论文标题
Bytestore：主内存列存储的混合布局
ByteStore: Hybrid Layouts for Main-Memory Column Stores
论文作者
论文摘要
主存储列的性能高度取决于基本列布局上的扫描和查找操作。现有的列商店采用均匀的列布局，导致实际工作负载的次优性能，因为不同的列具有不同的数据特征。在本文中，我们提出了Bytestore，Bytestore是一个对不同列使用不同存储布局的列存储。我们首先提出了一种新型的具有数据意识的列布局PP-VBS（前缀保留变量字节片）。 PP-VBS利用数据偏斜以加速扫描而不牺牲查找性能。然后，我们提出一个实验驱动的列布局顾问，以选择用于工作负载的单个列布局。实际数据上的广泛实验表明，Bytestore的表现优于均匀存储引擎，高达5.2倍。
The performance of main memory column stores highly depends on the scan and lookup operations on the base column layouts. Existing column-stores adopt a homogeneous column layout, leading to sub-optimal performance on real workloads since different columns possess different data characteristics. In this paper, we propose ByteStore, a column store that uses different storage layouts for different columns. We first present a novel data-conscious column layout, PP-VBS (Prefix-Preserving Variable Byte Slice). PP-VBS exploits data skew to accelerate scans without sacrificing lookup performance. Then, we present an experiment-driven column layout advisor to select individual column layouts for a workload. Extensive experiments on real data show that ByteStore outperforms homogeneous storage engines by up to 5.2X.
