alibaba/GraphScope

[BUG] Loading from large dataframe/large numpy requires holding all chunks in coordinator

Open

#2,342 创建于 2022年12月23日

在 GitHub 查看
 (0 评论) (1 反应) (0 负责人)HTML (2,401 star) (301 fork)batch import
bugcomponent:coordinatorgood first issue

描述

Describe the bug

It looks strange that we need to accumulate all chunks in the request stream into a list in coordinator before sending to analytical engine, that would requires large available memory for the coordinator pod.

https://github.com/alibaba/GraphScope/blob/b80a35599424580325a750e734f8a3b2dead2a5b/coordinator/gscoordinator/dag_manager.py#L77-L107

贡献者指南

技术栈
pythonnumpypandas
领域
backend
议题类型
bug
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
3
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
half day
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
stale
清晰度议题是否清楚说明期望改动、验收标准和下一步。
clear
前置要求
PythonNumPyGraphScope coordinator architecture
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
30
研究方向
Investigate the coordinator code in dag manager.py lines 77-107. The issue is that all chunks are accumulated in a list before being sent to the analytical engine, causing high memory usage. Consider modifying the code to stream chunks directly to the engine or send them in smaller batches. Look at the AnalyticalEngine interface to see if it supports streaming input. No comments or PRs exist, so this is an open opportunity for optimization.
[BUG] Loading from large dataframe/large numpy requires holding all chunks in coordinator · alibaba/GraphScope#2342 | Good First Issue