By utilizing the aggregation and grouping features, you can establish groups within the Result Matrix and subsequently perform aggregation operations on these groups. Such , such as SUM, COUNT, etc.
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Supported Aggregations
AVG
COUNT
MAX
MIN
SUM
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def groupByData = api.newMatrix() // Definition of result matrix (columns, rows). .withColumns('TextColumn1', 'TextColumn2', 'NumericColumn3', 'NumericColumn4') .withRows(rows) // Property `.withGroupBy` defines that the `TextColumn1` and `NumericColumn3` are used for group by (The order is important). .withGroupBy(['TextColumn1', 'NumericColumn3']) // Property `.withColumnAggregation` defines that the values for subtotal rows that will be calculated as SUM. // Values are based on the group by definition (`NumericColumn3`). andThis aredefinition to be calculated as SUMis optional. // This definition is optional. When not used, like e.g. for TextColumn1`TextColumn1`, there will be no aggregation calculated for the `TextColumn1`.*/ .withColumnAggregation('NumericColumn3', SUM) // Property `.calculateGroupByData` is an end statement for group definition. // This statement is only used together with `.withColumnAggregation`. .calculateGroupByData() |
Description
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Definition of result matrix (columns, rows).
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Property .withGroupBy
defines that the TextColumn1
and NumericColumn3
are used for group by (The order is important).
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( |
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) |
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Property .calculateGroupByData
is an end statement for group definition. This statement is only used together with .withColumnAggregation
.
Info | |||||
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Static import is required to use a predefined enum with aggregation types.
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Examples
Grouping Example
In the following example, we retrieve the data from the Products table and group them by the Business Unit, Product Group, and Size columns.
Code
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import net.pricefx.common.api.FieldFormatType def productList = null List<String> fields = ["ProductId", "label", "ProductGroup", "currency", "BusinessUnit", "ProductClass", "Size", "ProductLifeCycle" ] productList = api.find("P", 0, api.getMaxFindResultsLimit(), "ProductId", fields) def columnFormats = [ "ProductId": FieldFormatType.TEXT, "label": FieldFormatType.TEXT, "ProductGroup": FieldFormatType.TEXT, "currency": FieldFormatType.MONEY_EUR, "BusinessUnit": FieldFormatType.TEXT, "ProductClass": FieldFormatType.TEXT, "Size": FieldFormatType.TEXT, "ProductLifeCycle": FieldFormatType.TEXT, ] def rows = productList def resultMatrix = api.newMatrix() .withColumnFormats(columnFormats) .withRows(rows) .withGroupBy(['BusinessUnit']) .withGroupBy(['ProductGroup']) .withGroupBy(['Size']) return resultMatrix |
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Aggregation Example
In the following example, we retrieve the data from the Product Extensions table. We apply group by Currency column and then aggregate SUM on ListPrice column.
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import net.pricefx.common.api.FieldFormatType
import static net.pricefx.server.dto.calculation.ResultMatrixGrouping.AggregateFunctionType
import static net.pricefx.server.dto.calculation.ResultMatrixGrouping.AggregateFunctionType.SUM
def listPriceItems = null
def filter = [
Filter.equal("name", "ListPrice"),
]
List<String> fields = ["ProductId", "ListPrice", "Currency"]
def listPriceItems = api.find("PX3", 0, api.getMaxFindResultsLimit(), "ProductId", fields, *filter)
def rows = listPriceItems
def columnFormats = [
"ProductId": FieldFormatType.TEXT,
"ListPrice": FieldFormatType.MONEY,
"Currency" : FieldFormatType.MONEY,
]
def resultMatrix = api.newMatrix()
.withEnableClientFilter(true)
.withColumnFormats(columnFormats)
.withRows(rows)
.withGroupBy(['Currency'])
.withColumnAggregation('ListPrice', SUM)
.calculateGroupByData()
return resultMatrix |
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