Hadoop Directory Browser

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Snap type



This Snap browses a given directory path in the Hadoop file system (using the HDFS protocol) and generates a list of all the files in the directory and subdirectories. Use this Snap to identify the contents of a directory before you run any command that uses this information.

As of now, the Hadoop Directory Browser only supports URIs that use the HDFS protocol.

For example, if you need to iteratively run a specific command on a list of files, this Snap can help you view the list of all available files.

  • Path (string): The path to the directory being browsed.
  • Type (string): The type of file.
  • Owner (string): The name of the owner of the file.
  • Creation date (datetime): The date the file was created. In the Hadoop file system, this can often show up as 'null' due to limited API functionality.
  • Size (in bytes) (int): The size of the file.
  • Permissions (string): Read, Write, Execute.
  • Update date (datetime): Date of update.
  • Name (string): Name of the file.

Input and Output

  • Expected upstream Snaps: Any Snap that offers a directory URI. This can be even a CSV Generator with a collection of, say file names and their URIs.
  • Expected downstream Snaps: A document listing out attributes of the files contained in the directory specified.
  • Expected input: Directory Path to be browsed and the File Filter Pattern to be applied. For example: Directory Path: hdfs://hadoopcluster.domain.com:8020/<user>/<folder_details>; File Filter: *.conf
  • Expected output: The attributes of the files contained in the directory specified that matching the filter pattern.


The user executing the Snap must have at least Read permissions on the concerned directory.

Support and limitationsWorks in Ultra Task Pipelines.

This Snap uses account references created on the Accounts page of the SnapLogic Manager to handle access to this endpoint. 

This Snap supports Azure Data Lake Gen2 OAuth2 and Kerberos accounts.

InputThis Snap has at most one optional document input view. It contains values for the directory path to be browsed and the glob filter to be applied to select the contents.
OutputThis Snap has exactly one output view that provides the various attributes (such as Name, Type, Size, Owner, Last Modification Time) of the contents of the given directory path. Only those contents are selected that match the given glob filter.
ErrorThis Snap has at most one document error view and produces zero or more documents in the view.



Required. The name for the Snap. You can modify this to be more specific, especially if you have more than one of the same Snap in your pipeline.


The URL for the data source (directory). The Snap supports both HFDS and ABFS(S) protocols.

Syntax for a typical HDFS URL:

Syntax for a typical ABFS and an ABFSS URL:

When you use the ABFS protocol to connect to an endpoint, the account name and endpoint details provided in the URL override the corresponding values in the Account Settings fields.

Default value: [None]

File filter

Required. The GLOB pattern to be applied to select the contents (files/sub-folders) of the directory. You cannot recursively navigate the directory structures.

The File filter property can be a JavaScript expression, which will be evaluated with the values from the input view document.


  • *.txt

  • ab????xx.*x

  • *.[jJ][sS][oO][nN](as of the May 29th, 2015 release)

Default value: [None]

 Glob Pattern Interpretation Rules

Use glob patterns in this filter to select one or more files in the directory. For example:

  • *.java Matches file names ending in .java.
  • *.* Matches file names containing a dot.
  • *.{java,class} Matches file names ending with .java or .class.
  • foo.? Matches file names starting with foo. and a single character extension.

The following rules are used to interpret glob patterns:

  • The * character matches zero or more characters of a name component without crossing directory boundaries.
  • The ? character matches exactly one character of a name component.
  • The backslash character (\) is used to escape characters that would otherwise be interpreted as special characters. For example, the expression \\ matches a single backslash, and "\{" matches a left brace.
  • The ! character is used to exclude matching files from the output. 
  • The [ ] characters are a bracket expression that match a single character of a name component out of a set of characters. For example, [abc] matches 'a', 'b', or 'c'. The hyphen (-) may be used to specify a range; so, [a-z] specifies a range that matches from 'a' to 'z' (inclusive). These forms can be mixed; so, [abce-g] matches 'a'", 'b', 'c', 'e', 'f' or 'g'. If the character after the '[' is an '!', then it is used for negation; so, [!a-c] matches any character except 'a', 'b', or 'c'.
  • Within a bracket expression, the *, ?, and \ characters match themselves. The (-) character matches itself if it is the first character within the brackets, or the first character after the '!', if negating.
  • The { } characters are a group of subpatterns, where the group matches if any subpattern in the group matches. The ',' character is used to separate subpatterns. Groups cannot be nested.
  • Leading period / dot characters in file names are treated as regular characters in match operations. For example, the '*' glob pattern matches file name '.login'.
  • Some special characters are not supported. A partial list of unsupported special characters: #, ^, â, ê, î, ç, ¿, SPACE.

User Impersonation

Select this check box to enable user impersonation. For more information on working with user impersonation, click the link below.

Select this check box to enable user impersonation.

For encryption zones, use user impersonation. 

Default value:  Not selected

For more information on working with user impersonation, click the link below.

 User Impersonation Details

Generic User Impersonation Behavior

When the User Impersonation check box is selected, and Kerberos is the account type, the Client Principal configured in the Kerberos account impersonates the pipeline user.

When the User Impersonation option is selected, and Kerberos is not the account type, the user executing the pipeline is impersonated to perform HDFS Operations. For example, if the user logged into the SnapLogic platform is operator@snaplogic.com, the user name "operator" is used to proxy the super user. 

User impersonation behavior on pipelines running on Groundplex with a Kerberos account configured in the Snap

  • When the User Impersonation checkbox is selected in the Snap, it is the pipeline user who performs the file operation. For example, if the user logged into the SnapLogic platform is operator@snaplogic.com, the user name "operator" is used to proxy the super user.
  • When the User Impersonation checkbox is not selected in the Snap, the Client Principal configured in the Kerberos account performs the file operation.

For non-Kerberised clusters, you must activate Superuser access in the Configuration settings.

HDFS Snaps support the following accounts:

  • Azure storage account
  • Azure Data Lake account
  • Kerberos account
  • No account

When an account is configured with an HDFS Snap, user impersonation settings have no impact on all accounts, except the Kerberos account.

Ignore empty result

If selected, no document will be written to the output view when the result is empty. If this property is not selected and the Snap receives an input document, the input document is passed to the output view. If this property is not selected and there is no input document, an empty document is written to the output view.

Default value: Selected

Snap Execution

Select one of the three modes in which the Snap executes. Available options are:

  • Validate & Execute: Performs limited execution of the Snap, and generates a data preview during Pipeline validation. Subsequently, performs full execution of the Snap (unlimited records) during Pipeline runtime.
  • Execute only: Performs full execution of the Snap during Pipeline execution without generating preview data.
  • Disabled: Disables the Snap and all Snaps that are downstream from it.


Writing to S3 files with HDFS version CDH 5.8 or later

When running HDFS version later than CDH 5.8, the Hadoop Snap Pack may fail to write to S3 files. To overcome this, make the following changes in the Cloudera manager:

  1. Go to HDFS configuration.
  2. In Cluster-wide Advanced Configuration Snippet (Safety Valve) for core-site.xml, add an entry with the following details:
    • Name: fs.s3a.threads.max
    • Value: 15
  3. Click Save.
  4. Restart all the nodes.
  5. Under Restart Stale Services, select Re-deploy client configuration.
  6. Click Restart Now.


 Hadoop Directory Browser in Action

Hadoop Directory Browser in Action

The Hadoop Directory Browser Snap lists out the contents of a Hadoop file system directory. In this example, we shall:

  1. Read the contents of a Hadoop file system directory using the Hadoop Directory Browser Snap.
  2. Save the directory file list information as a file in the same directory.
  3. Run the Hadoop Directory Browser Snap again to retrieve the updated list of files.
  4. Compare and check whether the number of files in the directory has increased by 1 as expected.

If the pipeline executes successfully, the second execution of the Hadoop Directory Browser will list out one additional file: the one we created using the output of the first execution of the Hadoop Directory Browser Snap.

How This Works

The table below lists the tasks performed by each Snap and documents the configuration details required for each Snap.

SnapPurposeConfiguration DetailsComments
Hadoop Directory Browser Snap 1Retrieves the list of files in the identified HDFS directory.Directory: Enter here the address of the directory whose file-list you want to view.

Creates a copy of the output.

We will use this copy later when we compare this output with the final output created after the pipeline is executed.
FilterFilters the file-list returned by the upstream Snap using specific filter criteria.

Filter expression: $Name == '<the file you want to use to create the new file>'

Example: 'test_file.csv'

This helps you select one file from the list of files returned by the Hadoop Directory Browser Snap.
MapperMaps column headers in the retrieved file-list to those in the file selected using the Filter Snap.

Expression: $Path.substr(0,70)
Target Path: $Directory

Expression: $Name
Target Path: $Filename

This enables you to create the list of directories and file names that will populate the new fie you will create further downstream.
HDFS ReaderReads mapped data from the Mapper Snap and makes it available to be written as a new file.Directory: $Directory
File: $Filename

HDFS WriterWrites (Creates) a new file in the specified directory using the data made available upstream.

Directory: The address of the HDFS file system directory where you want to create the new file. For our example to work, this should be the same directory used in the first Snap.

File: The name of the new file. It's typically a good idea to include some kind of logic in the file name, so there's no need for manual intervention. We have gone for a randomizer.

MapperShortens the name of the new file, which could be very long, given that we have used a randomizer to generate a unique name for the file.Expression: $filename.substr(71,50)
Target Path: $filename
This reduces the length of the file name to 20 letters or less, starting from the 71st character from the left. This removes most of the common strings that form the path name and saves primarily that part of the path string that uniquely identifies each file.
Hadoop Directory BrowserRetrieves the list of files in the updated HDFS directory.Directory: Enter here the address of the directory in which the new file was created. For our example to work, this should be the same directory used in the first Snap.
DiffCompares the output of the two Hadoop Directory Browser Snaps. If there is one extra file in the final Hadoop Directory Browser Snap, the example works!Drag and drop the connection point from the Copy version of the initial file list to the Original connection point associated with the Diff Snap.

Run the pipeline. Once execution is done, click the Check Pipeline Statistics button to check whether it has worked. You should find the following changes:

  • Original: N Files (Depending on the number of files available in the concerned HDFS directory)
  • New: N+1 (This is the new file created using the output from the Hadoop Directory Browser Snap.)
  • Modified: 0
  • Deletions: 0
  • Insertions: 1 (This is the new file created using the output from the Hadoop Directory Browser Snap.)
  • Unmodified: N (Depending on the number of files available in the concerned HDFS directory)

Download the sample pipeline


Important steps to successfully reuse Pipelines

  1. Download and import the Pipeline into SnapLogic.
  2. Configure Snap accounts as applicable.
  3. Provide Pipeline parameters as applicable.

  File Modified

File Hadoop Directory Browser Example.slp

Jul 19, 2018 by Rakesh Chaudhary

Snap Pack History

 Click to view/expand
Release Snap Pack VersionDateType  Updates
4.29main15993 Stable

Enhanced the AWS S3 Account for Hadoop account to include the S3 Region field that allows cross-region or proxied cross-region access to S3 buckets in the Parquet Reader and Parquet Writer Snaps.

4.28 Patch428patches15216 LatestAdded the AWS S3 Dynamic account for Parquet Reader and Parquet Writer Snaps.
4.28main14627 StableUpgraded with the latest SnapLogic Platform release.
4.27 Patch427patches13769 Latest

Fixed an issue with the Hadoop Directory Browser Snap where the Snap was not listing the files in the given directory for Windows VM.

4.27 Patch427patches12999 LatestEnhanced the Parquet Reader Snap with int96 As Timestamp checkbox, which when selected enables the Date Time Format field. You can use this field to specify a date-time format of your choice for int96 data-type fields. The int96 As Timestamp checkbox is available only when you deselect Use old data format checkbox.





Enhanced the Parquet Writer and Parquet Reader Snaps with Azure SAS URI properties, and Azure Storage Account for Hadoop with SAS URI Auth Type. This enables the Snaps to consider SAS URI given in the settings if the SAS URI is selected in the Auth Type during account configuration. 

4.26426patches12288 Latest

Fixed a memory leak issue when using HDFS protocol in Hadoop Snaps.

4.26main11181 StableUpgraded with the latest SnapLogic Platform release.
4.25 Patch425patches9975 Latest

Fixed the dependency issue in Hadoop Parquet Reader Snap while reading from AWS S3. The issue is caused due to conflicting definitions for some of the AWS classes (dependencies) in the classpath.

  • Enhanced the HDFS Reader and HDFS Writer Snaps with the Retry mechanism that includes the following settings:
    • Number of Retries: Specifies the maximum number of retry attempts when the Snap fails to connect to the Hadoop server.
    • Retry Interval (seconds): Specifies the minimum number of seconds the Snap must wait before each retry attempt.
4.24 Patch424patches9262 Latest

Enhanced the AWS S3 Account for Hadoop to support role-based access when you select IAM role checkbox.

4.24 Patch424patches8876



Fixes the missing library error in Hadoop Snap Pack when running Hadoop Pipelines in JDK11 runtime.

StableUpgraded with the latest SnapLogic Platform release.
4.23 Patch423patches7440 Latest

Fixes the issue in HDFS Reader Snap by supporting to read and write files larger than 2GB using ABFS(S) protocol.

StableUpgraded with the latest SnapLogic Platform release.
StableUpgraded with the latest SnapLogic Platform release.
4.21 Patchhadoop8853 Latest

Updates the Parquet Writer and Parquet Reader Snaps to support the yyyy-MM-dd format for the DATE logical type.



StableUpgraded with the latest SnapLogic Platform release.
4.20 Patchhadoop8776 Latest

Updates the Hadoop Snap Pack to use the latest version of org.xerial.snappy:snappy-java for compression type Snappy, in order to resolve the java.lang.UnsatisfiedLinkError: org.xerial.snappy.SnappyNative.maxCompressedLength(I)I error.

StableUpgraded with the latest SnapLogic Platform release.
4.19 Patchhadoop8270 Latest

Fixes an issue with the Hadoop Parquet Writer Snap wherein the Snap throws an exception when the input document includes one or all of the following:

  • Empty lists.
  • Lists with all null values.
  • Maps with all null values.
StableUpgraded with the latest SnapLogic Platform release.
4.18 Patchhadoop8033 Latest

Fixed an issue with the Parquet Writer Snap wherein the Snap throws an error when working with WASB protocol.


Pushed automatic rebuild of the latest version of each Snap Pack to SnapLogic UAT and Elastic servers.


Added the Snap Execution field to all Standard-mode Snaps. In some Snaps, this field replaces the existing Execute during preview check box.


Added a new property, Output for each file written, to handle multiple binary input data in the HDFS Writer Snap.

  • Added two new Snaps: HDFS ZipFile Reader and HDFS ZipFile Writer.
  • Added support for the Data Catalog Snaps in Parquet Reader and Parquet Writer Snaps.
4.14 Patchhadoop5888 Latest

Fixed an issue wherein the Hadoop snaps were throwing an exception when a Kerberized account is provided, but the snap is run in a non-kerberized environment.

  • Added the Hadoop Directory Browser Snap, which browses a given directory path in the Hadoop file system using the HDFS protocol and generates a list of all the files in the directory. It also lists subdirectories and their contents.
  • Added support for S3 file protocol in the ORC Reader, and ORC Writer Snaps.
  • Added support for reading nested schema in the Parquet Reader Snap.
4.13 Patchhadoop5318 Latest
  • Fixed the HDFS Reader/Writer and Parquet Reader/Writer Snaps, wherein Hadoop configuration information does not parse from the client's configuration files.
  • Fixed the HDFS Reader/Writer and Parquet Reader/Writer Snaps, wherein User Impersonation does not work on Hadooplex.


  • KMS encryption support added to AWS S3 account in the Hadoop Snap Pack.
  • Enhanced the Parquet Reader, Parquet Writer, HDFS Reader, and HDFS Writer Snaps to support WASB and ADLS file protocols.
  • Added the AWS S3 account support to the Parquet Reader and Writer Snaps. 
  • Added second input view to the Parquet Reader Snap that when enabled, accepts table schema.
  • Supported with AWS S3, Azure Data Lake, and Azure Storage Accounts.
4.12 Patchhadoop5132 Latest

Fixed an issue with the HDFS Reader Snap wherein the pipeline becomes stale while writing to the output view.



StableUpgraded with the latest SnapLogic Platform release.
4.11 Patchhadoop4275

Addressed an issue with Parquet Reader Snap leaking file descriptors (connections to HDFS data nodes). The Open File descriptor values work stable now,


Added Kerberos support to the standard mode Parquet Reader and Parquet Writer Snaps.

4.10 Patchhadoop4001 Latest

Supported HDFS Writer to write to the encryption zone.

4.10 Patchhadoop3887 Latest

Addressed the suggest issue for the HDFS Reader on Hadooplex.

4.10 Patchhadoop3851 Latest
  • ORC supports read/write from local file system.
  • Addressed an issue to bind the Hive Metadata to Parquet Writer Schema at Runtime.
4.10 Patchhadoop3838 Latest

Made HDFS Snaps work with Zone encrypted HDFS.



  • Updated the Parquet Writer Snap with Partition by property to support the data written into HDFS based on the partition definition in the schema in Standard mode.
  • Support for S3 accounts with IAM Roles added to Parquet Reader and Parquet Writer
  • HDFS Reader/Writer with Kerberos support on Groundplex (including user impersonation).
4.9 Patchhadoop3339 Latest

Addressed the following issues:

  • ORC Reader passing, but ORC Writer failing when run on a Cloudplex.
  • ORC Reader Snap is not routing error to error view.
  • Intermittent failures with the ORC Writer
4.9.0 Patchhadoop3020 Latest

Added missing dependency org.iq80.snappy:snappy to Hadoop Snap Pack.

StableUpgraded with the latest SnapLogic Platform release.



Snap-aware error handling policy enabled for Spark mode in Sequence Formatter and Sequence Parser. This ensures the error handling specified on the Snap is used.

4.7.0 Patchhadoop2343 Latest

Spark Validation: Resolved an issue with validation failing when setting the output file permissions.



  • Updated the HDFS Writer and HDFS Reader Snaps with Azure Data Lake account for standard mode pipelines.
  • HDFS Writer: Spark mode support added to write to a specified directory in an Azure Storage Layer using the wasb file system protocol.
  • HDFS Reader: Spark mode support added to read a single file or an HDFS directory from an Azure Storage Layer.
  • The following Snaps now support error view in Spark mode: HDFS Reader, Sequence Parser.
  • Resolved an issue in HDFS Writer Snap that sends the same data in output & error view.


  • HDFS Reader and HDFS Writer Snaps updated to support IAM Roles for Amazon EC2.
  • Support for Spark mode added to Parquet Reader, Parquet Writer
  • The HBase Snaps are no longer available as of this release.
  • Resolved an issue with Sequence Formatter not working in Spark mode.
  • Resolved an issue with HDFSReader not using the filter set when configuring SparkExec paths.
  • NEW! Parquet Reader and Writer Snaps
  • NEW! ORC Reader and Writer Snaps
  • Spark support added to the HDFS Reader, HDFS Writer, Sequence Formatter, and Sequence Parser Snaps.
  • Behavior change: HDFS Writer in SnapReduce mode now requires the File property to be blank.
  • Implemented wasbs:// protocol support in Hadoop Snap Pack.
  • Resolved an issue with HDFS Reader unable to read all files under a folder (including all files under its subfolders) using the ** filter.