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Big data & Spark

PySpark jobs, partitioning, batch processing, and large-dataset transform patterns.

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Big data & Spark easy

How to Mock a Hash Join on Large and Small Tables in Python

This code efficiently joins a large dataset (1000 rows) with a small lookup table (20 rows) by building a dictionary hash lookup, mimicking a hash join strategy used in big data systems.

hash-join dictionaries data-join
Python 
import random
from pprint import pprint

# Large table: 1000 rows (id, group_id, value)
large = [{"id": i, "group_id": random.randint(1, 20), "value": random.random() * 100} for i in range(1000)]

# Small table: 20 rows (group_id, label)
small = [{"group_id": g, "label": f"Group-{g}"} for g in range(1, 21)]

# Mock a …
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