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Sohu Tech Products
Sohu Tech Products
Jan 24, 2024 · Databases

Optimizing Database Expression Evaluation with JIT Technology Using Gandiva

The article explains how database expression evaluation—especially in WHERE and SELECT clauses—can be dramatically accelerated by replacing interpreted AST traversal with Just‑In‑Time compilation using Apache Gandiva, which leverages LLVM to generate SIMD‑optimized machine code for Arrow columnar data, and discusses extensions such as timestamp, array, higher‑order functions, and UDF support.

Apache ArrowApache GandivaDatabase Optimization
0 likes · 17 min read
Optimizing Database Expression Evaluation with JIT Technology Using Gandiva
DataFunTalk
DataFunTalk
Dec 11, 2023 · Databases

Interview with Wu Li on Columnar Storage, JIT Compilation, and Push Mode in Modern Database Systems

The interview with Wu Li, a research engineer at Shanghai Yanhuang Data, explores how columnar storage, JIT compilation, and push-mode processing are reshaping modern database performance, highlighting hardware constraints, software optimizations, and product‑centric goals in the era of big data analytics.

JIT compilationOLAPcolumnar storage
0 likes · 11 min read
Interview with Wu Li on Columnar Storage, JIT Compilation, and Push Mode in Modern Database Systems
DataFunSummit
DataFunSummit
Dec 10, 2023 · Databases

Interview with Wu Li on Database Evolution: Columnar Storage, JIT Compilation, and Push Mode

In this technical interview, Wu Li, a research engineer at Shanghai Yanhuang Data, explains how hardware constraints drive database evolution, why columnar storage and SIMD acceleration are crucial for OLAP, and how JIT compilation and push‑mode processing improve query performance and product experience.

Data EngineeringJIT compilationOLAP
0 likes · 10 min read
Interview with Wu Li on Database Evolution: Columnar Storage, JIT Compilation, and Push Mode
DataFunTalk
DataFunTalk
Dec 8, 2023 · Databases

Interview with Wu Li on Database Evolution: Columnar Storage, JIT Compilation, and Push Mode

The article presents an interview with Wu Li, a research engineer at Shanghai Yanhuang Data, discussing how hardware limits have driven database evolution toward columnar storage, the adoption of Apache Arrow and Gandiva for SIMD‑enabled JIT compilation, and the shift from pull to push processing modes to improve OLAP performance.

Apache ArrowDatabase OptimizationGandiva
0 likes · 10 min read
Interview with Wu Li on Database Evolution: Columnar Storage, JIT Compilation, and Push Mode
Model Perspective
Model Perspective
Aug 16, 2022 · Fundamentals

Boost Python Speed Instantly with Numba: A Practical Guide

Numba is a Python just‑in‑time compiler that transforms functions into fast native machine code, enabling near C‑level performance without rewriting code; by adding simple decorators like @jit or @njit, you can accelerate loops, NumPy operations, and even leverage parallel or GPU execution.

JIT compilationNumPyNumba
0 likes · 7 min read
Boost Python Speed Instantly with Numba: A Practical Guide