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Big data & Spark

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

8 matches
Big data & Spark medium

Bloom Filter Join Mock in Python

A mock hash join that uses a Bloom filter to pre-filter one table before performing an exact match, reducing the number of comparisons in large dataset joins.

bloom filter join hashing
Python
import hashlib
import random
import string


class BloomFilter:
    def __init__(self, size: int = 200, num_hashes: int = 3):
        self.bits = [False] * size
        self.size = size
        self.num_hashes = num_hashes

    def _hashes(self, item: str):
        result = []
        for seed in range(self.num_hashes…
13 0 Open
Big data & Spark medium

Delta Lake ACID Transaction Log Mock in Python

Simulates Delta Lake's transactional log with JSON files for atomic commits, versioned operations, and crash recovery

delta-lake transaction-log acid
Python
import json
import time
from pathlib import Path

class DeltaLog:
    def __init__(self, path):
        self.log_dir = Path(path)
        self.log_dir.mkdir(parents=True, exist_ok=True)
        self.version = 0

    def _write_txn(self, action, payload):
        txn = {
            "version": self.version,
           …
16 0 Open
Big data & Spark easy

How to Implement MapReduce Word Count in Python Using a Dict

Simulate a MapReduce word count pipeline in Python with a mock dict, splitting text into words, shuffling, and reducing to frequency counts.

mapreduce word-count dictionary
Python
def map_reduce_word_count(text: str) -> dict:
    """Simulate a MapReduce pipeline to count word frequencies."""
    # MAP phase: split into words and emit (word, 1) pairs
    mapped = []
    for word in text.lower().split():
        # Clean word of punctuation
        clean_word = ''.join(char for char in word if cha…
16 0 Open
Big data & Spark easy

How to Mock DataFrame Schema Columns in Python

Create an empty pandas DataFrame with only the specified column names to mock a schema before any data is loaded.

pandas dataframe schema
Python
import pandas as pd

def mock_schema(columns):
    return pd.DataFrame(columns=columns)

if __name__ == "__main__":
    cols = ["name", "age", "city"]
    df = mock_schema(cols)
    print(df)
    print(f"Columns: {list(df.columns)}, Shape: {df.shape}")
14 0 Open
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 …
13 0 Open
Big data & Spark easy

How to Shuffle Items by Group in Python

Randomly shuffle items within each group while keeping groups contiguous, using a seed for reproducible results.

random shuffle grouping
Python
import random

def shuffle_sort_groups(items, group_key, seed=None):
    """Randomize order within groups, keeping groups contiguous."""
    rng = random.Random(seed)
    
    groups = {}
    for item in items:
        key = group_key(item)
        groups.setdefault(key, []).append(item)
    
    result = []
    for k…
13 0 Open
Big data & Spark easy

How to select specific columns in Python with SQLite

A reusable function that connects to a SQLite database and returns only the requested columns from a given table.

sqlite sql database
Python
import sqlite3

def select_pruned_columns(db_path, table, columns):
    with sqlite3.connect(db_path) as conn:
        cursor = conn.cursor()
        col_list = ", ".join(columns)
        query = f"SELECT {col_list} FROM {table}"
        return cursor.execute(query).fetchall()

if __name__ == "__main__":
    conn = sq…
15 0 Open
Big data & Spark easy

Hudi Upsert Mock Copy on Write in Python

Simulates Apache Hudi's Copy-on-Write upsert behavior by merging update records into a deep copy of base records, replacing matches or appending new ones.

hudi upsert copy-on-write
Python
import copy
from typing import Dict, List, Any

def upsert_copy_on_write(base_records: List[Dict[str, Any]], updates: List[Dict[str, Any]], key_field: str = "id") -> List[Dict[str, Any]]:
    """Simulate Hudi Copy-on-Write upsert: merge updates into a copy of base records."""
    result = copy.deepcopy(base_records)
 …
14 0 Open

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