Azure Blob Storage Walkthrough
  • 1 Minute to read
  • Dark
    Light
  • PDF

Azure Blob Storage Walkthrough

  • Dark
    Light
  • PDF

Article Summary

This provides a general description of Azure Blob Storage and its capabilities.

Introduction

Azure Blob storage is Microsoft's cloud object storage solution. Blob storage is designed to accommodate large amounts of unstructured data. Unstructured data is data that doesn't adhere to a particular data model or definition, such as text or binary data.


Source Details

Connection

To connect Azure Blob storage with your destination, follow our step-by-step tutorial.
Choose a Source connection after you've created a connection, as seen here:

image.png

Container Name

After you've created a Container, click the curved arrow next to Container Name on the right side of the row to select a name from the drop down list:
image.png

Extraction Modes

In Azure Blob storage, there are 3 types of extraction modes:

  • All
  • Incremental load by file modified timestamp.
  • Incremental run: by template.

All

Choose 'All' to retrieve all data regardless of time periods.

Incremental load by file modified timestamp

Incremental Load by File Modified Timestamp allows you to control the date range of your data:

image.png

Note:

  • Start Date is mandatory.
  • Data can be retrieved for the date range specified between the start and end dates.
  • If you leave the end date blank, the data will be pulled at the current time of the river's run.
  • Dates timezone: UTC time.

Incremental run: by template

Templates allow you to run over folders and load files in the order in which they were created.
Simply choose a template type (Timestamp or Epoc time) and a data date range:

  1. image.png

  2. image.png

Note:

  • Start Value is mandatory.
  • Data can be retrieved for the date range specified between the start and end values.
  • If you leave the end date blank, the data will be pulled at the current time of the river's run.
  • Dates timezone: UTC time.


image.png

Note:

  • Splitting the requests into smaller chunks may improve the performance of the connection and reduce the time it takes to pull the data.
  • You'll need to pull the date column to figure out when each record in the results was created.

Was this article helpful?