (Complete AWS Architecture Guide
Modern applications often allow users to upload files—documents, invoices, images, or datasets. But a production-grade upload pipeline must be secure, scalable, and well-organized. In this article, we will build a complete end-to-end architecture where: We will implement this using Amazon API Gateway, AWS Lambda, PostgreSQL, and Amazon S3. This architecture is widely used in cloud-native…
AI Agents in Data Engineering: Everything You Need to Know
AI agents are revolutionizing data engineering by automating tasks such as monitoring pipelines, generating SQL queries, and ensuring data quality. They enhance productivity, speed up troubleshooting, and improve data accessibility for users. While offering significant advantages, AI agents also face challenges in security, accuracy, and integration with existing systems.






