This package implements both an admin- and client-side interface to [Azure Storage Services](https://docs.microsoft.com/en-us/rest/api/storageservices/). The admin interface uses R6 classes and extends the framework provided by [AzureRMR](https://github.com/Azure/AzureRMR). The client interface provides several S3 methods for efficiently managing storage and performing file transfers.
The primary repo for this package is at https://github.com/Azure/AzureStor; please submit issues and PRs there. It is also mirrored at the Cloudyr org at https://github.com/cloudyr/AzureStor. You can install the development version of the package with `devtools::install_github("Azure/AzureStor")`.
The interface for accessing storage is similar across blobs, files and ADLSGen2. You call the `storage_endpoint` function and provide the endpoint URI, along with your authentication credentials. AzureStor will figure out the type of storage from the URI.
AzureStor supports all the different ways you can authenticate with a storage endpoint:
In the case of an AAD token, you can also provide an object obtained via `AzureAuth::get_azure_token()`. If you do this, AzureStor can automatically refresh the token for you when it expires.
As noted above, you can transfer multiple files in parallel using the `storage_multiupload/download` functions. These functions utilise a background process pool supplied by AzureRMR to do the transfers in parallel, which usually results in major speedups when transferring multiple small files. The pool is created the first time a parallel file transfer is performed, and persists for the duration of the R session; this means you don't have to wait for the pool to be (re-)created each time.
AzureStor includes convenience functions to transfer data in a number of commonly used formats: RDS, RData, TSV (tab-delimited), CSV, and CSV2 (semicolon-delimited). These work via connections and so don't create temporary files on disk.
```r
# save an R object to storage and read it back again
You can upload a (single) in-memory R object via a connection, and similarly, you can download a file to a connection, or return it as a raw vector. This lets you transfer an object without having to create a temporary file as an intermediate step.
The `copy_url_to_storage` function lets you transfer the contents of a URL directly to storage, without having to download it to your local machine first. The `multicopy_url_to_storage` function does the same, but for a vector of URLs. Currently, these only work for blob storage.
```r
# copy from a public URL: Iris data from UCI machine learning repository
AzureStor supports uploading to append blobs. An append blob is comprised of blocks and is optimized for append operations; it is well suited for data that is constantly growing, but should not be modified once written, such as server logs.
To upload to an append blob, specify `type="AppendBlob"` in the `storage_upload` call. To append data (rather than overwriting an existing blob), include the argument `append=TRUE`. See `?upload_blob` for more details.
AzureStor includes an interface to [AzCopy](https://docs.microsoft.com/en-us/azure/storage/common/storage-use-azcopy-v10), Microsoft's high-performance commandline utility for copying files to and from storage. To take advantage of this, simply include the argument `use_azcopy=TRUE` on any upload or download function. AzureStor will then call AzCopy to perform the file transfer, rather than using its own internal code. In addition, a `call_azcopy` function is provided to let you use AzCopy for any task.
Finally, AzureStor's admin-side interface allows you to easily create and delete resource accounts, as well as obtain access keys and generate a SAS. Here is a sample workflow:
