Version

    Aggregate

    Aggregate 64x64

    Short Description

    Ports

    Metadata

    Aggregate Attributes

    Details

    Examples

    See also

    Short Description

    Aggregate computes statistical information about input data records.

    Component Same input metadata Sorted inputs Inputs Outputs Java CTL Auto-propagated metadata

    Aggregate

    -

    1

    1-n

    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 Req 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 of CloverDX, 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.

    1. 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.

    2. 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.

    3. For each output field, a constant may also be assigned to it.

      $outputField:="Clover"

    Aggregate Functions
    Table 60. List of 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;.