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Log file too big to open?
Direct answer: don't open it — stream it. Editors fail on multi-GB logs because they load everything into memory; a streamed tool reads bounded slices, assembles entries, and keeps only per-problem aggregates. The grouper below does that in your browser for files up to ~500 MB, with progress and cancel.
Stream a big log here
⚠ Raw values are visible on this screen only. Saved board data and every export stay redacted — exports never contain raw values.
Time range in file: —
This board was restored from this browser's storage — stored samples are the redacted copies by design. The raw-view toggle has no effect on restored boards.
| Severity | Problem (first sample line) | Count | First seen | Last seen |
|---|
No repeated problems — every entry in this file was seen exactly once. Check the singletons below.
Singletons — entries seen exactly once
Grouping is deterministic normalisation: timestamps, IDs, IPs and numbers are masked, then entries are matched on the masked message plus the top application frame. It groups — it does not diagnose. Check a group's samples before you act on it.
First aid on the command line
While a big file analyses, these read without loading it: tail -n 200 app.log for the end,
grep -c "ERROR" app.log for a level census, grep "09:1[0-9]" app.log for a rough
time window. less also streams and is safe on huge files. What to avoid: opening in a GUI
editor, cat-ing it into a chat window, or uploading it to a web tool that wants the whole file
over the wire before it starts.
Cut by time, not by lines
If the file must be reduced first, the safe cut is a time window around the incident:
grep -E "^2026-11-08 09:[0-5]" app.log > window.log. Entries stay whole (a trace's lines share
its header's minute, give or take a boundary straggler), the window is what you actually care about, and the
reduction is usually 50–100×. Line-count cuts (head -n 100000) answer a different, usually
useless, question: "what did the log start with?"
How the streaming grouper works
The tool above reads the file in slices, in your browser, decodes them as a stream, assembles entries line by line, and updates aggregates — nothing waits for the whole file, and the whole file is never in memory. Progress shows lines read and distinct problems so far; cancel stops cleanly and boards what was read. The board itself is aggregates only, which is why it can outlive the session in your browser's storage without keeping your log. Method details: how to group repeated errors in a log.
Frequently asked questions
Why do editors fail on big log files?
Most editors load the whole file into memory — often into a data structure several times the file size — and build indexes over it before showing a single line. Multi-GB files exhaust RAM or take minutes to open. The fix is not a bigger editor; it is tools that stream: read a bounded slice, process it, keep only aggregates.
What does "streamed" processing actually keep in memory?
Only the current chunk, the line being assembled, and the aggregate tables (one row per distinct problem, a few samples each). A 500 MB log with 300 distinct problems needs barely more memory than a 5 MB log with the same 300 problems. That is the design used by the grouper on this page: file slices in, Triage Board out.
Should I split the file first with split or head?
Only as a last resort. Splitting mid-entry can cut a stack trace in half and skew counts; head/tail show you the beginning or the end, but incidents hide in the middle. If you must reduce volume before analysis, cut by time (grep a timestamp window, or the app’s own rotation) rather than by line count — entries stay whole and the window is usually what you wanted anyway.