{
  "id": 71268,
  "title": "Kernel is very slow in running",
  "url": "/competitions/ga-customer-revenue-prediction/discussion/71268",
  "author_name": "",
  "post_date": "2018-11-12T04:33:39.462420300Z",
  "votes": null,
  "comment_count": 4,
  "views": 0,
  "content": "<p>I am trying to run my kernel but it is taking forever to run. Even loading train_v2.csv as DataFrame is taking inordinately long time. After some time the kernel hangs. Is anyone else facing the same issue?</p>",
  "messages": [
    {
      "id": "419502",
      "postDate": "11/12/2018 04:33:39",
      "content": "<p>I am trying to run my kernel but it is taking forever to run. Even loading train_v2.csv as DataFrame is taking inordinately long time. After some time the kernel hangs. Is anyone else facing the same issue?</p>",
      "rawMarkdown": "I am trying to run my kernel but it is taking forever to run. Even loading train_v2.csv as DataFrame is taking inordinately long time. After some time the kernel hangs. Is anyone else facing the same issue?",
      "votes": null
    },
    {
      "id": "419571",
      "postDate": "11/12/2018 08:13:41",
      "content": "<p>Hello Vivek,</p>\n\n<p>It's very long because train_v2 is more than 20gb.. and test_v2 is 7 gb.. so firstly, it will be very long to load, secondly, it's bigger than the RAM available in the Kaggle Kernel (16gb) so you won't be able to load train_v2 fully. </p>",
      "rawMarkdown": "Hello Vivek,\n\nIt's very long because train_v2 is more than 20gb.. and test_v2 is 7 gb.. so firstly, it will be very long to load, secondly, it's bigger than the RAM available in the Kaggle Kernel (16gb) so you won't be able to load train_v2 fully.",
      "votes": null
    },
    {
      "id": "419583",
      "postDate": "11/12/2018 08:55:20",
      "content": "<p>Thanks Assous! I am still learning the ropes. What is the way out? I am getting the message \"The kernel appears to have died. It will restart automatically.\"</p>",
      "rawMarkdown": "Thanks Assous! I am still learning the ropes. What is the way out? I am getting the message \"The kernel appears to have died. It will restart automatically.\"",
      "votes": null
    },
    {
      "id": "419587",
      "postDate": "11/12/2018 08:59:37",
      "content": "<p>The reason why you get this message is that the kernel is running out of ram. If you look at the top right of the kernel, when you load the dataset, you will see that you will exceed 16gb of ram. </p>\n\n<p>Basically, there is no way out if you want to continue to use the kaggle kernel.. either you use AWS.. or a computer with 32gb ram.. \nOR you can load the train_v2 et test_v2 without the \"hits\" column which contrains most of the information. </p>",
      "rawMarkdown": "The reason why you get this message is that the kernel is running out of ram. If you look at the top right of the kernel, when you load the dataset, you will see that you will exceed 16gb of ram. \n\nBasically, there is no way out if you want to continue to use the kaggle kernel.. either you use AWS.. or a computer with 32gb ram.. \nOR you can load the train_v2 et test_v2 without the \"hits\" column which contrains most of the information.",
      "votes": null
    },
    {
      "id": "420121",
      "postDate": "11/13/2018 05:05:16",
      "content": "<p>Thanks Assous! I tried to load test_v2.csv which is 7.6 gb in size. Somehow loading it as a DataFrame is consuming 15 gb of 17.2 gb available. It seems DataFrame consume even more memory than csv file.</p>",
      "rawMarkdown": "Thanks Assous! I tried to load test_v2.csv which is 7.6 gb in size. Somehow loading it as a DataFrame is consuming 15 gb of 17.2 gb available. It seems DataFrame consume even more memory than csv file.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 419571,
      "author_name": "xtelima",
      "author_url": "",
      "post_date": "11/12/2018 08:13:41",
      "content": "<p>Hello Vivek,</p>\n\n<p>It's very long because train_v2 is more than 20gb.. and test_v2 is 7 gb.. so firstly, it will be very long to load, secondly, it's bigger than the RAM available in the Kaggle Kernel (16gb) so you won't be able to load train_v2 fully. </p>",
      "votes": null,
      "replies": [
        {
          "id": 419583,
          "author_name": "vivekrai11",
          "author_url": "",
          "post_date": "11/12/2018 08:55:20",
          "content": "<p>Thanks Assous! I am still learning the ropes. What is the way out? I am getting the message \"The kernel appears to have died. It will restart automatically.\"</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 419587,
          "author_name": "xtelima",
          "author_url": "",
          "post_date": "11/12/2018 08:59:37",
          "content": "<p>The reason why you get this message is that the kernel is running out of ram. If you look at the top right of the kernel, when you load the dataset, you will see that you will exceed 16gb of ram. </p>\n\n<p>Basically, there is no way out if you want to continue to use the kaggle kernel.. either you use AWS.. or a computer with 32gb ram.. \nOR you can load the train_v2 et test_v2 without the \"hits\" column which contrains most of the information. </p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 420121,
          "author_name": "vivekrai11",
          "author_url": "",
          "post_date": "11/13/2018 05:05:16",
          "content": "<p>Thanks Assous! I tried to load test_v2.csv which is 7.6 gb in size. Somehow loading it as a DataFrame is consuming 15 gb of 17.2 gb available. It seems DataFrame consume even more memory than csv file.</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "419502": "I am trying to run my kernel but it is taking forever to run. Even loading train_v2.csv as DataFrame is taking inordinately long time. After some time the kernel hangs. Is anyone else facing the same issue?",
    "419571": "Hello Vivek,\n\nIt's very long because train_v2 is more than 20gb.. and test_v2 is 7 gb.. so firstly, it will be very long to load, secondly, it's bigger than the RAM available in the Kaggle Kernel (16gb) so you won't be able to load train_v2 fully.",
    "419583": "Thanks Assous! I am still learning the ropes. What is the way out? I am getting the message \"The kernel appears to have died. It will restart automatically.\"",
    "419587": "The reason why you get this message is that the kernel is running out of ram. If you look at the top right of the kernel, when you load the dataset, you will see that you will exceed 16gb of ram. \n\nBasically, there is no way out if you want to continue to use the kaggle kernel.. either you use AWS.. or a computer with 32gb ram.. \nOR you can load the train_v2 et test_v2 without the \"hits\" column which contrains most of the information.",
    "420121": "Thanks Assous! I tried to load test_v2.csv which is 7.6 gb in size. Somehow loading it as a DataFrame is consuming 15 gb of 17.2 gb available. It seems DataFrame consume even more memory than csv file."
  },
  "source": "meta"
}