Copy data into Azure Data Lake Storage using DistCp - Azure Storage (original) (raw)

You can use DistCp to copy data between a general purpose V2 storage account and a general purpose V2 storage account with hierarchical namespace enabled. This article provides instructions on how to use the DistCp tool.

DistCp provides various command-line parameters and we strongly encourage you to read this article in order to optimize your usage of it. This article shows basic functionality while focusing on its use for copying data to a hierarchical namespace enabled account.

Prerequisites

• An Azure subscription. For more information, see Get Azure free trial.
• An existing Azure Storage account without Data Lake Storage capabilities (hierarchical namespace) enabled.
• An Azure Storage account with Data Lake Storage capabilities (hierarchical namespace) enabled. For instructions on how to create one, see Create an Azure Storage account
• A container that has been created in the storage account with hierarchical namespace enabled.
• An Azure HDInsight cluster with access to a storage account with the hierarchical namespace feature enabled. For more information, see Use Azure Data Lake Storage with Azure HDInsight clusters. Make sure you enable Remote Desktop for the cluster.

Use DistCp from an HDInsight Linux cluster

An HDInsight cluster comes with the DistCp utility, which can be used to copy data from different sources into an HDInsight cluster. If you have configured the HDInsight cluster to use Azure Blob Storage and Azure Data Lake Storage together, the DistCp utility can be used out-of-the-box to copy data between as well. In this section, we look at how to use the DistCp utility.

1. Create an SSH session to your HDInsight cluster. For more information, see Connect to a Linux-based HDInsight cluster.
2. Verify whether you can access your existing general purpose V2 account (without hierarchical namespace enabled).

hdfs dfs -ls wasbs://<container-name>@<storage-account-name>.blob.core.windows.net/  

The output should provide a list of contents in the container. 3. Similarly, verify whether you can access the storage account with hierarchical namespace enabled from the cluster. Run the following command:

hdfs dfs -ls abfss://<container-name>@<storage-account-name>.dfs.core.windows.net/  

The output should provide a list of files/folders in the Data Lake storage account. 4. Use DistCp to copy data from Windows Azure Storage Blob (WASB) to a Data Lake Storage account.

hadoop distcp wasbs://<container-name>@<storage-account-name>.blob.core.windows.net/example/data/gutenberg abfss://<container-name>@<storage-account-name>.dfs.core.windows.net/myfolder  

The command copies the contents of the /example/data/gutenberg/ folder in Blob storage to /myfolder in the Data Lake Storage account. 5. Similarly, use DistCp to copy data from Data Lake Storage account to Blob Storage (WASB).

hadoop distcp abfss://<container-name>@<storage-account-name>.dfs.core.windows.net/myfolder wasbs://<container-name>@<storage-account-name>.blob.core.windows.net/example/data/gutenberg  

The command copies the contents of /myfolder in the Data Lake Store account to /example/data/gutenberg/ folder in WASB.

Performance considerations while using DistCp

Because DistCp's lowest granularity is a single file, setting the maximum number of simultaneous copies is the most important parameter to optimize it against Data Lake Storage. Number of simultaneous copies is equal to the number of mappers (m) parameter on the command line. This parameter specifies the maximum number of mappers that are used to copy data. Default value is 20.

Example

hadoop distcp -m 100 wasbs://<container-name>@<storage-account-name>.blob.core.windows.net/example/data/gutenberg abfss://<container-name>@<storage-account-name>.dfs.core.windows.net/myfolder

How do I determine the number of mappers to use?

Here's some guidance that you can use.

• Step 1: Determine total memory available to the 'default' YARN app queue - The first step is to determine the memory available to the 'default' YARN app queue. This information is available in the Ambari portal associated with the cluster. Navigate to YARN and view the Configs tab to see the YARN memory available to the 'default' app queue. This is the total available memory for your DistCp job (which is actually a MapReduce job).
• Step 2: Calculate the number of mappers - The value of m is equal to the quotient of total YARN memory divided by the YARN container size. The YARN container size information is available in the Ambari portal as well. Navigate to YARN and view the Configs tab. The YARN container size is displayed in this window. The equation to arrive at the number of mappers (m) is
  m = (number of nodes * YARN memory for each node) / YARN container size

Example

Let's assume that you have a 4x D14v2s cluster and you're trying to transfer 10 TB of data from 10 different folders. Each of the folders contains varying amounts of data and the file sizes within each folder are different.

• Total YARN memory: From the Ambari portal you determine that the YARN memory is 96 GB for a D14 node. So, total YARN memory for four node cluster is:
  YARN memory = 4 * 96 GB = 384 GB
• Number of mappers: From the Ambari portal you determine that the YARN container size is 3,072 MB for a D14 cluster node. So, number of mappers is:
  m = (four nodes * 96 GB) / 3072 MB = 128 mappers

If other applications are using memory, then you can choose to only use a portion of your cluster's YARN memory for DistCp.

Copying large datasets

When the size of the dataset to be moved is large (for example, >1 TB) or if you have many different folders, you should consider using multiple DistCp jobs. There's likely no performance gain, but it spreads out the jobs so that if any job fails, you only need to restart that specific job rather than the entire job.

Limitations

• DistCp tries to create mappers that are similar in size to optimize performance. Increasing the number of mappers might not always increase performance.
• DistCp is limited to only one mapper per file. Therefore, you shouldn't have more mappers than you have files. Since DistCp can only assign one mapper to a file, this limits the amount of concurrency that can be used to copy large files.
• If you have a few large files, then you should split them into 256-MB file chunks to give you more potential concurrency.