Duplicate Log Line Remover

Repeat chatter buries signal fast. Duplicate Log Line Remover deduplicates any paste, keeping the first occurrence of each line and reporting how many exact repeats were dropped.

For timestamps that make otherwise-identical lines unique, the ignore-timestamp mode strips the leading time — ISO, space-separated, Apache/nginx brackets, syslog or epoch — so genuinely repeated messages collapse correctly instead of surviving as “different” lines just because the clock ticked forward.

Matching is exact-text by default: two lines are duplicates only if every remaining character lines up, which makes the tool safe for JSON payloads, stack traces, or any line where a fuzzy match could hide a real difference.

• First-wins — original order preserved; the earliest occurrence of each line represents the group.
• Ignore timestamp — strips a leading ISO, space-separated, Apache/nginx-bracket, syslog or epoch timestamp before comparing, so repeated events at different times still dedupe.
• Case toggle — switch between case-sensitive and case-insensitive matching for logs that vary only in casing.
• Clear stats — total, unique and removed counts after every run.
• Exact-text safety — no fuzzy matching, so JSON lines and structured payloads are compared reliably.
• Copyable output — the deduplicated list, in original order, ready to paste elsewhere.

1. Paste the log with repeated lines into the text area.
2. Tune the “ignore leading timestamp” toggle if repeated events carry different timestamps, and the case-insensitive toggle if casing varies.
3. Run. Exact duplicates (after the chosen comparison rules) collapse to their first occurrence.
4. Check the stats — total lines in, unique lines out, and how many were removed.
5. Copy the unique lines for further analysis or to attach to a report.

Example 1 — Repeated errors. A crash loop spams the same stack trace once a second for an hour; with ignore-timestamp on, all of those collapse to a single representative line plus a removed count that quantifies the noise.

Example 2 — Healthcheck noise. Identical INFO heartbeats every minute drown out real events; deduplicating reduces them to one line so the log becomes scannable again.

Example 3 — Report dedupe. Before counting events for a summary, remove exact repeats so your totals reflect distinct occurrences rather than the same line echoed by a retry or a duplicate log shipper.

Example 4 — Case-drift cleanup. Two services log the same event with different capitalization (Connection Reset vs connection reset); the case-insensitive toggle merges them into one line.

• Instant cleanup — collapses repeat noise without writing a dedupe script.
• Order preserved — the first occurrence of each unique line stays exactly where it appeared.
• Smart modes — timestamp-agnostic and case-insensitive comparisons handle the two most common reasons “identical” lines look different.
• Safe for structured data — exact-text comparison won’t silently merge JSON lines that differ in one field.
• Private — deduplication runs entirely in your browser.