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SAP EWM Help Latest Questions

Feature OData v2 OData v4 Release Year 2010 2014 (OASIS Standard) Standardization Microsoft proprietary Official OASIS and ISO standard Data Format Atom (XML) and JSON (limited) Optimized JSON (no Atom), cleaner structure Metadata Format CSDL in XML CSDL in XML and JSON Navigation $expand (basic support) Improved $expand with deeper levels Actions/Functions Limited Fully supported, standardized Enum Support Not available Supported Containment Not supported Supported (better ...

Feature REST OData Definition Architectural style for web services A protocol based on REST for querying and updating data Standardization Not strictly standardized Fully standardized (by OASIS and ISO) Query Support Limited or custom Rich query support via URL options ($filter, $select, etc.) Metadata Not provided by default Automatically exposes metadata ($metadata) Data Format Typically JSON ...

SAP R/3 is based on a 3-tier client-server architecture, which separates presentation, application, and database layers. This design provides scalability, flexibility, and better performance. Three-Tier Architecture: 1. Presentation Layer (Client Tier) Interface between the user and SAP system Usually a SAP ...

You can build a new internal table with only selected entries and fields like this: *&---------------------------------------------------------------------* *& Report  ZREP_LCLCLASS *&---------------------------------------------------------------------* *& Demonstrates modern ABAP syntax: REDUCE, FILTER, FOR expressions *&---------------------------------------------------------------------* REPORT zrep_lclclass. *---------------------------- * Example 1: REDUCE Operator *---------------------------- TYPES: BEGIN OF ty_order,          id     TYPE i,          amount TYPE i,        END OF ty_order. DATA: lt_orders TYPE STANDARD TABLE OF ty_order WITH EMPTY KEY,       lv_total  TYPE i. lt_orders = VALUE #(   ( id = 1 amount = 100 )   ( id = 2 amount = 250 )   ( id = 3 amount = 150 ) ). lv_total = REDUCE i( INIT sum = 0                      FOR order IN lt_orders                      NEXT sum = sum + order-amount ). WRITE: / '--- REDUCE Example ---',        / 'Total Amount:', lv_total. *---------------------------- * Example 2: FILTER Operator *---------------------------- TYPES: BEGIN OF ty_user,          name   TYPE string,          status TYPE string,        END OF ty_user. DATA: lt_users TYPE STANDARD TABLE OF ty_user WITH EMPTY KEY,       lt_active_users TYPE STANDARD TABLE OF ty_user WITH EMPTY KEY. lt_users = VALUE #(   ( name = 'Alice'   status = 'ACTIVE' )   ( name = 'Bob'     status = 'INACTIVE' )   ( name = 'Charlie' status = 'ACTIVE' ) ). lt_active_users = FILTER #( lt_users WHERE status = 'ACTIVE' ). WRITE: / '--- FILTER Example ---'. LOOP AT lt_active_users INTO DATA(user).   WRITE: / user-name, user-status. ENDLOOP. *------------------------------------------------------ * Example 3: FOR Expression - Extract Specific Fields *------------------------------------------------------ DATA: lt_names TYPE STANDARD TABLE OF string WITH EMPTY KEY. lt_names = VALUE string_table(   FOR user IN lt_users   WHERE ( status = 'ACTIVE' )   ( user-name ) ). WRITE: / '--- FOR Expression Example ---'. LOOP AT lt_names INTO DATA(name).   WRITE: / name. ENDLOOP. This creates a new string table containing only the names of users whose status = 'ACTIVE'—short, clean, and readable. Output: — ...