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Big data & Spark

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

9 matches
Big data & Spark medium

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.

hyperloglog distinct-count probabilistic
Python
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 = …
14 0 Open
Big data & Spark easy

How to Create a Mock Kafka Producer in Python

Build a Kafka producer that generates mock streaming records with JSON serialization and error handling for local testing.

kafka streaming producer
Python
import json
import time
from kafka import KafkaProducer
from kafka.errors import KafkaError

def create_mock_producer(bootstrap_servers="localhost:9092", topic="input-topic"):
    """Create a Kafka producer that generates mock streaming data."""
    producer = KafkaProducer(
        bootstrap_servers=bootstrap_servers…
16 0 Open
Big data & Spark medium

How to Implement a Streaming Watermark in Python

Mock structured streaming watermarks in Python to track late event times and compute a watermark for windowed processing.

streaming watermark spark
Python
from datetime import datetime, timedelta
import time

class StreamingWatermark:
    """Mock watermark tracker for structured streaming."""

    def __init__(self, watermark_delay_seconds):
        self.watermark_delay = timedelta(seconds=watermark_delay_seconds)
        self.max_event_time = None

    def observe_even…
14 0 Open
Big data & Spark medium

How to Mock Spark Streaming Micro-Batches in Python

Simulate Spark's micro-batch streaming with a simple deque-based class that collects events over time and processes them in timed batches.

spark streaming micro-batch
Python
import time
from collections import deque
from datetime import datetime


class MicroBatchStream:
    def __init__(self, batch_interval_sec=2):
        self.batch_interval = batch_interval_sec
        self.source = deque()
        self.processed = []

    def add_events(self, events):
        self.source.extend(events…
13 0 Open
Big data & Spark easy

How to Mock a Socket Stream in Python

Simulate a streaming socket source with a generator to test stream-read and buffering logic without a real network.

socket mock streaming
Python
import socket
import threading
import time

def mock_socket_stream(data_chunks, delay=0.1):
    """Generator that simulates a streaming socket source."""
    for chunk in data_chunks:
        time.sleep(delay)
        yield chunk

def read_stream_socket(stream_gen):
    """Reads from mock stream and prints received ch…
14 0 Open
Big data & Spark medium

How to Mock and Test a Rate-Limited Source Stream in Python

Build a class that rate-limits emitted items using a sliding window and test it with a simulated stream in Python.

rate-limiting mock-testing streaming
Python
import time
from collections import deque


class RateLimitedSource:
    def __init__(self, max_rate, window=1.0):
        self.max_rate = max_rate
        self.window = window
        self._timestamps = deque()

    def emit(self, item):
        now = time.monotonic()
        while self._timestamps and self._timestam…
16 0 Open
Big data & Spark medium

How to implement a tumbling window aggregation in Python

Build a mock tumbling window aggregator in Python that groups streaming events into fixed time intervals and computes count, sum, and average per window.

tumbling-window streaming aggregation
Python
import time
from collections import deque

class TumblingWindow:
    def __init__(self, duration_seconds):
        self.duration = duration_seconds
        self.buffer = deque()
        self.window_start = None

    def add(self, item):
        current_time = time.time()
        if self.window_start is None:
         …
13 0 Open
Big data & Spark medium

How to use foreachBatch with a mock sink in PySpark

Demonstrates using Spark Structured Streaming's foreachBatch sink to capture and verify streaming batches by writing them into a custom mock sink object.

pyspark structured-streaming foreachbatch
Python
from pyspark.sql import SparkSession
from pyspark.sql.functions import col, lit

class MockSink:
    def __init__(self):
        self.batches = []
    
    def write_batch(self, batch_df, batch_id):
        # Collect batch data as list of dicts for verification
        records = batch_df.collect()
        self.batches…
14 0 Open
Big data & Spark easy

Sliding Window Streaming Mock in Python

A simple Python class that maintains a sliding window of recent streaming values and computes the running average.

streaming sliding-window averages
Python
import time
import random

class StreamingMock:
    """Produces a stream of numbers using a sliding window."""
    
    def __init__(self, window_size=5):
        self.window = []
        self.window_size = window_size
        
    def push(self, value):
        """Add a value, sliding the window forward."""
        s…
12 0 Open

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Big data & Spark — Python code examples

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