You can join the tables and build ts_vector with columns from whatever tables you’d like to search on. Just like in the video when he references name or description, it could have been table1.name and table2.description if they were in two different tables that you joined.
10:56 on my end, line 68 didn't seem to utilize the index on line 76. Because the index on line 76 is using to_tsvector('english', document), I had to match that as well in the WHERE clause in line 68. WHERE TO_TSVECTOR('english', document) @@ WEBSEARCH_TO_TSQUERY('thor')
Excellent ! Short, concise ... really clean explanation. Thanks
that's a really good explanation. Thank you for making this video.
Excellent... very easy to understand the explanations.
A very good tutorial thanks so much for this explanation 😊
Awesome video!!
great synopsis, thank you!
What if i want to join multiple tables and perform search on those columns
You can join the tables and build ts_vector with columns from whatever tables you’d like to search on. Just like in the video when he references name or description, it could have been table1.name and table2.description if they were in two different tables that you joined.
@@jeyfus thanks
what about using similarity() ?
Great video! Thanks!
Nice video
Thanks for sharing
Great job man!! ❤
What coding IDE are you using?
Looks like rider with a theme.
Datagrip
Great explanation, thanks!
Glad you enjoyed it!
Great intro!
10:56 on my end, line 68 didn't seem to utilize the index on line 76. Because the index on line 76 is using to_tsvector('english', document), I had to match that as well in the WHERE clause in line 68.
WHERE TO_TSVECTOR('english', document) @@ WEBSEARCH_TO_TSQUERY('thor')
Thank you man!
super helpful thanks
Спасибо за видео!
Hi, whichi software are you typing sql at ? looks gorgeous
Datagrip by jetbrains
Thank you!
great video
what is the song from intro? 🔥
What's the SQL editor you're using?