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CrUX Cookbook

Recipes for extracting insights from the Chrome User Experience Report (CrUX).

Guided Tour of CrUX

  1. Counting the number of distinct origins
  2. Searching for origins by their domain
  3. Generating First Contentful Paint (FCP) histogram data for an origin
  4. Generating FCP histograms for each device
  5. Measuring proportion of device usage
  6. Generating FCP histogram with normalized bin widths
  7. Generating timeseries of competitors' fast FCP

Contributing

Pull requests welcome!

  • Standard SQL preferred
  • Match formatting of existing recipes ("Format Query" on BigQuery doesn't always look good)
  • Name your recipe using descriptive keywords (eg median-fcp.sql)
  • Use lots of comments whenever needed to help users understand what you're doing, why you're doing it that way, and any limitations of your approach
  • Queries that consume 10+ GB must be noted in the comments
  • Assign PR to @rviscomi for review

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SQL recipes for extracting meaningful insights from the Chrome User Experience Report (CrUX)

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