TD_SEASONALNORMALIZE Function Examples | Teradata Vantage - TD_SEASONALNORMALIZE Examples - Teradata Vantage

Teradata® VantageCloud Lake

Deployment
VantageCloud
Edition
Lake
Product
Teradata Vantage
Published
January 2023
ft:locale
en-US
ft:lastEdition
2024-12-11
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phg1621910019905.ditamap
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pny1626732985837.ditaval
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phg1621910019905

Example: TD_SEASONALNORMALIZE Call to Normalize River Velocity

EXECUTE FUNCTION INTO VOLATILE ART(NORM_SERIES)
TD_SEASONALNORMALIZE(
   SERIES_SPEC(TABLE_NAME(RiverData),ROW_AXIS(TIMECODE(timevalue)), SERIES_ID(StationID),
      PAYLOAD(FIELDS(FlowVelocity), CONTENT(REAL)),INTERVAL(CAL_MONTHS(1)) ),
   FUNC_PARAMS(SEASON_CYCLE(CYCLES("CAL_MONTHS"), DURATION(1))), 
      OUTPUT_FMT( INDEX_STYLE(NUMERICAL_SEQUENCE) )
);

TD_SEASONALNORMALIZE Output for Normalize River Velocity

SELECT TOP 10 * FROM NORM_SERIES ORDER BY ROW_I;
StationID ROW_I FlowVelocity
----------- -------------------- ----------------------
101201 0 -4.70735178251868E-001
101201 1 2.17754337960899E 000
101201 2 3.97661379474619E 000
101201 3 -3.29385753287450E-002
101201 4 -4.79530199292734E-001
101201 5 -7.56084749799974E-001
101201 6 -8.89964514533161E-001
101201 7 -9.55438560059611E-001
101201 8 -9.81823623182210E-001
101201 9 -9.90618644223076E-001

TD_SEASONALNORMALIZE Input Table StoreSales

ROW_ID TD_TIMECODE StoreID Sales
1 2022-01-16 16:05:00.000000 43300 120.00000
2 2022-01-17 16:05:00.000000 43300 105.00000
3 2022-01-18 16:05:00.000000 43300 115.00000
4 2022-02-16 16:05:00.000000 43300 140.00000
5 2022-02-17 16:05:00.000000 43300 145.00000
... ... ... ...

Example: TD_SEASONALNORMALIZE Call for Store Sales

EXECUTE FUNCTION INTO VOLATILE ART(NORM_STORE_SALES)
TD_SEASONALNORMALIZE(
   SERIES_SPEC(TABLE_NAME(StoreSales), ROW_AXIS(TIMECODE(TD_TIMECODE)), 
      SERIES_ID(StoreID), PAYLOAD( FIELDS(Sales), CONTENT(REAL)),
      INTERVAL(CAL_MONTHS(1))),
   FUNC_PARAMS(SEASON_CYCLE(CYCLES("CAL_YEARS"), DURATION(1)), SEASON_INFO(3) ),
      OUTPUT_FMT( INDEX_STYLE(FLOW_THROUGH) ) 
);

TD_SEASONALNORMALIZE Output for Store Sales

SELECT TOP 10 * FROM NORM_STORE_SALES ORDER BY ROW_I;
StoreID ROW_I SEASON_NO CYCLE_NO Sales
----------- -------------------------- -------------------- -------------------- ----------------------
43300 2022-01-16 16:05:00.000000 0 1 1.06904496764970E 000
43300 2022-01-17 16:05:00.000000 0 1 -1.33630620956212E 000
43300 2022-01-18 16:05:00.000000 0 1 2.67261241912425E-001
43300 2022-02-16 16:05:00.000000 1 1 -9.80580675690921E-001
43300 2022-02-17 16:05:00.000000 1 1 -3.92232270276369E-001
43300 2022-02-18 16:05:00.000000 1 1 1.37281294596729E 000
43300 2022-03-16 16:05:00.000000 2 1 1.06904496764970E 000
43300 2022-03-17 16:05:00.000000 2 1 -1.33630620956212E 000
43300 2022-03-18 16:05:00.000000 2 1 2.67261241912425E-001
43300 2022-04-16 16:05:00.000000 3 1 -9.80580675690921E-001

Example: TD_SEASONALNORMALIZE Call for Secondary Result Set

EXECUTE FUNCTION INTO VOLATILE ART(NORM_METADATA)
TD_EXTRACT_RESULTS( 
   ART_SPEC(TABLE_NAME(NORM_STORE_SALES), LAYER(ARTMETADATA) ) 
);

TD_SEASONALNORMALIZE Output for Secondary Result Set

SELECT * FROM NORM_METADATA;
StoreID ROW_I MEAN_Sales SD_Sales
----------- -------------------- ---------------------- ----------------------
43300 0 1.13333333333333E 002 6.23609564462324E 000
43300 1 1.48333333333333E 002 8.49836585598797E 000
43300 2 1.13333333333333E 002 6.23609564462324E 000
43300 3 1.48333333333333E 002 8.49836585598797E 000
43300 4 1.13333333333333E 002 6.23609564462324E 000
43300 5 1.48333333333333E 002 8.49836585598797E 000
43300 6 1.13333333333333E 002 6.23609564462324E 000
43300 7 1.48333333333333E 002 8.49836585598797E 000
43300 8 1.13333333333333E 002 6.23609564462324E 000
43300 9 1.48333333333333E 002 8.49836585598797E 000
43300 10 1.13333333333333E 002 6.23609564462324E 000
43300 11 1.48333333333333E 002 8.49836585598797E 000