Filter a table based on another table unique values with conditions

[Balaji_Pandian]

Hi All,

Please let me know the following task can be done in the Alteryx data model. 
I have two tables, Table 1: is having unique 5 series (col. [Num1]) values Table 2: is a dump table.

We need to filter each num 1 value from table 1 into table 2 to create output data

once table 2 filters, we have to check if any 4 serial numbers are found in Num2 columns in the filtered data.

4 series values might be found / not found in num2 column

if 4 series values are found in the Num2 column then we need to filter every 4 serial numbers into the dump num1 column to create group table of the 5 series 

the looping to be continued till 4 series values appear in Num 2 column (Pls ref. Output table, example. 56111)

if 4 series value is not found then looping should stop and search for the next 5 series values in Table 1

Additionally, 2 blank rows to be inserted between each 5 series table in the output, 1 blank row to be inserted between each 4 series table in the output

Table 1:

Num1	Status
51482	Active
56111	Active
55782	Active

Table 2: (Dump)

Col1	Num1	Col4	Num2	Col6	Col7	Col8
1100	45619	1,000.000	14381	1.22	98.79 %	99.00%
1100	45619	1,000.000	16338	0.80	99.21 %	99.21%
1100	45619	1,000.000	45620	0.00	0.00	0.00
1100	45620	1,000.000	16001	3.09	97.00 %	96.99%
1100	45620	1,000.000	16193	3.09	97.00 %	96.99%
1100	45620	1,000.000	16195	3.09	97.00 %	96.99%
1100	45620	1,000.000	16338	0.80	99.21 %	99.21%
1100	45631	1,000.000	45619	0.00	0.00	0.00
1100	45631	1,000.000	72275	1.21	98.80 %	99.00%
1100	51482	6,000.000	12001	24.91	80.06 %	81.95%
1100	51482	6,000.000	16338	7.07	93.40 %	94.49%
1100	51482	6,000.000	60484	0.48	0.48	99.57%
1100	51482	6,000.000	70336	0.48	0.48	99.57%
1100	51482	6,000.000	71617	0.48	0.48	99.57%
1100	56111	5,310.000	45631	0.00	0.00	0.00
1100	56111	5,310.000	70334	0.48	0.48	99.57%
1100	56111	5,310.000	71611	0.48	0.48	99.57%
1100	55782	5,310.000	48631	0.00	0.00	0.00
1100	55782	5,310.000	49619	0.00	0.00	0.00
1100	55782	5,310.000	78334	0.48	0.48	99.57%
1100	48631	1,000.000	16193	3.09	97.00 %	96.99%
1100	48631	1,000.000	16195	3.09	97.00 %	96.99%
1100	48631	1,000.000	16338	0.80	99.21 %	99.21%
1100	49619	1,000.000	72275	1.21	98.80 %	99.00%

Output table: (with explanation)

I have attached the sample data set for your review. Please help me achieve this requirement in the Alteryx workflow.