Median Absolute Deviation (MAD) Examples | Teradata Vantage - Examples - Advanced SQL Engine - Teradata Database

Time Series Tables and Operations
Product
Advanced SQL Engine
Teradata Database
Release Number
17.05
17.00
Published
June 2020
Language
English (United States)
Last Update
2021-01-22
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cxa1555383531762.ditamap
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dita:id
B035-1208
lifecycle
previous
Product Category
Teradata Vantage™

Example: Finding the Median Absolute Deviation

/*PTI Table*/
SELECT $TD_TIMECODE_RANGE, $TD_GROUP_BY_TIME, BUOYID, MAD(1, TEMPERATURE), COUNT(*)
FROM OCEAN_BUOYS
WHERE TD_TIMECODE BETWEEN TIMESTAMP '2014-01-06 08:00:00' AND TIMESTAMP '2014-01-06 10:30:00'
GROUP BY TIME (MINUTES(30) AND BUOYID)
ORDER BY 3,2,1;

/*Non-PTI Table*/
SELECT $TD_TIMECODE_RANGE, $TD_GROUP_BY_TIME, BUOYID, MAD(1, TEMPERATURE), COUNT(*)
FROM OCEAN_BUOYS_NONPTI
WHERE TIMECODE BETWEEN TIMESTAMP '2014-01-06 08:00:00' AND TIMESTAMP '2014-01-06 10:30:00'
GROUP BY TIME (MINUTES(30) AND BUOYID)
USING TIMECODE(TIMECODE)
ORDER BY 3,2,1;

The results are the same for both tables:

TIMECODE_ RANGE GROUP BY TIME (MINUTES(10)) BUOYID Mad(1, TEMPERATURE) Count(*)
('2014-01-06 08:00:00.000000+00:00', '2014-01-06 08:30:00.000000+00:00') 1 0 4.45000000000000E 001 5
('2014-01-06 09:00:00.000000+00:00', '2014-01-06 09:30:00.000000+00:00') 3 1 3.50000000000000E 000 6
('2014-01-06 10:00:00.000000+00:00', '2014-01-06 10:30:00.000000+00:00') 5 44 3.00000000000000E 000 11

Example: Reporting Groups of Two or More with An Odd Number of Values

/*PTI Table*/
SELECT $TD_TIMECODE_RANGE, $TD_GROUP_BY_TIME, BUOYID, MAD(1, TEMPERATURE), COUNT(*)
FROM OCEAN_BUOYS
WHERE TD_TIMECODE BETWEEN TIMESTAMP '2014-01-06 08:00:00' AND TIMESTAMP '2014-01-06 10:30:00'
GROUP BY TIME (MINUTES(30) AND BUOYID)
HAVING COUNT(*) MOD 2 = 1 AND COUNT(*) > 2
ORDER BY 3,2,1;

/*Non-PTI Table*/
SELECT $TD_TIMECODE_RANGE, $TD_GROUP_BY_TIME, BUOYID, MAD(1, TEMPERATURE), COUNT(*)
FROM OCEAN_BUOYS_NONPTI
WHERE TIMECODE BETWEEN TIMESTAMP '2014-01-06 08:00:00' AND TIMESTAMP '2014-01-06 10:30:00'
GROUP BY TIME (MINUTES(30) AND BUOYID)
USING TIMECODE(TIMECODE)
HAVING COUNT(*) MOD 2 = 1 AND COUNT(*) > 2
ORDER BY 3,2,1;

The results are the same for both tables:

TIMECODE_ RANGE GROUP BY TIME (MINUTES(10)) BUOYID Mad(1, TEMPERATURE) Count(*)
('2014-01-06 08:00:00.000000+00:00', '2014-01-06 08:30:00.000000+00:00') 1 0 4.45000000000000E 001 50
('2014-01-06 10:00:00.000000+00:00', '2014-01-06 10:30:00.000000+00:00') 5 44 3.00000000000000E 000 11

Example: Using the Default Constant Multiplier

/*PTI Table*/
SELECT $TD_TIMECODE_RANGE, $TD_GROUP_BY_TIME, BUOYID, MAD(TEMPERATURE), COUNT(*)
FROM OCEAN_BUOYS
WHERE TD_TIMECODE BETWEEN TIMESTAMP '2014-01-06 08:00:00' AND TIMESTAMP '2014-01-06 10:30:00'
GROUP BY TIME (MINUTES(30) AND BUOYID)
ORDER BY 3,2,1;

/*Non-PTI Table*/
SELECT $TD_TIMECODE_RANGE, $TD_GROUP_BY_TIME, BUOYID, MAD(TEMPERATURE), COUNT(*)
FROM OCEAN_BUOYS_NONPTI
WHERE TIMECODE BETWEEN TIMESTAMP '2014-01-06 08:00:00' AND TIMESTAMP '2014-01-06 10:30:00'
GROUP BY TIME (MINUTES(30) AND BUOYID)
USING TIMECODE(TIMECODE)
ORDER BY 3,2,1;

The results are the same for both tables:

TIMECODE_RANGE GROUP BY TIME (MINUTES(10)) BUOYID Mad(1.4826, TEMPERATURE) Count(*)
('2014-01-06 08:00:00.000000+00:00', '2014-01-06 08:30:00.000000+00:00') 1 0 6.59757000000000E 001 5
('2014-01-06 09:00:00.000000+00:00', '2014-01-06 09:30:00.000000+00:00') 3 1 5.18910000000000E 000 6
('2014-01-06 10:00:00.000000+00:00', '2014-01-06 10:30:00.000000+00:00') 5 44 4.44780000000000E 000 11