RimoChan/internet-dataset

【数据集】好耶，是互联网数据集！

互联网数据集

我的搜索引擎已经运行了1年多了，收集到了不少有用的数据。

我想，这些数据应该还是挺有价值的，不如就把它们拿出来和大家1起分享吧。

数据量

数据量正在持续增长中，截至2023年5月大约有130G的数据，包含这些内容——

• 域名数据_(5.8G)包含14,000,000个域名，来自4,000,000个1级域名。

• 网页数据_(24.9G)包含115,000,000个网页。

• 反向索引数据_(99.7G)包含22,000,000个词，每个词对应1~30000个网页。

下载地址

你可以选1个自己喜欢的地方下载:

• GitHub Release

• OneDrive _{(感谢@skoqaq帮我传了OneDrive，但是这是2022年的数据)}

数据内容

• 域名级别

  • ip
  • 最后访问时间
  • 访问次数 _{(搜索引擎爬取该域名下页面的次数，数值越高，其他的字段越可靠)}
  • 语种 _{(fasttext的语种识别结果，对该域名下的所有网页滑动平均)}
  • 链接 _{(该域名下的所有网页的指向其他域名的链接，滑动抽样200个左右)}
  • 重定向 _{(该域名下的所有网页被重定向的情况，滑动抽样40个左右)}
  • ======下面的属性只针对该域名的首页======
  • https可用
  • 关键词 _{(频率最高的词)}
  • 结构 _{(将HTML结构映射到字符串，用于过滤模板生成的大量域名)}

• 网页级别

  • 网页的标题
  • 网页的介绍 _{(meta description，截断到256字符)}
  • 网页的文本 _{(截断到256字符)}
  • 最后访问时间

注意:

• ip字段并不完整，基本上是东亚地区的解析结果。

• 如果网站是动态的，关键词就不可靠_{(比如新闻网站的首页)}。中文和英文以外的网站也不可靠。

• 与语言相关的字段都是有偏的。出现这个差别的原因是因为在选择爬取目标时，包含更多中文网页的域名的权重更高，而这些域名链接到其他域名的中文网页的概率也更高，因此滑动平均的结果上中文的比例会偏高。

• 有些域名会缺字段，这个是正常的。主要原因是有些字段是后来陆续加上的，没有回扫或者只回扫了1部分。

此外，还有1些没有列出的字段，它们大多是没有意义或者是已经被废弃的字段。看到的话不用去管它们就行了。

样例

• https://github.com/的网页信息

[
  "GitHub: Let’s build from here · GitHub",
  "GitHub is where over 100 million developers shape the future of software, together. Contribute to the open source community, manage your Git repositories, review code like a pro, track bugs and features, power your CI/CD and DevOps workflows, and secure co",
  "Skip to content Toggle navigation Sign up Product Actions Automate any workflow Packages Host and manage packages Security Find and fix vulnerabilities Codespaces Instant dev environments Copilot Write better code with AI Code review Manage code changes Is",
  1683401341
]

• github.com的域名信息

{
  "https可用": true,
  "ip": ["20.205.243.166"],
  "关键词": ["github", "your", "you", "code", "octocat", "classifier", "all", "actions", "s", "build", "open", "sign", "pull", "up", "learn", "world", "more", "community", "review", "readme", "requests", "security", "merge", "software", "git", "https", "source", "developers", "jump", "can", "repositories", "added", "packages", "cli", "codespaces", "million", "developer", "available", "windows", "cloud"],
  "成功率": 0.9450735409551977,
  "最后访问时间": 1683429300,
  "结构": "[[20,[[18,[1,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,21,1,1,1,1,1,1,1,1,1,1,1,1,1,1,3,3,1,1,1,1,1,1,1,1,1,1,1,1,1,1,3,1,1,1,1,1,1,1,1,1,1,1,1,1,3,3,3,3,1,1,1,3,3,3,1,3]],[19,[[0,[[32,[[0,[[0,[0,[0,[14]]]],[0,[[0,[14]],11,[0,[[0,[[0,[[0,[[16,[[10,[7,7,7,0]]]]]]]]]],0]]]]]]]]]],0,[0,[[38,[[0,[[0,[14,0]]]]]]]],\"include-fragment\",[0,[[44,[[0,[[0,[[0,[[0,[[0,[[0,[30,[16,[[0,[[17,[[15,[10]],[9,[7]]]],7,14]]]],[0,[[0,[[0,[[0,[[0,[4]],[0,[4]],[0,[4]],[0,[5]]]]]]",
  "访问次数": 556694.9000000316,
  "语种": {
    "ar": 0.00012560604452730657,
    "bg": 5.067841852608503e-11,
    "cs": 2.5e-323,
    "de": 3.7523861649975535e-10,
    "el": 1.0593663757620937e-07,
    "en": 0.9744931624632813,
    "eo": 2.5e-323,
    "es": 4.333235886036386e-05,
    "eu": 2.5e-323,
    "fa": 1.0508114267205955e-12,
    "fr": 7.0824680275658e-05,
    "hu": 0.0004203567032961541,
    "id": 2.5e-323,
    "it": 3.063911176630927e-15,
    "ja": 0.0017088828225574997,
    "ko": 0.0015900679303152115,
    "ne": 2.5e-323,
    "nl": 0.0005624524911557625,
    "pl": 1.717507063606e-312,
    "pt": 4.0744963011521734e-06,
    "ru": 0.0009116465126009326,
    "sk": 2.5e-323,
    "th": 0.000237629139099449,
    "tr": 2.830707100472314e-05,
    "uk": 1.9260313777921886e-12,
    "vi": 2.5e-323,
    "zh": 0.019803550921189992
  },
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}

数据格式

首先要把zip包解压缩。

网页数据和域名数据都是被简单压缩过的json格式，所以可以这样读取——

import json
import brotli

print(json.loads(brotli.decompress(open(path, 'rb').read())))

反向索引的数据是1个比较奇怪的2进制格式_{(由于历史原因还有两种)}，所以读取的代码比较复杂，像是下面这样——

import json
import struct
import brotli


def _load1(b: bytes):
    n = struct.unpack('i', b[:4])[0]
    字符串长度 = struct.unpack(f'{n}h', b[4:4+n*2])
    吸0 = struct.unpack(f'{n}e', b[4+n*2:4+n*4])
    文hint = ''.join([f'{x}s' for x in 字符串长度])
    吸1 = struct.unpack(文hint, b[4+n*4:])
    吸1 = [x.decode('utf8') for x in 吸1]
    return [*zip(吸0, 吸1)]


def _load2(b: bytes):
    assert b[:6] == b'yn0001', '版本不对'
    n = struct.unpack('i', b[6:10])[0]
    吸0 = struct.unpack(f'{n}e', b[10:10+n*2])
    吸1 = json.loads(b[10+n*2:])
    assert len(吸0) == len(吸1), '数据不完整'
    return [*zip(吸0, 吸1)]


def load(b: bytes):
    if b.startswith(b'yn0001'):
        return _load2(b)
    return _load1(b)


print(load(brotli.decompress(open(path, 'rb').read())))

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