Big data & Spark
PySpark jobs, partitioning, batch processing, and large-dataset transform patterns.
How to Shuffle Items by Group in Python
Randomly shuffle items within each group while keeping groups contiguous, using a seed for reproducible results.
import random
def shuffle_sort_groups(items, group_key, seed=None):
"""Randomize order within groups, keeping groups contiguous."""
rng = random.Random(seed)
groups = {}
for item in items:
key = group_key(item)
groups.setdefault(key, []).append(item)
result = []
for k…Skew Join Salting Key in Python (Demo)
Demonstrates skew join salting by expanding a smaller side with salt keys and matching rows on the larger side via random salt assignment.
import random
def skew_join_salting_key(left_df, right_df, salt_range=4):
"""
Demonstrates skew join salting: expand the smaller side with salt keys,
then attach a salt key to each row on the larger side.
Returns a list of (left, right, salt) tuples.
"""
skewed_left = []
for row in left_d…Browse by section
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Big data & Spark — Python code examples
What you will find here
This page collects big data & spark snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.