Hadoop Azure Support: ABFS - Azure Data Lake Storage Gen2

Introduction

The hadoop-azure module provides support for the Azure Data Lake Storage Gen2 storage layer through the “abfs” connector

To make it part of Apache Hadoop’s default classpath, make sure that HADOOP_OPTIONAL_TOOLS environment variable has hadoop-azure in the list, on every machine in the cluster

export HADOOP_OPTIONAL_TOOLS=hadoop-azure

You can set this locally in your .profile/.bashrc, but note it won’t propagate to jobs running in-cluster.

Features of the ABFS connector.

  • Supports reading and writing data stored in an Azure Blob Storage account.
  • Fully Consistent view of the storage across all clients.
  • Can read data written through the wasb: connector.
  • Presents a hierarchical file system view by implementing the standard Hadoop FileSystem interface.
  • Supports configuration of multiple Azure Blob Storage accounts.
  • Can act as a source or destination of data in Hadoop MapReduce, Apache Hive, Apache Spark.
  • Tested at scale on both Linux and Windows by Microsoft themselves.
  • Can be used as a replacement for HDFS on Hadoop clusters deployed in Azure infrastructure.

For details on ABFS, consult the following documents:

Getting started

Concepts

The Azure Storage data model presents 3 core concepts:

  • Storage Account: All access is done through a storage account.
  • Container: A container is a grouping of multiple blobs. A storage account may have multiple containers. In Hadoop, an entire file system hierarchy is stored in a single container.
  • Blob: A file of any type and size stored with the existing wasb connector

The ABFS connector connects to classic containers, or those created with Hierarchical Namespaces.

Hierarchical Namespaces (and WASB Compatibility)

A key aspect of ADLS Gen 2 is its support for hierachical namespaces These are effectively directories and offer high performance rename and delete operations —something which makes a significant improvement in performance in query engines writing data to, including MapReduce, Spark, Hive, as well as DistCp.

This feature is only available if the container was created with “namespace” support.

You enable namespace support when creating a new Storage Account, by checking the “Hierarchical Namespace” option in the Portal UI, or, when creating through the command line, using the option --hierarchical-namespace true

You cannot enable Hierarchical Namespaces on an existing storage account

Containers in a storage account with Hierarchical Namespaces are not (currently) readable through the wasb: connector.

Some of the az storage command line commands fail too, for example:

$ az storage container list --account-name abfswales1
Blob API is not yet supported for hierarchical namespace accounts. ErrorCode: BlobApiNotYetSupportedForHierarchicalNamespaceAccounts

Creating an Azure Storage Account

The best documentation on getting started with Azure Datalake Gen2 with the abfs connector is Using Azure Data Lake Storage Gen2 with Azure HDInsight clusters

It includes instructions to create it from the Azure command line tool, which can be installed on Windows, MacOS (via Homebrew) and Linux (apt or yum).

The az storage subcommand handles all storage commands, az storage account create does the creation.

Until the ADLS gen2 API support is finalized, you need to add an extension to the ADLS command.

az extension add --name storage-preview

Check that all is well by verifying that the usage command includes --hierarchical-namespace:

$  az storage account
usage: az storage account create [-h] [--verbose] [--debug]
     [--output {json,jsonc,table,tsv,yaml,none}]
     [--query JMESPATH] --resource-group
     RESOURCE_GROUP_NAME --name ACCOUNT_NAME
     [--sku {Standard_LRS,Standard_GRS,Standard_RAGRS,Standard_ZRS,Premium_LRS,Premium_ZRS}]
     [--location LOCATION]
     [--kind {Storage,StorageV2,BlobStorage,FileStorage,BlockBlobStorage}]
     [--tags [TAGS [TAGS ...]]]
     [--custom-domain CUSTOM_DOMAIN]
     [--encryption-services {blob,file,table,queue} [{blob,file,table,queue} ...]]
     [--access-tier {Hot,Cool}]
     [--https-only [{true,false}]]
     [--file-aad [{true,false}]]
     [--hierarchical-namespace [{true,false}]]
     [--bypass {None,Logging,Metrics,AzureServices} [{None,Logging,Metrics,AzureServices} ...]]
     [--default-action {Allow,Deny}]
     [--assign-identity]
     [--subscription _SUBSCRIPTION]

You can list locations from az account list-locations, which lists the name to refer to in the --location argument:

$ az account list-locations -o table

DisplayName          Latitude    Longitude    Name
-------------------  ----------  -----------  ------------------
East Asia            22.267      114.188      eastasia
Southeast Asia       1.283       103.833      southeastasia
Central US           41.5908     -93.6208     centralus
East US              37.3719     -79.8164     eastus
East US 2            36.6681     -78.3889     eastus2
West US              37.783      -122.417     westus
North Central US     41.8819     -87.6278     northcentralus
South Central US     29.4167     -98.5        southcentralus
North Europe         53.3478     -6.2597      northeurope
West Europe          52.3667     4.9          westeurope
Japan West           34.6939     135.5022     japanwest
Japan East           35.68       139.77       japaneast
Brazil South         -23.55      -46.633      brazilsouth
Australia East       -33.86      151.2094     australiaeast
Australia Southeast  -37.8136    144.9631     australiasoutheast
South India          12.9822     80.1636      southindia
Central India        18.5822     73.9197      centralindia
West India           19.088      72.868       westindia
Canada Central       43.653      -79.383      canadacentral
Canada East          46.817      -71.217      canadaeast
UK South             50.941      -0.799       uksouth
UK West              53.427      -3.084       ukwest
West Central US      40.890      -110.234     westcentralus
West US 2            47.233      -119.852     westus2
Korea Central        37.5665     126.9780     koreacentral
Korea South          35.1796     129.0756     koreasouth
France Central       46.3772     2.3730       francecentral
France South         43.8345     2.1972       francesouth
Australia Central    -35.3075    149.1244     australiacentral
Australia Central 2  -35.3075    149.1244     australiacentral2

Once a location has been chosen, create the account

az storage account create --verbose \
    --name abfswales1 \
    --resource-group devteam2 \
    --kind StorageV2 \
    --hierarchical-namespace true \
    --location ukwest \
    --sku Standard_LRS \
    --https-only true \
    --encryption-services blob \
    --access-tier Hot \
    --tags owner=engineering \
    --assign-identity \
    --output jsonc

The output of the command is a JSON file, whose primaryEndpoints command includes the name of the store endpoint:

{
  "primaryEndpoints": {
    "blob": "https://abfswales1.blob.core.windows.net/",
    "dfs": "https://abfswales1.dfs.core.windows.net/",
    "file": "https://abfswales1.file.core.windows.net/",
    "queue": "https://abfswales1.queue.core.windows.net/",
    "table": "https://abfswales1.table.core.windows.net/",
    "web": "https://abfswales1.z35.web.core.windows.net/"
  }
}

The abfswales1.dfs.core.windows.net account is the name by which the storage account will be referred to.

Now ask for the connection string to the store, which contains the account key

az storage account  show-connection-string --name abfswales1
{
  "connectionString": "DefaultEndpointsProtocol=https;EndpointSuffix=core.windows.net;AccountName=abfswales1;AccountKey=ZGlkIHlvdSByZWFsbHkgdGhpbmsgSSB3YXMgZ29pbmcgdG8gcHV0IGEga2V5IGluIGhlcmU/IA=="
}

You then need to add the access key to your core-site.xml, JCEKs file or use your cluster management tool to set it the option fs.azure.account.key.STORAGE-ACCOUNT to this value.

<property>
  <name>fs.azure.account.key.abfswales1.dfs.core.windows.net</name>
  <value>ZGlkIHlvdSByZWFsbHkgdGhpbmsgSSB3YXMgZ29pbmcgdG8gcHV0IGEga2V5IGluIGhlcmU/IA==</value>
</property>

Creation through the Azure Portal

Creation through the portal is covered in Quickstart: Create an Azure Data Lake Storage Gen2 storage account

Key Steps

  1. Create a new Storage Account in a location which suits you.
  2. “Basics” Tab: select “StorageV2”.
  3. “Advanced” Tab: enable “Hierarchical Namespace”.

You have now created your storage account. Next, get the key for authentication for using the default “Shared Key” authentication.

  1. Go to the Azure Portal.
  2. Select “Storage Accounts”
  3. Select the newly created storage account.
  4. In the list of settings, locate “Access Keys” and select that.
  5. Copy one of the access keys to the clipboard, add to the XML option, set in cluster management tools, Hadoop JCEKS file or KMS store.

Creating a new container

An Azure storage account can have multiple containers, each with the container name as the userinfo field of the URI used to reference it.

For example, the container “container1” in the storage account just created will have the URL abfs://container1@abfswales1.dfs.core.windows.net/

You can create a new container through the ABFS connector, by setting the option fs.azure.createRemoteFileSystemDuringInitialization to true. Though the same is not supported when AuthType is SAS.

If the container does not exist, an attempt to list it with hadoop fs -ls will fail

$ hadoop fs -ls abfs://container1@abfswales1.dfs.core.windows.net/

ls: `abfs://container1@abfswales1.dfs.core.windows.net/': No such file or directory

Enable remote FS creation and the second attempt succeeds, creating the container as it does so:

$ hadoop fs -D fs.azure.createRemoteFileSystemDuringInitialization=true \
 -ls abfs://container1@abfswales1.dfs.core.windows.net/

This is useful for creating accounts on the command line, especially before the az storage command supports hierarchical namespaces completely.

Listing and examining containers of a Storage Account.

You can use the Azure Storage Explorer

Configuring ABFS

Any configuration can be specified generally (or as the default when accessing all accounts) or can be tied to a specific account. For example, an OAuth identity can be configured for use regardless of which account is accessed with the property fs.azure.account.oauth2.client.id or you can configure an identity to be used only for a specific storage account with fs.azure.account.oauth2.client.id.<account_name>.dfs.core.windows.net.

This is shown in the Authentication section.

Authentication

Authentication for ABFS is ultimately granted by Azure Active Directory.

The concepts covered there are beyond the scope of this document to cover; developers are expected to have read and understood the concepts therein to take advantage of the different authentication mechanisms.

What is covered here, briefly, is how to configure the ABFS client to authenticate in different deployment situations.

The ABFS client can be deployed in different ways, with its authentication needs driven by them.

  1. With the storage account’s authentication secret in the configuration: “Shared Key”.
  2. Using OAuth 2.0 tokens of one form or another.
  3. Deployed in-Azure with the Azure VMs providing OAuth 2.0 tokens to the application, “Managed Instance”.
  4. Using Shared Access Signature (SAS) tokens provided by a custom implementation of the SASTokenProvider interface.
  5. By directly configuring a fixed Shared Access Signature (SAS) token in the account configuration settings files.

Note: SAS Based Authentication should be used only with HNS Enabled accounts.

What can be changed is what secrets/credentials are used to authenticate the caller.

The authentication mechanism is set in fs.azure.account.auth.type (or the account specific variant). The possible values are SharedKey, OAuth, Custom and SAS. For the various OAuth options use the config fs.azure.account.oauth.provider.type. Following are the implementations supported ClientCredsTokenProvider, UserPasswordTokenProvider, MsiTokenProvider, RefreshTokenBasedTokenProvider and WorkloadIdentityTokenProvider. An IllegalArgumentException is thrown if the specified provider type is not one of the supported.

All secrets can be stored in JCEKS files. These are encrypted and password protected —use them or a compatible Hadoop Key Management Store wherever possible

AAD Token fetch retries

The exponential retry policy used for the AAD token fetch retries can be tuned with the following configurations. * fs.azure.oauth.token.fetch.retry.max.retries: Sets the maximum number of retries. Default value is 5. * fs.azure.oauth.token.fetch.retry.min.backoff.interval: Minimum back-off interval. Added to the retry interval computed from delta backoff. By default this is set as 0. Set the interval in milli seconds. * fs.azure.oauth.token.fetch.retry.max.backoff.interval: Maximum back-off interval. Default value is 60000 (sixty seconds). Set the interval in milli seconds. * fs.azure.oauth.token.fetch.retry.delta.backoff: Back-off interval between retries. Multiples of this timespan are used for subsequent retry attempts . The default value is 2.

Default: Shared Key

This is the simplest authentication mechanism of account + password.

The account name is inferred from the URL; the password, “key”, retrieved from the XML/JCECKs configuration files.

<property>
  <name>fs.azure.account.auth.type.ACCOUNT_NAME.dfs.core.windows.net</name>
  <value>SharedKey</value>
  <description>
  </description>
</property>
<property>
  <name>fs.azure.account.key.ACCOUNT_NAME.dfs.core.windows.net</name>
  <value>ACCOUNT_KEY</value>
  <description>
  The secret password. Never share these.
  </description>
</property>

Note: The source of the account key can be changed through a custom key provider; one exists to execute a shell script to retrieve it.

A custom key provider class can be provided with the config fs.azure.account.keyprovider. If a key provider class is specified the same will be used to get account key. Otherwise the Simple key provider will be used which will use the key specified for the config fs.azure.account.key.

To retrieve using shell script, specify the path to the script for the config fs.azure.shellkeyprovider.script. ShellDecryptionKeyProvider class use the script specified to retrieve the key.

OAuth 2.0 Client Credentials

OAuth 2.0 credentials of (client id, client secret, endpoint) are provided in the configuration/JCEKS file.

The specifics of this process is covered in hadoop-azure-datalake; the key names are slightly different here.

<property>
  <name>fs.azure.account.auth.type</name>
  <value>OAuth</value>
  <description>
  Use OAuth authentication
  </description>
</property>
<property>
  <name>fs.azure.account.oauth.provider.type</name>
  <value>org.apache.hadoop.fs.azurebfs.oauth2.ClientCredsTokenProvider</value>
  <description>
  Use client credentials
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.client.endpoint</name>
  <value></value>
  <description>
  URL of OAuth endpoint
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.client.id</name>
  <value></value>
  <description>
  Client ID
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.client.secret</name>
  <value></value>
  <description>
  Secret
  </description>
</property>

OAuth 2.0: Username and Password

An OAuth 2.0 endpoint, username and password are provided in the configuration/JCEKS file.

<property>
  <name>fs.azure.account.auth.type</name>
  <value>OAuth</value>
  <description>
  Use OAuth authentication
  </description>
</property>
<property>
  <name>fs.azure.account.oauth.provider.type</name>
  <value>org.apache.hadoop.fs.azurebfs.oauth2.UserPasswordTokenProvider</value>
  <description>
  Use user and password
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.client.endpoint</name>
  <value></value>
  <description>
  URL of OAuth 2.0 endpoint
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.user.name</name>
  <value></value>
  <description>
  username
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.user.password</name>
  <value></value>
  <description>
  password for account
  </description>
</property>

OAuth 2.0: Refresh Token

With an existing Oauth 2.0 token, make a request of the Active Directory endpoint https://login.microsoftonline.com/Common/oauth2/token for this token to be refreshed.

<property>
  <name>fs.azure.account.auth.type</name>
  <value>OAuth</value>
  <description>
  Use OAuth 2.0 authentication
  </description>
</property>
<property>
  <name>fs.azure.account.oauth.provider.type</name>
  <value>org.apache.hadoop.fs.azurebfs.oauth2.RefreshTokenBasedTokenProvider</value>
  <description>
  Use the Refresh Token Provider
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.refresh.token</name>
  <value></value>
  <description>
  Refresh token
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.refresh.endpoint</name>
  <value></value>
  <description>
  Refresh token endpoint
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.client.id</name>
  <value></value>
  <description>
  Optional Client ID
  </description>
</property>

Azure Managed Identity

Azure Managed Identities, formerly “Managed Service Identities”.

OAuth 2.0 tokens are issued by a special endpoint only accessible from the executing VM (http://169.254.169.254/metadata/identity/oauth2/token). The issued credentials can be used to authenticate.

The Azure Portal/CLI is used to create the service identity.

<property>
  <name>fs.azure.account.auth.type</name>
  <value>OAuth</value>
  <description>
  Use OAuth authentication
  </description>
</property>
<property>
  <name>fs.azure.account.oauth.provider.type</name>
  <value>org.apache.hadoop.fs.azurebfs.oauth2.MsiTokenProvider</value>
  <description>
  Use MSI for issuing OAuth tokens
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.msi.tenant</name>
  <value></value>
  <description>
  Optional MSI Tenant ID
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.msi.endpoint</name>
  <value></value>
  <description>
   MSI endpoint
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.client.id</name>
  <value></value>
  <description>
  Optional Client ID
  </description>
</property>

Azure Workload Identity

Azure Workload Identities, formerly “Azure AD pod identity”.

OAuth 2.0 tokens are written to a file that is only accessible from the executing pod (/var/run/secrets/azure/tokens/azure-identity-token). The issued credentials can be used to authenticate.

The Azure Portal/CLI is used to create the service identity.

<property>
  <name>fs.azure.account.auth.type</name>
  <value>OAuth</value>
  <description>
  Use OAuth authentication
  </description>
</property>
<property>
  <name>fs.azure.account.oauth.provider.type</name>
  <value>org.apache.hadoop.fs.azurebfs.oauth2.WorkloadIdentityTokenProvider</value>
  <description>
  Use Workload Identity for issuing OAuth tokens
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.msi.tenant</name>
  <value>${env.AZURE_TENANT_ID}</value>
  <description>
  Optional MSI Tenant ID
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.client.id</name>
  <value>${env.AZURE_CLIENT_ID}</value>
  <description>
  Optional Client ID
  </description>
</property>
<property>
  <name>fs.azure.account.oauth2.token.file</name>
  <value>${env.AZURE_FEDERATED_TOKEN_FILE}</value>
  <description>
  Token file path
  </description>
</property>

Custom OAuth 2.0 Token Provider

A Custom OAuth 2.0 token provider supplies the ABFS connector with an OAuth 2.0 token when its getAccessToken() method is invoked.

<property>
  <name>fs.azure.account.auth.type</name>
  <value>Custom</value>
  <description>
  Custom Authentication
  </description>
</property>
<property>
  <name>fs.azure.account.oauth.provider.type</name>
  <value></value>
  <description>
  classname of Custom Authentication Provider
  </description>
</property>

The declared class must implement org.apache.hadoop.fs.azurebfs.extensions.CustomTokenProviderAdaptee and optionally org.apache.hadoop.fs.azurebfs.extensions.BoundDTExtension.

The declared class also holds responsibility to implement retry logic while fetching access tokens.

Delegation Token Provider

A delegation token provider supplies the ABFS connector with delegation tokens, helps renew and cancel the tokens by implementing the CustomDelegationTokenManager interface.

<property>
  <name>fs.azure.enable.delegation.token</name>
  <value>true</value>
  <description>Make this true to use delegation token provider</description>
</property>
<property>
  <name>fs.azure.delegation.token.provider.type</name>
  <value>{fully-qualified-class-name-for-implementation-of-CustomDelegationTokenManager-interface}</value>
</property>

In case delegation token is enabled, and the config fs.azure.delegation.token .provider.type is not provided then an IlleagalArgumentException is thrown.

Shared Access Signature (SAS) Token Provider

A shared access signature (SAS) provides secure delegated access to resources in your storage account. With a SAS, you have granular control over how a client can access your data. To know more about how SAS Authentication works refer to Grant limited access to Azure Storage resources using shared access signatures (SAS)

There are three types of SAS supported by Azure Storage: - User Delegation SAS: Recommended for use with ABFS Driver with HNS Enabled ADLS Gen2 accounts. It is Identity based SAS that works at blob/directory level) - Service SAS: Global and works at container level. - Account SAS: Global and works at account level.

Known Issues With SAS

  • SAS Based Authentication works only with HNS Enabled ADLS Gen2 Accounts which is a recommended account type to be used with ABFS.
  • Certain root level operations are known to fail with SAS Based Authentication.

Using User Delegation SAS with ABFS

  • Description: ABFS allows you to implement your custom SAS Token Provider that uses your identity to create a user delegation key which then can be used to create SAS instead of storage account key. The declared class must implement org.apache.hadoop.fs.azurebfs.extensions.SASTokenProvider.

  • Configuration: To use this method with ABFS Driver, specify the following properties in your core-site.xml file:

    1. Authentication Type:

      <property>
        <name>fs.azure.account.auth.type</name>
        <value>SAS</value>
      </property>
      
    2. Custom SAS Token Provider Class:

      <property>
        <name>fs.azure.sas.token.provider.type</name>
        <value>CUSTOM_SAS_TOKEN_PROVIDER_CLASS</value>
      </property>
      

    Replace CUSTOM_SAS_TOKEN_PROVIDER_CLASS with fully qualified class name of your custom token provider implementation. Depending upon the implementation you might need to specify additional configurations that are required by your custom implementation.

  • Example: ABFS Hadoop Driver provides a MockDelegationSASTokenProvider implementation that can be used as an example on how to implement your own custom SASTokenProvider. This requires the Application credentials to be specifed using the following configurations apart from above two:

    1. App Service Principle Tenant Id:
      <property>
        <name>fs.azure.test.app.service.principal.tenant.id</name>
        <value>TENANT_ID</value>
      </property>
      
    2. App Service Principle Object Id:
      <property>
        <name>fs.azure.test.app.service.principal.object.id</name>
        <value>OBJECT_ID</value>
      </property>
      
    3. App Id:
      <property>
        <name>fs.azure.test.app.id</name>
        <value>APPLICATION_ID</value>
      </property>
      
    4. App Secret:
      <property>
        <name>fs.azure.test.app.secret</name>
        <value>APPLICATION_SECRET</value>
      </property>
      
  • Security: More secure than Shared Key and allows granting limited access to data without exposing the access key. Recommended to be used only with HNS Enabled, ADLS Gen 2 storage accounts.

Using Account/Service SAS with ABFS

  • Description: ABFS allows user to use Account/Service SAS for authenticating requests. User can specify them as fixed SAS Token to be used across all the requests.

  • Configuration: To use this method with ABFS Driver, specify the following properties in your core-site.xml file:

    1. Authentication Type:

      <property>
        <name>fs.azure.account.auth.type</name>
        <value>SAS</value>
      </property>
      
    2. Fixed SAS Token:

      <property>
        <name>fs.azure.sas.fixed.token</name>
        <value>FIXED_SAS_TOKEN</value>
      </property>
      

    Replace FIXED_SAS_TOKEN with fixed Account/Service SAS. You can also generate SAS from Azure portal. Account -> Security + Networking -> Shared Access Signature

  • Security: Account/Service SAS requires account keys to be used which makes them less secure. There is no scope of having delegated access to different users.

Note: When fs.azure.sas.token.provider.type and fs.azure.fixed.sas.token are both configured, precedence will be given to the custom token provider implementation.

Technical notes

Proxy setup

The connector uses the JVM proxy settings to control its proxy setup.

See The Oracle Java documentation for the options to set.

As the connector uses HTTPS by default, the https.proxyHost and https.proxyPort options are those which must be configured.

In MapReduce jobs, including distcp, the proxy options must be set in both the mapreduce.map.java.opts and mapreduce.reduce.java.opts.

# this variable is only here to avoid typing the same values twice.
# It's name is not important.
export DISTCP_PROXY_OPTS="-Dhttps.proxyHost=web-proxy.example.com -Dhttps.proxyPort=80"

hadoop distcp \
  -D mapreduce.map.java.opts="$DISTCP_PROXY_OPTS" \
  -D mapreduce.reduce.java.opts="$DISTCP_PROXY_OPTS" \
  -update -skipcrccheck -numListstatusThreads 40 \
  hdfs://namenode:8020/users/alice abfs://backups@account.dfs.core.windows.net/users/alice

Without these settings, even though access to ADLS may work from the command line, distcp access can fail with network errors.

Security

As with other object stores, login secrets are valuable pieces of information. Organizations should have a process for safely sharing them.

Limitations of the ABFS connector

  • File last access time is not tracked.
  • Extended attributes are not supported.
  • File Checksums are not supported.
  • The Syncable interfaces hsync() and hflush() operations are supported if fs.azure.enable.flush is set to true (default=true). With the Wasb connector, this limited the number of times either call could be made to 50,000 HADOOP-15478. If abfs has the a similar limit, then excessive use of sync/flush may cause problems.

Consistency and Concurrency

As with all Azure storage services, the Azure Datalake Gen 2 store offers a fully consistent view of the store, with complete Create, Read, Update, and Delete consistency for data and metadata.

Performance and Scalability

For containers with hierarchical namespaces, the scalability numbers are, in Big-O-notation, as follows:

Operation Scalability
File Rename O(1)
File Delete O(1)
Directory Rename: O(1)
Directory Delete O(1)

For non-namespace stores, the scalability becomes:

Operation Scalability
File Rename O(1)
File Delete O(1)
Directory Rename: O(files)
Directory Delete O(files)

That is: the more files there are, the slower directory operations get.

Further reading: Azure Storage Scalability Targets

Extensibility

The ABFS connector supports a number of limited-private/unstable extension points for third-parties to integrate their authentication and authorization services into the ABFS client.

  • CustomDelegationTokenManager : adds ability to issue Hadoop Delegation Tokens.
  • SASTokenProvider: allows for custom provision of Azure Storage Shared Access Signature (SAS) tokens.
  • CustomTokenProviderAdaptee: allows for custom provision of Azure OAuth tokens.
  • KeyProvider.

Consult the source in org.apache.hadoop.fs.azurebfs.extensions and all associated tests to see how to make use of these extension points.

Warning These extension points are unstable.

Other configuration options

Consult the javadocs for org.apache.hadoop.fs.azurebfs.constants.ConfigurationKeys, org.apache.hadoop.fs.azurebfs.constants.FileSystemConfigurations and org.apache.hadoop.fs.azurebfs.AbfsConfiguration for the full list of configuration options and their default values.

Client Correlation Options

1. Client CorrelationId Option

Config fs.azure.client.correlationid provides an option to correlate client requests using this client-provided identifier. This Id will be visible in Azure Storage Analytics logs in the request-id-header field. Reference: Storage Analytics log format

This config accepts a string which can be maximum of 72 characters and should contain alphanumeric characters and/or hyphens only. Defaults to empty string if input is invalid.

1. Correlation IDs Display Options

Config fs.azure.tracingcontext.format provides an option to select the format of IDs included in the request-id-header. This config accepts a String value corresponding to the following enum options. SINGLE_ID_FORMAT : clientRequestId ALL_ID_FORMAT : all IDs (default) TWO_ID_FORMAT : clientCorrelationId:clientRequestId

Flush Options

1. Azure Blob File System Flush Options

Config fs.azure.enable.flush provides an option to render ABFS flush APIs - HFlush() and HSync() to be no-op. By default, this config will be set to true.

Both the APIs will ensure that data is persisted.

2. OutputStream Flush Options

Config fs.azure.disable.outputstream.flush provides an option to render OutputStream Flush() API to be a no-op in AbfsOutputStream. By default, this config will be set to true.

Hflush() being the only documented API that can provide persistent data transfer, Flush() also attempting to persist buffered data will lead to performance issues.

Hundred Continue Options

fs.azure.account.expect.header.enabled: This configuration parameter is used to specify whether you wish to send a expect 100 continue header with each append request or not. It is configured to true by default. This flag configures the client to check with the Azure store before uploading a block of data from an output stream. This allows the client to throttle back gracefully -before actually attempting to upload the block. In experiments this provides significant throughput improvements under heavy load. For more information : - https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/Expect

Account level throttling Options

fs.azure.account.operation.idle.timeout: This value specifies the time after which the timer for the analyzer (read or write) should be paused until no new request is made again. The default value for the same is 60 seconds.

HNS Check Options

Config fs.azure.account.hns.enabled provides an option to specify whether the storage account is HNS enabled or not. In case the config is not provided, a server call is made to check the same.

Access Options

Config fs.azure.enable.check.access needs to be set true to enable the AzureBlobFileSystem.access().

Operation Idempotency

Requests failing due to server timeouts and network failures will be retried. PUT/POST operations are idempotent and need no specific handling except for Rename and Delete operations.

Rename idempotency checks are made by ensuring the LastModifiedTime on destination is recent if source path is found to be non-existent on retry.

Delete is considered to be idempotent by default if the target does not exist on retry.

Primary User Group Options

The group name which is part of FileStatus and AclStatus will be set the same as the username if the following config is set to true fs.azure.skipUserGroupMetadataDuringInitialization.

IO Options

The following configs are related to read and write operations.

fs.azure.io.retry.max.retries: Sets the number of retries for IO operations. Currently this is used only for the server call retry logic. Used within AbfsClient class as part of the ExponentialRetryPolicy. The value should be greater than or equal to 0.

fs.azure.io.retry.min.backoff.interval: Sets the minimum backoff interval for retries of IO operations. Currently this is used only for the server call retry logic. Used within AbfsClient class as part of the ExponentialRetryPolicy. This value indicates the smallest interval (in milliseconds) to wait before retrying an IO operation. The default value is 3000 (3 seconds).

fs.azure.io.retry.max.backoff.interval: Sets the maximum backoff interval for retries of IO operations. Currently this is used only for the server call retry logic. Used within AbfsClient class as part of the ExponentialRetryPolicy. This value indicates the largest interval (in milliseconds) to wait before retrying an IO operation. The default value is 30000 (30 seconds).

fs.azure.io.retry.backoff.interval: Sets the default backoff interval for retries of IO operations. Currently this is used only for the server call retry logic. Used within AbfsClient class as part of the ExponentialRetryPolicy. This value is used to compute a random delta between 80% and 120% of the specified value. This random delta is then multiplied by an exponent of the current IO retry number (i.e., the default is multiplied by 2^(retryNum - 1)) and then contstrained within the range of [fs.azure.io.retry.min.backoff.interval, fs.azure.io.retry.max.backoff.interval] to determine the amount of time to wait before the next IO retry attempt. The default value is 3000 (3 seconds).

fs.azure.write.request.size: To set the write buffer size. Specify the value in bytes. The value should be between 16384 to 104857600 both inclusive (16 KB to 100 MB). The default value will be 8388608 (8 MB).

fs.azure.read.request.size: To set the read buffer size.Specify the value in bytes. The value should be between 16384 to 104857600 both inclusive (16 KB to 100 MB). The default value will be 4194304 (4 MB).

fs.azure.read.alwaysReadBufferSize: Read request size configured by fs.azure.read.request.size will be honoured only when the reads done are in sequential pattern. When the read pattern is detected to be random, read size will be same as the buffer length provided by the calling process. This config when set to true will force random reads to also read in same request sizes as sequential reads. This is a means to have same read patterns as of ADLS Gen1, as it does not differentiate read patterns and always reads by the configured read request size. The default value for this config will be false, where reads for the provided buffer length is done when random read pattern is detected.

fs.azure.readaheadqueue.depth: Sets the readahead queue depth in AbfsInputStream. In case the set value is negative the read ahead queue depth will be set as Runtime.getRuntime().availableProcessors(). By default the value will be 2. To disable readaheads, set this value to 0. If your workload is doing only random reads (non-sequential) or you are seeing throttling, you may try setting this value to 0.

fs.azure.read.readahead.blocksize: To set the read buffer size for the read aheads. Specify the value in bytes. The value should be between 16384 to 104857600 both inclusive (16 KB to 100 MB). The default value will be 4194304 (4 MB).

fs.azure.buffered.pread.disable: By default the positional read API will do a seek and read on input stream. This read will fill the buffer cache in AbfsInputStream and update the cursor positions. If this optimization is true it will skip usage of buffer and do a lock free REST call for reading from blob. This optimization is very much helpful for HBase kind of short random read over a shared AbfsInputStream instance. Note: This is not a config which can be set at cluster level. It can be used as an option on FutureDataInputStreamBuilder. See FileSystem#openFile(Path path)

To run under limited memory situations configure the following. Especially when there are too many writes from the same process.

fs.azure.write.max.concurrent.requests: To set the maximum concurrent write requests from an AbfsOutputStream instance to server at any point of time. Effectively this will be the threadpool size within the AbfsOutputStream instance. Set the value in between 1 to 8 both inclusive.

fs.azure.write.max.requests.to.queue: To set the maximum write requests that can be queued. Memory consumption of AbfsOutputStream instance can be tuned with this config considering each queued request holds a buffer. Set the value 3 or 4 times the value set for s.azure.write.max.concurrent.requests.

fs.azure.analysis.period: The time after which sleep duration is recomputed after analyzing metrics. The default value for the same is 10 seconds.

Security Options

fs.azure.always.use.https: Enforces to use HTTPS instead of HTTP when the flag is made true. Irrespective of the flag, AbfsClient will use HTTPS if the secure scheme (ABFSS) is used or OAuth is used for authentication. By default this will be set to true.

fs.azure.ssl.channel.mode: Initializing DelegatingSSLSocketFactory with the specified SSL channel mode. Value should be of the enum DelegatingSSLSocketFactory.SSLChannelMode. The default value will be DelegatingSSLSocketFactory.SSLChannelMode.Default.

Encryption Options

Only one of the following two options can be configured. If config values of both types are set, ABFS driver will throw an exception. If using the global key type, ensure both pre-computed values are provided.

Customer-Provided Global Key

A global encryption key can be configured by providing the following pre-computed values. The key will be applied to any new files created post setting the configuration, and will be required in the requests to read ro modify the contents of the files.

fs.azure.encryption.encoded.client-provided-key: The Base64 encoded version of the 256-bit encryption key.

fs.azure.encryption.encoded.client-provided-key-sha: The Base64 encoded version of the SHA256 has of the 256-bit encryption key.

Encryption Context Provider

ABFS driver supports an interface called EncryptionContextProvider that can be used as a plugin for clients to provide custom implementations for the encryption framework. This framework allows for an encryptionContext and an encryptionKey to be generated by the EncryptionContextProvider for a file to be created. The server keeps track of the encryptionContext for each file. To perform subsequent operations such as read on the encrypted file, ABFS driver will fetch the corresponding encryption key from the EncryptionContextProvider implementation by providing the encryptionContext string retrieved from a GetFileStatus request to the server.

fs.azure.encryption.context.provider.type: The canonical name of the class implementing EncryptionContextProvider.

Server Options

fs.azure.io.read.tolerate.concurrent.append: When the config is made true, the If-Match header sent to the server for read calls will be set as * otherwise the same will be set with ETag. This is basically a mechanism in place to handle the reads with optimistic concurrency. Please refer the following links for further information. 1. https://docs.microsoft.com/en-us/rest/api/storageservices/datalakestoragegen2/path/read 2. https://azure.microsoft.com/de-de/blog/managing-concurrency-in-microsoft-azure-storage-2/

fs.azure.list.max.results: listStatus API fetches the FileStatus information from server in a page by page manner. The config is used to set the maxResults URI param which sets the page size(maximum results per call). The value should be > 0. By default, this will be 5000. Server has a maximum value for this parameter as 5000. So even if the config is above 5000 the response will only contain 5000 entries. Please refer the following link for further information. https://docs.microsoft.com/en-us/rest/api/storageservices/datalakestoragegen2/path/list

fs.azure.enable.checksum.validation: When the config is set to true, Content-MD5 headers are sent to the server for read and append calls. This provides a way to verify the integrity of data during transport. This will have performance impact due to MD5 Hash re-computation on Client and Server side. Please refer to the Azure documentation for Read and Append APIs for more details

Throttling Options

ABFS driver has the capability to throttle read and write operations to achieve maximum throughput by minimizing errors. The errors occur when the account ingress or egress limits are exceeded and, the server-side throttles requests. Server-side throttling causes the retry policy to be used, but the retry policy sleeps for long periods of time causing the total ingress or egress throughput to be as much as 35% lower than optimal. The retry policy is also after the fact, in that it applies after a request fails. On the other hand, the client-side throttling implemented here happens before requests are made and sleeps just enough to minimize errors, allowing optimal ingress and/or egress throughput. By default the throttling mechanism is enabled in the driver. The same can be disabled by setting the config fs.azure.enable.autothrottling to false.

Rename Options

fs.azure.atomic.rename.key: Directories for atomic rename support can be specified comma separated in this config. The driver prints the following warning log if the source of the rename belongs to one of the configured directories. “The atomic rename feature is not supported by the ABFS scheme ; however, rename, create and delete operations are atomic if Namespace is enabled for your Azure Storage account.” The directories can be specified as comma separated values. By default the value is “/hbase”

Infinite Lease Options

fs.azure.infinite-lease.directories: Directories for infinite lease support can be specified comma separated in this config. By default, multiple clients will be able to write to the same file simultaneously. When writing to files contained within the directories specified in this config, the client will obtain a lease on the file that will prevent any other clients from writing to the file. When the output stream is closed, the lease will be released. To revoke a client’s write access for a file, the AzureBlobFilesystem breakLease method may be called. If the client dies before the file can be closed and the lease released, breakLease will need to be called before another client will be able to write to the file.

fs.azure.lease.threads: This is the size of the thread pool that will be used for lease operations for infinite lease directories. By default the value is 0, so it must be set to at least 1 to support infinite lease directories.

Perf Options

1. HTTP Request Tracking Options

If you set fs.azure.abfs.latency.track to true, the module starts tracking the performance metrics of ABFS HTTP traffic. To obtain these numbers on your machine or cluster, you will also need to enable debug logging for the AbfsPerfTracker class in your log4j config. A typical perf log line appears like:

h=KARMA t=2019-10-25T20:21:14.518Z a=abfstest01.dfs.core.windows.net
c=abfs-testcontainer-84828169-6488-4a62-a875-1e674275a29f cr=delete ce=deletePath
r=Succeeded l=32 ls=32 lc=1 s=200 e= ci=95121dae-70a8-4187-b067-614091034558
ri=97effdcf-201f-0097-2d71-8bae00000000 ct=0 st=0 rt=0 bs=0 br=0 m=DELETE
u=https%3A%2F%2Fabfstest01.dfs.core.windows.net%2Ftestcontainer%2Ftest%3Ftimeout%3D90%26recursive%3Dtrue

The fields have the following definitions:

h: host name t: time when this request was logged a: Azure storage account name c: container name cr: name of the caller method ce: name of the callee method r: result (Succeeded/Failed) l: latency (time spent in callee) ls: latency sum (aggregate time spent in caller; logged when there are multiple callees; logged with the last callee) lc: latency count (number of callees; logged when there are multiple callees; logged with the last callee) s: HTTP Status code e: Error code ci: client request ID ri: server request ID ct: connection time in milliseconds st: sending time in milliseconds rt: receiving time in milliseconds bs: bytes sent br: bytes received m: HTTP method (GET, PUT etc) u: Encoded HTTP URL

Note that these performance numbers are also sent back to the ADLS Gen 2 API endpoints in the x-ms-abfs-client-latency HTTP headers in subsequent requests. Azure uses these settings to track their end-to-end latency.

Driver Metric Options

Config fs.azure.metric.format provides an option to select the format of IDs included in the header for metrics. This config accepts a String value corresponding to the following enum options. INTERNAL_METRIC_FORMAT : backoff + footer metrics INTERNAL_BACKOFF_METRIC_FORMAT : backoff metrics INTERNAL_FOOTER_METRIC_FORMAT : footer metrics EMPTY : default

fs.azure.metric.account.name: This configuration parameter is used to specify the name of the account which will be used to push the metrics to the backend. We can configure a separate account to push metrics to the store or use the same for as the existing account on which other requests are made.

<property>
    <name>fs.azure.metric.account.name</name>
    <value>METRICACCOUNTNAME.dfs.core.windows.net</value>
</property>

fs.azure.metric.account.key: This is the access key for the storage account used for pushing metrics to the store.

<property>
    <name>fs.azure.metric.account.key</name>
    <value>ACCOUNTKEY</value>
</property>

fs.azure.metric.uri: This configuration provides the uri in the format of ‘https://<accountname> .dfs.core.windows.net/<containername>’. This should be a part of the config in order to prevent extra calls to create the filesystem. We use an existing filsystem to push the metrics.

<property>
    <name>fs.azure.metric.uri</name>
    <value>https://METRICACCOUNTNAME.dfs.core.windows.net/CONTAINERNAME</value>
</property>

Troubleshooting

The problems associated with the connector usually come down to, in order

  1. Classpath.
  2. Network setup (proxy etc.).
  3. Authentication and Authorization.
  4. Anything else.

If you log org.apache.hadoop.fs.azurebfs.services at DEBUG then you will see more details about any request which is failing.

One useful tool for debugging connectivity is the cloudstore storediag utility.

This validates the classpath, the settings, then tries to work with the filesystem.

bin/hadoop jar cloudstore-0.1-SNAPSHOT.jar storediag abfs://container@account.dfs.core.windows.net/
  1. If the storediag command cannot work with an abfs store, nothing else is likely to.
  2. If the storediag store does successfully work, that does not guarantee that the classpath or configuration on the rest of the cluster is also going to work, especially in distributed applications. But it is at least a start.

ClassNotFoundException: org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem

The hadoop-azure JAR is not on the classpah.

java.lang.RuntimeException: java.lang.ClassNotFoundException:
    Class org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem not found
  at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2625)
  at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:3290)
  at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3322)
  at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:136)
  at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3373)
  at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3341)
  at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:491)
  at org.apache.hadoop.fs.Path.getFileSystem(Path.java:361)
Caused by: java.lang.ClassNotFoundException:
    Class org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem not found
  at org.apache.hadoop.conf.Configuration.getClassByName(Configuration.java:2529)
  at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2623)
  ... 16 more

Tip: if this is happening on the command line, you can turn on debug logging of the hadoop scripts:

export HADOOP_SHELL_SCRIPT_DEBUG=true

If this is happening on an application running within the cluster, it means the cluster (somehow) needs to be configured so that the hadoop-azure module and dependencies are on the classpath of deployed applications.

ClassNotFoundException: com.microsoft.azure.storage.StorageErrorCode

The azure-storage JAR is not on the classpath.

Server failed to authenticate the request

The request wasn’t authenticated while using the default shared-key authentication mechanism.

Operation failed: "Server failed to authenticate the request.
 Make sure the value of Authorization header is formed correctly including the signature.",
 403, HEAD, https://account.dfs.core.windows.net/container2?resource=filesystem&timeout=90
  at org.apache.hadoop.fs.azurebfs.services.AbfsRestOperation.execute(AbfsRestOperation.java:135)
  at org.apache.hadoop.fs.azurebfs.services.AbfsClient.getFilesystemProperties(AbfsClient.java:209)
  at org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.getFilesystemProperties(AzureBlobFileSystemStore.java:259)
  at org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.fileSystemExists(AzureBlobFileSystem.java:859)
  at org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.initialize(AzureBlobFileSystem.java:110)

Causes include:

  • Your credentials are incorrect.
  • Your shared secret has expired. in Azure, this happens automatically
  • Your shared secret has been revoked.
  • host/VM clock drift means that your client’s clock is out of sync with the Azure servers —the call is being rejected as it is either out of date (considered a replay) or from the future. Fix: Check your clocks, etc.

Configuration property _something_.dfs.core.windows.net not found

There’s no fs.azure.account.key. entry in your cluster configuration declaring the access key for the specific account, or you are using the wrong URL

$ hadoop fs -ls abfs://container@abfswales2.dfs.core.windows.net/

ls: Configuration property abfswales2.dfs.core.windows.net not found.
  • Make sure that the URL is correct
  • Add the missing account key.

No such file or directory when trying to list a container

There is no container of the given name. Either it has been mistyped or the container needs to be created.

$ hadoop fs -ls abfs://container@abfswales1.dfs.core.windows.net/

ls: `abfs://container@abfswales1.dfs.core.windows.net/': No such file or directory
  • Make sure that the URL is correct
  • Create the container if needed

“HTTP connection to https://login.microsoftonline.com/something failed for getting token from AzureAD. Http response: 200 OK”

  • it has a content-type text/html, text/plain, application/xml

The OAuth authentication page didn’t fail with an HTTP error code, but it didn’t return JSON either

$ bin/hadoop fs -ls abfs://container@abfswales1.dfs.core.windows.net/

 ...

ls: HTTP Error 200;
  url='https://login.microsoftonline.com/02a07549-0a5f-4c91-9d76-53d172a638a2/oauth2/authorize'
  AADToken: HTTP connection to
  https://login.microsoftonline.com/02a07549-0a5f-4c91-9d76-53d172a638a2/oauth2/authorize
  failed for getting token from AzureAD.
  Unexpected response.
  Check configuration, URLs and proxy settings.
  proxies=none;
  requestId='dd9d526c-8b3d-4b3f-a193-0cf021938600';
  contentType='text/html; charset=utf-8';

Likely causes are configuration and networking:

  1. Authentication is failing, the caller is being served up the Azure Active Directory signon page for humans, even though it is a machine calling.
  2. The URL is wrong —it is pointing at a web page unrelated to OAuth2.0
  3. There’s a proxy server in the way trying to return helpful instructions.

java.io.IOException: The ownership on the staging directory /tmp/hadoop-yarn/staging/user1/.staging is not as expected. It is owned by <principal_id>. The directory must be owned by the submitter user1 or user1

When using Azure Managed Identities, the files/directories in ADLS Gen2 by default will be owned by the service principal object id i.e. principal ID & submitting jobs as the local OS user ‘user1’ results in the above exception.

The fix is to mimic the ownership to the local OS user, by adding the below properties tocore-site.xml.

<property>
  <name>fs.azure.identity.transformer.service.principal.id</name>
  <value>service principal object id</value>
  <description>
  An Azure Active Directory object ID (oid) used as the replacement for names contained
  in the list specified by “fs.azure.identity.transformer.service.principal.substitution.list”.
  Notice that instead of setting oid, you can also set $superuser here.
  </description>
</property>
<property>
  <name>fs.azure.identity.transformer.service.principal.substitution.list</name>
  <value>user1</value>
  <description>
  A comma separated list of names to be replaced with the service principal ID specified by
  “fs.azure.identity.transformer.service.principal.id”.  This substitution occurs
  when setOwner, setAcl, modifyAclEntries, or removeAclEntries are invoked with identities
  contained in the substitution list. Notice that when in non-secure cluster, asterisk symbol *
  can be used to match all user/group.
  </description>
</property>

Once the above properties are configured, hdfs dfs -ls abfs://container1@abfswales1.dfs.core.windows.net/ shows the ADLS Gen2 files/directories are now owned by ‘user1’.

Known Issues

Following failures are known and expected to fail as of now. 1. AzureBlobFileSystem.setXAttr() and AzureBlobFileSystem.getXAttr() will fail when attempted on root (“/”) path with Operation failed: "The request URI is invalid.", HTTP 400 Bad Request

Testing ABFS

See the relevant section in Testing Azure.