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 Mock Sticky Session Read-Your-Writes in Python
Simulates a sticky session store that routes reads for a session to the node where the last write occurred, demonstrating read-your-writes consistency.
class StickySessionStore:
def __init__(self):
self.data = {}
self.session_nodes = {}
def write(self, session_id, key, value):
self.data[key] = value
self.session_nodes[session_id] = key
return f"Wrote {key}={value} for session {session_id}"
def read(self, session_i…How to Speed Up Column Lookups with DataFrame Index in Python
Use pandas set_index to make repeated column value lookups O(1)-style fast instead of scanning the whole DataFrame each time.
import pandas as pd
# Mock dataset with duplicate customer IDs
data = {"customer_id": [101, 102, 103, 101, 104, 102],
"order_amount": [250.0, 85.5, 300.0, 175.25, 420.0, 95.75]}
df = pd.DataFrame(data)
df = df.set_index("customer_id")
# Simulated lookup request
search_id = 102
# Fast index-based lookup (no…Browse by section
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Database scaling & optimization — Python code examples
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