探秘新一代向量存储格式Lance-format (七) 编码器与解码器实现

第7章：编码器与解码器实现

概述

编码器与解码器是 Lance 的高效率数据处理引擎。本章讨论编码器、解码器的设计、上下方案、优化策略。

编码器接口设计

rust 复制代码

pub trait Encoder: Send + Sync {
    // 编码一个批次
    fn encode(&mut self, batch: &RecordBatch) -> Result<EncodedBatch>;
    
    // 编码配置
    fn encoding_type(&self) -> EncodingType;
    
    // 编码统计
    fn statistics(&self) -> Option<EncodingStatistics>;
}

pub struct EncodedBatch {
    pub data: Vec<u8>,
    pub page_headers: Vec<PageHeader>,
    pub statistics: EncodingStatistics,
}

pub enum EncodingType {
    Bitpacking(u32),
    Dictionary,
    Delta,
    RLE,
    Prefix,
    Plain,
}

Encoder 实例

rust 复制代码

pub struct BitpackingEncoder {
    bit_width: u32,
    buffer: Vec<u8>,
}

impl Encoder for BitpackingEncoder {
    fn encode(&mut self, batch: &RecordBatch) -> Result<EncodedBatch> {
        // 编码数据
        let encoded_data = bitpack_array(&batch.data, self.bit_width)?;
        
        Ok(EncodedBatch {
            data: encoded_data,
            page_headers: vec![],
            statistics: EncodingStatistics {
                original_size: batch.size(),
                encoded_size: self.buffer.len(),
                compression_ratio: (self.buffer.len() as f64) / (batch.size() as f64),
            },
        })
    }
    
    fn encoding_type(&self) -> EncodingType {
        EncodingType::Bitpacking(self.bit_width)
    }
    
    fn statistics(&self) -> Option<EncodingStatistics> {
        Some(EncodingStatistics {
            original_size: 0,
            encoded_size: self.buffer.len(),
            compression_ratio: 1.0,
        })
    }
}

解码器接口设计

rust 复制代码

pub trait Decoder: Send + Sync {
    // 解码批次
    async fn decode(
        &self,
        data: &[u8],
        page_header: &PageHeader,
        row_range: Option<Range<u64>>,
    ) -> Result<RecordBatch>;
    
    // 解码统计
    fn statistics(&self) -> Option<DecodingStatistics>;
}

pub struct DecodingStatistics {
    pub encoded_size: u64,
    pub decoded_size: u64,
    pub decoding_time_ms: u64,
}

Decoder 实例

rust 复制代码

pub struct BitpackingDecoder {
    bit_width: u32,
}

impl Decoder for BitpackingDecoder {
    async fn decode(
        &self,
        data: &[u8],
        page_header: &PageHeader,
        row_range: Option<Range<u64>>,
    ) -> Result<RecordBatch> {
        // 准备解码
        let start = Instant::now();
        
        // 解码批次
        let decoded = bitunpack_array(data, self.bit_width, page_header.num_rows)?;
        
        // 履行控制批次范例
        let batch = if let Some(range) = row_range {
            decoded.slice(range.start, range.end - range.start)?
        } else {
            decoded
        };
        
        Ok(batch)
    }
    
    fn statistics(&self) -> Option<DecodingStatistics> {
        None
    }
}

批次编码流程

rust 复制代码

pub struct BatchEncoder {
    encoders: HashMap<String, Box<dyn Encoder>>,
    compression_config: CompressionConfig,
}

impl BatchEncoder {
    pub async fn encode_batch(
        &mut self,
        batch: &RecordBatch,
    ) -> Result<EncodedBatch> {
        let mut encoded_batch = EncodedBatch::new();
        
        // 序列编码所有列
        for field in batch.schema().fields() {
            let column_data = batch.column_by_name(field.name())?;
            
            // 选择适当的编码器
            let encoder = self.select_encoder(field, column_data);
            
            // 编码该列
            let encoded = encoder.encode(&column_data)?;
            
            // 适当的压缩
            let compressed = self.compress(&encoded, &self.compression_config)?;
            
            encoded_batch.add_column(field.name(), compressed);
        }
        
        Ok(encoded_batch)
    }
}

总结

编码器与解码器是 Lance 的核心优化组件：

接口准一：上下设计讯问
批次处理：并列编解码
RepDef 支持：支供嵌套数据
缓存优化：批次缓存减排
核心衡量：合并类及批次并列

下一章讨论 IO 抽象与对象存储。