SELECT date, wban, stn, year, mo, da, temp, count_temp, dewp, count_dewp, slp, count_slp, stp, count_stp, visib, count_visib, wdsp, count_wdsp, mxpsd, gust, max, flag_max, min, flag_min, prcp, flag_prcp, sndp, fog, rain_drizzle, snow_ice_pellets, hail, thunder, tornado_funnel_cloud, usaf, name, country, state, call, lat, lon, elev, begin, end, point_gis, fake_date FROM `fh-bigquery.weather_gsod.all_geoclustered` WHERE lat IS NOT NULL AND lon IS NOT NULL AND lat != 0 AND lon != 0 AND lat != 1 AND lon != 1 AND lat != -1 AND lon != -1 AND lat != 2 AND lon != 2 AND lat != -2 AND lon != -2 AND lat != 3 AND lon != 3 AND lat != -3 AND lon != -3 AND lat != 4 AND lon != 4 AND lat != -4 AND lon != -4 AND lat != 5 AND lon != 5 AND lat != -5 AND lon != -5 AND lat != 6 AND lon != 6 AND lat != -6 AND lon != -6 AND lat != 7 AND lon != 7 AND lat != -7 AND lon != -7 AND lat != 8 AND lon != 8 AND lat != -8 AND lon
Show HN: Describe SQL using natural language, and execute against real data
31–37 of 37 posts
Re: Show HN: Describe SQL using natural language, and execute against real data
#32This demo sent us on a warpath today. We have a fairly clean SQL schema for which we need to craft a lot of queries that handle things like business logic, reporting and configuration. If we could get even 50% success rate on a reasonable starting point for the generated SQL each time, that would be the biggest value-add our organization has ever seen. I think our use case is compelling because we have to implement t…
Possibly relevant: https://yale-lily.github.io/spider
I briefly worked on a startup to commercialize this tech, but we decided it wasn't accurate enough to be useful. It was very cool when it actually worked. If you can only produce what you want half the time on simple queries, that doesn't seem very useful to me though.
Re: Show HN: Describe SQL using natural language, and execute against real data
#33This demo sent us on a warpath today. We have a fairly clean SQL schema for which we need to craft a lot of queries that handle things like business logic, reporting and configuration. If we could get even 50% success rate on a reasonable starting point for the generated SQL each time, that would be the biggest value-add our organization has ever seen. I think our use case is compelling because we have to implement t…
Re: Show HN: Describe SQL using natural language, and execute against real data
#34Re: Show HN: Describe SQL using natural language, and execute against real data
#35This demo sent us on a warpath today. We have a fairly clean SQL schema for which we need to craft a lot of queries that handle things like business logic, reporting and configuration. If we could get even 50% success rate on a reasonable starting point for the generated SQL each time, that would be the biggest value-add our organization has ever seen. I think our use case is compelling because we have to implement t…
There are projects out there that do this. Possibly relevant: https://yale-lily.github.io/spider I briefly worked on a startup to commercialize this tech, but we decided it wasn't accurate enough to be useful. It was very cool when it actually worked. If you can only produce what you want half the time on simple queries, that doesn't seem very useful to me though.
Re: Show HN: Describe SQL using natural language, and execute against real data
#36Earlier quoted context omitted.
There are projects out there that do this. Possibly relevant: https://yale-lily.github.io/spider I briefly worked on a startup to commercialize this tech, but we decided it wasn't accurate enough to be useful. It was very cool when it actually worked. If you can only produce what you want half the time on simple queries, that doesn't seem very useful to me though.
Can you elaborate on what kind of use cases you were trying to tackle using NL2SQL in that startup? Who was the target audience/persona?
The success rate was just not good enough, even for relatively simple queries. You'd probably need to adjust the query 90% of the time, and the other 10% you couldn't even really trust that the answer was correct.