Apache Paimon Full Text Index

Standalone Tantivy-based full-text index library for Apache Paimon-style data lake storage. The project follows the same shape as paimon-vector-index:

core: Rust implementation and v1 storage format.
ffi: C ABI over the Rust core.
jni: Java JNI bridge over the Rust core.
java: public Java API.
python: Python ctypes API over the C ABI.

The index file is self-describing. Readers only need positional read_at I/O and do not depend on Paimon manifest metadata.

Current Status

Implemented:

Rust writer, reader, v1 envelope, and search.
C FFI writer/reader/search JSON.
Java API and JNI bridge.
Python ctypes package.
Cross-boundary round-trip tests for Rust core, FFI, and Python.

Supported tokenizers in this first implementation:

default
simple
whitespace
raw
ngram

Reserved for follow-up:

jieba
stemming
built-in and custom stop-word filters
true seek-on-demand Tantivy directory instead of loading segment files into memory at reader open

Build

cargo test -p paimon-ftindex-core
cargo test -p paimon-ftindex-ffi
cargo build -p paimon-ftindex-ffi
cargo check -p paimon-ftindex-jni
mvn -q -f java/pom.xml test
PYTHONPATH=python python3 -m pytest -q python/tests

Rust Example

use paimon_ftindex_core::io::{PosWriter, SliceReader};
use paimon_ftindex_core::{
    FullTextIndexConfig, FullTextIndexReader, FullTextIndexWriter, FullTextQuery,
};

let mut writer = FullTextIndexWriter::new(FullTextIndexConfig::new())?;
writer.add_document(1, "Apache Paimon full text search")?;

let mut bytes = Vec::new();
writer.write(&mut PosWriter::new(&mut bytes))?;

let mut reader = FullTextIndexReader::open(SliceReader::new(bytes))?;
let result = reader.search(FullTextQuery::match_query("paimon", "text"), 10)?;

Python Example

from io import BytesIO
from paimon_ftindex import FullTextIndexReader, FullTextIndexWriter, MatchQuery

out = BytesIO()
with FullTextIndexWriter() as writer:
    writer.add_document(1, "Apache Paimon full text search")
    writer.write(out)

class Input:
    def __init__(self, data):
        self.data = data
    def pread(self, pos, length):
        return self.data[pos:pos + length]

with FullTextIndexReader(Input(out.getvalue())) as reader:
    ids, scores = reader.search(MatchQuery("paimon"), limit=10)