---
title: "SpBench: An Agent-Native Framework for Cross-Engine Lakehouse Benchmarking"
source: "arXiv AI/CL/LG（论文）"
source_tier: "t2"
url: "https://arxiv.org/abs/2611.00449v1"
permalink: "https://feed.astralor.com/items/itm_9ef8d3e6f36c825121fc7261"
published: "2026-10-30T23:05:21.000Z"
score: 56
channel: "tech"
tags: ["LLM","AI Agent","SpBench","Agent-Native Framework","Cross-Engine Lakehouse Benchmarking","Snowpark","Snowpark Connect","Apache Spark"]
---

# SpBench: An Agent-Native Framework for Cross-Engine Lakehouse Benchmarking

## At a glance

SpBench is an agent-native framework for cross-engine lakehouse benchmarking, in production use for benchmarking Snowpark, Snowpark Connect for Apache Spark, and other execution environments across standardized suites -…

## Key points

- SpBench is an agent-native framework for cross-engine lakehouse benchmarking, in production use for benchmarking Snowpark, Snowpark Connect for Apache Spark, and other execution environments across standardized suites -…
- It runs continuously across a broad portfolio of workloads, guiding the performance roadmap and detecting regressions for production-scale data engines.
- Benchmarking has historically been an expensive investment requiring continuous cross-functional collaboration and domain expertise, making it difficult to obtain actionable performance insights.

## Full text

SpBench is an agent-native framework for cross-engine lakehouse benchmarking, in production use for benchmarking Snowpark, Snowpark Connect for Apache Spark, and other execution environments across standardized suites -- such as TPCx-BB and TPC-DI -- and custom benchmarks distilled from production workload patterns. It runs continuously across a broad portfolio of workloads, guiding the performance roadmap and detecting regressions for production-scale data engines. Benchmarking has historically been an expensive investment requiring continuous cross-functional collaboration and domain expertise, making it difficult to obtain actionable performance insights. SpBench provides (i) a typed, code-generated benchmark substrate that compiles platform-agnostic benchmark definitions into fair, comparable platform-specific implementations; (ii) a structured-telemetry contract recording every run as queryable fact and dimension data, letting LLM agents query results deterministically; and (iii) an agent-native harness of three composable skills to expedite building benchmarks and analyzing results. This agent-native architecture enabled the rapid development of more than 400 benchmark queries that run on a regular cadence to detect performance regressions; catching these has directly led to improvements in production.

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