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The purpose of this project is to provide an API for manipulating time series on top of Apache Spark. Functionality includes featurization using lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, and downsampling & interpolation. This has been tested on TB-scale of historical data and is unit tested for quality pur…

github.com/databrickslabs/tempo

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tempo - Time Series Utilities for Data Teams Using Databricks

Project Description

Welcome to Tempo: timeseries manipulation for Spark. This project builds upon the capabilities of PySpark to provide a suite of abstractions and functions that make operations on timeseries data easier and highly scalable.

NOTE that the Scala version of Tempo is now deprecated and no longer in development.

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The purpose of this project is to provide an API for manipulating time series on top of Apache Spark. Functionality includes featurization using lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, and downsampling & interpolation. This has been tested on TB-scale of historical data and is unit tested for quality pur…

github.com/databrickslabs/tempo

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