{
  "id": 192122,
  "title": "Problem with submitting with large file",
  "url": "/competitions/riiid-test-answer-prediction/discussion/192122",
  "author_name": "",
  "post_date": "2020-10-20T07:40:58.236643300Z",
  "votes": null,
  "comment_count": 2,
  "views": 0,
  "content": "<p>Hello, i'll start by saying im new to kaggle so forgive me. Im really struggling with managing such a big dataframe and so submitting my work due to leak of memory in kaggle notebooks. Is there a way to make submission possible via kaggle? if not how should i do it ?</p>\n<p>Im asking that because i see a lot of notebooks that are apparently working, but if i copy and run it memory error show up and obviusly im unable to make submission.</p>\n<p>Thanks for you time.</p>",
  "messages": [
    {
      "id": "1054826",
      "postDate": "10/20/2020 07:40:58",
      "content": "<p>Hello, i'll start by saying im new to kaggle so forgive me. Im really struggling with managing such a big dataframe and so submitting my work due to leak of memory in kaggle notebooks. Is there a way to make submission possible via kaggle? if not how should i do it ?</p>\n<p>Im asking that because i see a lot of notebooks that are apparently working, but if i copy and run it memory error show up and obviusly im unable to make submission.</p>\n<p>Thanks for you time.</p>",
      "rawMarkdown": "Hello, i'll start by saying im new to kaggle so forgive me. Im really struggling with managing such a big dataframe and so submitting my work due to leak of memory in kaggle notebooks. Is there a way to make submission possible via kaggle? if not how should i do it ?\n\nIm asking that because i see a lot of notebooks that are apparently working, but if i copy and run it memory error show up and obviusly im unable to make submission.\n\nThanks for you time.",
      "votes": null
    },
    {
      "id": "1055537",
      "postDate": "10/20/2020 23:07:53",
      "content": "<p>Hi there, </p>\n<p>I'm also new to Kaggle but I'll share what I've done to overcome this problem - </p>\n<ol>\n<li>Work with a smaller dataset </li>\n<li>Use something like the Datatable package to read your file </li>\n<li>Use the Google Cloud Platform to boost your RAM</li>\n</ol>\n<p>Currently, I have found option number 3 to be the best for me</p>",
      "rawMarkdown": "Hi there, \n\nI'm also new to Kaggle but I'll share what I've done to overcome this problem - \n1. Work with a smaller dataset \n2. Use something like the Datatable package to read your file \n3. Use the Google Cloud Platform to boost your RAM\n\nCurrently, I have found option number 3 to be the best for me",
      "votes": null
    },
    {
      "id": "1056441",
      "postDate": "10/21/2020 17:46:10",
      "content": "<p><a href=\"https://www.kaggle.com/federicogalli\" target=\"_blank\">@federicogalli</a> You might find <a href=\"https://www.kaggle.com/rohanrao/riiid-with-blazing-fast-rid\" target=\"_blank\">https://www.kaggle.com/rohanrao/riiid-with-blazing-fast-rid</a> helpful 🙂</p>",
      "rawMarkdown": "federicogalli You might find https://www.kaggle.com/rohanrao/riiid-with-blazing-fast-rid helpful 🙂",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1055537,
      "author_name": "dinodelao",
      "author_url": "",
      "post_date": "10/20/2020 23:07:53",
      "content": "<p>Hi there, </p>\n<p>I'm also new to Kaggle but I'll share what I've done to overcome this problem - </p>\n<ol>\n<li>Work with a smaller dataset </li>\n<li>Use something like the Datatable package to read your file </li>\n<li>Use the Google Cloud Platform to boost your RAM</li>\n</ol>\n<p>Currently, I have found option number 3 to be the best for me</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1056441,
      "author_name": "nyakaggle",
      "author_url": "",
      "post_date": "10/21/2020 17:46:10",
      "content": "<p><a href=\"https://www.kaggle.com/federicogalli\" target=\"_blank\">@federicogalli</a> You might find <a href=\"https://www.kaggle.com/rohanrao/riiid-with-blazing-fast-rid\" target=\"_blank\">https://www.kaggle.com/rohanrao/riiid-with-blazing-fast-rid</a> helpful 🙂</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1054826": "Hello, i'll start by saying im new to kaggle so forgive me. Im really struggling with managing such a big dataframe and so submitting my work due to leak of memory in kaggle notebooks. Is there a way to make submission possible via kaggle? if not how should i do it ?\n\nIm asking that because i see a lot of notebooks that are apparently working, but if i copy and run it memory error show up and obviusly im unable to make submission.\n\nThanks for you time.",
    "1055537": "Hi there, \n\nI'm also new to Kaggle but I'll share what I've done to overcome this problem - \n1. Work with a smaller dataset \n2. Use something like the Datatable package to read your file \n3. Use the Google Cloud Platform to boost your RAM\n\nCurrently, I have found option number 3 to be the best for me",
    "1056441": "federicogalli You might find https://www.kaggle.com/rohanrao/riiid-with-blazing-fast-rid helpful 🙂"
  },
  "source": "meta"
}