Aggregate

Short Description

Aggregate computes statistical information about input data records.

COMPONENT	SAME INPUT METADATA	SORTED INPUTS	INPUTS	OUTPUTS	JAVA	CTL	AUTO-PROPAGATED METADATA
Aggregate	-	x	1	1-n	x	x	x

Ports

PORT TYPE	NUMBER	REQUIRED	DESCRIPTION	METADATA
Input	0	✓	For input data records	Any1
Output	0-n	✓	For statistical information	Any2

This component has one input port and one or more output ports.

Metadata

Aggregate does not propagate metadata.
Aggregate has no metadata template.
Metadata on the output ports must be same.

Aggregate Attributes

ATTRIBUTE	DESCRIPTION	POSSIBLE VALUES
BASIC
Aggregate key	A key according to which records are grouped. For more information, see Group Key.	E.g. `first_name;`
Aggregation mapping	A sequence of individual mappings for output field names separated from each other by a semicolon. Each mapping can have the following form: `$outputField:=constant` or `$outputField:=$inputField` (this must be a field name from the Aggregate key) or `$outputField:=somefunction($inputField)`. The semicolon after the last mapping is optional and may be omitted.
Charset	Encoding of incoming data records.	UTF-8 \| other encoding
Sorted input	By default, input data records are supposed to be sorted according to Aggregate key. If they are not sorted as specified, switch this value to `false`.	true (default) \| false
Equal NULL	By default, records with null values are considered to be different. If set to `true`, records with null values are considered to be equal.	false (default) \| true
DEPRECATED
Old aggregation mapping	A mapping that was used in older versions, its use is deprecated now.

Details

Aggregate receives data records through a single input port, computes statistical information about input data records and sends them to all output ports.

Aggregation Mapping

Aggregate mapping requires metadata on input and output edges of the component. You must assign metadata to the component input and output before you can create the transformation.
Define Aggregate key. The key field is necessary for grouping.
Click the Aggregation mapping attribute row to open the Aggregation mapping dialog. In it, you can define both the mapping and the aggregation.

The dialog consists of two panes. You can see the Input field pane on the left and the Aggregation mapping pane on the right.

Each Aggregate key field can be mapped to the output. Drag the input field and drop it to the Mapping column in the right pane at the row of the desired output field name. After that, the selected input field appears in the Mapping column.
The following mapping can only be done for key fields: $outField=$keyField.
Fields that are not part of Aggregate key can be used in aggregation functions and the result of the aggregation function is mapped to the output.
To define a function for a field (either contained in the key or not), click the row in the Function column, select a function from the combo list and click Enter.
Aggregation function count() has no parameter, therefore it requires no input field.
For each output field, a constant may also be assigned to it.
$outputField:="Clover"

Aggregate Functions

FUNCTION NAME	DESCRIPTION	INPUT DATA TYPE	OUTPUT DATA TYPE	INPUT CAN BE LIST
avg	Returns an average value of numbers. Null values are ignored. If all aggregated values are null, returns null.	numeric data type	numeric data type	no
count	Count records, null values are counted as well as other values.	-	numeric data type	yes
countnotnull	Counts records, if the field contains null, it is not counted in.	any	numeric data type	yes
countunique	Counts unique values. `null` is unique value. The function assumes 1, 2, 2, 2, null, 1, null as 3 unique values.	any	numeric data type	yes
crc32	Calculates crc32 checksum. Crc of null is null.	any	long	no
first	Returns the first value of group. If the first value is null, returns null.	any	any	yes
firstnotnull	Returns the first value, which is not null. If all received values were null, returns null.	any	any	yes
last	Returns the last value of the group. If last value is null, returns null.	any	any	yes
lastnotnull	Returns the last not-null value. If all values are null, returns null.	any	any	yes
max	Returns the maximum value. If all values are null, returns `null`.	numeric data type	numeric data type	yes
md5	If a group contains one record, returns base64-encoded md5 checksum. If a group contains more records, the particular input records are concatenated together before the calculation of md5 checksum. If an input is string, it is converted to sequence of bytes using encoding set up in the component first. If an input is integer or long, it is printed to the string first. If an input is null, returns null. Use md5sum instead of md5.	any	string	no
md5sum	If a group contains one record, returns md5sum of the field. If a group contains more records, the field values are concatenated first. If an input is null, returns null.	byte	string	no
median	Returns median value. Null values are not counted in. If all input values are null, returns null.	numeric data type	numeric data type	no
min	Returns minimum value. If all input values are null, returns null.	numeric data type	numeric data type	yes
modus	Returns the most frequently used value (null values are not counted in). If there are more candidates, the first one is returned. If all input values are null, returns null.	any	any	yes
sha1sum	If a group contains one record, returns sha1sum of the field. If a group contains more records, the field values are concatenated first. If an input field is null, returns null.	byte	string	no
sha256sum	If an input group contains one record, returns sha256sum of the field. If a group contains more records, the field values are concatenated first. If all input values are null, returns null.	byte	string	no
stddev	Returns a standard deviation. Null values are not counted in. If all input values are null, returns null.	numeric data type	numeric data type	no
sum	Returns sum of input values. If all input values are null, returns null.	numeric data type	numeric data type	no

You can calculate md5sum, sha1sum and sha256sum checksums incrementally: the group of records corresponds to the whole file whereas particular records contain blocks of the file.

For example, there are 3 records grouped together by a value in the field f1. The field f2 contains particular blocks: a, b and c (as bytes). Each value is in the different record. The sha1sum applied on field f2 returns sha1sum("abc").

Examples

Basic Usage

Input metadata contains fields Weight and ProductType.
Output fields are: ProductType, Count, TotalWeight, AverageWeight, and Date. Output metadata can also have other fields.
Aggregate records of the same ProductType field. Set Date to 2015-08-20.

Solution
Set Aggregate key to ProductType.
Set Aggregate mapping:

Map ProductType to ProductType.
Use the count() aggregation function to count records with a same key.
Use the sum() and avg() functions to calculate total and average weight of grouped items. Both functions require an input field as an argument. Drag the input field weight to the Mapping column.
Set the Mapping field of Date to 2015-08-20.

The Aggregate mapping is $ProductType:=$ProductType;$Count:=count();$TotalWeight:=sum($weight);$AverageWeight:=avg($weight);Date:=2015-08-20;.