The copy operation is synchronous so when the command returns, that indicates that all files have been copied. AzCopy uses server-to-server APIs , so data is copied directly between storage servers. These copy operations don't use the network bandwidth of your computer. To learn more, see Increase Concurrency. You can also copy specific versions of a files by referencing the DateTime value of a share snapshot. You can synchronize the contents of a local file system with a file share or synchronize the contents of a file share with another file share.
You can also synchronize the contents of a directory in a file share with the contents of a directory that is located in another file share. Synchronization is one way.
In other words, you choose which of these two endpoints is the source and which one is the destination. Synchronization also uses server to server APIs. Currently, this scenario is supported for accounts that have enabled hierarchical namespace via the blob endpoint. The sync command compares file names and last modified timestamps. Set the --delete-destination optional flag to a value of true or prompt to delete files in the destination directory if those files no longer exist in the source directory.
If you set the --delete-destination flag to true , AzCopy deletes files without providing a prompt. If you want a prompt to appear before AzCopy deletes a file, set the --delete-destination flag to prompt. If you plan to set the --delete-destination flag to prompt or false , consider using the copy command instead of the sync command and set the --overwrite parameter to ifSourceNewer. The copy command consumes less memory and incurs less billing costs because a copy operation doesn't have to index the source or destination prior to moving files.
The machine on which you run the sync command should have an accurate system clock because the last modified times are critical in determining whether a file should be transferred. If your system has significant clock skew, avoid modifying files at the destination too close to the time that you plan to run a sync command. This example encloses path arguments with single quotes ''.
The first file share that appears in this command is the source. The second one is the destination. The first directory that appears in this command is the source. To learn more about share snapshots, see Overview of share snapshots for Azure Files. Skip to main content. This browser is no longer supported.
Download Microsoft Edge More info. Contents Exit focus mode. To complete this tutorial, you must have completed the previous Storage tutorial: Upload large amounts of random data in parallel to Azure storage. To create a remote desktop session with the virtual machine, use the following command on your local machine.
When prompted, enter the credentials used when creating the virtual machine. In the previous tutorial, you only uploaded files to the storage account. Replace the Main method with the following sample. This example comments out the upload task and uncomments the download task and the task to delete the content in the storage account when complete.
After the application has been updated, you need to build the application again. Rebuild the application by running dotnet build as seen in the following example:. Now that the application has been rebuilt it is time to run the application with the updated code. The application reads the containers located in the storage account specified in the storageconnectionstring. It iterates through the blobs using the GetBlobs method and downloads them to the local machine using the DownloadToAsync method.
It iterates through the blobs 10 at a time using the ListBlobsSegmentedAsync method in the containers and downloads them to the local machine using the DownloadToFileAsync method. The following table shows the BlobRequestOptions defined for each blob as it is downloaded.
While the files are being downloaded, you can verify the number of concurrent connections to your storage account. This command shows the number of connections that are currently opened.
As you can see from the following example, over connections were open when downloading files from the storage account. In part three of the series, you learned about downloading large amounts of data from a storage account, including how to:.
Verify throughput and latency metrics in the portal. Skip to main content. This article provides an overview of the data transfer solutions when you have moderate to high network bandwidth in your environment and you are planning to transfer large datasets. The article also describes the recommended data transfer options and the respective key capability matrix for this scenario.
To understand an overview of all the available data transfer options, go to Choose an Azure data transfer solution. Large datasets refer to data sizes in the order of TBs to PBs. Moderate to high network bandwidth refers to Mbps to 10 Gbps. The options recommended in this scenario depend on whether you have moderate network bandwidth or high network bandwidth.
With moderate network bandwidth, you need to project the time for data transfer over the network. Use the following table to estimate the time and based on that, choose between an offline transfer or over the network transfer.
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