La expresion REDUCE permite agregar y acumular valores a traves de una iteracion. Es comparable con fold o reduce de lenguajes de programacion funcionales y reemplaza muchas construcciones LOOP con variables acumuladoras.
Sintaxis
REDUCE <tipo>( INIT <acumulador1> = <valor_inicial1> [ <acumulador2> = <valor_inicial2> ... ] FOR <variable> IN <tabla> [ WHERE ( <condicion> ) ] [ FOR <variable2> ... ] NEXT <acumulador1> = <expresion1> [ <acumulador2> = <expresion2> ... ])Principio Basico
- INIT: Inicializa uno o mas acumuladores
- FOR: Itera sobre una tabla (o varias)
- NEXT: Actualiza los acumuladores por iteracion
- El resultado es el valor del primer acumulador despues de la ultima iteracion
Ejemplos
1. Calcular Suma Simple
DATA: lt_numbers TYPE TABLE OF i.
lt_numbers = VALUE #( ( 10 ) ( 20 ) ( 30 ) ( 40 ) ( 50 ) ).
" Clasico con LOOPDATA: lv_sum TYPE i.LOOP AT lt_numbers INTO DATA(lv_num). lv_sum = lv_sum + lv_num.ENDLOOP.
" Moderno con REDUCEDATA(lv_sum2) = REDUCE i( INIT sum = 0 FOR num IN lt_numbers NEXT sum = sum + num).
WRITE: / 'Suma:', lv_sum2. " 1502. Suma de Tabla de Estructuras
TYPES: BEGIN OF ty_order, order_id TYPE i, amount TYPE p DECIMALS 2, END OF ty_order.
DATA: lt_orders TYPE TABLE OF ty_order.
lt_orders = VALUE #( ( order_id = 1 amount = '100.50' ) ( order_id = 2 amount = '200.00' ) ( order_id = 3 amount = '150.75' )).
" Calcular importe totalDATA(lv_total) = REDUCE p DECIMALS 2( INIT total = CONV p DECIMALS 2( 0 ) FOR ls_order IN lt_orders NEXT total = total + ls_order-amount).
WRITE: / 'Importe total:', lv_total. " 451.253. Contar con WHERE
TYPES: BEGIN OF ty_product, id TYPE i, category TYPE string, active TYPE abap_bool, END OF ty_product.
DATA: lt_products TYPE TABLE OF ty_product.
lt_products = VALUE #( ( id = 1 category = 'A' active = abap_true ) ( id = 2 category = 'B' active = abap_false ) ( id = 3 category = 'A' active = abap_true ) ( id = 4 category = 'A' active = abap_false )).
" Cantidad de productos activos de categoria ADATA(lv_count) = REDUCE i( INIT count = 0 FOR ls_prod IN lt_products WHERE ( category = 'A' AND active = abap_true ) NEXT count = count + 1).
WRITE: / 'Cantidad:', lv_count. " 24. Encontrar Maximo
DATA: lt_values TYPE TABLE OF i.
lt_values = VALUE #( ( 42 ) ( 17 ) ( 99 ) ( 8 ) ( 73 ) ).
" Encontrar maximoDATA(lv_max) = REDUCE i( INIT max = 0 FOR val IN lt_values NEXT max = nmax( val1 = max val2 = val )).
WRITE: / 'Maximo:', lv_max. " 995. Encontrar Minimo
" Encontrar minimo (con primer valor como valor inicial)DATA(lv_min) = REDUCE i( INIT min = lt_values[ 1 ] FOR val IN lt_values NEXT min = nmin( val1 = min val2 = val )).
WRITE: / 'Minimo:', lv_min. " 86. Concatenar Strings
DATA: lt_names TYPE TABLE OF string.
lt_names = VALUE #( ( `Anna` ) ( `Bernd` ) ( `Clara` ) ).
" Concatenar nombres con comaDATA(lv_concat) = REDUCE string( INIT result = `` FOR name IN lt_names NEXT result = COND #( WHEN result IS INITIAL THEN name ELSE result && `, ` && name )).
WRITE: / lv_concat. " Anna, Bernd, Clara7. Multiples Acumuladores
TYPES: BEGIN OF ty_stats, sum TYPE i, count TYPE i, END OF ty_stats.
DATA: lt_numbers TYPE TABLE OF i.
lt_numbers = VALUE #( ( 10 ) ( 20 ) ( 30 ) ( 40 ) ).
" Calcular suma y cantidad simultaneamenteDATA(ls_stats) = REDUCE ty_stats( INIT sum = 0 count = 0 FOR num IN lt_numbers NEXT sum = sum + num count = count + 1).
DATA(lv_average) = ls_stats-sum / ls_stats-count.
WRITE: / 'Suma:', ls_stats-sum. " 100WRITE: / 'Cantidad:', ls_stats-count. " 4WRITE: / 'Promedio:', lv_average. " 258. Construir Tabla desde Tabla
TYPES: ty_names TYPE TABLE OF string WITH EMPTY KEY.
DATA: lt_persons TYPE TABLE OF ty_person.
lt_persons = VALUE #( ( name = 'Max' age = 30 ) ( name = 'Anna' age = 25 ) ( name = 'Peter' age = 35 )).
" Extraer nombres a nueva tablaDATA(lt_names) = REDUCE ty_names( INIT names = VALUE ty_names( ) FOR ls_person IN lt_persons NEXT names = VALUE #( BASE names ( ls_person-name ) )).
" Resultado: Max, Anna, Peter9. Filtrar y Agregar Combinado
TYPES: BEGIN OF ty_sale, region TYPE string, amount TYPE p DECIMALS 2, END OF ty_sale.
DATA: lt_sales TYPE TABLE OF ty_sale.
lt_sales = VALUE #( ( region = 'NORTH' amount = '1000.00' ) ( region = 'SOUTH' amount = '2000.00' ) ( region = 'NORTH' amount = '1500.00' ) ( region = 'EAST' amount = '800.00' )).
" Suma solo para region NORTHDATA(lv_north_total) = REDUCE p DECIMALS 2( INIT total = CONV p DECIMALS 2( 0 ) FOR ls_sale IN lt_sales WHERE ( region = 'NORTH' ) NEXT total = total + ls_sale-amount).
WRITE: / 'Ventas NORTH:', lv_north_total. " 2500.0010. Iteracion Anidada (dos FOR)
TYPES: BEGIN OF ty_category, name TYPE string, items TYPE TABLE OF i WITH EMPTY KEY, END OF ty_category.
DATA: lt_categories TYPE TABLE OF ty_category.
lt_categories = VALUE #( ( name = 'A' items = VALUE #( ( 10 ) ( 20 ) ) ) ( name = 'B' items = VALUE #( ( 30 ) ( 40 ) ( 50 ) ) )).
" Suma de todos los Items sobre todas las categoriasDATA(lv_total_all) = REDUCE i( INIT total = 0 FOR ls_cat IN lt_categories FOR lv_item IN ls_cat-items NEXT total = total + lv_item).
WRITE: / 'Suma total:', lv_total_all. " 15011. FOR con UNTIL/WHILE
" Iteracion con condicion (no sobre tabla)DATA(lv_factorial) = REDUCE i( INIT fact = 1 n = 1 UNTIL n > 5 NEXT fact = fact * n n = n + 1).
WRITE: / '5! =', lv_factorial. " 120
" Con WHILEDATA(lv_sum_while) = REDUCE i( INIT sum = 0 i = 1 WHILE i <= 10 NEXT sum = sum + i i = i + 1).
WRITE: / 'Suma 1-10:', lv_sum_while. " 5512. LET para Variables Auxiliares Locales
TYPES: BEGIN OF ty_item, quantity TYPE i, price TYPE p DECIMALS 2, END OF ty_item.
DATA: lt_items TYPE TABLE OF ty_item.
lt_items = VALUE #( ( quantity = 5 price = '10.00' ) ( quantity = 3 price = '25.00' ) ( quantity = 10 price = '5.00' )).
" Calcular valor total (Cantidad * Precio)DATA(lv_total_value) = REDUCE p DECIMALS 2( INIT total = CONV p DECIMALS 2( 0 ) FOR ls_item IN lt_items LET line_total = ls_item-quantity * ls_item-price IN NEXT total = total + line_total).
WRITE: / 'Valor total:', lv_total_value. " 175.0013. Agrupacion con REDUCE
TYPES: BEGIN OF ty_group_result, category TYPE string, sum TYPE i, END OF ty_group_result, ty_group_results TYPE TABLE OF ty_group_result WITH EMPTY KEY.
DATA: lt_items TYPE TABLE OF ty_product.
lt_items = VALUE #( ( id = 1 category = 'A' active = abap_true ) ( id = 2 category = 'B' active = abap_true ) ( id = 3 category = 'A' active = abap_true ) ( id = 4 category = 'A' active = abap_false ) ( id = 5 category = 'B' active = abap_true )).
" Contar cantidad por categoriaDATA(lt_by_category) = REDUCE ty_group_results( INIT result = VALUE ty_group_results( ) FOR ls_item IN lt_items FOR GROUPS <group> OF <item> IN lt_items GROUP BY <item>-category NEXT result = VALUE #( BASE result ( category = <group> sum = REDUCE i( INIT cnt = 0 FOR m IN GROUP <group> NEXT cnt = cnt + 1 ) ) )).14. Agregacion Booleana (ANY/ALL)
" Verificar si AL MENOS UN elemento cumple la condicion (ANY)DATA(lv_any_active) = REDUCE abap_bool( INIT any = abap_false FOR ls_prod IN lt_products NEXT any = xsdbool( any = abap_true OR ls_prod-active = abap_true )).
" Verificar si TODOS los elementos cumplen la condicion (ALL)DATA(lv_all_active) = REDUCE abap_bool( INIT all = abap_true FOR ls_prod IN lt_products NEXT all = xsdbool( all = abap_true AND ls_prod-active = abap_true )).
IF lv_any_active = abap_true. WRITE: / 'Al menos un producto esta activo'.ENDIF.
IF lv_all_active = abap_true. WRITE: / 'Todos los productos estan activos'.ELSE. WRITE: / 'No todos los productos estan activos'.ENDIF.15. REDUCE en Llamadas de Metodos
METHODS: display_total IMPORTING iv_total TYPE p.
" Directamente como parametrodisplay_total( iv_total = REDUCE p DECIMALS 2( INIT sum = CONV p DECIMALS 2( 0 ) FOR ls_order IN lt_orders NEXT sum = sum + ls_order-amount )).Comparacion: REDUCE vs. LOOP
" === CLASICO CON LOOP ===DATA: lv_sum TYPE i, lv_count TYPE i, lv_max TYPE i.
LOOP AT lt_numbers INTO DATA(lv_num). lv_sum = lv_sum + lv_num. lv_count = lv_count + 1. IF lv_num > lv_max. lv_max = lv_num. ENDIF.ENDLOOP.
" === MODERNO CON REDUCE ===DATA(ls_result) = REDUCE ty_result( INIT sum = 0 count = 0 max = 0 FOR num IN lt_numbers NEXT sum = sum + num count = count + 1 max = nmax( val1 = max val2 = num )).Notas Importantes / Mejores Practicas
- El primer acumulador determina el tipo de retorno de
REDUCE. - Para multiples resultados: Use un acumulador de estructura o varios acumuladores.
FOR ... INitera sobre tablas,FOR ... UNTIL/WHILEpara iteracion condicional.WHEREfiltra la iteracion - mas eficiente queIFen elNEXT.LETpermite variables auxiliares locales dentro de la iteracion.FORanidados son posibles para datos multidimensionales.BASEenVALUE #()conserva entradas de tabla existentes al construir.- Combine con
VALUE,CONDyFILTER. REDUCEes funcional - sin efectos secundarios en variables externas.- Para logica compleja un
LOOP ATpuede ser mas legible.