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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,159 @@ | ||
| use std::{io::Cursor, sync::Arc}; | ||
|
|
||
| use arrow_array::RecordBatch; | ||
| use arrow_schema::Schema; | ||
| use datafusion::datasource::avro_to_arrow::ReaderBuilder; | ||
| use denormalized_common::DenormalizedError; | ||
|
|
||
| use super::Decoder; | ||
|
|
||
| #[derive(Clone)] | ||
| pub struct AvroDecoder { | ||
| schema: Arc<Schema>, | ||
| cache: Vec<Vec<u8>>, | ||
| size: usize, | ||
| } | ||
|
|
||
| impl Decoder for AvroDecoder { | ||
| fn push_to_buffer(&mut self, bytes: Vec<u8>) { | ||
| self.cache.push(bytes); | ||
| self.size += 1; | ||
| } | ||
|
|
||
| fn to_record_batch(&mut self) -> Result<arrow_array::RecordBatch, DenormalizedError> { | ||
| if self.size == 0 { | ||
| return Ok(RecordBatch::new_empty(self.schema.clone())); | ||
| } | ||
| let all_bytes: Vec<u8> = self.cache.iter().flatten().cloned().collect(); | ||
| // Create a cursor from the concatenated bytes | ||
| let cursor = Cursor::new(all_bytes); | ||
|
|
||
| // Build the reader | ||
| let mut reader = ReaderBuilder::new() | ||
| .with_batch_size(self.size) | ||
| .with_schema(self.schema.clone()) | ||
| .build(cursor)?; | ||
|
|
||
| // Read the batch | ||
| match reader.next() { | ||
| Some(Ok(batch)) => Ok(batch), | ||
| Some(Err(e)) => Err(DenormalizedError::Arrow(e)), | ||
| None => Ok(RecordBatch::new_empty(self.schema.clone())), | ||
| } | ||
| } | ||
| } | ||
|
|
||
| impl AvroDecoder { | ||
| pub fn new(schema: Arc<Schema>) -> Self { | ||
| AvroDecoder { | ||
| schema, | ||
| cache: Vec::new(), | ||
| size: 0, | ||
| } | ||
| } | ||
| } | ||
|
|
||
| #[cfg(test)] | ||
| mod tests { | ||
| use super::*; | ||
| use apache_avro::{types::Record, Schema as AvroSchema, Writer}; | ||
| use arrow_array::{Int32Array, StringArray}; | ||
| use arrow_schema::{DataType, Field}; | ||
|
|
||
| fn create_test_schema() -> Arc<Schema> { | ||
| Arc::new(Schema::new(vec![ | ||
| Field::new("id", DataType::Int32, false), | ||
| Field::new("name", DataType::Utf8, false), | ||
| ])) | ||
| } | ||
|
|
||
| fn create_avro_data(records: Vec<(i32, &str)>) -> Vec<u8> { | ||
| let avro_schema = AvroSchema::parse_str( | ||
| r#" | ||
| { | ||
| "type": "record", | ||
| "name": "test", | ||
| "fields": [ | ||
| {"name": "id", "type": "int"}, | ||
| {"name": "name", "type": "string"} | ||
| ] | ||
| } | ||
| "#, | ||
| ) | ||
| .unwrap(); | ||
|
|
||
| let mut writer = Writer::new(&avro_schema, Vec::new()); | ||
|
|
||
| for (id, name) in records { | ||
| let mut record: Record<'_> = Record::new(writer.schema()).unwrap(); | ||
| record.put("id", id); | ||
| record.put("name", name); | ||
| writer.append(record).unwrap(); | ||
| } | ||
|
|
||
| writer.into_inner().unwrap() | ||
| } | ||
|
|
||
| #[test] | ||
| fn test_push_to_buffer() { | ||
| let schema = create_test_schema(); | ||
| let mut decoder = AvroDecoder::new(schema); | ||
|
|
||
| decoder.push_to_buffer(vec![1, 2, 3]); | ||
| decoder.push_to_buffer(vec![4, 5, 6]); | ||
|
|
||
| assert_eq!(decoder.size, 2); | ||
| assert_eq!(decoder.cache, vec![vec![1, 2, 3], vec![4, 5, 6]]); | ||
| } | ||
|
|
||
| #[test] | ||
| fn test_empty_record_batch() { | ||
| let schema = create_test_schema(); | ||
| let mut decoder = AvroDecoder::new(schema.clone()); | ||
|
|
||
| let result = decoder.to_record_batch().unwrap(); | ||
|
|
||
| assert_eq!(result.schema(), schema); | ||
| assert_eq!(result.num_rows(), 0); | ||
| } | ||
|
|
||
| #[test] | ||
| fn test_record_batch_with_data() { | ||
| let schema = create_test_schema(); | ||
| let mut decoder = AvroDecoder::new(schema.clone()); | ||
|
|
||
| let avro_data = create_avro_data(vec![(1, "Alice")]); | ||
| decoder.push_to_buffer(avro_data); | ||
|
|
||
| let result = decoder.to_record_batch().unwrap(); | ||
|
|
||
| assert_eq!(result.schema(), schema); | ||
| assert_eq!(result.num_rows(), 1); | ||
|
|
||
| let id_array = result | ||
| .column(0) | ||
| .as_any() | ||
| .downcast_ref::<Int32Array>() | ||
| .unwrap(); | ||
| let name_array = result | ||
| .column(1) | ||
| .as_any() | ||
| .downcast_ref::<StringArray>() | ||
| .unwrap(); | ||
|
|
||
| assert_eq!(id_array.value(0), 1); | ||
| assert_eq!(name_array.value(0), "Alice"); | ||
| } | ||
|
|
||
| #[test] | ||
| fn test_invalid_avro_data() { | ||
| let schema = create_test_schema(); | ||
| let mut decoder = AvroDecoder::new(schema); | ||
|
|
||
| decoder.push_to_buffer(vec![1, 2, 3]); | ||
|
|
||
| let result = decoder.to_record_batch(); | ||
|
|
||
| assert!(matches!(result, Err(DenormalizedError::DataFusion(_)))); | ||
| } | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,10 +1,12 @@ | ||
| use arrow_array::RecordBatch; | ||
| use denormalized_common::DenormalizedError; | ||
|
|
||
| pub trait Decoder { | ||
| pub trait Decoder: Send + Sync { | ||
| fn push_to_buffer(&mut self, bytes: Vec<u8>); | ||
|
|
||
| fn to_record_batch(&mut self) -> Result<RecordBatch, DenormalizedError>; | ||
| } | ||
|
|
||
| pub mod avro; | ||
| pub mod json; | ||
| pub mod utils; |
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