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npx wrangler d1 insights <dbname> you can see query timing data)Ɽ
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MMⱤMⱤMMwrangler d1 insights for historical data (like 31 days) will be inaccurate for a bit
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npx wrangler@latest d1 insights <dbname> --sortBy reads --timePeriod 7d, will tell you the queries doing thisMAAAM
SSMMSMwrangler d1 insights, as well as the Cloudflare dashboard (see the Metrics tab for your D1 database). You can use that data to figure out what D1 will cost you.
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.sql file been added yet? The ability to back up / download the DB locally, ideally from the Dashboard, is what’s keeping me from using this over Turso / sqld
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Gnpx wrangler --persist-to ../../../.wrangler d1 execute content --local --file sql/content.articles.sql
wrangler 3.28.1
-------------------Mapping SQL input into an array of statements
workerd/jsg/setup.c++:493: error: CODE_MOVED for unknown code block?
workerd/jsg/setup.c++:493: error: CODE_MOVED for unknown code block?
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45332.058900462966 which I thought was easier to query. the numeric part is the number of days while the decimal is the time.. if I am querying a BETWEEN statement, the process will be straightforward..D
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npx wrangler d1 insights <dbname>wrangler d1 insightswrangler d1 insightsnpx wrangler@latest d1 insights <dbname> --sortBy reads --timePeriod 7d "avgRowsRead": 92284,
"totalRowsRead": 7659605,
"avgRowsWritten": 0,
"totalRowsWritten": 0,
"avgDurationMs": 26.3779313253012,
"totalDurationMs": 2189.3682999999996,
"numberOfTimesRun": 83.sql45332.058900462966INSERT INTO db VALUES (1), (2)const MS_PER_DAY = 24 * 60 * 60 * 1000;
const EPOCH_1900 = new Date('1899-12-30T00:00:00.000Z').getTime();
export function dateToExcelNumberWithTime(date: Date): number {
const gmtOffset = date.getTimezoneOffset();
const adjustment = (0 - gmtOffset) * 60 * 1000;
const finalDate = (date.getTime() - EPOCH_1900 + adjustment) / MS_PER_DAY;
return finalDate;
}