Big data & Spark
PySpark jobs, partitioning, batch processing, and large-dataset transform patterns.
How to Mock a Catalyst Logical Plan in Python
Build a small Python class that mimics Spark Catalyst's logical plan tree for teaching or testing query optimizations.
from typing import Any, Dict, List, Optional
class CatalystLogicalPlan:
"""A minimal mock of Catalyst's logical plan for teaching purposes."""
def __init__(self, node_type: str, **kwargs: Any) -> None:
self.node_type = node_type
self.attributes: Dict[str, Any] = kwargs
self.child…Modeling a Hive Metastore Table Schema in Python
A dataclass that mimics a Hive metastore table schema—columns, partition keys, storage format, and location—with helper methods for description and mutation.
from dataclasses import dataclass, field
from typing import Dict, List, Optional
@dataclass
class HiveTable:
"""Simple mock of a Hive metastore table schema."""
name: str
database: str = "default"
columns: List[Dict[str, str]] = field(default_factory=list)
partition_keys: List[Dict[str, str]] = f…Browse by section
Each section groups closely related Python snippets.
Big data & Spark — Python code examples
What you will find here
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.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.