About

Data sanitation often begins with uniqueness. Redundant entries in SQL dumps, email lists, or server logs distort analytics and break import scripts. This tool isolates unique lines from raw text blocks using high-efficiency hashing algorithms. It is specifically engineered to handle large datasets where manual filtering is impossible.

Accuracy in deduplication depends on defining what constitutes a match. A trailing space or a capitalized letter can treat two otherwise identical lines as distinct. This utility provides granular control over these variables (whitespace trimming and case sensitivity) to ensure the resulting dataset meets specific structural requirements. The processing occurs strictly on the client side using O(n) complexity logic.

Formulas

The efficiency of deduplication is determined by the algorithmic complexity. Naive comparison methods compare every line against every other line, resulting in exponential slowness as data grows.

Naive Complexity = O(n²)

This tool utilizes a Hash Set data structure to store unique signatures. This reduces the time complexity to linear time, allowing for the processing of 100,000 lines in milliseconds rather than minutes.

Optimized Complexity = O(n)

When Case Insensitivity is active, the comparator function transforms the input vector v before hashing:

key = toLowerCase(trim(line))

Reference Data

Transformation Type	Input Sample	Output Result	Logic Applied
Exact Match	Apple Apple	Apple	String literal equality (s₁ = s₂).
Case Insensitive	User1 user1	User1	Normalized comparison (lower(s)). First occurrence retained.
Trim Whitespace	data data	data	Removal of leading/trailing ASCII 32.
Empty Removal	A B	A B	Length check (len > 0).
Lexicographical Sort	Zebra Alpha	Alpha Zebra	ASCII value comparison.
Numeric Sort	10 2	2 10	Value parsing and ordering.
JSON Dedupe	{"id":1} {"id":1}	{"id":1}	Stringified object hashing.
CSV Line	a,b,c a,b,c	a,b,c	Full line buffer comparison.

Frequently Asked Questions

The tool retains the first instance found in the list (FIFO - First In, First Out). If "Case Insensitive" is checked, "Apple" and "apple" are treated as duplicates; if "Apple" appears first, it remains, and "apple" is discarded.

We rely on the JavaScript Set object, which uses a hash map implementation. This allows for constant-time insertion and lookup. We also batch DOM updates to prevent the browser rendering engine from freezing during the operation.

Text sorting uses ASCII/Unicode values (1, 10, 2, 20). Numeric sorting parses the string values to arrange them by magnitude (1, 2, 10, 20). Use Numeric Sort when processing lists of IDs or financial figures.

No. The tool processes data line-by-line. It checks the uniqueness of the entire row string. It does not parse or alter individual columns within a CSV file, ensuring integrity is maintained as long as the rows are exact matches.