DTW Input - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
9.02
9.01
2.0
1.3
Published
February 2022
Language
English (United States)
Last Update
2022-02-10
dita:mapPath
rnn1580259159235.ditamap
dita:ditavalPath
ybt1582220416951.ditaval
dita:id
B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢
Table Description
InputTable Contains information for one or more time series.
ReferenceTable Defines correspondence between InputTable and ReferenceTable 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.

MappingTable Defines correspondence between InputTable and MappingTable 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.

InputTable 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.

ReferenceTable 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 InputTable that corresponds to time series specified by timeseriesid in this table.
value DOUBLE PRECISION Value.

MappingTable Schema

Column Data Type Description
timeseriesid INTEGER Time series identifier.
templateid INTEGER Identifier of time series in InputTable that corresponds to time series specified by timeseriesid in this table.

In MappingTable, DTW supports a single ID column in the InputTable and ReferenceTable.