with out using Generic out like bellow

[rajareddyjkl]

INPUT :

TAB1:

Load * Inline [

Id , Type ,Date

01,A,1/1/2018

01,B,1/2/2018

01,C,1/3/2018

01,D,1/4/2018

01,E,1/5/2018

01,F,1/6/2018

25,s,1/1/2018

26,D,1/1/2018

];

OUTPUT:

with out  using  Generic  load  i  need out put  like 

ID            A                  B                 C               D              E                 F             S                      D

01         1/2/2018

Thanks 

raja

[sibin_jacob]

You need to hardcode Type value, if you are not ready to use Generic load.

Please try the below script.

Tab2:

Load ID, if(Type='A',Date) as A,

if(Type='B',Date) as B,

if(Type='C',Date) as C,

1 as Value

resident TAB1;

Drop table TAB1;

Tab3:

noConcatenate

Load Sum(Value) as Value,ID,A,B,C

resident Tab2

Group by ID,A,B,C;

Drop table TAB2;

[rajareddyjkl]

in  my case  i have  92  fields how  to do it  can  have  better  way ...

[sibin_jacob]

I made minor change in the above script;

I am not sure about other method.

TAB1:

Load * Inline [

Id , Type ,Date

01,A,1/1/2018

01,B,1/2/2018

01,C,1/3/2018

];

Tab2:

Load Id, if(Type='A',Date(Date#(Date,'DD/MM/YYYY'),'DD/MM/YYYY')) as A,

if(Type='B',Date(Date#(Date,'DD/MM/YYYY'),'DD/MM/YYYY')) as B,

if(Type='C',Date(Date#(Date,'DD/MM/YYYY'),'DD/MM/YYYY')) as C

resident TAB1;

Drop table TAB1;

Tab3:

noConcatenate

Load Id,max(A) as A,max(B) as B,max(C) as C

resident Tab2

Group by Id;

Drop table Tab2;

[thannila]

Try this below code:

INPUT :

Load * Inline [

Id , Type ,Date

01,A,1/1/2018

01,B,1/2/2018

01,C,1/3/2018

01,D,1/4/2018

01,E,1/5/2018

01,F,1/6/2018

25,s,1/1/2018

26,D,1/1/2018

];

FinalTable:

LOAD DISTINCT Id

Resident INPUT;

For i = 1 to FieldValueCount('Type')

LET vField = FieldValue('Type', $(i));

Left Join (FinalTable)

LOAD DISTINCT Id,

Date as [$(vField)]

Resident INPUT

Where Type = '$(vField)';

Next

DROP Table INPUT;

[rajareddyjkl]

in  my case    Table  load time  it takes around  10 mins

any  better way  please suggests me..?

[thannila]

why it takes around 10 mins?

[marcus_sommer]

A better way might be to skip this task at all and using another approach to calculate your needed results maybe with some set analysis within UI expressions.

The reason for it is that you create with your approach from a data-stream a large crosstable. Beside a quite expensive handling of these many fields within other tables/dimensions/expressions it's a quite heavy transformation of data and it will always need some time especially if the number of records are rather large.

In your mentioned case it would require 92 loads of a resident-table with a where-clause and joining the result to the final table ... If it's done with a loop like above mentioned or a generic load-approach or any other way ... it couldn't be fast ... compared to a normal data-load.

- Marcus