Data Engineering Template:

Work with Time Series Data with Flexible Granularity

Extract or compute data values at different granularity of times with time series data

Time series data parsing from timestamp Flow The flow view of this template

datetime functions (unixtimeformat), array and object functions (listif, unnest)

This template shows how you can work with time series data that’s expressed in timestamp format and identify last value at a lower granularity (milliseconds) when rolled up to a higher granularity (seconds).

It makes use of several array functions such as listif and unnest. This technique can be reused to work with any other time series data when you wish to extract or compute values at different granularity levels.

New user?

If your data is mostly on Google Cloud Platform, please use Dataprep. Otherwise, choose Designer Cloud.

Use in Designer Cloud Use in Dataprep