Big data & Spark
PySpark jobs, partitioning, batch processing, and large-dataset transform patterns.
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.
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…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.
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}")How to Mock a Parquet partitionBy Sink in Python
Manually write a DataFrame to partitioned Parquet files, mimicking Spark's partitionBy sink behavior without Spark.
import pyarrow as pa
import pyarrow.parquet as pq
from pathlib import Path
import tempfile
import shutil
def mock_partition_by_sink(data, output_dir, partition_cols):
table = pa.Table.from_pandas(data)
schema = table.schema
unique_combos = table.select(partition_cols).to_pylist()
seen = set()
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Big data & Spark — Python code examples
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This page collects big data & spark snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
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