Arguments - Aster Analytics

Teradata Aster Analytics Foundation User Guide

Product
Aster Analytics
Release Number
6.21
Published
November 2016
Language
English (United States)
Last Update
2018-04-14
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kiu1466024880662.ditamap
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AA-notempfilter_pdf_output.ditaval
dita:id
B700-1021
lifecycle
previous
Product Category
Software
Argument Category Description
InputTable Required Specifies the name of the input table or view that contains the coefficients generated by DWT2D. Typically, this table is the output table of DWT2D.
MetaTable Required Specifies the name of the input table or view that contains the meta information used in DWT2D. Typically, this table is the meta table output by DWT2D.
OutputTable Required Specifies the name for the table that the function creates to store the reconstructed result. This table must not exist.
InputColumns Required Specifies the names of the columns in the input table or view that contain the data to be transformed. These columns must contain numeric values between -1e308 and 1e308. The function treats NULL as 0.
SortColumn Required Specifies the name of the input column that represents the order of coefficients in each sequence (the waveletid column in the DWT2D output table). The column must contain a sequence of integer values that start from 1 for each sequence. If a value is missing from the sequence, then the function treats the corresponding data column as 0.
PartitionColumns Optional Specifies the names of the partition columns, which identify the sequences. Rows with the same partition column values belong to the same sequence. If you specify multiple partition columns, then the function treats the first one as the distribute key of the output and meta tables.

By default, all rows belong to one sequence, and the function generates a distribute key column named dwt_idrandom_name in both the output table and the meta table. In both tables, every cell of dwt_idrandom_name has the value 1.

VerboseFlag Optional Specifies whether to ignore (not output) rows in which all coefficient values are very small (having an absolute value less than 1e-12). The default value is 'true'. For a sparse input matrix, ignoring such rows reduces the output table size.