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
Welcome to Tempo: timeseries manipulation for Spark. This project builds upon the capabilities of [PySpark](https://spark.apache.org/docs/latest/api/python/index.html) to provide a suite of abstractions and functions that make operations on timeseries data easier and highly scalable. The project is written primarily in Jupyter Notebook, distributed under the Other license, first published in 2020. Key topics include: data-analysis, data-science, pandas, python, scala.
tempo - Time Series Utilities for Data Teams Using Databricks
<p align="center"> <img src="https://raw.githubusercontent.com/databrickslabs/tempo/master/tempo%20-%20light%20background.svg" width="300px"/> </p>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.
Tempo Project Documentation
Contributors
Showing top 12 contributors by commit count.
![dependabot[bot]](https://avatars.githubusercontent.com/in/29110?v=4)
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