Linked Lists: Powering Data Engineering Workflows

Data engineers juggle a diverse arsenal of data structures to manage ever-growing data volumes and complex formats. Among these tools, Linked Lists emerge as a powerful weapon, offering flexibility and dynamism. This blog post delves into the core concepts of Linked Lists, explores their applications in data engineering, particularly within Extract, Transform, Load (ETL) pipelines, and demonstrates how they empower efficient and scalable data processing solutions.

Understanding Linked Lists: Building Blocks for Flexibility

Imagine a train with connected cars. Each car (node) carries valuable data and is linked to the next car (reference) in the sequence. This analogy captures the essence of a Linked List: a dynamic data structure where elements (nodes) are not stored contiguously in memory but rather connected through references. This flexibility offers distinct advantages:

Dynamic Sizing: Unlike arrays, Linked Lists don't require pre-allocation of memory. You can add or remove nodes on the fly, making them ideal for scenarios where data size is unpredictable.

Efficient Insertion/Removal: Inserting or removing elements at any position becomes a breeze as you only need to manipulate the references between nodes. This is a stark contrast to arrays, where insertion or removal in the middle can involve significant data shifting.

Types of Linked Lists

Linked lists are fundamental data structures that store elements in a linear fashion. Unlike arrays, elements in a linked list are not stored contiguously in memory. Instead, each element (node) holds data and a reference (pointer) to the next node in the sequence. This dynamic allocation allows for efficient insertions and deletions at any point in the list.

There are two main types of linked lists, each offering distinct advantages:

Single Linked List:
- Each node points to the next node in the list, enabling traversal in one direction (forward).
- Simpler to implement compared to double linked lists.
Double Linked List:
- Each node points to both the next and the previous node, allowing for traversal in both directions (forward and backward).
- Offers more flexibility for operations like removing elements or inserting in the middle.

Code Example: A Glimpse into Single Linked Lists (Java)

To solidify our understanding, let's explore a basic single linked list implementation in Java:

class Node {

int data;

Node next;

public Node(int data) {

this.data = data;

}

public class SingleLinkedList {

private Node head;

public void addFirst(int data) {

Node newNode = new Node(data);

newNode.next = head;

head = newNode;

}

public void printList() {

Node current = head;

while (current != null) {

System.out.print(current.data + " -> ");

current = current.next;

}

System.out.println("NULL");

}

public static void main(String[] args) {

SingleLinkedList list = new SingleLinkedList();

list.addFirst(5);

list.addFirst(3);

list.addFirst(1);

list.printList(); // Output: 1 -> 3 -> 5 -> NULL

}

This code demonstrates a single linked list where we can add elements at the beginning (addFirst) and traverse the list using a while loop until we encounter the null reference at the end.

Beyond Caching: Linked Lists in Action

While linked lists excel in handling collisions in caching and maintaining insertion order in hash sets/maps, their applications extend far beyond:

Semi-structured Data Processing: While linked lists can represent semi-structured data like JSON or XML, where the order of elements might be significant, with nodes holding data elements and child elements linked as sub-lists, tree-based data structures like binary trees or n-ary trees are generally more efficient and commonly used for representing and manipulating hierarchical data structures.
Streaming Data Processing: In real-time data pipelines, linked lists can be used to buffer incoming data streams. New data elements are added at the head, and older elements are removed from the tail, ensuring efficient processing of the most recent data.
Graph Algorithms: Linked lists are fundamental building blocks for representing graphs (networks of nodes connected by edges) used in big data applications. Nodes in the linked list represent vertices in the graph, and edges can be implemented using references between nodes.

Linked Lists and DAGs: Orchestrating ETL Pipelines

Directed Acyclic Graphs (DAGs) are crucial for representing the dependencies between stages in ETL pipelines. Here's where linked lists come into play:

Nodes as Data Structures: Each node in the DAG can be implemented as a data structure containing information about the task (e.g., function to execute, input data) and references (links) to its dependent tasks.
Linked List for Dependencies: These references can be formed using a linked list structure. A node can point to the next nodes in the sequence that depend on its output data.
Sequential Processing: The linked list structure enforces a sequential order. A task can only be executed once its predecessor tasks (nodes preceding it in the list) have completed.

This approach ensures tasks are triggered in the correct order based on their dependencies.

Sources

I hope this provides a clear and concise explanation of linked lists, focusing on single and double linked lists!