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了解 Dask-ML

[英]Understanding Dask-ML

原文 2020-05-04 08:05:14 2 1 python/ parallel-processing/ dask/ dask-distributed/ dask-delayed

I have read through Dask-ML documentation and I have googled around, but have 2 questions I would like some clarity on if anyone could assists:我已经阅读了 Dask-ML 文档，并且在 Google 上搜索过，但是有两个问题我想弄清楚是否有人可以提供帮助：

by saying "using a cluster of computers", does it mean processing is distributed across other people's computers who are connected to the network?通过说“使用计算机集群”，是否意味着处理分布在连接到网络的其他人的计算机上？ If yes, would there be any privacy issues with this?如果是，这会不会有任何隐私问题？
would we be able to know how many computers are there in a cluster at any point in time?我们能否随时知道集群中有多少台计算机？

Please point me to the right direction or if there are any link that I could read more about this.请指出我正确的方向，或者如果有任何链接我可以阅读更多关于此的内容。 Thanks in advance.提前致谢。

1 个解决方案

It sounds like you're looking for general documentation on Dask听起来您正在寻找有关 Dask 的一般文档

https://docs.dask.org/en/latest https://docs.dask.org/en/latest

And in particular on how to set up Dask on a set of machines特别是关于如何在一组机器上设置 Dask

https://docs.dask.org/en/latest/setup.html https://docs.dask.org/en/latest/setup.html

在 dask-ml 中估算单列的平均值 - Impute mean of single column in dask-ml

dask-ml 预处理引发 AttributeError - dask-ml preprocessing raise AttributeError

安装 dask-ml 会引发“解决环境”错误 - Installing dask-ml throws “Solving Environment” error

同时运行两个 dask-ml 输入器，而不是顺序运行 - Running two dask-ml imputers simultaneously instead of sequentially

Dask-ML 的 Client() function 中参数的默认值是多少 - What are the default values for the parameters in Dask-ML's Client() function

当我在使用 Dask-ML 时一直超过 memory 时该怎么办 - What can I do when I keep exceeding memory used while using Dask-ML

如果我在 HPC 上使用 Dask-Jobqueue，是否还需要使用 Dask-ML 来运行 scikit-learn 代码？ - If I am using Dask-Jobqueue on a HPC, do I still need to use Dask-ML to run scikit-learn codes?

了解Dask调度程序和客户端 - Understanding Dask scheduler and client

了解分区在Dask中的工作原理 - Understanding How Partitions Work in Dask

使用 dask ml StandardScaler 的属性错误 - atribute error using dask ml StandardScaler

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相关问题 在 dask-ml 中估算单列的平均值 - Impute mean of single column in dask-ml dask-ml 预处理引发 AttributeError - dask-ml preprocessing raise AttributeError 安装 dask-ml 会引发“解决环境”错误 - Installing dask-ml throws “Solving Environment” error 同时运行两个 dask-ml 输入器，而不是顺序运行 - Running two dask-ml imputers simultaneously instead of sequentially Dask-ML 的 Client() function 中参数的默认值是多少 - What are the default values for the parameters in Dask-ML's Client() function 当我在使用 Dask-ML 时一直超过 memory 时该怎么办 - What can I do when I keep exceeding memory used while using Dask-ML 如果我在 HPC 上使用 Dask-Jobqueue，是否还需要使用 Dask-ML 来运行 scikit-learn 代码？ - If I am using Dask-Jobqueue on a HPC, do I still need to use Dask-ML to run scikit-learn codes? 了解Dask调度程序和客户端 - Understanding Dask scheduler and client 了解分区在Dask中的工作原理 - Understanding How Partitions Work in Dask 使用 dask ml StandardScaler 的属性错误 - atribute error using dask ml StandardScaler

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