Logflare | Cloudflare, Vercel & Elixir Logging

~/ endpoints /functions.invocation-stats

id: a43bca12-967b-4c39-963d-070d6c08ceee

BigQuery SQL


with arr as (
  SELECT  (
      CASE
        WHEN @interval = '5min' THEN  `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(5, "minute_second")
        WHEN @interval = '15min' THEN  `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(15, "minute_minute")
        WHEN @interval = '1hr' THEN `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(1, "hour_minute")
        WHEN @interval = '1day' THEN `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(1, "day_hour")
        WHEN @interval = '7day' THEN `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(7, "day_day")
        ELSE `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(1, "day_hour")
      END
  ) as d
),
dates as (
  select d from arr, unnest(`arr`.d) as d
),
agg as (
SELECT 
  dates.d as timestamp,
  count(id) as count,
  avg(m.execution_time_ms) as avg_execution_time,
  max(m.execution_time_ms) as max_execution_time,
  min(m.execution_time_ms) as min_execution_time,
  COUNTIF(r.status_code >= 400) as error_count,
  COUNTIF(r.status_code >= 100 AND r.status_code < 200 ) as one_xx_status_code_count,
  COUNTIF(r.status_code >= 200 AND r.status_code < 300 ) as two_xx_status_code_count,
  COUNTIF(r.status_code >= 300 AND r.status_code < 400 ) as three_xx_status_code_count,
  COUNTIF(r.status_code >= 400 AND r.status_code < 500 ) as four_xx_status_code_count,
  COUNTIF(r.status_code >= 500 AND r.status_code < 600 ) as five_xx_status_code_count,
  APPROX_QUANTILES(m.execution_time_ms, 100) as p95_array,
  APPROX_QUANTILES(m.execution_time_ms, 100) as p99_array,
FROM
  arr, dates left join `deno-relay-logs` on dates.d = (
        CASE
            WHEN @interval = '5min' THEN timestamp_trunc(timestamp, second)
            WHEN @interval = '15min' THEN timestamp_trunc(timestamp, minute)
            WHEN @interval = '1hr' THEN timestamp_trunc(timestamp, minute)
            WHEN @interval = '1day' THEN timestamp_trunc(timestamp, hour)
            WHEN @interval = '7day' THEN timestamp_trunc(timestamp, day)
        ELSE timestamp_trunc(timestamp, hour)
      END)
CROSS JOIN UNNEST(metadata) as m
CROSS JOIN UNNEST(m.response) as r
WHERE
  m.project_ref = @project 
  AND CASE WHEN COALESCE(@function_id, '') = '' THEN  TRUE ELSE  m.function_id = @function_id END
  and timestamp >= arr.d[offset(0)]
GROUP BY
  timestamp
ORDER BY
  timestamp ASC
)

select
  timestamp,
  min_execution_time,
  max_execution_time,
  avg_execution_time,
  p95_array[offset(95)] as p95_execution_time,
  p99_array[offset(99)] as p99_execution_time,
  count,
  error_count
from
  agg

max rows: 1000
caching: 900 seconds
cache warming: 300 seconds
query sandboxing: disabled


WITH arr AS (SELECT (CASE WHEN @interval = '5min' THEN `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(5, "minute_second") WHEN @interval = '15min' THEN `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(15, "minute_minute") WHEN @interval = '1hr' THEN `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(1, "hour_minute") WHEN @interval = '1day' THEN `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(1, "day_hour") WHEN @interval = '7day' THEN `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(7, "day_day") ELSE `supabase-analytics-eu.logflare.generate_timestamp_trunc_array`(1, "day_hour") END) AS d), dates AS (SELECT d FROM arr, UNNEST(`arr`.d) AS d), agg AS (SELECT dates.d AS timestamp, count(id) AS count, avg(m.execution_time_ms) AS avg_execution_time, max(m.execution_time_ms) AS max_execution_time, min(m.execution_time_ms) AS min_execution_time, COUNTIF(r.status_code >= 400) AS error_count, COUNTIF(r.status_code >= 100 AND r.status_code < 200) AS one_xx_status_code_count, COUNTIF(r.status_code >= 200 AND r.status_code < 300) AS two_xx_status_code_count, COUNTIF(r.status_code >= 300 AND r.status_code < 400) AS three_xx_status_code_count, COUNTIF(r.status_code >= 400 AND r.status_code < 500) AS four_xx_status_code_count, COUNTIF(r.status_code >= 500 AND r.status_code < 600) AS five_xx_status_code_count, APPROX_QUANTILES(m.execution_time_ms, 100) AS p95_array, APPROX_QUANTILES(m.execution_time_ms, 100) AS p99_array FROM arr, dates LEFT JOIN `deno-relay-logs` ON dates.d = (CASE WHEN @interval = '5min' THEN timestamp_trunc(timestamp, second) WHEN @interval = '15min' THEN timestamp_trunc(timestamp, minute) WHEN @interval = '1hr' THEN timestamp_trunc(timestamp, minute) WHEN @interval = '1day' THEN timestamp_trunc(timestamp, hour) WHEN @interval = '7day' THEN timestamp_trunc(timestamp, day) ELSE timestamp_trunc(timestamp, hour) END) CROSS JOIN UNNEST(metadata) AS m CROSS JOIN UNNEST(m.response) AS r WHERE m.project_ref = @project AND CASE WHEN COALESCE(@function_id, '') = '' THEN true ELSE m.function_id = @function_id END AND timestamp >= arr.d[offset(0)] GROUP BY timestamp ORDER BY timestamp ASC) SELECT timestamp, min_execution_time, max_execution_time, avg_execution_time, p95_array[offset(95)] AS p95_execution_time, p99_array[offset(99)] AS p99_execution_time, count, error_count FROM agg

Call your endpoint


      # By UUID
      curl "https://api.logflare.app/api/endpoints/query/a43bca12-967b-4c39-963d-070d6c08ceee" \
      -H 'X-API-KEY: YOUR-ACCESS-TOKEN' \
      -H 'Content-Type: application/json; charset=utf-8' \
      -G -d "function_id=VALUE" -d "project=VALUE" -d "interval=VALUE"


      # By name
      curl "https://api.logflare.app/api/endpoints/query/functions.invocation-stats" \
      -H 'X-API-KEY: YOUR-ACCESS-TOKEN' \
      -H 'Content-Type: application/json; charset=utf-8' \
      -G -d "function_id=VALUE" -d "project=VALUE" -d "interval=VALUE"