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wrangler d1 insights to see what the high rows_read queries areMselect * from (select count(*) from table...);TTMTTT
select sqlite master and select (select contributes almost 10kMMTTMMTTMT
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DROP TABLE IF EXISTS at the start of your schema.sql, you can then add a package.json script that runs wrangler d1 execute dbname --local --file=schema.sql to reinitialize the db as needed
DMDD
BD1PreparedStatement if we could just D1Database->exec()? I get it can be "faster" to prepare a statement and bind different values, but since CloudFlare Workers are temporary, then what's the point? If we know that our worker is always gonna execute the same single query over and over (not multiple queries), does it make a difference in performance?
KKKK
SELECT ? FROM foo;) is not what SQLite runs. SQLite has to compile that and run it.wrangler d1 insightsselect * from (select count(*) from table...);select sqlite masterselect (selectDROP TABLE IF EXISTSwrangler d1 execute dbname --local --file=schema.sqlD1PreparedStatementD1Database->exec()SELECT ? FROM foo;db.batch([
db.insert(users).values(),
db.insert(posts).values({ userId: sql`last_insert_rowid()` })
])