Below are instructions on how to configure  to point to S3.

• 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/.

Base Storage Layer

• If base storage layer is S3: you can enable read/write access to S3.
• If base storage layer is not S3: you can enable read only access to S3.

Limitations

• The  supports S3 connectivity for the following distributions: 
  

  NOTE: You must use a Hadoop version that is supported for your release of the product.

  • Cloudera 5.10 and later. See  Supported Deployment Scenarios for Cloudera.

  • Hortonworks 2.5 and later. See Supported Deployment Scenarios for Hortonworks.

• The  only supports running S3-enabled instances over AWS.
• Access to AWS S3 Regional Endpoints through internet protocol is required. If the machine hosting the  is in a VPC with no internet access, a VPC endpoint enabled for S3 services is required. The  does not support access to S3 through a proxy server.

• Write access requires using S3 as the base storage layer. See Set Base Storage Layer.

Pre-requisites

• On the , you must install the Oracle Java Runtime Environment for Java 1.8. Other versions of the JRE are not supported. For more information on the JRE, see http://www.oracle.com/technetwork/java/javase/downloads/index.html. 

Required AWS Account Permissions

All access to S3 sources occurs through a single AWS account (system mode) or through an individual user's account (user mode). For either mode, the AWS access key and secret combination must provide access to the default bucket associated with the account. 

Read-only access polices

The policy statement to enable read-only access to your default S3 bucket should look similar to the following. Replace 3c-my-s3-bucket with the name of your bucket:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor0",
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:ListBucket",
                "s3:GetBucketLocation"
            ],
            "Resource": [
                "arn:aws:s3:::3c-my-s3-bucket",
                "arn:aws:s3:::3c-my-s3-bucket/*",
            ]
        }
    ]
}

Write access polices

Write access is enabled by adding the PutObject and DeleteObject actions to the above. Replace 3c-my-s3-bucket with the name of your bucket:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor0",
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:ListBucket",
                "s3:GetBucketLocation",
                "s3:PutObject",
                "s3:DeleteObject"
            ],
            "Resource": [
                "arn:aws:s3:::3c-my-s3-bucket",
                "arn:aws:s3:::3c-my-s3-bucket/*",
            ]
        }
    ]
}

Other AWS policies for S3

Policy for access to 

To access S3 assets that are managed by , you must apply the following policy definition to any IAM role that is used to access . This bucket contain demo assets for the On-Boarding tour:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor1",
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::trifacta-public-datasets/*",
                "arn:aws:s3:::trifacta-public-datasets"
            ]
        }
    ]
}

For more information on creating policies, see https://console.aws.amazon.com/iam/home#/policies.

KMS policy

If any accessible bucket is encrypted with KMS-SSE, another policy must be deployed. For more information, see https://docs.aws.amazon.com/kms/latest/developerguide/iam-policies.html.

Configuration

Depending on your S3 environment, you can define:

• read access to S3
• access to additional S3 buckets

• S3 as base storage layer

• Write access to S3
  • S3 bucket that is the default write destination

Define base storage layer

The base storage layer is the default platform for storing results.

Required for:

• Write access to S3
• Connectivity to Redshift

For more information on the various options for storage, see Storage Deployment Options.

For more information on setting the base storage layer, see Set Base Storage Layer.

Enable read access to S3

When read access is enabled,  can explore S3 buckets for creating datasets. 

Steps:

1. 

2. Set the following property to true:
   
   

   "aws.s3.enabled": true,

   
   

3. Save your changes.
4. In the S3 configuration section, set enabled=true, which allows  to browse S3 buckets through the .

5. Specify the AWS key and secret values for the user to access S3 storage.

S3 access modes

The  supports the following modes for access S3. You must choose one access mode and then complete the related configuration steps.

System mode

(default) Access to S3 buckets is enabled and defined for all users of the platform. All users use the same AWS access key, secret, and default bucket.

System mode - read-only access

For read-only access, the key, secret, and default bucket must be specified in configuration.

Steps:

1. 
   

2. Locate the following parameters:
   

   Parameters	Description
   aws.s3.key	Set this value to the AWS key to use to access S3.
   aws.s3.secret	Set this value to the secret corresponding to the AWS key provided.
   aws.s3.bucket.name	Set this value to the name of the S3 bucket from which users may read data. NOTE: Additional buckets may be specified. See below.

   
   

3. Save your changes.

User mode

Optionally, access to S3 can be defined on a per-user basis. This mode allows administrators to define access to specific buckets using various key/secret combinations as a means of controlling permissions.

To enable:

1. 

2. Please verify that the settings below have been configured:

   "aws.s3.enabled": true, "aws.mode": "user",

   
   

3. Additional configuration is required for per-user authentication. For more information, see Configure AWS Per-User Authentication.

User mode - Create encryption key file

If you have enabled user mode for S3 access, you must create and deploy an encryption key file. For more information, see Create Encryption Key File.

System mode - additional configuration

The following sections apply only to system access mode.

Define default S3 write bucket

When S3 is defined as the base storage layer, write access to S3 is enabled. The  attempts to store outputs in the designated default S3 bucket. 

Steps:

1. Define S3 to be the base storage layer. See Set Base Storage Layer.
2. Enable read access. See Enable read access.

3. Specify a value for  aws.s3.bucket.name , which defines the S3 bucket where data is written. Do not include a protocol identifier. For example, if your bucket address is s3://MyOutputBucket, the value to specify is the following:

   MyOutputBucket

   
   

   NOTE: Specify the top-level bucket name only. There should not be any backslashes in your entry.

   
   

Adding additional S3 buckets

When read access is enabled, all S3 buckets of which the specified user is the owner appear in the . You can also add additional S3 buckets from which to read.

Steps:

1. 

2. Locate the following parameter: aws.s3.extraBuckets:

   1. In the Admin Settings page, specify the extra buckets as a comma-separated string of additional S3 buckets that are available for storage. Do not put any quotes around the string. Whitespace between string values is ignored.

   2. In , specify the extraBuckets array as a comma-separated list of buckets as in the following: 

      "extraBuckets": ["MyExtraBucket01","MyExtraBucket02","MyExtraBucket03"]

      
      

      NOTE: Specify the top-level bucket name only. There should not be any backslashes in your entry.

      
      

3. Specify the extraBuckets array as a comma-separated list of buckets as in the following: 

   "extraBuckets": ["MyExtraBucket01","MyExtraBucket02","MyExtraBucket03"]

   
   

4. These values are mapped to the following bucket addresses:

   s3://MyExtraBucket01 s3://MyExtraBucket02 s3://MyExtraBucket03

   
   

S3 Configuration

Configuration reference

"aws.s3.enabled": true,
"aws.s3.bucket.name": "<BUCKET_FOR_OUTPUT_IF_WRITING_TO_S3>"
"aws.s3.key": "<AWS_KEY>",
"aws.s3.secret": "<AWS_SECRET>",
"aws.s3.extraBuckets": ["<ADDITIONAL_BUCKETS_TO_SHOW_IN_FILE_BROWSER>"]

Enable use of server-side encryption

You can configure the  to publish data on S3 when a server-side encryption policy is enabled. SSE-S3 and SSE-KMS methods are supported. For more information, see http://docs.aws.amazon.com/AmazonS3/latest/dev/serv-side-encryption.html.

Notes:

• When encryption is enabled, all buckets to which you are writing must share the same encryption policy. Read operations are unaffected.
• This feature is supported for the following Hadoop distributions:
  • SSE-S3: CDH 5.10 or later, HDP 2.6 or later
  • SSE-KMS: CDH 5.11 or later, HDP 2.6.1 or later

To enable, please specify the following parameters.

Server-side encryption method

"aws.s3.serverSideEncryption": "none",

Set this value to the method of encryption used by the S3 server. Supported values:

• sse-s3
• sse-kms
• none

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.

"aws.s3.serverSideKmsKeyId": "",

Notes:

• Access to the key:
  • Access must be provided to the authenticating user.

  • The AWS IAM role must be assigned to this key.

• Encrypt/Decrypt permissions for the specified KMS key ID:
  • Permissions must be assigned to the authenticating user.

  • The AWS IAM role must be given these permissions.

  • For more information, see https://docs.aws.amazon.com/kms/latest/developerguide/key-policy-modifying.html .

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.

Save your changes and restart the platform.

Configure S3 filewriter

The following configuration can be applied through the Hadoop site-config.xml file. If your installation does not have a copy of this file, you can insert the properties listed in the steps below into to configure the behavior of the S3 filewriter.

Steps:

1. 

2. Locate the filewriter.hadoopConfig block, where you can insert the following Hadoop configuration properties:

   "filewriter": { max: 16, "hadoopConfig": { "fs.s3a.buffer.dir": "/tmp", "fs.s3a.fast.upload": "true" }, ... }

   
   

   Property	Description
   fs.s3a.buffer.dir	Specifies the temporary directory on the to use for buffering when uploading to S3. If fs.s3a.fast.upload is set to false, this parameter is unused. NOTE: This directory must be accessible to the Batch Job Runner process during job execution.
   fs.s3a.fast.upload	Set to true to enable buffering in blocks. When set to false, buffering in blocks is disabled. For a given file, the entire object is buffered to the disk of the . Depending on the size and volume of your datasets, the node can run out of disk space.

   
   

3. Save your changes and restart the platform.

Create Redshift Connection

For more information, see Create Redshift Connections.

Hadoop distribution-specific configuration

Hortonworks

Additional Configuration for S3

The following parameters can be configured through the  to affect the integration with S3. You may or may not need to modify these values for your deployment.

s3.us-east-1.amazonaws.com

Testing

Restart services. See Start and Stop the Platform.

Try running a simple job from the . For more information, see Verify Operations.

Troubleshooting

Profiling consistently fails for S3 sources of data

If you are executing visual profiles of datasets sourced from S3, you may see an error similar to the following in the batch-job-runner.log file:

01:19:52.297 [Job 3] ERROR com.trifacta.hadoopdata.joblaunch.server.BatchFileWriterWorker - BatchFileWriterException: Batch File Writer unknown error:
{jobId=3, why=bound must be positive}
01:19:52.298 [Job 3] INFO com.trifacta.hadoopdata.joblaunch.server.BatchFileWriterWorker - Notifying monitor for job 3 with status code FAILURE

This issue is caused by improperly configuring buffering when writing to S3 jobs. The specified local buffer cannot be accessed as part of the batch job running process, and the job fails to write results to S3.

Solution:

You may do one  of the following:

• Use a valid temp directory when buffering to S3.
• Disable buffering to directory completely.

Steps:

• 

• Locate the following, where you can insert either of the following Hadoop configuration properties:

  "filewriter": { max: 16, "hadoopConfig": { "fs.s3a.buffer.dir": "/tmp", "fs.s3a.fast.upload": false }, ... }

  
  

  Property	Description
  fs.s3a.buffer.dir	Specifies the temporary directory on the to use for buffering when uploading to S3. If fs.s3a.fast.upload is set to false, this parameter is unused.
  fs.s3a.fast.upload	When set to false, buffering is disabled.

  
  

• Save your changes and restart the platform.

Spark local directory has no space

During execution of a Spark job, you may encounter the following error:

org.apache.hadoop.util.DiskChecker$DiskErrorException: No space available in any of the local directories.

Solution:

• Restart , which may free up some temporary space.
• Use the steps in the preceding solution to reassign a temporary directory for Spark to use (fs.s3a.buffer.dir).