Crate arrow_odbc
source · [−]Expand description
Fill Apache Arrow arrays from ODBC data sources.
Usage
use arrow_odbc::{odbc_api::Environment, OdbcReader};
const CONNECTION_STRING: &str = "\
Driver={ODBC Driver 17 for SQL Server};\
Server=localhost;\
UID=SA;\
PWD=My@Test@Password1;\
";
fn main() -> Result<(), anyhow::Error> {
// Your application is fine if you spin up only one Environment.
let odbc_environment = Environment::new()?;
// Connect with database.
let connection = odbc_environment.connect_with_connection_string(CONNECTION_STRING)?;
// This SQL statement does not require any arguments.
let parameters = ();
// Execute query and create result set
let cursor = connection
.execute("SELECT * FROM MyTable", parameters)?
.expect("SELECT statement must produce a cursor");
// Each batch shall only consist of maximum 10.000 rows.
let max_batch_size = 10_000;
// Read result set as arrow batches. Infer Arrow types automatically using the meta
// information of `cursor`.
let arrow_record_batches = OdbcReader::new(cursor, max_batch_size)?;
for batch in arrow_record_batches {
// ... process batch ...
}
Ok(())
}
Re-exports
Structs
Allows setting limits for buffers bound to the ODBC data source. Check this out if you find that
you get memory allocation, or zero sized column errors. Used than constructing a reader using
crate::OdbcReader::with.
Arrow ODBC reader. Implements the arrow::record_batch::RecordBatchReader trait so it can be
used to fill Arrow arrays from an ODBC data source.
Enums
A variation of things which can go wrong then creating an crate::OdbcReader.
Functions
Query the metadata to create an arrow schema. This method is invoked automatically for you by
crate::OdbcReader::new. You may want to call this method in situtation ther you want to
create an arrow schema without creating the reader yet.