• marxisthayaca [he/him,they/them]
    ·
    2 years ago

    you can click the emoji icon on replies or comments and look for the closest thing you are trying to find - but we really need better naming conventions.

      • Ho_Chi_Chungus [she/her]
        ·
        2 years ago

        ::think-mark: me using all my brain power to remember who tf the name of the star trek man is we use as the drake point meme

      • invalidusernamelol [he/him]
        ·
        2 years ago

        We just need a fuzzy dictionary for each one, have a user poll for generating the fuzzy names for them or something.

        • hexaflexagonbear [he/him]
          ·
          2 years ago

          I was having flashbacks to doing fuzzy matches in sql, then realized that the number of emojis isn't too crazy. Could probably cache the common searches people are doing too.

          • invalidusernamelol [he/him]
            ·
            2 years ago

            Oh yeah, I guess fuzzy search is the wrong term to use as it implies the SQL tools. What would really work is just a list of alternative names that the emote goes by attached to it's record.

            Or if possible a hashed table where each alternative name returns a pointer to the correct name.

            • hexaflexagonbear [he/him]
              ·
              2 years ago

              Oh yeah, I guess fuzzy search is the wrong term to use as it implies the SQL tools

              Nah, that's not what I meant. I've just had to do fuzzy search before in sql, and the issue is that fuzzy matching doesn't scale well. It's nightmarish how long it takes if you don't do proper filtering ahead of time (and have a table with 10s of millions of rows).

              • invalidusernamelol [he/him]
                ·
                2 years ago

                My brief foray into SQL and data engineering through ArcGIS has me absolutely amazed at how seamless so much of the internet is. Even doing a spatial query of a small town can take several minutes for a dataset with say 30,000 records. I tried some of my usual geospatial join and query techniques on a dataset of 175 million and my timeframe quickly approached the heat death of the universe.