Redshift

Description

The Redshift offline store provides support for reading RedshiftSources.

  • All joins happen within Redshift.

  • Entity dataframes can be provided as a SQL query or can be provided as a Pandas dataframe. A Pandas dataframes will be uploaded to Redshift temporarily in order to complete join operations.

Getting started

In order to use this offline store, you'll need to run pip install 'feast[aws]'. You can get started by then running feast init -t aws.

Example

feature_store.yaml
project: my_feature_repo
registry: data/registry.db
provider: aws
offline_store:
  type: redshift
  region: us-west-2
  cluster_id: feast-cluster
  database: feast-database
  user: redshift-user
  s3_staging_location: s3://feast-bucket/redshift
  iam_role: arn:aws:iam::123456789012:role/redshift_s3_access_role

The full set of configuration options is available in RedshiftOfflineStoreConfig.

Functionality Matrix

The set of functionality supported by offline stores is described in detail here. Below is a matrix indicating which functionality is supported by the Redshift offline store.

Redshift

get_historical_features (point-in-time correct join)

yes

pull_latest_from_table_or_query (retrieve latest feature values)

yes

pull_all_from_table_or_query (retrieve a saved dataset)

yes

offline_write_batch (persist dataframes to offline store)

yes

write_logged_features (persist logged features to offline store)

yes

Below is a matrix indicating which functionality is supported by RedshiftRetrievalJob.

Redshift

export to dataframe

yes

export to arrow table

yes

export to arrow batches

yes

export to SQL

yes

export to data lake (S3, GCS, etc.)

no

export to data warehouse

yes

export as Spark dataframe

no

local execution of Python-based on-demand transforms

yes

remote execution of Python-based on-demand transforms

no

persist results in the offline store

yes

preview the query plan before execution

yes

read partitioned data

yes

To compare this set of functionality against other offline stores, please see the full functionality matrix.

Permissions

Feast requires the following permissions in order to execute commands for Redshift offline store:

Command

Permissions

Resources

Apply

redshift-data:DescribeTable

redshift:GetClusterCredentials

arn:aws:redshift:<region>:<account_id>:dbuser:<redshift_cluster_id>/<redshift_username>

arn:aws:redshift:<region>:<account_id>:dbname:<redshift_cluster_id>/<redshift_database_name>

arn:aws:redshift:<region>:<account_id>:cluster:<redshift_cluster_id>

Materialize

redshift-data:ExecuteStatement

arn:aws:redshift:<region>:<account_id>:cluster:<redshift_cluster_id>

Materialize

redshift-data:DescribeStatement

*

Materialize

s3:ListBucket

s3:GetObject

s3:DeleteObject

arn:aws:s3:::<bucket_name>

arn:aws:s3:::<bucket_name>/*

Get Historical Features

redshift-data:ExecuteStatement

redshift:GetClusterCredentials

arn:aws:redshift:<region>:<account_id>:dbuser:<redshift_cluster_id>/<redshift_username>

arn:aws:redshift:<region>:<account_id>:dbname:<redshift_cluster_id>/<redshift_database_name>

arn:aws:redshift:<region>:<account_id>:cluster:<redshift_cluster_id>

Get Historical Features

redshift-data:DescribeStatement

*

Get Historical Features

s3:ListBucket

s3:GetObject

s3:PutObject

s3:DeleteObject

arn:aws:s3:::<bucket_name>

arn:aws:s3:::<bucket_name>/*

The following inline policy can be used to grant Feast the necessary permissions:

{
    "Statement": [
        {
            "Action": [
                "s3:ListBucket",
                "s3:PutObject",
                "s3:GetObject",
                "s3:DeleteObject"
            ],
            "Effect": "Allow",
            "Resource": [
                "arn:aws:s3:::<bucket_name>/*",
                "arn:aws:s3:::<bucket_name>"
            ]
        },
        {
            "Action": [
                "redshift-data:DescribeTable",
                "redshift:GetClusterCredentials",
                "redshift-data:ExecuteStatement"
            ],
            "Effect": "Allow",
            "Resource": [
                "arn:aws:redshift:<region>:<account_id>:dbuser:<redshift_cluster_id>/<redshift_username>",
                "arn:aws:redshift:<region>:<account_id>:dbname:<redshift_cluster_id>/<redshift_database_name>",
                "arn:aws:redshift:<region>:<account_id>:cluster:<redshift_cluster_id>"
            ]
        },
        {
            "Action": [
                "redshift-data:DescribeStatement"
            ],
            "Effect": "Allow",
            "Resource": "*"
        }
    ],
    "Version": "2012-10-17"
}

In addition to this, Redshift offline store requires an IAM role that will be used by Redshift itself to interact with S3. More concretely, Redshift has to use this IAM role to run UNLOAD and COPY commands. Once created, this IAM role needs to be configured in feature_store.yaml file as offline_store: iam_role.

The following inline policy can be used to grant Redshift necessary permissions to access S3:

{
    "Statement": [
        {
            "Action": "s3:*",
            "Effect": "Allow",
            "Resource": [
                "arn:aws:s3:::feast-integration-tests",
                "arn:aws:s3:::feast-integration-tests/*"
            ]
        }
    ],
    "Version": "2012-10-17"
}

While the following trust relationship is necessary to make sure that Redshift, and only Redshift can assume this role:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "Service": "redshift.amazonaws.com"
      },
      "Action": "sts:AssumeRole"
    }
  ]
}

Redshift Serverless

In order to use AWS Redshift Serverless, specify a workgroup instead of a cluster_id and user.

feature_store.yaml
project: my_feature_repo
registry: data/registry.db
provider: aws
offline_store:
  type: redshift
  region: us-west-2
  workgroup: feast-workgroup
  database: feast-database
  s3_staging_location: s3://feast-bucket/redshift
  iam_role: arn:aws:iam::123456789012:role/redshift_s3_access_role

Please note that the IAM policies above will need the redshift-serverless version, rather than the standard redshift.