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How to Validate Fact Table Grain Row Counts in Python
Validate fact table grain by checking dimension key references, unique grain combinations, duplicate rows, and dimension cardinality from a CSV file.
import csv
import hashlib
from pathlib import Path
def validate_fact_grain(fact_file: Path, expected_dim_keys: dict[str, set[str]]) -> dict:
"""
Validate fact table grain by checking each row's dimension keys exist
in expected dimension tables and row count consistency.
"""
dim_references = {}
…Approximate Distinct Count in Python with HyperLogLog
Mock a large data stream and estimate the number of distinct items with a HyperLogLog-style probabilistic counter to save memory.
import random
import string
from collections import Counter
import math
class ApproxCountDistinct:
def __init__(self, num_buckets=16):
self.num_buckets = num_buckets
self.max_zeros = [0] * num_buckets
def _hash(self, item):
# Simple string hash to a 32-bit integer
h = …HyperLogLog Cardinality Estimation in Python
A small HyperLogLog implementation using MD5 hashing and 256 registers to estimate the number of unique items in a large stream with fixed memory.
import hashlib
import math
class HyperLogLog:
def __init__(self, b=8):
self.b = b
self.m = 1 << b
self.registers = [0] * self.m
self.alpha = 0.7213 / (1 + 1.079 / self.m)
def add(self, item):
h = int(hashlib.md5(str(item).encode()).hexdigest(), 16)
idx = h & (s…Approximate Count with HyperLogLog in Python
A mock HyperLogLog implementation uses hash-based registers to estimate cardinality of large datasets with sublinear memory.
import hashlib
class HyperLogLog:
def __init__(self, precision=4):
if precision < 4 or precision > 16:
raise ValueError("precision must be between 4 and 16")
self.precision = precision
self.registers = [0] * (1 << precision)
def _hash(self, value):
return int(hashl…Simulate Shard Key Cardinality in Python
Generate mock data with configurable cardinality to evaluate shard key distribution and detect hotspots in database scaling design.
import random
import string
def calculate_cardinality(values):
"""Return the number of distinct values in the given list."""
return len(set(values))
def generate_mock_data(num_records, cardinality):
"""Generate mock records for a shard key with given cardinality."""
possible_keys = [f"key_{i:04d}" fo…Browse by section
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