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PQL46 (PQL Function Library - CPM 4.6)

PU_QUANTILE

Applies to: CELONIS 4.0 CELONIS 4.2 CELONIS 4.3 CELONIS 4.4 CELONIS 4.5 CELONIS 4.6

Description

Calculates the quantile of the specified column for each element of the given child table.

Like the regular QUANTILE operator, the column can either be an INT, FLOAT or DATE column. The data type of the result is the same as the input column data type. The given quantile has to be a float number between 0 (same as PU_MIN) and 1.0 (same as PU_MAX ).

If no value in the parent table exists for the element in the child table (either because all values of the parent table column are filtered out, or because no corresponding value exists in the first place), NULL will be returned.

Syntax
PU_QUANTILE ( child_table, parent_table.column, quantile [, filter_expression] )
PU_QUANTILE ( DOMAIN_TABLE ( column1,...,columnN ), parent_table.column, quantile [, filter_expression])
Examples

[1] Calculate the 0.5 quantile of the case table values for each company code. This produces the same result as PU_MEDIAN since QUANTILE(0.5) == MEDIAN().

Query

Column1

"companyDetail"."companyCode"

Column2

PU_QUANTILE ( "companyDetail" , "caseTable"."value" , 0.5 )

Input

Output

caseTable

caseId : INT

companyCode : STRING

value : INT

1

'001'

600

2

'001'

400

3

'001'

200

4

'002'

300

5

'002'

300

6

'003'

200

companyDetail

companyCode : STRING

country : STRING

'001'

'DE'

'002'

'DE'

'003'

'US'

Foreign Keys

caseTable.companyCode

companyDetail.companyCode

Result

Column1 : STRING

Column2 : INT

'001'

400

'002'

300

'003'

200

[2] PU functions can be used in a FILTER. In this example, the company codes are filtered such that the corresponding 0.5 quantile of the case table values is smaller than 300.

Query

Filter

FILTER PU_QUANTILE ( "companyDetail" , "caseTable"."value" , 0.5 ) < 300;

Column1

"companyDetail"."companyCode"

Input

Output

caseTable

caseId : INT

companyCode : STRING

value : INT

1

'001'

600

2

'001'

400

3

'001'

200

4

'002'

300

5

'002'

300

6

'003'

200

companyDetail

companyCode : STRING

country : STRING

'001'

'DE'

'002'

'DE'

'003'

'US'

Foreign Keys

caseTable.companyCode

companyDetail.companyCode

Result

Column1 : STRING

'003'

[3] PU functions can be used inside another aggregation function. In this example, the maximum value of all 0.5 quantiles of the case table values for each company code is calculated.

Query

Column1

MAX ( PU_QUANTILE ( "companyDetail" , "caseTable"."value" , 0.5 ) )

Input

Output

caseTable

caseId : INT

companyCode : STRING

value : INT

1

'001'

600

2

'001'

400

3

'001'

200

4

'002'

300

5

'002'

300

6

'003'

200

companyDetail

companyCode : STRING

country : STRING

'001'

'DE'

'002'

'DE'

'003'

'US'

Foreign Keys

caseTable.companyCode

companyDetail.companyCode

Result

Column1 : INT

400

[4] Calculate the 0.0 quantile of the case table values for each company code. This produces the same result as PU_MIN since QUANTILE(0.0) == MIN().

Query

Column1

"companyDetail"."companyCode"

Column2

PU_QUANTILE ( "companyDetail" , "caseTable"."value" , 0.0 )

Input

Output

caseTable

caseId : INT

companyCode : STRING

value : INT

1

'001'

600

2

'001'

400

3

'001'

200

4

'002'

300

5

'002'

300

6

'003'

200

companyDetail

companyCode : STRING

country : STRING

'001'

'DE'

'002'

'DE'

'003'

'US'

Foreign Keys

caseTable.companyCode

companyDetail.companyCode

Result

Column1 : STRING

Column2 : INT

'001'

200

'002'

300

'003'

200

[5] Calculate the 1.0 quantile of the case table values for each company code. This produces the same result as PU_MAX since QUANTILE(1.0) == MAX().

Query

Column1

"companyDetail"."companyCode"

Column2

PU_QUANTILE ( "companyDetail" , "caseTable"."value" , 1.0 )

Input

Output

caseTable

caseId : INT

companyCode : STRING

value : INT

1

'001'

600

2

'001'

400

3

'001'

200

4

'002'

300

5

'002'

300

6

'003'

200

companyDetail

companyCode : STRING

country : STRING

'001'

'DE'

'002'

'DE'

'003'

'US'

Foreign Keys

caseTable.companyCode

companyDetail.companyCode

Result

Column1 : STRING

Column2 : INT

'001'

600

'002'

300

'003'

200

[6] Calculate the 0.5 quantile of the case table values for each company code. Only consider cases with an ID larger than 2. This produces the same result as PU_MEDIAN since QUANTILE(0.5) == MEDIAN().

Query

Column1

"companyDetail"."companyCode"

Column2

PU_QUANTILE ( "companyDetail" , "caseTable"."value" , 0.5 , "caseTable"."caseID" > 2 )

Input

Output

caseTable

caseId : INT

companyCode : STRING

value : INT

1

'001'

600

2

'001'

400

3

'001'

200

4

'002'

300

5

'002'

300

6

'003'

200

companyDetail

companyCode : STRING

country : STRING

'001'

'DE'

'002'

'DE'

'003'

'US'

Foreign Keys

caseTable.companyCode

companyDetail.companyCode

Result

Column1 : STRING

Column2 : INT

'001'

200

'002'

300

'003'

200

[7] Calculate the 0.5 quantile of the case table values for each company code. Only consider cases with an ID larger than 3. All case table values for companyCode '001' are filtered out, which means that in this case, NULL is returned. This produces the same result as PU_MEDIAN since QUANTILE(0.5) == MEDIAN().

Query

Column1

"companyDetail"."companyCode"

Column2

PU_QUANTILE ( "companyDetail" , "caseTable"."value" , 0.5 , "caseTable"."caseID" > 3 )

Input

Output

caseTable

caseId : INT

companyCode : STRING

value : INT

1

'001'

600

2

'001'

400

3

'001'

200

4

'002'

300

5

'002'

300

6

'003'

200

companyDetail

companyCode : STRING

country : STRING

'001'

'DE'

'002'

'DE'

'003'

'US'

Foreign Keys

caseTable.companyCode

companyDetail.companyCode

Result

Column1 :

STRING

Column2 : INT

'001'

null

'002'

300

'003'

200

[8] Calculate the 0.25 quantile of the case table values for each company code.

Query

Column1

"companyDetail"."companyCode"

Column2

PU_QUANTILE ( "companyDetail" , "caseTable"."value" , 0.25 )

Input

Output

caseTable

caseId : INT

companyCode : STRING

value : INT

1

'001'

600

2

'001'

400

3

'001'

200

4

'002'

300

5

'002'

300

6

'003'

200

companyDetail

companyCode : STRING

country : STRING

'001'

'DE'

'002'

'DE'

'003'

'US'

Foreign Keys

caseTable.companyCode

companyDetail.companyCode

Result

Column1 : STRING

Column2 : INT

'001'

200

'002'

300

'003'

200

[9] Example over three tables: For each entry in table B, calculate the 0.5 quantile of the values that are larger than 100 in table C. This produces the same result as PU_MEDIAN since QUANTILE(0.5) == MEDIAN(): Tables B and C do not have a direct connection, but are connected via table A.

Query

Column1

"B"."B_KEY"

Column2

PU_QUANTILE ( "B" , "C"."VALUE" , 0.5 , "C"."VALUE" > 100 )

Input

Output

A

B_KEY : INT

C_KEY : STRING

VALUE : INT

1

'A'

100

1

'B'

200

2

'C'

300

2

'D'

400

3

'E'

500

3

'F'

600

B

B_KEY : INT

1

2

C

C_KEY : STRING

VALUE : INT

'A'

400

'A'

100

'A'

200

'B'

100

'C'

200

'D'

500

Foreign Keys

C.C_KEY

A.C_KEY

B.B_KEY

A.B_KEY

Result

Column1 : INT

Column2 : INT

1

400

2

500

[10] For each case ID, calculate the 0.5 quantile of the case table values for the associated company code using DOMAIN_TABLE. This produces the same result as PU_MEDIAN since QUANTILE(0.5) == MEDIAN().

Query

Column1

"caseTable"."caseId"

Column2

PU_QUANTILE(DOMAIN_TABLE("caseTable"."companyCode"), "caseTable"."value", 0.5)

Input

Output

caseTable

caseId : INT

companyCode : STRING

value : INT

1

'001'

600

2

'001'

400

3

'001'

200

4

'002'

300

5

'002'

300

6

'003'

200

Result

Column1 : INT

Column2 : INT

1

400

2

400

3

400

4

300

5

300

6

200