Database scaling & optimization
Indexing, connection pooling, read replicas, query tuning, and throughput-aware SQL.
Broadcast a Small Reference Table in Python
Simulates SQL-style broadcasting of a small lookup table against a larger fact table in memory for mockups or load tests.
import random
def broadcast_mock(target, source, columns):
result = {}
for col in columns:
if col in target and col in source:
result[col] = target[col] + [source[col][i % len(source[col])] for i in range(len(target[col]))]
elif col in target:
result[col] = target[col]
…How to Batch Load JSON Data in Python for Database Optimization
This code parses JSON data into records and loads them in batches to simulate efficient database insertion, reducing load and improving performance.
import json
import time
def parse_and_load(data, batch_size=100):
"""
Parse JSON data and batch-load into a list of dicts.
Demonstrates batching for database efficiency.
"""
records = json.loads(data)
batches = []
for i in range(0, len(records), batch_size):
batch = records[i:i + …Route SELECT Queries to Read Replicas in Python
A mock round-robin router that forwards SELECT queries to read replicas and sends writes to the primary.
import random
class ReadReplicaRouter:
"""Round-robin router that sends SELECT queries to read replicas."""
def __init__(self, replicas):
self.replicas = replicas
self.counter = 0
def route(self, sql):
if sql.strip().upper().startswith("SELECT"):
replica = sel…Browse by section
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Database scaling & optimization — Python code examples
What you will find here
This page collects database scaling & optimization 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.
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