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##### READ SPARK DATAFRAME | |
df = spark.read.option("header", "true").option("inferSchema", "true").csv(fname) | |
# store the schema from the CSV w/ the header in the first file, and infer the types for the columns | |
df_schema = df.schema | |
##### SAVE JSON SCHEMA INTO S3 / BLOB STORAGE | |
# save the schema to load from the streaming job, which we will load during the next job | |
dbutils.fs.rm("/home/mwc/airline_schema.json", True) | |
with open("/dbfs/home/mwc/airline_schema.json", "w") as f: |
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let i = 0 | |
const start = Date.now() | |
setInterval(() => console.log(++i, Date.now() - start), 1000) | |
console.time('bigcalc') | |
for (let i = 0; i < 10000000000; ++i) { | |
Math.cos(37863443 * Math.exp(23749374)) | |
} | |
console.timeEnd('bigcalc') |
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#!/usr/bin/env ruby | |
# Copy a heroku app (buildpacks, add-ons, labs, config, users). | |
# This script is idempotent so it can run against an existing app. | |
# | |
# Usage: | |
# $> clone-heroku-app source-app target-app | |
require 'json' |
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