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Big data & Spark

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

4 matches
Big data & Spark easy

How to Filter and Project Spark DataFrames with PySpark SQL

Simulate a SQL SELECT with WHERE using PySpark DataFrame select and filter to project columns and apply conditions.

pyspark dataframe filter
Python
from pyspark.sql import SparkSession
from pyspark.sql.functions import col

spark = SparkSession.builder.appName("QueryFilterMock").master("local[2]").getOrCreate()

data = [
    ("Alice", 28, "Engineering"),
    ("Bob", 35, "Sales"),
    ("Carol", 32, "Engineering"),
    ("David", 25, "Marketing"),
    ("Eve", 29, "E…
14 0 Open
Big data & Spark medium

How to Implement row_number Window Function in Python

This code implements a SQL-style ROW_NUMBER() window function in pure Python, partitioning rows by a set of columns and ranking them within each partition by an ordered set of columns.

window-functions data-processing row-number
Python
from collections import defaultdict
import itertools


def row_number(rows, partition_by, order_by):
    partitions = defaultdict(list)
    for index, row in enumerate(rows):
        key = tuple(row[col] for col in partition_by)
        partitions[key].append((index, row))

    result = []
    for key in partitions:
 …
17 0 Open
Big data & Spark easy

How to Mock Hive Support in PySpark with unittest.mock

This code demonstrates how to mock Hive support in a PySpark environment using unittest.mock to simulate SQL queries returning fixed data.

pyspark hive mock
Python
from unittest.mock import Mock, patch


def get_hive_tables(spark):
    """Mock Hive support by returning a fixed list of tables."""
    return spark.sql("SHOW TABLES").collect()


class HiveTable:
    """Simple class that mimics a Hive table row."""
    def __init__(self, database, tableName):
        self.database =…
14 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

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Big data & Spark — Python code examples

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