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Asked: 2026-05-16T23:50:21+00:00

here is how my tables are currently setup: Dataset | – Dataset_Id – Int

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here is how my tables are currently setup:

Dataset
 |
 - Dataset_Id - Int
 |
 - Timestamp - Timestamp

Flowrate
 |
 -Flowrate_id - int
 |
 -Dataset_id - ALL NULL (INT)
 |
 -TimeStamp - TimeStamp
 |
 -FlowRate - FLoat

I want to update the flowrate dataset_id column so that its ids corespond to the dataset dataset_ids. The Dataset table has over close to 400000 rows…. How can I do this so that it does not take forever. This data came from different data loggers and that’s why I need to link them with their timestamps….

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1 Answer

  1. Editorial Team
    UPDATE
  Flowrate JOIN Dataset ON (Flowrate.TimeStamp = Dataset.Timestamp)
  SET Flowrate.Dataset_id = Dataset.Dataset_Id

    completely independent from Python of course (what a weird tag to put here — as if MySql cared what language you’re using to send fixed SQL statements to it?!). Will be fast if and only if the tables are properly indexed, of course.

    Absolutely weird capitalization irregularities you have in your schema, BTW — would drive me absolutely bonkers if anybody used lowercase vs uppercase at random spots of column names that are so obviously “meant to” be identical! Nevertheless I’ve tried to reproduce it exactly, but I hope you reconsider this absurd style choice.

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