alibaba/GraphScope

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

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#2,342 opened on Dec 23, 2022

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bugcomponent:coordinatorgood first issue

Description

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

Contributor guide

Tech stack
pythonnumpypandas
Domain
backend
Issue type
bug
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
half day
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
PythonNumPyGraphScope coordinator architecture
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
30
Research direction
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.