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**TLDR** Refactor WebhoonAnalytics Graph to a more abstract version AnalyticsGraph (in analytics module). Thus enabling the components to be used on different instances (ex: new endpoint, new kind of graph). **In order to test:** 1. Set ANALYTICS_ENABLED to true 2. Set TINYBIRD_JWT_TOKEN to the ADMIN token from the workspace twenty_analytics_playground 3. Set TINYBIRD_JWT_TOKEN to the datasource or your admin token from the workspace twenty_analytics_playground 4. Create a Webhook in twenty and set wich events it needs to track 5. Run twenty-worker in order to make the webhooks work. 6. Do your tasks in order to populate the data 7. Enter to settings> webhook>your webhook and the statistics section should be displayed. --------- Co-authored-by: Félix Malfait <felix@twenty.com>
29 lines
1.2 KiB
Plaintext
29 lines
1.2 KiB
Plaintext
INCLUDE "../includes/timeSeries.incl"
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-- I decided to separate the error count and the success rate because I think we should maintain the bijection
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-- between an endpoint and a graph in the front-end.
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NODE timeSeriesServerlessFunctionErrorCountData
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SQL >
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%
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SELECT
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{% if granularity == "hour" %} toStartOfHour(timestamp)
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{% else %} toDateTime64(toStartOfDay(timestamp), 3)
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{% end %} AS interval,
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uniqIf(*, success = false) as error_count
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FROM serverlessFunctionEventMV
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WHERE
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true
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AND workspaceId
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={{ String(workspaceId, '20202020-1c25-4d02-bf25-6aeccf7ea419', required=True) }}
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AND functionId = {{ String(functionId, 'ad018fc5-eace-4f7e-942f-929560a16459', required=True) }}
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AND timestamp >= parseDateTime64BestEffort({{ String(start, '2024-11-01T00:00:00.000Z') }}, 3)
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AND timestamp < parseDateTime64BestEffort({{ String(end, '2024-11-02T00:00:00.000Z') }}, 3)
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GROUP BY interval
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ORDER BY interval
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NODE endpoint
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SQL >
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%
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SELECT formatDateTime(interval, '%FT%T.000%z') as start, error_count
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FROM selectIntervalByGranularity
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LEFT JOIN timeSeriesServerlessFunctionErrorCountData USING interval
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