A native Rust library for Apache Hudi, with bindings to Python
The hudi-rs project aims to broaden the use of Apache Hudi for a diverse range of
users and projects.
| Source | Installation Command |
|---|---|
| PyPi | pip install hudi |
| Crates.io | cargo add hudi |
Example usage
[!NOTE] These examples expect a Hudi table exists at
/tmp/trips_table, created using the quick start guide.
Python
Read a Hudi table into a PyArrow table.
from hudi import HudiTable
hudi_table = HudiTable("/tmp/trips_table")
records = hudi_table.read_snapshot()
import pyarrow as pa
import pyarrow.compute as pc
arrow_table = pa.Table.from_batches(records)
result = arrow_table.select(
["rider", "ts", "fare"]).filter(
pc.field("fare") > 20.0)
print(result)Rust
Add crate hudi with datafusion feature to your application to query a Hudi table.
```shell cargo new my_project --bin && cd my_project cargo add tokio@1 datafusion@39 cargo add hudi --features datafusion ``` Update `src/main.rs` with the code snippet below then `cargo run`.use std::sync::Arc;
use datafusion::error::Result;
use datafusion::prelude::{DataFrame, SessionContext};
use hudi::HudiDataSource;
#[tokio::main]
async fn main() -> Result<()> {
let ctx = SessionContext::new();
let hudi = HudiDataSource::new("/tmp/trips_table").await?;
ctx.register_table("trips_table", Arc::new(hudi))?;
let df: DataFrame = ctx.sql("SELECT * from trips_table where fare > 20.0").await?;
df.show().await?;
Ok(())
}Work with cloud storage
Ensure cloud storage credentials are set properly as environment variables, e.g., AWS_*, AZURE_*, or GOOGLE_*.
Relevant storage environment variables will then be picked up. The target table's base uri with schemes such
as s3://, az://, or gs:// will be processed accordingly.
Contributing
Check out the contributing guide for all the details about making contributions to the project.