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Code Issues 775 Packages Projects Releases 10 Wiki Activity

memory 100% #12472

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opened 2026-02-21 19:07:35 -05:00 by yindo · 2 comments
yindo commented 2026-02-21 19:07:35 -05:00
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Originally created by @Dong09 on GitHub (Apr 2, 2025).

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  • This is only for bug report, if you would like to ask a question, please head to Discussions.
  • I have searched for existing issues search for existing issues, including closed ones.
  • I confirm that I am using English to submit this report (我已阅读并同意 Language Policy).
  • [FOR CHINESE USERS] 请务必使用英文提交 Issue，否则会被关闭。谢谢！:)
  • Please do not modify this template :) and fill in all the required fields.

Dify version

1.1.3

Cloud or Self Hosted

Self Hosted (Docker)

Steps to reproduce

When I download a plugin or create a knowledge base on dedify, the memory footprint goes to 100% and when restarting docker, the previously downloaded plugins and created knowledge bases and chatflows are cleared out

✔️ Expected Behavior

No response

❌ Actual Behavior

Image

Originally created by @Dong09 on GitHub (Apr 2, 2025). ### Self Checks - [x] This is only for bug report, if you would like to ask a question, please head to [Discussions](https://github.com/langgenius/dify/discussions/categories/general). - [x] I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones. - [x] I confirm that I am using English to submit this report (我已阅读并同意 [Language Policy](https://github.com/langgenius/dify/issues/1542)). - [x] [FOR CHINESE USERS] 请务必使用英文提交 Issue，否则会被关闭。谢谢！:) - [x] Please do not modify this template :) and fill in all the required fields. ### Dify version 1.1.3 ### Cloud or Self Hosted Self Hosted (Docker) ### Steps to reproduce When I download a plugin or create a knowledge base on dedify, the memory footprint goes to 100% and when restarting docker, the previously downloaded plugins and created knowledge bases and chatflows are cleared out ### ✔️ Expected Behavior _No response_ ### ❌ Actual Behavior ![Image](https://github.com/user-attachments/assets/7756fc56-8a57-4d4f-bd05-ec7c27b049ef)
yindo added the 🐞 bug label 2026-02-21 19:07:35 -05:00
yindo closed this issue 2026-02-21 19:07:35 -05:00
yindo commented 2026-02-21 19:07:35 -05:00
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@dosubot[bot] commented on GitHub (Apr 2, 2025):

Hey @Dong09! 👋 I'm here to assist you with bug fixes, answer your questions, and help you become a contributor. Let's tackle this issue together!

I found a similar unsolved discussion regarding abnormal disk usage after upgrading to version 1.0.0, where the disk size keeps increasing rapidly even without actual use [1]. Additionally, there is a closed issue about the knowledge base frequently disappearing, which was resolved by a pull request that fixed an embedding model name translation issue [2].

For your specific issue with memory usage reaching 100% and data being cleared after restarting Docker, here are some suggestions:

  1. Batch Processing: Consider processing data in smaller batches to reduce peak memory usage.
  2. Increase Memory Allocation: Adjust Docker settings to allocate more memory to the container.
  3. Optimize Embedding Size: If feasible, reduce the dimensionality of the embeddings.
  4. Use Swap Space: Configure your system to use swap space to handle memory spikes.
  5. Monitor and Log Memory Usage: Use tools like objgraph to monitor memory usage and identify inefficiencies [3].

Additionally, ensure that your Docker Compose configuration includes volume mounts for data persistence. This will help maintain your downloaded plugins and created knowledge bases across Docker restarts [4].

To continue talking to Dosu, mention @dosu.

Help Dosu learn! Give it feedback: Great Response | Irrelevant Answer | Incorrect Sources | Too Verbose | Hallucination | Bug Report | Other

@dosubot[bot] commented on GitHub (Apr 2, 2025): <!-- Greeting --> Hey @Dong09! 👋 I'm here to assist you with bug fixes, answer your questions, and help you become a contributor. Let's tackle this issue together! <!-- Answer --> I found a similar unsolved discussion regarding abnormal disk usage after upgrading to version 1.0.0, where the disk size keeps increasing rapidly even without actual use <sup>[[1]](https://github.com/langgenius/dify/discussions/15421)</sup>. Additionally, there is a closed issue about the knowledge base frequently disappearing, which was resolved by a pull request that fixed an embedding model name translation issue <sup>[[2]](https://github.com/langgenius/dify/issues/14793)</sup>. For your specific issue with memory usage reaching 100% and data being cleared after restarting Docker, here are some suggestions: 1. **Batch Processing**: Consider processing data in smaller batches to reduce peak memory usage. 2. **Increase Memory Allocation**: Adjust Docker settings to allocate more memory to the container. 3. **Optimize Embedding Size**: If feasible, reduce the dimensionality of the embeddings. 4. **Use Swap Space**: Configure your system to use swap space to handle memory spikes. 5. **Monitor and Log Memory Usage**: Use tools like `objgraph` to monitor memory usage and identify inefficiencies <sup>[[3]](https://github.com/langgenius/dify/issues/12893)</sup>. Additionally, ensure that your Docker Compose configuration includes volume mounts for data persistence. This will help maintain your downloaded plugins and created knowledge bases across Docker restarts <sup>[[4]](https://github.com/langgenius/dify/blob/main/docker/docker-compose-template.yaml)</sup>. <!-- Dosu Comment Footer --> *To continue talking to [Dosu](https://dosu.dev), mention @dosu.* --- <sup>Help Dosu learn! Give it feedback: [Great Response](https://app.dosu.dev/response-feedback/d943cb57-eb8b-45ac-b730-55d4c03287a9?feedback_type=great_response) | [Irrelevant Answer](https://app.dosu.dev/response-feedback/d943cb57-eb8b-45ac-b730-55d4c03287a9?feedback_type=irrelevant_answer) | [Incorrect Sources](https://app.dosu.dev/response-feedback/d943cb57-eb8b-45ac-b730-55d4c03287a9?feedback_type=incorrect_sources) | [Too Verbose](https://app.dosu.dev/response-feedback/d943cb57-eb8b-45ac-b730-55d4c03287a9?feedback_type=too_verbose) | [Hallucination](https://app.dosu.dev/response-feedback/d943cb57-eb8b-45ac-b730-55d4c03287a9?feedback_type=hallucination) | [Bug Report](https://app.dosu.dev/response-feedback/d943cb57-eb8b-45ac-b730-55d4c03287a9?feedback_type=bug_report) | [Other](https://app.dosu.dev/response-feedback/d943cb57-eb8b-45ac-b730-55d4c03287a9?feedback_type=other)</sup>
yindo commented 2026-02-21 19:07:35 -05:00
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@mamema commented on GitHub (Apr 15, 2025):

regarding this:

Batch Processing: Consider processing data in smaller batches to reduce peak memory usage.

The cause for using Batch processing in the first place is to throw a (huge) bunch of files on something and let the application do the rest. So, why should a human resize the batches? This needs manual (recurring) intervention.
Why can´t we throw 500 files into the batch and dify is handling the working on the individual files, as dify surely knows better which resources are currently available

@mamema commented on GitHub (Apr 15, 2025): regarding this: >Batch Processing: Consider processing data in smaller batches to reduce peak memory usage. The cause for using Batch processing in the first place is to throw a (huge) bunch of files on something and let the application do the rest. So, why should a human resize the batches? This needs manual (recurring) intervention. Why can´t we throw 500 files into the batch and dify is handling the working on the individual files, as dify surely knows better which resources are currently available
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Reference: langgenius/dify#12472
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