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Page Weight 2024 Queries (#3732)
* Queries of page-weight 2024 * Fix linter errors * Fix wrong css bytes name * CWV trend SQL implemented * Fix linter issues * fix cwv and css request type calculation --------- Co-authored-by: burak.gueneli <burak.gueneli@uberall.com>
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‎sql/2024/page-weight/bytes_per_type.sql‎

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SELECT
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percentile,
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client,
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is_root_page,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesTotal') AS INT64) / 1024, 1000)[OFFSET(percentile * 10)] AS total_kbytes,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesHtml') AS INT64) / 1024, 1000)[OFFSET(percentile * 10)] AS html_kbytes,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesJS') AS INT64) / 1024, 1000)[OFFSET(percentile * 10)] AS js_kbytes,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesCss') AS INT64) / 1024, 1000)[OFFSET(percentile * 10)] AS css_kbytes,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesImg') AS INT64) / 1024, 1000)[OFFSET(percentile * 10)] AS img_kbytes,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesOther') AS INT64) / 1024, 1000)[OFFSET(percentile * 10)] AS other_kbytes,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesHtmlDoc') AS INT64) / 1024, 1000)[OFFSET(percentile * 10)] AS html_doc_kbytes,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesFont') AS INT64) / 1024, 1000)[OFFSET(percentile * 10)] AS font_kbytes
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FROM
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`httparchive.all.pages`,
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UNNEST([10, 25, 50, 75, 90, 100]) AS percentile
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WHERE
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date = '2024-06-01'
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GROUP BY
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percentile,
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client,
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is_root_page
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ORDER BY
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client,
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is_root_page,
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percentile

‎sql/2024/page-weight/compression-usage.sql‎

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SELECT
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client,
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is_root_page,
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COUNTIF(JSON_VALUE(lighthouse, '$.audits.uses-text-compression.score') IS NULL) AS null_count,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.uses-text-compression.score') AS FLOAT64) >= 0.9) AS pass_count,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.uses-text-compression.score') AS FLOAT64) < 0.9) AS fail_count,
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COUNT(0) AS total,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.uses-text-compression.score') AS FLOAT64) >= 0.9) / COUNT(0) AS pct_pass,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.uses-text-compression.score') AS FLOAT64) < 0.9) / COUNT(0) AS pct_fail
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FROM
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`httparchive.all.pages`
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WHERE
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date = '2024-06-01'
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GROUP BY
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client,
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is_root_page
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ORDER BY
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client,
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is_root_page,
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null_count,
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pass_count,
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fail_count

‎sql/2024/page-weight/cwv_trend.sql‎

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WITH metrics_data AS (
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SELECT
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date,
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client,
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CAST(JSON_VALUE(summary, '$.bytesTotal') AS INT64) AS bytes_total,
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CAST(JSON_VALUE(lighthouse, '$.audits.largest-contentful-paint.numericValue') AS FLOAT64) AS lcp,
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CAST(JSON_VALUE(lighthouse, '$.audits.cumulative-layout-shift.numericValue') AS FLOAT64) AS cls,
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CAST(JSON_VALUE(lighthouse, '$.audits.total-blocking-time.numericValue') AS FLOAT64) AS tbt,
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CAST(JSON_VALUE(lighthouse, '$.audits.first-contentful-paint.numericValue') AS FLOAT64) AS fcp,
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CAST(JSON_VALUE(lighthouse, '$.audits.interactive.numericValue') AS FLOAT64) AS tti,
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CAST(JSON_VALUE(lighthouse, '$.categories.performance.score') AS FLOAT64) AS performance_score
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FROM
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`httparchive.all.pages`
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WHERE
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date >= '2023-06-01' AND
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date <= '2024-06-01' AND
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EXTRACT(DAY FROM date) = 1 -- Only include data from the first day of each month
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)
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SELECT
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date,
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client,
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COUNT(DISTINCT IF(bytes_total > 0, bytes_total, NULL)) AS total_pages,
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-- Page Size metrics
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ROUND(APPROX_QUANTILES(bytes_total, 1000)[OFFSET(100)] / 1024, 2) AS p10_page_size_kb,
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ROUND(APPROX_QUANTILES(bytes_total, 1000)[OFFSET(250)] / 1024, 2) AS p25_page_size_kb,
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ROUND(APPROX_QUANTILES(bytes_total, 1000)[OFFSET(500)] / 1024, 2) AS p50_page_size_kb,
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ROUND(APPROX_QUANTILES(bytes_total, 1000)[OFFSET(750)] / 1024, 2) AS p75_page_size_kb,
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ROUND(APPROX_QUANTILES(bytes_total, 1000)[OFFSET(900)] / 1024, 2) AS p90_page_size_kb,
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-- LCP metrics
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ROUND(APPROX_QUANTILES(lcp, 1000)[OFFSET(100)], 2) AS p10_lcp,
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ROUND(APPROX_QUANTILES(lcp, 1000)[OFFSET(250)], 2) AS p25_lcp,
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ROUND(APPROX_QUANTILES(lcp, 1000)[OFFSET(500)], 2) AS p50_lcp,
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ROUND(APPROX_QUANTILES(lcp, 1000)[OFFSET(750)], 2) AS p75_lcp,
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ROUND(APPROX_QUANTILES(lcp, 1000)[OFFSET(900)], 2) AS p90_lcp,
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-- CLS metrics
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ROUND(APPROX_QUANTILES(cls, 1000)[OFFSET(100)], 3) AS p10_cls,
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ROUND(APPROX_QUANTILES(cls, 1000)[OFFSET(250)], 3) AS p25_cls,
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ROUND(APPROX_QUANTILES(cls, 1000)[OFFSET(500)], 3) AS p50_cls,
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ROUND(APPROX_QUANTILES(cls, 1000)[OFFSET(750)], 3) AS p75_cls,
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ROUND(APPROX_QUANTILES(cls, 1000)[OFFSET(900)], 3) AS p90_cls,
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-- TBT metrics (as a proxy for FID)
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ROUND(APPROX_QUANTILES(tbt, 1000)[OFFSET(100)], 2) AS p10_tbt,
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ROUND(APPROX_QUANTILES(tbt, 1000)[OFFSET(250)], 2) AS p25_tbt,
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ROUND(APPROX_QUANTILES(tbt, 1000)[OFFSET(500)], 2) AS p50_tbt,
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ROUND(APPROX_QUANTILES(tbt, 1000)[OFFSET(750)], 2) AS p75_tbt,
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ROUND(APPROX_QUANTILES(tbt, 1000)[OFFSET(900)], 2) AS p90_tbt,
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-- FCP metrics
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ROUND(APPROX_QUANTILES(fcp, 1000)[OFFSET(100)], 2) AS p10_fcp,
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ROUND(APPROX_QUANTILES(fcp, 1000)[OFFSET(250)], 2) AS p25_fcp,
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ROUND(APPROX_QUANTILES(fcp, 1000)[OFFSET(500)], 2) AS p50_fcp,
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ROUND(APPROX_QUANTILES(fcp, 1000)[OFFSET(750)], 2) AS p75_fcp,
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ROUND(APPROX_QUANTILES(fcp, 1000)[OFFSET(900)], 2) AS p90_fcp,
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-- TTI metrics
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ROUND(APPROX_QUANTILES(tti, 1000)[OFFSET(100)], 2) AS p10_tti,
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ROUND(APPROX_QUANTILES(tti, 1000)[OFFSET(250)], 2) AS p25_tti,
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ROUND(APPROX_QUANTILES(tti, 1000)[OFFSET(500)], 2) AS p50_tti,
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ROUND(APPROX_QUANTILES(tti, 1000)[OFFSET(750)], 2) AS p75_tti,
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ROUND(APPROX_QUANTILES(tti, 1000)[OFFSET(900)], 2) AS p90_tti,
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-- Performance Score metrics
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ROUND(APPROX_QUANTILES(performance_score, 1000)[OFFSET(900)] * 100, 2) AS p10_performance_score,
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ROUND(APPROX_QUANTILES(performance_score, 1000)[OFFSET(750)] * 100, 2) AS p25_performance_score,
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ROUND(APPROX_QUANTILES(performance_score, 1000)[OFFSET(500)] * 100, 2) AS p50_performance_score,
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ROUND(APPROX_QUANTILES(performance_score, 1000)[OFFSET(250)] * 100, 2) AS p75_performance_score,
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ROUND(APPROX_QUANTILES(performance_score, 1000)[OFFSET(100)] * 100, 2) AS p90_performance_score,
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-- Good CWV percentages
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ROUND(COUNTIF(lcp <= 2500) / COUNT(0) * 100, 2) AS good_lcp_percent,
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ROUND(COUNTIF(cls <= 0.1) / COUNT(0) * 100, 2) AS good_cls_percent,
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ROUND(COUNTIF(tbt <= 300) / COUNT(0) * 100, 2) AS good_tbt_percent,
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ROUND(COUNTIF(fcp <= 1800) / COUNT(0) * 100, 2) AS good_fcp_percent
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FROM
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metrics_data
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GROUP BY
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date,
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client
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ORDER BY
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date DESC,
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client

‎sql/2024/page-weight/facades-usage.sql‎

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SELECT
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client,
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is_root_page,
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COUNTIF(JSON_VALUE(lighthouse, '$.audits.third-party-facades.score') IS NULL) AS null_count,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.third-party-facades.score') AS FLOAT64) >= 0.9) AS pass_count,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.third-party-facades.score') AS FLOAT64) < 0.9) AS fail_count,
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COUNT(0) AS total,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.third-party-facades.score') AS FLOAT64) >= 0.9) / COUNT(0) AS pct_pass,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.third-party-facades.score') AS FLOAT64) < 0.9) / COUNT(0) AS pct_fail
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FROM
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`httparchive.all.pages`
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WHERE
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date = '2024-06-01'
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GROUP BY
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client,
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is_root_page
17+
ORDER BY
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client,
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is_root_page,
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null_count,
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pass_count,
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fail_count

‎sql/2024/page-weight/minified_css_usage.sql‎

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SELECT
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client,
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is_root_page,
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COUNTIF(JSON_VALUE(lighthouse, '$.audits.unminified-css.score') IS NULL) AS null_count,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.unminified-css.score') AS FLOAT64) >= 0.9) AS pass_count,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.unminified-css.score') AS FLOAT64) < 0.9) AS fail_count,
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COUNT(0) AS total,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.unminified-css.score') AS FLOAT64) >= 0.9) / COUNT(0) AS pct_pass,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.unminified-css.score') AS FLOAT64) < 0.9) / COUNT(0) AS pct_fail
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FROM
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`httparchive.all.pages`
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WHERE
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date = '2024-06-01'
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GROUP BY
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client,
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is_root_page
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ORDER BY
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client,
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is_root_page,
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null_count,
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pass_count,
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fail_count

‎sql/2024/page-weight/minified_js_usage.sql‎

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SELECT
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client,
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is_root_page,
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COUNTIF(JSON_VALUE(lighthouse, '$.audits.unminified-javascript.score') IS NULL) AS null_count,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.unminified-javascript.score') AS FLOAT64) >= 0.9) AS pass_count,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.unminified-javascript.score') AS FLOAT64) < 0.9) AS fail_count,
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COUNT(0) AS total,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.unminified-javascript.score') AS FLOAT64) >= 0.9) / COUNT(0) AS pct_pass,
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COUNTIF(SAFE_CAST(JSON_VALUE(lighthouse, '$.audits.unminified-javascript.score') AS FLOAT64) < 0.9) / COUNT(0) AS pct_fail
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FROM
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`httparchive.all.pages`
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WHERE
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date = '2024-06-01'
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GROUP BY
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client,
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is_root_page
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ORDER BY
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client,
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is_root_page,
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null_count,
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pass_count,
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fail_count

‎sql/2024/page-weight/page_weight_trend.sql‎

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SELECT
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date,
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client,
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is_root_page,
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ROUND(APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesTotal') AS INT64), 1000)[OFFSET(100)] / 1024, 2) AS p10,
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ROUND(APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesTotal') AS INT64), 1000)[OFFSET(250)] / 1024, 2) AS p25,
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ROUND(APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesTotal') AS INT64), 1000)[OFFSET(500)] / 1024, 2) AS p50,
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ROUND(APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesTotal') AS INT64), 1000)[OFFSET(750)] / 1024, 2) AS p75,
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ROUND(APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.bytesTotal') AS INT64), 1000)[OFFSET(900)] / 1024, 2) AS p90
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FROM
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`httparchive.all.pages`
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WHERE
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date >= '2023-06-01' AND date <= '2024-06-01' AND -- Adjust this range as needed
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CAST(JSON_VALUE(summary, '$.bytesTotal') AS INT64) > 0 AND
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EXTRACT(DAY FROM date) = 1 -- Only include data from the first day of each month
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GROUP BY
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date,
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client,
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is_root_page
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ORDER BY
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date DESC,
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client,
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is_root_page

‎sql/2024/page-weight/request_type_distribution.sql‎

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SELECT
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percentile,
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client,
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is_root_page,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.reqTotal') AS INT64), 1000)[OFFSET(percentile * 10)] AS total_req,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.reqHtml') AS INT64), 1000)[OFFSET(percentile * 10)] AS html_req,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.reqJS') AS INT64), 1000)[OFFSET(percentile * 10)] AS js_req,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.reqCss') AS INT64), 1000)[OFFSET(percentile * 10)] AS css_req,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.reqImg') AS INT64), 1000)[OFFSET(percentile * 10)] AS img_req,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.reqJson') AS INT64), 1000)[OFFSET(percentile * 10)] AS json_req,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.reqOther') AS INT64), 1000)[OFFSET(percentile * 10)] AS other_req,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.reqFont') AS INT64), 1000)[OFFSET(percentile * 10)] AS font_req
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FROM
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`httparchive.all.pages`,
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UNNEST([10, 25, 50, 75, 90, 100]) AS percentile
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WHERE
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date = '2024-06-01' -- Adjust this date as needed
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GROUP BY
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percentile,
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client,
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is_root_page
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ORDER BY
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client,
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is_root_page,
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percentile

‎sql/2024/page-weight/response_format_distribution.sql‎

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SELECT
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client,
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percentile,
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CAST(JSON_VALUE(summary, '$.type') AS STRING) AS format,
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is_root_page,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.respBodySize') AS INT64) / 1024, 1000)[OFFSET(percentile * 10)] AS resp_size
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FROM
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`httparchive.all.requests`,
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UNNEST([10, 25, 50, 75, 90, 100]) AS percentile
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WHERE
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date = '2024-06-01' -- Adjust this date as needed
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GROUP BY
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client,
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percentile,
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format,
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is_root_page
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ORDER BY
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format,
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client,
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is_root_page,
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percentile

‎sql/2024/page-weight/response_type_distribution.sql‎

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SELECT
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client,
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percentile,
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CAST(JSON_VALUE(summary, '$.type') AS STRING) AS type,
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is_root_page,
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APPROX_QUANTILES(CAST(JSON_VALUE(summary, '$.respSize') AS INT64) / 1024, 1000)[OFFSET(percentile * 10)] AS resp_size
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FROM
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`httparchive.all.requests`,
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UNNEST([10, 25, 50, 75, 90, 100]) AS percentile
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WHERE
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date = '2024-06-01' -- Adjust this date as needed
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GROUP BY
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client,
14+
percentile,
15+
type,
16+
is_root_page
17+
ORDER BY
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client,
19+
type,
20+
is_root_page,
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percentile

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