S3 as an ObjectStore for Datafusion.
This crate implements the DataFusion ObjectStore trait on AWS S3 and implementers of the S3 standard. We leverage the official AWS Rust SDK for interacting with S3. While it is our understanding that the AWS APIs we are using a relatively stable, we can make no assurances on API stability either on AWS' part or within this crate. This crates API is tightly connected with DataFusion, a fast moving project, and as such we will make changes inline with those upstream changes.
Examples for querying AWS and other implementors, such as MinIO, are shown below.
Load credentials from default AWS credential provider (such as environment or ~/.aws/credentials)
let s3_file_system = Arc::new(S3FileSystem::default().await);S3FileSystem::default() is a convenience wrapper for S3FileSystem::new(None, None, None, None, None, None).
Connect to implementor of S3 API (MinIO, in this case) using access key and secret.
// Example credentials provided by MinIO
const ACCESS_KEY_ID: &str = "AKIAIOSFODNN7EXAMPLE";
const SECRET_ACCESS_KEY: &str = "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY";
const PROVIDER_NAME: &str = "Static";
const MINIO_ENDPOINT: &str = "http://localhost:9000";
let s3_file_system = S3FileSystem::new(
Some(SharedCredentialsProvider::new(Credentials::new(
MINIO_ACCESS_KEY_ID,
MINIO_SECRET_ACCESS_KEY,
None,
None,
PROVIDER_NAME,
))), // Credentials provider
None, // Region
Some(Endpoint::immutable(Uri::from_static(MINIO_ENDPOINT))), // Endpoint
None, // RetryConfig
None, // AsyncSleep
None, // TimeoutConfig
)
.await;Using DataFusion's ListingTableConfig we register a table into a DataFusion ExecutionContext so that it can be queried.
let filename = "data/alltypes_plain.snappy.parquet";
let config = ListingTableConfig::new(s3_file_system, filename).infer().await?;
let table = ListingTable::try_new(config)?;
let mut ctx = ExecutionContext::new();
ctx.register_table("tbl", Arc::new(table))?;
let df = ctx.sql("SELECT * FROM tbl").await?;
df.show()We can also register the S3FileSystem directly as an ObjectStore on an ExecutionContext. This provides an idiomatic way of creating TableProviders that can be queried.
execution_ctx.register_object_store(
"s3",
Arc::new(S3FileSystem::default().await),
);
let input_uri = "s3://parquet-testing/data/alltypes_plain.snappy.parquet";
let (object_store, _) = ctx.object_store(input_uri)?;
let config = ListingTableConfig::new(s3_file_system, filename).infer().await?;
let mut table_provider: Arc<dyn TableProvider + Send + Sync> = Arc::new(ListingTable::try_new(config)?);Tests are run with MinIO which provides a containerized implementation of the Amazon S3 API.
First clone the test data repository:
git submodule update --init --recursiveThen start the MinIO container:
docker run \
--detach \
--rm \
--publish 9000:9000 \
--publish 9001:9001 \
--name minio \
--volume "$(pwd)/parquet-testing:/data" \
--env "MINIO_ROOT_USER=AKIAIOSFODNN7EXAMPLE" \
--env "MINIO_ROOT_PASSWORD=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY" \
quay.io/minio/minio server /data \
--console-address ":9001"Once started, run tests in normal fashion:
cargo test
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