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Trifacta SaaS



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Feature Availability: This feature is available in the following editions:

  • Trifacta Enterprise Edition
  • Trifacta Professional Edition
  • Trifacta Premium

Contents:


You can create connections to specific S3 buckets through the Trifacta application.  These connections to S3 enable workspace users to read from and write to specific S3 buckets. 

Simple Storage Service (S3) is an online data storage service provided by Amazon, which provides low-latency access through web services. For more information, see https://aws.amazon.com/s3/.


  • Read: Supported
  • Write: Supported

Prerequisites

Before you begin, please verify that your Trifacta® environment meets the following requirements:

  • Integration: Your  Trifacta instance is connected to a running environment supported by your product edition.

  • Multiple region: Multiple S3 connections can be configured in different regions.

  • Verify that Enable S3 Connectivity has been enabled in the Workspace Settings Page

  • Acquire the Access Key ID and Secret Key for the S3 bucket or buckets to which you are connecting. For more information on acquiring your key/secret combination, contact your S3 administrator.

Permissions

Access to S3 requires:

  • Each user must have appropriate permissions to access S3.

    NOTE: If a user does not have write permissions to the specified S3 bucket, publishing jobs to the bucket fail.

  • To browse multiple buckets through a single S3 connection, additional permissions are required. See below.

Limitations

  • Authentication using IAM roles is not supported.
  • Automatic region detection in the create and edit connection is not supported.
  • Publishing the output to multi-part files is not supported.

    NOTE: For some file formats, like Parquet, multi-part files are the default output.

  • Publishing the output using compression option is not supported for Trifacta Photon jobs.

    Workaround: If you need to generate an output using compression to this S3 bucket, you can run the job on another running environment.

Create Connection

You can create additional S3 connections by the following method:

Create through application

You can create a S3 connection through the application.

Steps:

  1. Login to the application.
  2. In the left navigation bar, click the Connections icon.
  3. In the Create Connection page, click the External Amazon S3 card.

  4. Specify the connection properties:

    PropertyDescription
    DefaultBucket

    (Optional) The default S3 bucket to which to connect. When the connection is first accessed for browsing, the contents of this bucket are displayed.

    If this value is not provided, then the list of available buckets based on the key/secret combination is displayed when browsing through the connection.

    NOTE: To see the list of available buckets, the connecting user must have the getBucketList permission. If that permission is not present and no default bucket is listed, then the user cannot browse S3.

    Access Key ID

    Access Key ID for the S3 connection.

    Secret Key

    Secret Key for the S3 connection.

    Server Side EncryptionIf server-side encryption has been enabled on your bucket, you can select the server-side encryption policy to use when writing to the bucket. SSE-S3 and SSE-KMS methods are supported.  For more information, see http://docs.aws.amazon.com/AmazonS3/latest/dev/serv-side-encryption.html.
    Server Side Kms key Id

    When KMS encryption is enabled, you must specify the AWS KMS key ID to use for the server-side encryption. For more information, see "Server Side KMS Key Identifier" below.


    For more information on the other options, see Create Connection Window.

  5. Click Save

Server Side KMS Key Identifier

When KMS encryption is enabled, you must specify the AWS KMS key ID to use for the server-side encryption.

The format for referencing this key is the following:

"arn:aws:kms:<regionId>:<acctId>:key/<keyId>"

You can use an AWS alias in the following formats. The format of the AWS-managed alias is the following:

"alias/aws/s3"

The format for a custom alias is the following:

"alias/<FSR>"

where:

<FSR> is the name of the alias for the entire key.

Create via API

For more information on the vendor and type information to use, see Connection Types.

For more information, see  Trifacta SaaS API Reference docs: Enterprise | Professional | Premium


Java VFS Service

The Java VFS Service has been modified to handle an optional connection ID, enabling S3 URLs with connection ID and credentials. The other connection details are fetched through the Trifacta application to create the required URL and configuration.

// sample URI
s3://bucket-name/path/to/object?connectionId=136


// sample java-vfs-service CURL request with s3
curl -H 'x-trifacta-person-workspace-id: 1' -X GET 'http://localhost:41917/vfsList?uri=s3://bucket-name/path/to/object?connectionId=136'

Write

You can publish results to your external S3 buckets. Configure an output destination to write to your external S3 bucket.

  1. In Flow View, create or edit an output object. 
    1. To edit, right-click an output object. The object details are displayed in the Details panel.
  2. In the Details panel, click Edit.
  3. Modify the output destination to use the External S3 buckets connection.
  4. Navigate the bucket to select the appropriate location for the output. Specify the file as needed.
  5. To save your changes, click Update

For more information, see Create Outputs.

Testing

  1. Import a dataset from External Amazon S3.
  2. Add it to a flow and run a job, publishing results back to S3.

For more information, see Verify Operations.

Using S3 Connections

Uses of S3

The Trifacta platform can use S3 for the following tasks:

  1. Enabled S3 Integration: The Trifacta platform has been configured to integrate with your S3 instance.

  2. Creating Datasets from S3 Files: You can read in source data stored in S3. An imported dataset may be a single S3 file or a folder of identically structured files. See Reading from Sources in S3 below.
  3. Reading Datasets: When creating a dataset, you can pull your data from a source in S3. See Creating Datasets below.
  4. Writing Results: After a job has been executed, you can write the results back to S3.See Writing Results below.

In the Trifacta application, S3 is accessed through the S3 browser. See S3 Browser.

NOTE: When the Trifacta platform executes a job on a dataset, the source data is untouched. Results are written to a new location, so that no data is disturbed by the process.

Before you begin using S3

  • Access: If you are using system-wide permissions, your administrator must configure access parameters for S3 locations. If you are using per-user permissions, this requirement does not apply.

    Avoid using /trifacta/uploads for reading and writing data. This directory is used by the Trifacta application.

  • Your administrator should provide a writeable home output directory for you. This directory location is available through your user profile. See Storage Config Page.

Secure access

Your administrator can grant access on a per-user basis or for the entire Trifacta platform.

The Trifacta platform utilizes an S3 key and secret to access your S3 instance. These keys must enable read/write access to the appropriate directories in the S3 instance.

NOTE: If you disable or revoke your S3 access key, you must update the S3 keys for each user or for the entire system.

Storing data in S3

Your administrator should provide raw data or locations and access for storing raw data within S3. All Trifacta users should have a clear understanding of the folder structure within S3 where each individual can read from and write results.

  • Users should know where shared data is located and where personal data can be saved without interfering with or confusing other users.
  • The Trifacta application stores the results of each job in a separate folder in S3.

NOTE: The Trifacta platform does not modify source data in S3. Source data stored in S3 is read without modification from source locations, and source data uploaded to the Trifacta platform is stored in /trifacta/uploads.

Reading from sources in S3

You can create an imported dataset from one or more files stored in S3.

NOTE: Import of glaciered objects is not supported.


Wildcards:

You can parameterize your input paths to import source files as part of the same imported dataset. For more information, see Overview of Parameterization.

Folder selection:

When you select a folder in S3 to create your dataset, you select all files in the folder to be included.

Notes:

  • This option selects all files in all sub-folders and bundles them into a single dataset. If your sub-folders contain separate datasets, you should be more specific in your folder selection.
  • All files used in a single imported dataset must be of the same format and have the same structure. For example, you cannot mix and match CSV and JSON files if you are reading from a single directory.

When a folder is selected from S3, the following file types are ignored:

  • *_SUCCESS and *_FAILED files, which may be present if the folder has been populated by the running environment.

NOTE: If you have a folder and file with the same name in S3, search only retrieves the file. You can still navigate to locate the folder. 

Creating datasets

When creating a dataset, you can choose to read data in from a source stored from S3 or local file.

  • S3 sources are not moved or changed.
  • Local file sources are uploaded to /trifacta/uploads where they remain and are not changed.

Data may be individual files or all of the files in a folder. In the Import Data page, click the S3 tab. See Import Data Page.

Writing results

When you run a job, you can specify the S3 bucket and file path where the generated results are written. By default, the output is generated in your default bucket and default output home directory.

  • Each set of results must be stored in a separate folder within your S3 output home directory.
  • For more information on your output home directory, see Storage Config Page.

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