Clare S. Y. Huang csyhuang

git clone [email protected]:YOUR-USERNAME/YOUR-FORKED-REPO.git

cd into/cloned/fork-repo
git remote add upstream git://github.com/ORIGINAL-DEV-USERNAME/REPO-YOU-FORKED-FROM.git
git fetch upstream

Spark Tips & Tricks

If values are integers in [0, 255], Parquet will automatically compress to use 1 byte unsigned integers, thus decreasing the size of saved DataFrame by a factor of 8.
Partition DataFrames to have evenly-distributed, ~128MB partition sizes (empirical finding). Always err on the higher side w.r.t. number of partitions.
Pay particular attention to the number of partitions when using flatMap, especially if the following operation will result in high memory usage. The flatMap op usually results in a DataFrame with a [much] larger number of rows, yet the number of partitions will remain the same. Thus, if a subsequent op causes a large expansion of memory usage (i.e. converting a DataFrame of indices to a DataFrame of large Vectors), the memory usage per partition may become too high. In this case, it is beneficial to repartition the output of flatMap to a number of partitions that will safely allow for appropriate partition memory sizes, based upon the

kill $(jobs -p)

pytest --durations=0

$ python -m cProfile -o profile $(which py.test)

start new:

tmux

start new with session name:

tmux new -s myname

	#!/bin/bash

	# Based on http://algs4.cs.princeton.edu/linux/

	declare -r ALGS4_DIRECTORY=~/.local/algs4

	get_drjava() {
	wget http://algs4.cs.princeton.edu/linux/drjava.jar
	wget http://algs4.cs.princeton.edu/linux/drjava
	chmod 700 drjava