70:T456a,# feat: Search compressed data without decompression Compression saves space, but it usually makes your data *opaque*: to find anything you first have to decompress the whole thing. MinLZ changes that. A MinLZ stream can carry a small per\-block search index that lets `mz search` find a byte sequence while **skipping every block that provably can't contain it** — those blocks are never decompressed, and (with a sidecar) never even read from disk. The result: you keep your data compressed *and* searchable. > One number to set the scene: finding a specific string in a 10 GB CockroachDB log > (compressed to 578 MB) takes **0.14 s** with `mz search`, reading about 133 MB. Decompressing > that log and piping it to `grep` — the usual way to search compressed data — takes \~5 s and > reads the whole file. `zstd -dc | grep` takes \~5 s, `lz4 -dc | grep` \~10 s. Scanning the raw > 10 GB with `rg` takes \~8 s. The search index is stored as skippable chunks: older MinLZ readers ignore them and the compressed payload is byte\-for\-byte unchanged, so adding search is always backward\-compatible. Search indexes can be built while compressing or after the fact as sidecar streams, allowing them to be used separately from the compressed data. *** ## How it works (in 30 seconds) Every block gets a tiny bloom\-filter table: the byte\-windows in the block are hashed and their bits set. To search, `mz search` hashes the same\-length windows of your pattern and checks each block's table: - any window bit missing → the pattern is definitely not in that block → skip it (no decode); - all bits present → the block might match → decode and scan it. Longer/rarer patterns produce more independent window checks, so blocks that don't contain them are rejected with near\-certainty. Tables can live inline in the `.mz`, or in a sidecar `.mzs` file you build afterwards — handy for data you can't or don't want to re\-compress. This is why it matches with compression. Compressible data is very likely to produce search indexes that are also useful, meaning there is a reasonable reduction in the search table compared to the raw data. For full details: [SEARCH.md](https://github.com/minio/minlz/blob/main/SEARCH.md) (usage & tuning) and [SPEC\_SEARCH.md](https://github.com/minio/minlz/blob/main/SPEC_SEARCH.md) (wire format). *** ## When to use it — and when not We will use the command\-line tool `mz search` to demonstrate, but everything is available via the Go API. This is a specialized tool. It is dramatic when it fits and pointless when it doesn't, so read this part first. **Reach for `mz search` when:** - You search for literal byte strings — IDs, error codes, request paths, hostnames, JSON keys, hashes. (Not regex. See below.) - The pattern is reasonably selective — it appears in a minority of blocks. Rare → huge win. - The data is large, archived, or remote and you'd rather not materialize the whole thing. - You search the same corpus repeatedly — build the index once, query many times. - You are I/O\-bound: on object storage or a cold cache, skipped blocks issue *zero* reads. - You need to confirm a string is absent ("is this error anywhere in 10 GB?") — the fastest case of all. **Don't bother when:** - You need regex, case\-insensitive, or fuzzy matching. `mz search` is literal bytes only. - The pattern is very common or shorter than the index's match length — little or nothing gets skipped, and you pay a small table\-check tax on top of a full decode. - It's a one\-shot scan of small data that's already in RAM and you have `ripgrep` — `rg` is superb there and hard to beat. **Rule of thumb:** the speed\-up scales with how much the query lets MinLZ skip. Rare string → 100× faster. String in every record → no faster at all. *** ## Quick start You need an index. Either add one while compressing: ```bash mz c -search file.log # writes file.log.mz — still a normal, decodable .mz ``` …or add one to an existing `.mz` after the fact (this decodes each block and builds fresh tables; the original data is untouched): ```bash mz sidecar build file.log.mz # writes file.log.mz.mzs alongside it ``` Then search. The sidecar is auto\-detected: ```bash mz search "connection refused" file.log.mz # prints : mz search -c "connection refused" file.log.mz # count matching lines mz search -q "connection refused" file.log.mz # exit code only (0=found, 1=not) mz search -v -c "connection refused" file.log.mz # + timing and skip stats ``` Line output is `streamOffset:line`, e.g.: ``` 1976076142:{"tag":"cockroach.dev","channel":"DEV","severity":"ERROR",...} ``` `-v` shows you exactly what happened — here, "find all warnings" in the 10 GB log: ``` λ mz search -v -c '"severity":"WARNING"' cockroach.node1.log.mz cockroach.node1.log.mz: using sidecar cockroach.node1.log.mz.mzs cockroach.node1.log.mz: search info: matchLen=6 baseTableSize=23 (8388608 entries) no-prefix 92 cockroach.node1.log.mz took 231ms 45483.2 MB/s Blocks total: 1253, skipped: 1238 (98.8%), deferred: 1245 (99.4%, 1238 skipped) Blocks searched: 15 (1.2%), false positive: 7 (46.7%) Table total: 139345225 bytes, avg 111209 bytes/table, 1.33% of 10506623721 uncompressed ``` It looked at 15 of 1253 blocks and answered in a quarter of a second. While the table cost of 1.33% is acceptable for most cases, it is possible to reduce the size a lot by specializing the search index to a specific result. If you know you'll always search a particular field, you can tell MinLZ to index only the bytes that follow it. For example: ``` λ mz sidecar build -search.prefix='"severity":"' cockroach.node1.log.mz Building sidecar: cockroach.node1.log.mz -> cockroach.node1.log.mz.mzs Sidecar size: 50846 bytes λ mz search -v -c '"severity":"WARNING"' cockroach.node1.log.mz cockroach.node1.log.mz: using sidecar cockroach.node1.log.mz.mzs cockroach.node1.log.mz: search info: matchLen=6 baseTableSize=23 (8388608 entries) long-prefix="\"severity\":\"" 92 cockroach.node1.log.mz took 39ms 269400.6 MB/s Blocks total: 1253, skipped: 1245 (99.4%), deferred: 0 (0.0%, 0 skipped) Blocks searched: 8 (0.6%), false positive: 0 (0.0%) Table total: 38859 bytes, avg 31 bytes/table, 0.00% of 10506623721 uncompressed ``` Even when considering the sidecar headers, the index is less than 0.0005% of the data. *** ## Benchmarks **Setup:** AMD Ryzen 9 9950X (16C/32T), 61.6 GB RAM, Windows 11, `mz` [dev]. Warm page cache, best of 3 runs, literal (`-F`) patterns. `grep`'s output is sent to a file so it performs a full count scan (piping `grep -c` to `/dev/null` lets GNU grep quit at the first match — a common benchmarking trap). Every file below is in `cmd/mz/`; the commands are copy\-pasteable. ### Flagship: 10 GB of CockroachDB logs `cockroach.node1.log` is 10.5 GB of JSON log lines. It exists here in four forms: raw, MinLZ (`.mz`, 578 MB), Zstandard (`.zst`, 508 MB) and LZ4 (`.lz4`, 954 MB). Building the MinLZ search sidecar took 8.5 s and produced a 178 MB file (1.69% of the raw size). | Query | Matches | Blocks skipped | `mz search` | grep (raw) | rg (raw) | zstd → grep | lz4 → grep | mz cat → grep | | ----------------------------------- | -------:| --------------:| -----------:| ----------:| --------:| -----------:| ----------:| -------------:| | String not present | 0 | 99.9% | 0.14 s | 4.7 s | 8.2 s | 5.0 s | 9.8 s | 5.2 s | | Rare string (1 hit) | 1 | 99.9% | 0.14 s | 4.7 s | 8.2 s | 5.0 s | 9.8 s | 5.0 s | | All warnings | 92 | 98.8% | 0.21 s | 4.8 s | 8.2 s | 5.0 s | 9.8 s | 5.3 s | | `"severity":"INFO"` (in every line) | 16.5 M | 0% | 5.0 s | 5.0 s | 8.8 s | 5.0 s | 9.8 s | 5.3 s | *(`zstd`/`lz4` are decode\-bound, so their time is the same regardless of the query or how many hits there are.)* search_time

For selective queries `mz search` is \~30–60× faster than any approach that has to read the whole stream — because it doesn't. It processes the 10 GB dataset at an effective 40–55 GB/s by decompressing almost none of it. As the pattern gets more common the advantage shrinks, and for a field present in *every* record (`"severity":"INFO"`, 16.5 M hits, nothing to skip) it lands right where plain decompress\-and\-grep does — no better, no worse: skip_vs_selectivity

### Confirming a string is *absent* This is the case `mz search` was born for. To prove a string isn't in a file, every other tool must read the entire file. `mz search` checks each block's table, finds the pattern can't be there, and skips it — so a "not found" over 10 GB comes back in 0.14 s instead of 5–10 s. If you're scripting alert checks or grepping archives for an incident marker that's usually *not* present, this is the difference between an instant answer and a coffee break. ### Less I/O — the real lever for cold and remote data The warm\-cache times above actually understate the benefit, because they charge nothing for reading the file. In the real world — cold cache, network storage, S3 — bytes read is what you pay for. Here `mz search` reads the 178 MB index plus only the handful of candidate blocks; with a sidecar, skipped blocks issue no reads at all: bytes_read

**178 MB vs. 10.5 GB — 59× less data touched.** On object storage that ratio is your latency and your bill. ### The honest limit: common patterns and easy\-to\-scan data Switch to `nyc-taxi-data-10M.csv` (3.3 GB of plain\-ASCII CSV, `.mz` 758 MB, 174 MB sidecar) and the picture flips: | Query | Matches | Blocks skipped | `mz search` | rg (raw) | grep (raw) | mz cat → grep | | ----------------- | -------:| --------------:| -----------:| --------:| ----------:| -------------:| | A full coordinate | 397 | 17% | 2.70 s | 0.91 s | 2.0 s | 2.2 s | | `Manhattan` | 4.2 M | 0% | 1.85 s | 1.05 s | 2.0 s | 2.2 s | A full\-precision coordinate *looks* selective, but its 8\-byte windows (`40.7922`, `.792251`, …) are shared across millions of other coordinates, so only 17% of blocks can be skipped — and `mz search` ends up slower than just decompressing and grepping. `ripgrep` on the raw file wins outright here: plain ASCII hits its SIMD fast path (\~3.5 GB/s). (Notice `rg` was \~8 s on the UTF\-8\-heavy cockroach log but \~1 s here — `ripgrep`'s speed is very data\-dependent, whereas `grep` is steadier.) If your pattern isn't selective, or your data is small/ASCII/already in RAM, reach for `ripgrep`. `mz search` is for finding needles in big compressed haystacks. ### What the index costs Search tables are extra bytes. How many depends on the data and configuration: index_overhead

The default (no prefix) is a low single\-digit percentage. Telling MinLZ where values live — e.g. "only index bytes after `":`" in JSON — makes the tables far sparser and shrinks the index to a fraction of a percent, at the cost of only being usable for queries that contain the prefix. See [SEARCH.md](SEARCH.md#parameters) for tuning. ### Selective (longer prefix) indexes The no\-prefix index above records windows at *every* byte position, so its size scales with the data. If you know you'll always search a particular field, a long prefix tells MinLZ to index only the bytes that *follow* it — collapsing the index to a fraction of the size. CockroachDB log lines all carry `"timestamp":""`. We can index only what comes after `"timestamp":"`, and add `-search.extras=8` so each occurrence records 9 overlapping 8\-byte windows of the value (a little bloom filter over the timestamp itself, `matchLen + extras ≤ 16`): ```bash mz sidecar build -search.lens=8 -search.prefix='"timestamp":"' -search.extras=8 \ -o cockroach.node1.log.mz.ts.mzs cockroach.node1.log.mz ``` | Index | Size | % of 10.5 GB | | --------------------------- | ------:| ------------:| | no prefix (matchLen 8) | 178 MB | 1.69% | | `"timestamp":"` \+ extras 8 | 21 MB | 0.20% | That's **8× smaller** — and searching for a specific timestamp is, if anything, *faster*, because there's less index to walk: ```bash mz search -sidecar cockroach.node1.log.mz.ts.mzs \ '"timestamp":"1679865848.891225528"' cockroach.node1.log.mz # 1 match, 99.9% of blocks skipped, 94 ms (~110 GB/s effective) — count matches grep exactly ``` The catch is the one every prefix index has, and it's worth stating plainly: this index only helps queries that contain `"timestamp":"` followed by at least `matchLen + extras` (here 16) more bytes — a timestamp down to roughly microsecond precision. Searching it for an error string, or for a coarse `"timestamp":"1679` fragment, simply falls back to a full decode. So build one prefix index per field you actually query (a single sidecar can carry several configs at once), or a no\-prefix index when queries are arbitrary. See [SEARCH.md](SEARCH.md#prefixes) for byte\-, mask\- and long\-prefix modes. *** ## Limitations & gotchas - Literal bytes only. No regex, no case\-insensitivity, no wildcards. (Input is raw bytes, so it works on any data, not just text.) - Skipping tracks selectivity at the match length. Common patterns, or patterns whose match\-length windows are ubiquitous (digits, hex), skip little to nothing. - Patterns must be at least `matchLen` bytes (default 6) to use the index, otherwise the searcher falls back to a full decode. - A prefix\-tuned index only accelerates queries that contain the prefix. Others fall back to full decode. Build a no\-prefix index if queries are arbitrary. - Without a prefix, near\-random / incompressible blocks fill the table past its population limit, so they get no table and are always scanned. A prefix avoids this — only the positions after the prefix are indexed, keeping the table sparse (and useful) even on high\-entropy data. - You need an index. Searching a plain `.mz` with no tables is just decompress\-and\-scan. - `mz search -c` counts matching lines like `grep`/`rg`. Two display caveats: a matching line that continues past a block boundary is *printed* truncated at that boundary (its match offset is still exact), and `-n` prints a match ordinal, not a source line number. *** ## Try it Search ships in the `mz` CLI (`mz search`, `mz sidecar`) and in the Go library (`WriterSearchTable`, `BlockSearcher`, `BuildSidecar`, `NewSidecarSearcher`). - Repository: - Usage & tuning: [SEARCH.md](https://github.com/minio/minlz/blob/main/SEARCH.md) - Wire format: [SPEC\_SEARCH.md](https://github.com/minio/minlz/blob/main/SPEC_SEARCH.md) Reproduce the flagship benchmark: ```bash wget https://files.klauspost.com/compress/cockroach.node1.log.zst zstd -d cockroach.node1.log.zst mz c -3 -search -search.sidecar -search.len=8 cockroach.node1.log # compress & build the 132 MB index mz search -v -c "ALL SECURITY CONTROLS" cockroach.node1.log.mz # 0.14 s, 99.9% skipped # compare: zstd -dc cockroach.node1.log.zst | grep -c "ALL SECURITY CONTROLS" ``` ## What's Changed * Implement MinLZ Stream Search Tables by @klauspost in * Add mz stats by @klauspost in * Align assembly encoders with Go by @klauspost in * Add github.com/KarpelesLab/minlz\-rs to ports by @klauspost in * l3: Do re\-matching on borders by @klauspost in * Minor amd64 decoder tweaks by @klauspost in **Full Changelog**: 55:["$","$L6c",null,{"entries":[{"key":["platform",{"userId":"anon"},"repo","releases",{"owner":"minio","repo":"minlz"},"detail","v1.2.0"],"data":{"id":"240855","version":"v1.2.0","channel":"stable","title":"v1.2.0","publishedAt":"2026-07-13T08:43:28Z","summary":"# feat: Search compressed data without decompression","notesMarkdown":"$70","attachments":[{"id":"67985","name":"checksums.txt","size":4795,"sizeLabel":"4.7 KiB","contentType":"attachment","downloadUrl":"https://trylle.com/minio/minlz/releases/download/v1.2.0/checksums.txt"},{"id":"67986","name":"minlz-aix_ppc64.tar.gz","size":2998509,"sizeLabel":"2.9 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