AzureQstor: R interface to Azure Queue Storage now on GitHub

This article is originally published at https://blog.revolutionanalytics.com/

This post is to announce that the AzureQstor package is now on GitHub. AzureQstor provides an R interface to Azure queue storage, building on the facilities provided by AzureStor.

Queue Storage is a service for storing large numbers of messages, for example from automated sensors, that can be accessed remotely via authenticated calls using HTTP or HTTPS. A single queue message can be up to 64 KB in size, and a queue can contain millions of messages, up to the total capacity limit of a storage account. Queue storage is often used to create a backlog of work to process asynchronously.

AzureQstor uses a combination of S3 and R6 classes. The queue endpoint is an S3 object for compatibility with AzureStor, while R6 classes are used to represent queues and messages.

library(AzureQstor)

endp <- storage_endpoint("https://mystorage.queue.core.windows.net",
                         key="access_key")

# creating, retrieving and deleting queues
create_storage_queue(endp, "myqueue")
qu <- storage_queue(endp, "myqueue")

qu2 <- create_storage_queue(endp, "myqueue2")
delete_storage_queue(qu2)

The queue object exposes methods for getting (reading), peeking, deleting, updating, popping (reading and deleting) and putting (writing) messages:

qu$put_message("Hello queue")
msg <- qu$get_message()

msg$text
## [1] "Hello queue"

# get several messages at once
qu$get_messages(n=30)

The message object exposes methods for deleting and updating the message:

msg$update(visibility_timeout=30, text="Updated message")
msg$delete()

You can also get and set metadata for a queue with the AzureStor get/set_storage_metadata generics:

get_storage_metadata(qu)
set_storage_metadata(qu, name1="value1", name2="value2")

It’s anticipated that AzureQstor will be submitted to CRAN before long. If you are a queue storage user, please install it and give it a try; any feedback or bug report is much appreciated. You can email me or open an issue on GitHub.

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This article is originally published at https://blog.revolutionanalytics.com/
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