Azure DataBricks Accessing Data Lake (Using Access Key)

 

Introduction:
In this Blog post we are going to discuss about accessing Azure Data Lake Gen2.

 

How can we Access the Azure Data Lake Gen2:

Access can be done by

Ø  Using Storage Access key

Ø  Using Shared access signature (SAS token)

Ø  Using Service Principal

Ø  Using Azure Active directory authentication pass-through

Ø  Using unity catalog

 

In this post we are going to discuss about accessing Azure Data Lake Gent 2 by using Access key.





Authenticate Data Lake with Access Key:

·         Each storage account comes with 2 access keys

·         Each access key is 512 bits

·         Access key gives full access of storage account

·         Conceder it as super user

·         Key can be rotated (re-generated)

 

Access Key Spark configuration:

Here we take myschool as Azure Data Lake gen2 and there is a container within this data lake named bronze. The bronze containers have a csv file named school.csv

 

spark.conf.set(

    "fs.azure.account.key.myschool.dfs.core.windows.net",

    "<512 bit access key in Azure data Lake>")

 

 

Microsoft recommended abfs (azure blob file system) driver protocol to access

abfss://bronze@myschool.dfs.core.windows.net

Note book command:

spark.conf.set(

    "fs.azure.account.key.myschool.dfs.core.windows.net",

    "<512 bit access key in Azure data Lake>")

dbutils.fs.ls("abfss://bronze@myschool.dfs.core.windows.net")

è  It gives us the list of files within bronze containers

display(Spark.read.csv("abfss://bronze@myschool.dfs.core.windows.net/school.csv"))

è  It is going to read and display the school.csv file

Comments

Post a Comment

Popular Posts

Vertipaq Engine – Data Compression

Image
Introduction Microsoft introduces a very powerful engine for fast query named Vertipaq . Which is used in the Power BI and SSAS Tabular model? Here we are not going to discuss about Power BI or SSIS Tabular model. Our main concern is to identify how the Vertipaq Engine works and how it provide Fastest Query. The Vertipaq Engine stores the table in a columnar format and established relation between columns. In this blog post we are going to discuss about Data Compression mechanism and try to explain it.   Case Study We have a table which is imported into Vertipaq engine. Table Name:  Order_Details     How Vertipaq works on this Table Vertipaq Compress Text in a Table Text takes lot of space in data base. So Vertipaq need to compress it. It maintain another table with distinct Text value and Id number like this. It is also called Dictionary/ Hash compression.   Product_ID_Dictionary              Value Encoding Here Vertipaq tries to convert Value into One Digit where as possible. TO u
Read more

Azure Data Bricks Architecture Part-1

Image
  Introduction:   We decide to provide several blog posts for learning Azure DataBricks step by step. This blog post is useful for beginners who want to start Azure DataBricks.   Azure DataBricks High Level Diagram:   Azure DataBricks is an analytics platform optimized for the Microsoft Azure cloud services platform. It provides a collaborative environment with Apache Spark-based analytics that enables big data processing, real-time analytics, and machine learning tasks. Here are some key features of Azure DataBricks: ·          Optimized Apache Spark Environment: It allows you to set up an Apache Spark environment quickly, with autoscaling and auto-termination to optimize costs. ·          Collaborative Workspace: It supports multiple languages like Python, Scala, R, Java, and SQL, and integrates with tools like GitHub and Azure DevOps for version control. ·          Machine Learning Capabilities: Azure DataBricks integrates with Azure Machine Learning to provide au
Read more