Reference library

Database scaling & optimization

Indexing, connection pooling, read replicas, query tuning, and throughput-aware SQL.

4 matches
Database scaling & optimization medium

Composite index leftmost prefix in Python

Simulate a composite index in SQLite and check whether query columns match the leftmost prefix rule for index usage.

sqlite indexes database
Python
import sqlite3


def get_indexed_columns(table_name):
    """Simulate a composite index by reading column names that start with 'idx_'."""
    conn = sqlite3.connect(":memory:")
    conn.execute(f"CREATE TABLE {table_name} (id INTEGER, idx_col1 TEXT, idx_col2 INTEGER, other TEXT)")
    conn.execute(f"CREATE INDEX idx_…
13 0 Open
Database scaling & optimization medium

How to Simulate Colocated Shard Joins in Python

Groups shards by their node and merges co-located shards into a single logical unit, checking capacity constraints.

sharding database distributed-systems
Python
import random
from collections import defaultdict


def simulate_colocated_shards_join(nodes: list[dict], shards: list[dict]) -> dict:
    """
    Simulates the join of co-located shards (on the same node) into a single
    logical shard. Returns the resulting node-to-shard mapping.

    Each node: {'id': str, 'capaci…
11 0 Open
Database scaling & optimization easy

How to Validate Data Before Scaling in Python

A reusable Python helper that validates required fields and constraint checks on data rows before entering a database pipeline, improving data quality and throughput.

validation data-quality scaling
Python
def validate_data(data, required_fields, constraints=None):
    """
    Basic validation helper demonstrating data-quality workflows
    before scaling (catches bad rows early, improves throughput).
    """
    constraints = constraints or {}

    errors = []
    for field in required_fields:
        if field not in d…
15 0 Open
Database scaling & optimization easy

Monitor Database Index Bloat in Python

Simulates index bloat checks for database tables using random ratio thresholds and reports alerts per index.

database index monitoring
Python
import random
import time

class IndexBloatMonitor:
    def __init__(self, thresholds=(0.5, 0.8, 0.9)):
        self.thresholds = thresholds
        self.indices = {
            "users_pk": 48.2,
            "orders_created_idx": 124.7,
            "products_name_idx": 15.3,
            "payments_user_idx": 203.9,
   …
15 0 Open

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Database scaling & optimization — Python code examples

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