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@backloghq/termlog

Log-structured full-text search index — segment-based posting lists with LSM compaction, BM25 ranking, zero native dependencies.

Install

npm install @backloghq/termlog

Usage

import { TermLog } from "@backloghq/termlog";

const index = await TermLog.open({ dir: "./my-index" });

await index.add("doc-1", "the quick brown fox");
await index.add("doc-2", "the lazy dog");
await index.flush();

const results = await index.search("fox", { limit: 10 });
// [{ docId: "doc-1", score: 0.655... }]  (BM25 — exact value depends on corpus)

await index.remove("doc-1");
await index.close();

Why

Existing FTS engines (Lucene, Tantivy) require native deps or a JVM. Most pure-JS alternatives serialize the index to a single in-memory blob — fine for small corpora, but they hit per-file size cliffs in the tens of thousands of documents. Termlog uses immutable on-disk segments with LSM compaction so the corpus scales without those ceilings.

Architecture

  • Posting liststerm → [docId, tf], compressed with VByte / delta encoding. (Positions reserved for a future release.)
  • Term dictionary — sorted on disk; binary search for lookup.
  • Segments — self-contained immutable files (term dict + postings). New writes create a new segment. Compaction merges N segments into 1.
  • Query execution — boolean (AND/OR) via posting iterators (zigzag merge for AND, union scan for OR), BM25 scoring on top.
  • Storage — abstracted via StorageBackend; local FS by default, S3 via @backloghq/termlog-s3.

S3 backend

S3 support is provided by the companion package @backloghq/termlog-s3:

npm install @backloghq/termlog @backloghq/termlog-s3
import { TermLog } from "@backloghq/termlog";
import { S3Backend } from "@backloghq/termlog-s3";
import { S3Client } from "@aws-sdk/client-s3";

const index = await TermLog.open({
  dir: "my-index",
  backend: new S3Backend({
    client: new S3Client({ region: "us-east-1" }),
    bucket: "my-bucket",
    prefix: "my-index/",
  }),
});

See the termlog-s3 README for IAM permissions, lifecycle rules, and MinIO/LocalStack usage.

Options

Option Default Description
fanout 4 Same-tier segment count that triggers a merge (size-tiered LSM)
flushThreshold 1000 Docs in write buffer before auto-flush
k1 1.2 BM25 term-saturation parameter
b 0.75 BM25 length-normalization parameter

Errors

Class When thrown
ManifestCorruptionError manifest.json contains invalid JSON
ManifestVersionError manifest version is outside the supported range
SegmentCorruptionError CRC32 mismatch or missing segment file (.region tells you which)
MappingCorruptionError docids.snap or docids.log is corrupt
TokenizerMismatchError reopening an index with a different tokenizer config
IndexLockedError another process holds the advisory .lock file
WriteStreamError base class for streaming write failures (S3 multipart, etc.)

Stats

Method Returns Description
docCount() number Documents indexed across all flushed segments
segmentCount() number Number of active on-disk segments
estimatedBytes() number Approximate in-memory footprint (postings buffers + sidecar arrays + Maps); lower-bound estimate for memory-budget callers

Multi-writer / S3 safety

Termlog is single-writer per index directory. On local FS an advisory .lock file prevents concurrent opens in the same process group. On S3 (or any shared storage) there is no distributed lock — you must ensure at most one writer per index path.

License

MIT

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Log-structured full-text search index for TypeScript — segment-based posting lists with LSM compaction, BM25 ranking, zero native dependencies

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