Azure Lake Store is a world-wide hyper scale repository for big data analytic workloads. Azure Data Lake Store enables us to explore or capture data of any size, any inception speed, and any type etc., in a single place for performing an operation.
The following are the benefits of an Apache Hadoop Distributed File System for the cloud.No fixed limits on file size. No fixed limits on account size. Unstructured and structured data in their native format. Massive throughput to increase analytic performance. High durability, availability, and reliability. Azure Active Directory access control. Key capabilities of Azure Data Lake Store Built for Hadoop Unlimited storage, Peta byte file Performance tuning for Big Data Highly available and secure
You can directly access the data lake file system by using the following link.adl://<data_lake_store_name>.azuredatalakestore.net
Let’s get started.
Log into Azure Management Portal by clicking the link for creating a Data Lake Store Service in Microsoft Azure.
Now, click browse option in the Azure dashboard. In the browse blade, select Data Lake Store from intelligence and analytics.
In the Data Lake Store, click "Add" button to create a new service in Microsoft Azure. If you don’t see your subscription, click refresh option.
Now, in Data Lake Store creation wizard, fill the basic credits such as Name, Subscription, Resource group, and pricing, and tick the option - "Pin to dashboard".
It takes some time on Azure Management Portal and finally, the Data Lake Store is ready and configured to use.Creating Folders in Azure Data Lake Store
Open the Data Lake Store account that you just created. From the left pane, click Browse >> Data Lake Store. Now, from the Data Lake Store blade, click the account name under which you want to create folders.
Now, select "Data Explorer". Click "New Folder" and enter the name of the folder you need to create. Finally, the newly created folder is available.
Now, open the newly created folder and click upload. In upload wizard, select file and click "Start upload".
And the uploaded file is displayed as a preview in the preview window.
For removing a file from the folder or for removing a complete folder, click Delete file or folder option to delete.
Data - Structured, Unstructured, semi structured and raw data Processing - schema on read. Storage - designed for low cost storage. Users - Data scientist Security - Authentication and access control Summary -
In this article, we have created an account in Azure Data Lake Store and uploaded a sample file.
本文系统（windows）相关术语:三级网络技术 计算机三级网络技术 网络技术基础 计算机网络技术