Adrian Palacios msure

LookML vs Materialized Views

Say we're working with clickstream data:

CREATE TABLE pageviews (
  "timestamp"   timestamp,
  url           text,
  referrer      text,
 user_agent text,

PostgreSQL Data Types	AWS DMS Data Types	Redshift Data Types
INTEGER	INT4	INT4
SMALLINT	INT2	INT2
BIGINT	INT8	INT8
NUMERIC (p,s)	If precision is 39 or greater, then use STRING.	If the scale is => 0 and =< 37 then: NUMERIC (p,s) If the scale is => 38 and =< 127 then: VARCHAR (Length)
DECIMAL(P,S)	If precision is 39 or greater, then use STRING.	If the scale is => 0 and =< 37 then: NUMERIC (p,s) If the scale is => 38 and =< 127 then: VARCHAR (Length)
REAL	REAL4	FLOAT4
DOUBLE	REAL8	FLOAT8
SMALLSERIAL	INT2	INT2
SERIAL	INT4	INT4

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It's now here, in The Programmer's Compendium. The content is the same as before, but being part of the compendium means that it's actively maintained.

How many times shouldn't it happen...

-- https://news.ycombinator.com/item?id=11396045

SELECT count(*)
FROM (SELECT id, repo_name, path
        FROM [bigquery-public-data:github_repos.sample_files]
 ) AS F

	0-mail.com
	007addict.com
	020.co.uk
	027168.com
	0815.ru
	0815.su
	0clickemail.com
	0sg.net
	0wnd.net
	0wnd.org

	library(tidyverse)

	# data from https://www.kaggle.com/bls/american-time-use-survey

	df.resp <- read_csv('../data/atus/atusresp.csv')
	df.act <- read_csv('../data/atus/atusact.csv', col_types=cols(tustarttim = col_character(), tustoptime = col_character()))
	df.sum <- read_csv('../data/atus/atussum.csv')

	df.tmp <- df.act %>%
	mutate(activity = case_when(trtier2p == 1301 ~ 'Exercise',