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Big data & Spark

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

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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

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
Big data & Spark easy

Partition Data by Hash Key Mod N in Python

Returns a partition index for a string key by hashing it with MD5 and taking modulo N, then groups sample keys into partitions.

hashing partitioning hashlib
Python
import hashlib


def partition_key(key: str, num_partitions: int) -> int:
    """Return partition index for key using MD5 hash mod N."""
    digest = hashlib.md5(key.encode()).hexdigest()
    return int(digest, 16) % num_partitions


if __name__ == "__main__":
    keys = ["alice", "bob", "carol", "dave", "eve"]
    nu…
12 0 Open
Big data & Spark easy

Session window gap mock in Python

Group sorted timestamps into sessions where any gap between consecutive events exceeds a threshold starts a new session.

timestamps sessions windowing
Python
from datetime import datetime, timedelta


def session_windows(timestamps, gap_seconds=300):
    """Group timestamps into sessions where gaps > gap_seconds start new sessions."""
    if not timestamps:
        return []

    # Sort timestamps chronologically to ensure correct windowing
    timestamps = sorted(timestam…
14 0 Open

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Big data & Spark — Python code examples

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