Added example reading Avro produced by Kafka

examples/avro_kafka.rs

@@ -0,0 +1,54 @@
+use arrow2::{
+    datatypes::{DataType, Field},
+    error::Error,
+    io::avro,
+};
+
+fn read_schema_id<R: std::io::Read>(reader: &mut R) -> Result<i32, Error> {
+    let mut header = [0; 5];
+    reader.read_exact(&mut header)?;
+
+    if header[0] != 0 {
+        return Err(Error::ExternalFormat(
+            "Avro requires the first byte to be a zero".to_string(),
+        ));
+    }
+    Ok(i32::from_be_bytes(header[1..].try_into().unwrap()))
+}
+
+fn read_block<R: std::io::Read>(reader: &mut R, block: &mut avro::Block) -> Result<(), Error> {
+    // (we could lump multiple records together by extending the block instead of clearing)
+    block.data.clear();
+    reader.read_to_end(&mut block.data)?;
+    block.number_of_rows = 1;
+    Ok(())
+}
+
+fn main() -> Result<(), Error> {
+    // say we received the event from Kafka
+    let data = &[0, 0, 0, 0, 1, 6, 115, 99, 105, 6, 109, 97, 115];
+    let mut stream = std::io::Cursor::new(data);
+
+    // we can fetch its schema_id from the registry via:
+    let _schema_id = read_schema_id(&mut stream)?;
+
+    // say that from the registry we concluded that this schema has fields
+    let avro_fields = vec![
+        avro_schema::Schema::String(None),
+        avro_schema::Schema::String(None),
+    ];
+    // (which we map to arrow fields as)
+    let fields = vec![
+        Field::new("first_name", DataType::Utf8, false),
+        Field::new("last_name", DataType::Utf8, false),
+    ];
+
+    // the below allow us to read it to arrow (a chunk of a single element)
+    let mut block = avro::Block::default();
+    read_block(&mut stream, &mut block)?;
+
+    let chunk = avro::read::deserialize(&block, &fields, &avro_fields, &[true, true])?;
+
+    println!("{chunk:?}");
+    Ok(())
+}