虽然不是AWS的原生服务，但有Mixpeek，它在S3文件上运行文本提取，如Tika、Tesseract和ImageAI，然后将它们放在Lucene索引中，使它们可搜索。

在这里查看文档

积分如下:

Download the module: https://github.com/mixpeek/mixpeek-python Import the module and your API keys: from mixpeek import Mixpeek, S3 from config import mixpeek_api_key, aws Instantiate the S3 class (which uses boto3 and requests): s3 = S3( aws_access_key_id=aws['aws_access_key_id'], aws_secret_access_key=aws['aws_secret_access_key'], region_name='us-east-2', mixpeek_api_key=mixpeek_api_key ) Upload one or more existing S3 files: # upload all S3 files in bucket "demo" s3.upload_all(bucket_name="demo") # upload one single file called "prescription.pdf" in bucket "demo" s3.upload_one(s3_file_name="prescription.pdf", bucket_name="demo") Now simply search using the Mixpeek module: # mixpeek api direct mix = Mixpeek( api_key=mixpeek_api_key ) # search result = mix.search(query="Heartgard") print(result) Where result can be: [ { "_id": "REDACTED", "api_key": "REDACTED", "highlights": [ { "path": "document_str", "score": 0.8759502172470093, "texts": [ { "type": "text", "value": "Vetco Prescription\nVetcoClinics.com\n\nCustomer:\n\nAddress: Canine\n\nPhone: Australian Shepherd\n\nDate of Service: 2 Years 8 Months\n\nPrescription\nExpiration Date:\n\nWeight: 41.75\n\nSex: Female\n\n℞ " }, { "type": "hit", "value": "Heartgard" }, { "type": "text", "value": " Plus Green 26-50 lbs (Ivermectin 135 mcg/Pyrantel 114 mg)\n\nInstructions: Give one chewable tablet by mouth once monthly for protection against heartworms, and the treatment and\ncontrol of roundworms, and hookworms. " } ] } ], "metadata": { "date_inserted": "2021-10-07 03:19:23.632000", "filename": "prescription.pdf" }, "score": 0.13313256204128265 } ]

然后解析结果

有多种选择，没有一个是简单的“一次性”全文解决方案:

Key name pattern search: Searching for keys starting with some string- if you design key names carefully, then you may have rather quick solution. Search metadata attached to keys: when posting a file to AWS S3, you may process the content, extract some meta information and attach this meta information in form of custom headers into the key. This allows you to fetch key names and headers without need to fetch complete content. The search has to be done sequentialy, there is no "sql like" search option for this. With large files this could save a lot of network traffic and time. Store metadata on SimpleDB: as previous point, but with storing the metadata on SimpleDB. Here you have sql like select statements. In case of large data sets you may hit SimpleDB limits, which can be overcome (partition metadata across multiple SimpleDB domains), but if you go really far, you may need to use another metedata type of database. Sequential full text search of the content - processing all the keys one by one. Very slow, if you have too many keys to process.

几年来，我们每天存储1440个版本的文件(每分钟一个)，使用版本化桶，这是很容易实现的。但要获得一些较旧的版本需要时间，因为人们必须一个版本一个版本地按顺序进行。有时我使用简单的CSV记录索引，显示发布时间和版本id，有了这个，我可以很快跳转到旧版本。

正如你所看到的，AWS S3并不是为全文搜索而设计的，它是一个简单的存储服务。

我也面临同样的问题。在S3中进行搜索应该比目前的情况容易得多。这就是为什么我在S3中实现了这个用于搜索的开源工具。

search是完全开源的S3搜索工具。它的实现始终牢记性能是关键因素，并根据基准测试在几秒钟内搜索包含~1000个文件的桶。

安装很简单。你只需要下载docker-compose文件并运行它

docker-compose up

搜索将开始，你可以在任何桶搜索任何东西。

如果你在Windows上，没有时间找到一个好的grep替代品，一个快速而肮脏的方法是:

Aws s3 ls s3://your-bucket/folder/——recursive > myfile.txt

然后在myfile.txt中快速搜索

“文件夹”位是可选的。

附注:如果你没有安装AWS CLI -这里有一个使用Chocolatey包管理器的一行程序

Choco安装awscli

P.P.S.如果你没有巧克力包装管理器-得到它!你在Windows上的生活将变得更好10倍。(我和Chocolatey没有任何关系，但是嘿，这是一个必须要有的，真的)。

这是一个有点旧的话题——但也许可以帮助那些仍然在搜索的人——我就是那个搜索了一年的人。

解决方案可能是“AWS Athena”，您可以像这样搜索数据

'SELECT user_name FROM S3Object WHERE cast(age as int) > 20'

https://aws.amazon.com/blogs/developer/introducing-support-for-amazon-s3-select-in-the-aws-sdk-for-javascript/

目前1TB数据的价格是5美元——所以举例来说，如果你的查询搜索超过一个1TB文件的3倍你的成本是15美元——但举例来说，如果你想要读取的只有1列“转换柱状格式”，你将支付价格的1/3，即1.67美元/TB。

快进到2020年，使用aws-okta作为我们的2fa，下面的命令，尽管迭代这个特定bucket(+270,000)中的所有对象和文件夹非常缓慢，但运行良好。

aws-okta exec dev -- aws s3 ls my-cool-bucket --recursive | grep needle-in-haystax.txt