Conditional Load the data

టేబుల్ 1,టేబుల్ 2 వున్నాయి. టేబుల్ 1 లో Purchase Order వేలల్లో రికార్డ్స్ వున్నాయి. టేబుల్ 2 లో Purchase Order లక్షల రికార్డులు వున్నాయి.
రెండో టేబుల్ లో అవసరం లేని వాటిని క్లిక్ వ్యూ లోకి లోడ్ చెయ్యకుండా ఉండటం ఎలా?

I have two tables:
Table 1: Some list of InvoiceID and their Purchase Order (PO) Record
Table 2: A Purchase Order Record Master
Table 1 is having limited (few hundred thousand) data but Table 2 as the name suggest is has massive data (more than few millions rows)
So, when essentially, I am loading millions of excess record from Table 2 which is not reverent to me and just unnecessarily occupy space and make further computation complex.
So Is there any way I can do limit the load from Table 2 to the PO’s which are listed in Table 1?

Table1:

InvoiceID Purchase Order Value1
1 PO1 1
2 PO2 2
3 PO3 3
4 PO4 4
5 PO5 5
6 PO6 6
7 PO7 7
8 PO8 8
9 PO9 9
10 PO10 10
11 PO11 11
12 PO12 12
13 PO13 13

 

Table2:

 

Purchase Order Date Values2
PO1 1-Jan-18 1
PO2 2-Jan-18 2
PO3 3-Jan-18 3
PO4 4-Jan-18 4
PO5 5-Jan-18 5
PO6 6-Jan-18 6
PO7 7-Jan-18 7
PO8 8-Jan-18 8
PO9 9-Jan-18 9
PO10 10-Jan-18 10
PO11 11-Jan-18 11
PO12 12-Jan-18 12
PO13 13-Jan-18 13
PO14 14-Jan-18 1
PO15 15-Jan-18 2
PO16 16-Jan-18 3
PO17 17-Jan-18 4
PO18 18-Jan-18 5
PO19 19-Jan-18 6
PO20 20-Jan-18 7
PO21 21-Jan-18 8
PO22 22-Jan-18 9
PO23 23-Jan-18 10
PO24 24-Jan-18 11
PO25 25-Jan-18 12
PO26 26-Jan-18 13
PO27 27-Jan-18 11
PO28 28-Jan-18 12
PO29 29-Jan-18 13
PO30 30-Jan-18 14

 

Script:

Table1:
LOAD * INLINE [
InvoiceID,Purchase Order,Value1
1,PO1,1
2,PO2,2
3,PO3,3
4,PO4,4
5,PO5,5
6,PO6,6
7,PO7,7
8,PO8,8
9,PO9,9
10,PO10,10
11,PO11,11
12,PO12,12
13,PO13,13];

Table2:
LOAD * INLINE [
Purchase Order,Date,Values2
PO1,1-Jan-18,1
PO2,2-Jan-18,2
PO3,3-Jan-18,3
PO4,4-Jan-18,4
PO5,5-Jan-18,5
PO6,6-Jan-18,6
PO7,7-Jan-18,7
PO8,8-Jan-18,8
PO9,9-Jan-18,9
PO10,10-Jan-18,10
PO11,11-Jan-18,11
PO12,12-Jan-18,12
PO13,13-Jan-18,13
PO14,14-Jan-18,1
PO15,15-Jan-18,2
PO16,16-Jan-18,3
PO17,17-Jan-18,4
PO18,18-Jan-18,5
PO19,19-Jan-18,6
PO20,20-Jan-18,7
PO21,21-Jan-18,8
PO22,22-Jan-18,9
PO23,23-Jan-18,10
PO24,24-Jan-18,11
PO25,25-Jan-18,12
PO26,26-Jan-18,13
PO27,27-Jan-18,11
PO28,28-Jan-18,12
PO29,29-Jan-18,13
PO30,30-Jan-18,14]
where Exists ([Purchase Order]);

 

https://community.qlik.com/thread/312308

https://community.qlik.com/thread/312362

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