DTW Input - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
8.00
1.0
Published
May 2019
Language
English (United States)
Last Update
2019-11-22
dita:mapPath
blj1506016597986.ditamap
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dita:id
B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢
Table Description
input_table Contains information for one or more time series.
template_table Defines correspondence between input_table and template_table rows.

Columns by which these tables are ordered must agree in number and data type. That is, each i_order_column must have a corresponding t_order_column with the same data type. However, corresponding order columns can have different names.

mapping_table Defines correspondence between input_table and mapping_table rows.

Columns by which these are partitioned must agree in number and data type. That is, each i_partition_column must have a corresponding m_partition_column with the same data type. However, corresponding partition columns can have different names.

input_table Schema

Each row contains information for one time series.

Column Data Type Description
timeseriesid INTEGER Time series identifier.
timestamp INTEGER, SMALLINT, BIGINT, NUMERIC, or DOUBLE PRECISION Timestamp.
value DOUBLE PRECISION Value.

template_table Schema

Each row contains information for one time series.

Column Data Type Description
templateid INTEGER Time series identifier.
timestamp INTEGER, SMALLINT, BIGINT, NUMERIC, or DOUBLE PRECISION Identifier of time series in input_table that corresponds to time series specified by timeseriesid in this table.
value DOUBLE PRECISION Value.

mapping_table Schema

Column Data Type Description
timeseriesid INTEGER Time series identifier.
templateid INTEGER Identifier of time series in input_table that corresponds to time series specified by timeseriesid in this table.
In mapping_table, DTW supports a single ID column in the input_table and template_table.