将数据移入和移出 Azure Blob 存储Move data to and from Azure Blob storage

团队数据科学过程要求引入或载入各种不同存储环境中的数据在过程的每个阶段中都以最合适的方式进行处理或分析。The Team Data Science Process requires that data be ingested or loaded into a variety of different storage environments to be processed or analyzed in the most appropriate way in each stage of the process.

用于移动数据的不同技术Different technologies for moving data

以下文章介绍了如何使用不同技术将数据移入和移出 Azure Blob 存储。The following articles describe how to move data to and from Azure Blob storage using different technologies.

最合适的方法取决于具体的方案。Which method is best for you depends on your scenario. 用于 Azure 机器学习中高级分析的方案有助于确定用于高级分析过程的各种数据科学工作流所需的资源。The Scenarios for advanced analytics in Azure Machine Learning article helps you determine the resources you need for a variety of data science workflows used in the advanced analytics process.

Note

有关 Azure Blob 存储的完整介绍,请参阅 Azure Blob 基本知识Azure Blob 服务For a complete introduction to Azure blob storage, refer to Azure Blob Basics and to Azure Blob Service.

使用 Azure 数据工厂Using Azure Data Factory

或者,可使用 Azure 数据工厂来执行以下操作:As an alternative, you can use Azure Data Factory to:

  • 创建和计划从 Azure Blob 存储下载数据的管道,create and schedule a pipeline that downloads data from Azure blob storage,
  • 将其传递到已发布的 Azure 机器学习 Web 服务,pass it to a published Azure Machine Learning web service,
  • 接收预测分析结果,然后receive the predictive analytics results, and
  • 将结果上传到存储。upload the results to storage.

必备条件Prerequisites

本文假定已有 Azure 订阅、存储帐户,以及该帐户对应的存储密钥。This article assumes that you have an Azure subscription, a storage account, and the corresponding storage key for that account. 上传/下载数据之前,必须知道 Azure 存储帐户名和帐户密钥。Before uploading/downloading data, you must know your Azure storage account name and account key.