Hands On: Getting Started in QDS

Hands On: Getting Started in QDS

This hands-on lab allows you to experience the features and functionality of the Qubole Data Service (QDS) platform.

About this course

Welcome to Experience-Based Learning

We are excited to offer you the opportunity to practice the relevant concepts with hands-on labs to facilitate experienced-based learning. The labs can be launched using the link associated with the environment your company is using in production from the list below. In order to perform the labs, your administrator will need to have set up and invited you to your company's training environment, typically called qubole_training. Before you begin we recommend checking to confirm that you have a training account available for you to use.

QDS platform runs on multiple clouds, across multiple regions based on the cloud and the region you are located in. If you are in api.qubole.com or in.qubole.com, or gcp-eu.qubole.com, please update the URL in the QDS window to your respective environment.

The lab exercises in this course will help you gain a foundational understanding of how to perform end-to-end workflows as a User in the QDS platform.

Cannot Find Your Training Account?

If you have not yet been invited, please contact your administrator for assistance. If you are unsure who your administrator is, please contact your customer success manager. Once there is a training account, you may select the hands-on lab appropriate for you based on your QDS deployment (AWS/GCP).

 

No Account Set Up?

If you are responsible for creating and managing your company's QDS accounts please follow the steps below to configure a training account consistent with the instructions presented in the hands-on labs. If you are unsure who has the permissions to complete this setup, please contact your customer success manager.

  • Create a new QDS account and give it the title qubole_training so that all users can easily find the account. 
  • As the Administrator, create an isolated Hive metastore for the qubole_training account. This will allow users to practice creating and using schema tables for lab purposes. Create a hive database named qubole_training in the newly created and configured metastore - the lab instructions will direct the users to write to this location. (For details on creating a custom metastore see: https://docs.qubole.com/en/latest/user-guide/hive/custom-hive-metastore.html).
  • Make sure qubole_training can read from the paid-qubole bucket as this is where the lab-specific datasets reside and the users will need to read from here for the labs.

AWS

If you are using S3 then the following changes will be necessary to the IAM Roles that govern the new qubole-training account so that users can access the lab datasets within paid-qubole.

{

"Effect": "Allow",

"Action": [

  "s3:GetObject",

"s3:ListBucket"

   ],

 "Resource": [

"arn:aws:s3:::paid-qubole/*",

  "arn:aws:s3:::paid-qubole"

  ]

  }

 

GCP

If you are using GCP no changes are necessary in order for your users to access the paid-qubole bucket and access the lab datasets.  

Azure

If you are using Azure no changes are necessary in order for your users to access the paid-qubole bucket and access the lab datasets. 

  • Make sure the following clusters exist and are named as such - hadoop2, spark, presto.
  • Using your cloud credentials make sure qubole_training can read / write to / from your company storage and compute locations so that users can launch clusters.

Once the above has been completed your training account will be fully set up - Happy Learning!

Lab Exercises

  • Hands on Lab: AWS
  • Author and Execute Commands
  • Build a Story and Collaborate
  • Hands on Lab: GCP
  • Author and Execute Commands
  • Build a Story and Collaborate (coming soon)
  • Hands on Lab: Azure
  • Author and Execute Commands (coming soon)
  • Build a Story and Collaborate (coming soon)

About this course

Welcome to Experience-Based Learning

We are excited to offer you the opportunity to practice the relevant concepts with hands-on labs to facilitate experienced-based learning. The labs can be launched using the link associated with the environment your company is using in production from the list below. In order to perform the labs, your administrator will need to have set up and invited you to your company's training environment, typically called qubole_training. Before you begin we recommend checking to confirm that you have a training account available for you to use.

QDS platform runs on multiple clouds, across multiple regions based on the cloud and the region you are located in. If you are in api.qubole.com or in.qubole.com, or gcp-eu.qubole.com, please update the URL in the QDS window to your respective environment.

The lab exercises in this course will help you gain a foundational understanding of how to perform end-to-end workflows as a User in the QDS platform.

Cannot Find Your Training Account?

If you have not yet been invited, please contact your administrator for assistance. If you are unsure who your administrator is, please contact your customer success manager. Once there is a training account, you may select the hands-on lab appropriate for you based on your QDS deployment (AWS/GCP).

 

No Account Set Up?

If you are responsible for creating and managing your company's QDS accounts please follow the steps below to configure a training account consistent with the instructions presented in the hands-on labs. If you are unsure who has the permissions to complete this setup, please contact your customer success manager.

  • Create a new QDS account and give it the title qubole_training so that all users can easily find the account. 
  • As the Administrator, create an isolated Hive metastore for the qubole_training account. This will allow users to practice creating and using schema tables for lab purposes. Create a hive database named qubole_training in the newly created and configured metastore - the lab instructions will direct the users to write to this location. (For details on creating a custom metastore see: https://docs.qubole.com/en/latest/user-guide/hive/custom-hive-metastore.html).
  • Make sure qubole_training can read from the paid-qubole bucket as this is where the lab-specific datasets reside and the users will need to read from here for the labs.

AWS

If you are using S3 then the following changes will be necessary to the IAM Roles that govern the new qubole-training account so that users can access the lab datasets within paid-qubole.

{

"Effect": "Allow",

"Action": [

  "s3:GetObject",

"s3:ListBucket"

   ],

 "Resource": [

"arn:aws:s3:::paid-qubole/*",

  "arn:aws:s3:::paid-qubole"

  ]

  }

 

GCP

If you are using GCP no changes are necessary in order for your users to access the paid-qubole bucket and access the lab datasets.  

Azure

If you are using Azure no changes are necessary in order for your users to access the paid-qubole bucket and access the lab datasets. 

  • Make sure the following clusters exist and are named as such - hadoop2, spark, presto.
  • Using your cloud credentials make sure qubole_training can read / write to / from your company storage and compute locations so that users can launch clusters.

Once the above has been completed your training account will be fully set up - Happy Learning!

Lab Exercises

  • Hands on Lab: AWS
  • Author and Execute Commands
  • Build a Story and Collaborate
  • Hands on Lab: GCP
  • Author and Execute Commands
  • Build a Story and Collaborate (coming soon)
  • Hands on Lab: Azure
  • Author and Execute Commands (coming soon)
  • Build a Story and Collaborate (coming soon)