The purpose of this project is to make time series manipulation with Spark simpler. Operations covered under this package include AS OF joins, rolling statistics with user-specified window lengths, featurization of time series using lagged values, and Delta Lake optimization on time and partition fields.
shasidhar / tempo Goto Github PK
View Code? Open in Web Editor NEWThis project forked from databrickslabs/tempo
API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation
Home Page: https://pypi.org/project/dbl-tempo
License: Other