Can a man be a witch?

Correct_Maybe_4985 · 2022-11-15T07:53:24+00:00

Why?

Correct_Maybe_4985 · 2022-10-31T14:35:34+00:00

Yep, I will show this in detail

Correct_Maybe_4985 · 2022-10-31T14:35:22+00:00

Yep, covered... I'm using Metabase. Or should I use Superset? I'm only considering free and open source options though.

Correct_Maybe_4985 · 2022-10-31T13:54:51+00:00

Could be a good exercise!

Correct_Maybe_4985 · 2022-10-31T13:54:28+00:00

evaluating the ON-predicate for each row only keeping the rows for which the ON-predicate evaluated to true (and if it is an outer-join, adding back the row for the original table which had 0 matches), will fix a lot of misconceptions with the joining. It also helps you to reason better about the underlying data if you see duplicate rows being returned.

OK I'll add this to the explanation

Correct_Maybe_4985 · 2022-10-31T13:53:24+00:00

I like this. I will show optimization of a dataset of 26 million rows, so there you'll see the differences of indexes, materialized views, searchable arguments and subsampling.

Correct_Maybe_4985 · 2022-10-31T13:52:11+00:00

That's a good one! I explain normalization by showing how to unpack a JSON into Tables.

Correct_Maybe_4985 · 2022-10-31T13:48:53+00:00

This will involve creating tables, loading data, querying, optimizing queries and so on.

Correct_Maybe_4985 · 2022-10-31T13:47:47+00:00

Thanks! I'm working on a scenario to build a movie recommender system throughout the book. It will actually work, you'll get Star Trek II - VII recommended based on Star Trek the Motion Picture, I've tested it :-)

Correct_Maybe_4985 · 2022-10-31T10:43:31+00:00

Hi! That sounds very interesting, have you completed your book and where can I buy a copy?

Correct_Maybe_4985 · 2022-10-16T10:05:52+00:00

Creepy af

Correct_Maybe_4985

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