Azure datalake directory partioning naming convention

Anshal 2,251 Reputation points
2023-04-25T05:50:53.8266667+00:00

Hi friends, this is the subdirectories /containers naming convention for ADLS zones. This naming convention is new to me, what is the reasoning behind this type of naming convention and the advantages of using this kind of naming convention for partitioning raw, staging, and curated zones? User's image

Azure Data Lake Storage
Azure Data Lake Storage
An Azure service that provides an enterprise-wide hyper-scale repository for big data analytic workloads and is integrated with Azure Blob Storage.
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Azure
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  1. KranthiPakala-MSFT 46,642 Reputation points Microsoft Employee Moderator
    2023-04-27T01:05:33.5233333+00:00

    Hi @Anshal

    Thanks for using Microsoft Q&A forum and posting your query.

    In general, the naming convention you mentioned is a way to organize data in Azure Data Lake Storage (ADLS) zones. It uses a directory structure to group data based on different attributes, such as date, time or location. The advantages of this naming conventions are to allow better data organization, filtered searches, security, and automation in the processing. The level of granularity for the date structure is determined by the interval on which the data is uploaded or processed, such as hourly, daily, or even monthly. It helps to improve query performance, makes it easier to manage large volumes of data, and provides flexibility in how data is organized and accessed.

    Below are few highlights or benefits of partitioning data in ADLS zones as per the mentioned naming convention:

    Improved query performance: Partitioning data based on relevant attributes can significantly improve query performance by reducing the amount of data that needs to be scanned.

    Easier data management: Partitioning data into subdirectories based on relevant attributes can make it easier to manage and organize large volumes of data.

    Scalability: Partitioning data can help improve scalability by allowing data to be distributed across multiple nodes or clusters.

    1. Flexibility: Partitioning data based on different criteria can provide flexibility in how data is organized and accessed, making it easier to adapt to changing business needs.

    In addition, I would recommend going through below blogs for additional information.

    Hope this info helps.


    Please don’t forget to Accept Answer and Yes for "was this answer helpful" wherever the information provided helps you, this can be beneficial to other community members.

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