Time Series Aggregate Functions | Teradata Vantage - 17.00 - Time Series Aggregate Functions - Teradata Database

Teradata Vantageā„¢ - Time Series Tables and Operations

prodname
Advanced SQL Engine
Teradata Database
vrm_release
17.00
created_date
June 2020
category
Programming Reference
featnum
B035-1208-170K

A set of aggregate functions is provided to support time series data (optionally stored in Primary Time Index (PTI) tables). Additionally, some traditional functions support time series as well. To operate on time series data, both time series-specific functions and traditional functions are invoked in a GROUP BY TIME clause.

Parallel and Single Threaded Aggregate Functions

The aggregate functions are either fully parallel (FP) aggregates or single-threaded (ST) aggregates, depending on how they are evaluated. FP aggregates do not require the entire set of data to be present in order to compute the result. Rather, the result is computed by evaluating the aggregation on small subsets of the data in parallel and then computing a final aggregation of the intermediate results. ST aggregates require the entire set of data to be present in order to compute the result.

You can use the following aggregate functions on time series data in PTI tables by using the GROUP BY TIME clause and in non-PTI tables by using the GROUP BY TIME clause with the USING TIMECODE option.
  • AVERAGE
  • COUNT
  • KURTOSIS
  • MAXIMUM
  • MINIMUM
  • RANK (ANSI)
  • SKEW
  • STANDARD DEVIATION OF A POPULATION (STDDEV_POP)
  • STANDARD DEVIATION OF A SAMPLE (STDDEV_SAMP)
  • SUM
  • VARIANCE OF A POPULATION (VAR_POP)
  • VARIANCE OF A SAMPLE (VAR_SAMP)