HDFS ZipFile Writer

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Use the HDFS ZipFile Write Snap to read in-coming data and write it to a ZIP file in an HDFS directory. This Snap also enables you to specify file access permissions for the new ZIP file. You can also configure how the Snap handles the new ZIP file if the destination directory already has another ZIP file with the same name.

For the HDFS protocol, use a SnapLogic on-premises Groundplex and ensure that its instance is within the Hadoop cluster and that SSH authentication is established.

The HDFS protocol supported by this Snap is HDFS 2.4.0. This Snap supports both HDFS & ABFS (Azure Data Lake Storage Gen 2 ) protocols.

Expected Input and Output

  • Expected Input: Binary data stream containing documents to be written to a ZIP file.
  • Expected Output: Zipped file containing the incoming documents.
  • Expected Upstream Snaps: Required. Any Snap that offers binary data in its output view. Examples: JSON Formatter, HDFS Reader, File Reader.
  • Expected Downstream Snaps: Any Snap that takes document data as input. Examples: Mapper, HDFS Reader.


The user executing the Snap must have Write permissions on the concerned directory.

Configuring Accounts

This Snap uses account references created on the Accounts page of SnapLogic Manager to handle access to this endpoint. See Configuring Hadoop Accounts for information on setting up this type of account.

Configuring Views


This Snap has at least one document input view.
OutputThis Snap has at most one document output view.
ErrorThis Snap has at most one document error view.


None at this time.

Limitations and Known Issues

None at this time.


Snap Settings

LabelRequired. The name for the Snap. Modify this to be more specific, especially if there are more than one of the same Snap in the 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.

With the ABFS protocol, SnapLogic creates a temporary file to store the incoming data. Therefore, the hard drive where the JCC is running should have enough space to temporarily store all the account data coming in from ABFS.

Default value: [None]


The relative path and name of the file that must be created post execution.


  • sample.zip
  • tmp/another.zip
  • $filename

Default value:  [None]

User ImpersonationSelect 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.

File Action
Required. Use this field to specify what you want the Snap to do if the file you want it to create already exists. Available options are: Overwrite, Ignore, and Error.
  • Overwrite: If the target file exists, the Snap overwrites the file.

  • Ignore: If the file already exists, the Snap neither throws an exception nor does it overwrite the file, but creates an output document indicating that the new data has been ignored.
  • Error: The error displays in the Pipeline Run Log if the file already exists.

Default value: Overwrite

File Permissions

File permission sets to be assigned to the file. To assign file permissions:

  1. Click the + button against File permissions. This adds a row to the fieldset.
  2. Click the Suggestible icon in the User type field and select the user type for which you want to enable access. This drop-down offers the following options:
    • Owner: This is the user account under whose name the new file will be created.
    • Group: This is the user group to which the user being impersonated belongs.
    • Others: These are all other users who have at least Read access to the concerned directory.
  3. Click the Suggestible icon in the File permissions field and select the permission you want to enable for the user type selected in the User type field.
Base directoryEnter here the name of the root directory in the ZIP file.
Use input view label

If selected, the input view label is used for all names of the files added to the zip file. Otherwise, the input view ID is used instead, when input the binary stream does not have its content-location in its header. When this option is selected, if there are more than one binary input streams in an input view, for the second input stream and after, the file names will be the input view label appended with '_n'. If the label is in the format of 'name.ext', '_n' will be append to the 'name', e.g. name_2.ext for the second input stream.

Example: If this option is selected, if Base directory is testFolder and the input view label is test.csv, the file name for the first binary input stream in that input view will be testFolder/test.csv, and the second, testFolder/test_2.csv, and the third, testFolder/test_3.csv, and so on.

Default value: Not 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.

The binary document header content-location of the HDFS ZipFile Writer input is the name within the ZIP file. (Example: foo.txt). The Snap does not include the 'base directory'. It could contain subdirectories though. On the other hand, the binary document header content-location of the output of the HDFS ZipFile Reader is the name of the ZIP file, the base directory, and the content location provided to the writer. Thus, while each Snap works well independent of each other, it's currently not possible to have a Reader > Writer > Reader combination in a pipeline without using other intermediate Snaps to provide the binary document header information.


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.


Writing and Reading a ZIP File in HDFS

The first part of this example demonstrates how you can use the HDFS ZipFile Write Snap to zip and write a new file into HDFS. The second part of this example demonstrates how you can unzip and check the contents of the newly-created ZIP file.

Click here to download this pipeline. You can also downloaded this pipeline from the Downloads section below.

 Understanding the Sample Pipeline

Create the pipeline as shown below:

The Hadoop Directory Browser Snap

Use a Hadoop Directory Browser Snap to first check the contents of the target directory. This will help you check whether the new file got added to the HDFS directory as expected, later in the example.

Enter the Directory URL as appropriate and specify the File filter as *.zip. This instructs the Snap to list out all the ZIP files in the target directory.

If the Snap executes as expected, you should see the contents of your target directory, as shown below:

Generating a File for Upload

You now need to choose a file to upload into the target directory. You could either select a file directly or use a JSON Generator Snap coupled with a JSON Formatter Snap, as in the example pipeline.

The HDFS ZipFile Writer Snap

Your file is now ready. Configure the HDFS ZipFile Writer Snap to upload the file as a ZIP file into the target directory in HDFS, as shown below.

The Hadoop Directory Browser Snap

Use a Copy Snap to perform two tasks after the ZIP file is created: first, to check whether the new file was created as expected and second, to try and read the contents to the newly-created ZIP file from the target HDFS directory.

To check whether the new file was created, add an HDFS Directory Browser Snap to the pipeline.

If the ZIP file was created, you should see it in the output, as shown below:

HDFS ZipFile Reader

Once you have confirmed that the new ZIP file has been created, use the HDFS ZipFile Reader Snap to read the new ZIP file. If the contents of the new ZIP file is the same as the contents of the input file, you know that the pipeline works!

To read the output of the HDFS ZipFile Read Snap, use a File Reader Snap:

If the contents of the new file is the same as the contents of the original file, you know the example works.

Click here to download this Pipeline. You can also downloaded this pipeline from the Downloads section below.


Important steps to successfully reuse Pipelines

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

  File Modified

File HDFS_ZIPFILE_Read_Write.slp

Oct 19, 2018 by Rakesh Chaudhary

 Click to view/expand
Release Snap Pack VersionDateType  Updates
May 2024437patches26370 Latest

Enhanced the HDFS Writer Snap with the Write empty file checkbox to enable you to write an empty or a 0-byte file to all the supported protocols that are recognized and compatible with the target system or destination.

May 2024main26341 Stable

The Azure Data Lake Account has been removed from the Hadoop Snap Pack because Microsoft retired the Azure Data Lake Storage Gen1 protocol on February 29, 2024. We recommend replacing your existing Azure Data Lake Accounts (in Binary or Hadoop Snap Packs) with other Azure Accounts.

February 2024



Fixed a memory management issue in the HDFS Writer, HDFS ZipFile Writer, ORC Writer, and Parquet Writer Snaps, which previously caused out-of-memory errors when multiple Snaps were used in the pipeline. The Snap now conducts a pre-allocation memory check, dynamically adjusting the write buffer size based on available memory resources when writing to ADLS.

February 2024435patches25410Latest

Enhanced the AWS S3 Account for Hadoop with an External ID that enables you to access Hadoop resources securely.

February 2024main25112 StableUpdated and certified against the current SnapLogic Platform release.
November 2023435patches23904 Latest
  • Fixed an issue with the Parquet Writer Snap that displayed an error Failed to write parquet data when the decimal value passed from the second input view exceeded the specified scale.

  • Fixed an issue with the Parquet Writer Snap that previously failed to handle the conversion of BigInt/int64 (larger numbers) after the 4.35 GA now converts them accurately.

November 2023435patches23780 Latest

Fixed an issue related to error routing to the output view. Also fixed a connection timeout issue.

November 2023main23721StableUpdated and certified against the current SnapLogic Platform release.
August 2023434patches23173 Latest

Enhanced the Parquet Writer Snap with a Decimal Rounding Mode dropdown list to enable the rounding method for decimal values when the number exceeds the required decimal places.

August 2023434patches22662 Latest
  • Enhanced the Parquet Writer Snap with the support for LocalDate and DateTime. The Snap now shows the schema suggestions for LocalDate and DateTime correctly.

  • Enhanced the Parquet Reader Snap with the Use datetime types checkbox that supports LocalDate and DateTime datatypes.

Behavior change:

When you select the Use datetime types checkbox in the Parquet Reader Snap, the Snap displays the LocalDate and DateTime in the output for INT32 (DATE) and INT64 (TIMESTAMP_MILLIS) columns. When you deselect this checkbox, the columns retain the previous datatypes and display string and integer values in the output.

August 2023




Updated and certified against the current SnapLogic Platform release.

May 2023433patches22180 Latest

Introduced the HDFS Delete, which deletes the specified file, group of files, or directory from the supplied path and protocol in the Hadoop Distributed File System (HDFS).

May 2023433patches21494 LatestThe Hadoop Directory Browser Snap now returns all the output documents as expected after implementing pagination for the ABFS protocol.
May 2023main21015 StableUpgraded with the latest SnapLogic Platform release.
February 2023



Fixed an authorization issue that occurs with the Parquet Writer Snap when it receives empty document input.

February 2023432patches20209 Latest

The Apache Commons Compress library has been upgraded to version 1.22.

February 2023432patches20139 Latest

The Kerberos Account that is available for a subset of snaps in the Hadoop Snap pack now supports a configuration that enables you to read from and write to the Hadoop Distributed File System (HDFS) managed by multiple Hadoop clusters. You can specify the location of the Hadoop configuration files in the Hadoop config directory field. The value in this field overrides the value that is set on the Snaplex system property used for configuring a single cluster. 

February 2023

main19844 StableUpgraded with the latest SnapLogic Platform release.
November 2022main18944 Stable

The AWS S3 and S3 Dynamic accounts now support a maximum session duration of an IAM role defined in AWS.

August 2022main17386 StableExtended the AWS S3 Dynamic Account support to ORC Reader and ORC Writer Snaps to support AWS Security Token Service (STS) using temporary credentials.
4.29 Patch429patches16630 Latest
  • Extended the AWS S3 Dynamic Account support to ORC Reader and ORC Writer Snaps to support AWS Security Token Service (STS) using temporary credentials.
  • Fixed an issue in the following Snaps that use AWS S3 dynamic account, where the Snaps displayed the security credentials like Access Key, Secret Key, and Security Token in the logs. Now, the security credentials in the logs are blurred for the Snaps that use AWS S3 dynamic account.
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.