| MacBook-Pro-de-javi.local :) select cityHash64(groupArray(cityHash64(*))) from A a asof inner join (select * from B where ts<toDateTime('1970-01-01 02:00:00')) b on a.id=b.id and a.ts=b.ts where a.ts<toDateTime('1970-01-01 02:00:00'); | |
| SELECT cityHash64(groupArray(cityHash64(*))) | |
| FROM A AS a | |
| ASOF INNER JOIN | |
| ( | |
| SELECT * | |
| FROM B | |
| WHERE ts < toDateTime('1970-01-01 02:00:00') | |
| ) AS b ON (a.id = b.id) AND (a.ts = b.ts) |
| https://docs.google.com/presentation/d/1vURI9yYJvAm0couPbFeKz09sr8bvQuSzCfcTEBow7ec/edit#slide=id.g5294e95553_0_101 |
IMPORTANT, this worked with CH stable (76629e9) version on 2019/02/14
from the original osx build doc page https://clickhouse.yandex/docs/en/development/build_osx.html
Add /usr/local/include to the default path for gcc (for some reason gcc-7 was not using that folder on osx)
| """ | |
| projects a numpy array with (lon, lat) to (x, y) in mercator coordinates using numpy | |
| license: MIT | |
| adapted from https://github.com/mapbox/mercantile | |
| """ | |
| import numpy as np | |
| import math |
| """haversine function adapted to work with numpy arrays | |
| Adapted from https://github.com/mapado/haversine/blob/master/haversine/__init__.py | |
| License: MIT | |
| """ | |
| import math | |
| import numpy as np | |
| AVG_EARTH_RADIUS = 6371 * 1000 # m |
| set nocompatible | |
| set rtp+=~/.vim/bundle/vundle/ | |
| call vundle#rc() | |
| let g:ackprg = 'ag --nogroup --nocolor --column' | |
| map <F6> :%s/>\s*</>\r</g<CR>ggVG= | |
| "colorscheme koehler |
| // license: BSD3 | |
| const WEBMERCATOR_R = 6378137.0; | |
| const DIAMETER = WEBMERCATOR_R * 2 * Math.PI; | |
| class Mercator { | |
| static project(lon, lat) { | |
| var x = DIAMETER * lon/360.0; | |
| var sinlat = Math.sin(lat * Math.PI/180.0); | |
| var y = DIAMETER *Math.log((1+sinlat)/(1-sinlat)) / (4*Math.PI); | |
| return { x, y }; | |
| } |
| import urllib,sys,csv; | |
| print reduce(lambda p, new: (p[0] + (new - p[0])/p[1], p[1] + 1), map(float, (x['tip_amount'] for x in csv.DictReader(urllib.urlopen(sys.argv[1])))), (0, 1)) |
Build the following and make it run as fast as you possibly can using Python 3 (vanilla). The faster it runs, the more you will impress us!
Your code should:
All of that in the most efficient way you can come up with.
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta charset="utf-8"> | |
| <meta http-equiv="X-UA-Compatible" content="IE=edge"> | |
| <title>HOJA DE ESTILO DISEÑO ECONOMIA</title> | |
| <meta name="description" content="Hoja de estilo para diseño del Master Economia"> |