Addressed Memory Overflow in DataFrame Grouping

2 min read

📅 2023-08-25 — Session: Addressed Memory Overflow in DataFrame Grouping

🕒 19:15–19:25
🏷️ Labels: Memory Overflow, Dataframe, Dask, Optimization, Error Handling
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to address a memory overflow issue encountered during a multi-level index groupby operation in a DataFrame, optimize the process, and manage memory effectively.

Key Activities

  • Identified the root cause of the memory overflow during DataFrame groupby operations.
  • Discussed the oversight of not importing necessary libraries and planned to correct this mistake.
  • Proceeded with computation using Dask without re-importing modules, focusing on counting unique values in the ‘PROP’ column.
  • Addressed session statefulness issues and decided to proceed without the ProgressBar.
  • Suggested re-loading the PERSONA data due to its size and provided guidance on data operations.
  • Outlined a step-by-step approach to optimizing grouping operations using Dask, including code snippets.

Achievements

  • Clarified the cause of the memory overflow and outlined potential solutions for optimization.
  • Developed a plan to correct library import oversights.
  • Established a workflow for counting unique values in the ‘PROP’ column using Dask.

Pending Tasks

  • Re-import necessary libraries to ensure smooth execution in future sessions.
  • Re-run computations with optimized settings and correct session statefulness issues.
  • Load the PERSONA data or provide guidance for user-side operations due to its size.

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