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About Collectors

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• Python 3.6 - 3.10

• Access to the KADA Collector repository that contains the Athena whl

  • The repository is currently hosted in KADA’s Azure Blob Storage. You will be given a SAS token to access the repository. Reach out to KADA Support (support@kada.ai) if you do not have access.

  • Download the Athena whl (e.g. kada_collectors_extractors_athena-#.#.#-py3-none-any.whl)

  Access to K landing directory

• Access to Athena

Step 1: Establish Athena Access

The service user/account/role will require permissions to the following

1. Execute queries against Athena with access to the INFORMATION_SCHEMA in particular the following tables:

   1. information_schema.views

   2. information_schema.tables

   3. information_schema.columns

2. Executing queries in Athena requires an s3 bucket to temporary store results.
   The policy must also allow Read Write Listing access to objects within that bucket, conversely, the bucket must also have policy to allow to do the same.

3. Call the following Athena APIs

   1. list_databases

   2. list_table_metadata

   3. list_query_executions

   4. list_work_groups

   5. batch_get_query_executions

   6. start_query_execution

   7. get_query_execution

4. The service user/account/role will need permissions to access all workgroups to be able to extract all data, if you omit workgroups, that information will not be extracted and you may not see the complete picture in K.

5. See IAM policies for accessing workgroups - Amazon Athena on how to add policy entries to have fine grain control at the workgroup level. Note that the extractor runs queries on Athena, If you do choose to restrict workgroup access, ensure that Query based actions (e.g. StartQueryExecution) are allowed for the workgroup the service user/account/role is associated to.

Example Role Policy to allow Athena Access with least privileges for actions, this example allows the ACCOUNT ARN to assume the role. Note the variables ATHENA RESULTS BUCKET NAME. You may also choose to just assign the policy directly to a new user and use that user without assuming roles. In the scenario you do wish to assume a role, please note down the role ARN to be used when onbaording/extracting

AWSTemplateFormatVersion: "2010-09-09"
Description: 'AWS IAM Role - Athena and Cloudtrail Access to KADA'
Resources: 
  KadaAthenaRole: 
    Type: "AWS::IAM::Role"
    Properties: 
      RoleName: "KadaAthenaRole"
      MaxSessionDuration: 43200
      Path: "/"
      AssumeRolePolicyDocument: 
        Version: "2012-10-17"
        Statement: 
        - Effect: "Allow"
          Principal:
            AWS: "[ACCOUNT ARN]"
          Action: "sts:AssumeRole"

  KadaAthenaPolicy: 
    Type: 'AWS::IAM::Policy'
    Properties:
      PolicyName: root
      PolicyDocument:
        Version: "2012-10-17"
        Statement:
          - Effect: Allow
            Action: 
              - athena:BatchGetQueryExecution
              - athena:GetQueryExecution
              - athena:GetQueryResults
              - athena:GetQueryResultsStream
              - athena:ListQueryExecutions
              - athena:StartQueryExecution
              - athena:ListWorkGroups
              - athena:ListDataCatalogs
              - athena:ListDatabases
              - athena:ListTableMetadata
            Resource: '*'
          - Effect: Allow
            Action: 
              - s3:GetBucketLocation
              - s3:GetObject
              - s3:ListBucket
              - s3:ListBucketMultipartUploads
              - s3:ListMultipartUploadParts
              - s3:AbortMultipartUpload
              - s3:PutObject
              - s3:PutBucketPublicAccessBlock
              - s3:DeleteObject
            Resource:
              - arn:aws:s3:::[ATHENA RESULTS BUCKET NAME]
      Roles:
        - !Ref KadaAthenaRole

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• DBT Cloud

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Step 1: Create the Source in K

Create an Athena DBT Cloud source in K

• Go to Settings, Select Sources and click Add Source

• Select “Load from File system” option
  

  Image RemovedImage Added

• Give the source a Name - e.g. Athena DBT Cloud Production

• Add the Host name for the Athena DBT Cloud Server

• Click Finish Setup

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2: Getting Access to the Source Landing Directory

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3: Install the Collector

It is recommended to use a python environment such as pyenv or pipenv if you are not intending to install this package at the system level.

Some python packages also have dependencies on the OS level packages, so you may be required to install additional OS packages if the below fails to install.

You can download the Latest Core Library and whl via Platform Settings → Sources → Download Collectors

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Run the following command to install the collector

pip install kada_collectors_extractors_athena-3.0.0-py3-<version>-none-any.whl

You will also need to install the common library kada_collectors_lib -1.0.0 for this collector to function properly.

pip install kada_collectors_lib-1.0.0-py3<version>-none-any.whl

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Under the covers this uses boto3 and may have OS dependencies see https://boto3.amazonaws.com/v1/documentation/api/latest/guide/quickstart.html

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Step 4: Configure the Collector

The collector requires a set of parameters to connect to and extract metadata from AthenaDBT Cloud

{
    "60125": "af33141.australia-east.azure",
    "76e1e02270ddad585ed8ebf607230deeb779b3e5": "af33141.australia-east.azure"
}

These parameters can be added directly into the run or you can use pass the parameters in via a JSON file. The following is an example you can use that is included in the example run code below.

kada_athenadbt_extractor_config.json

{
    "keyaccount_id": "",
    "secrettoken": "",
    "serveroutput_path": "athena",
    "bucket": "s3://examplebucket/examplefolder/tmp/output",
    "catalogstimeout": ["AwsDataCatalog"]20,
    "regionmapping": "ap-southeast-2"{},
    "role": "",
    "output_path": "/tmp/output",
    "mask": truedry_run": false,
    "compress": true
}

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5: Run the Collector

The following code is an example of how to run the extractor. You may need to uplift this code to meet any code standards at your organisation.

This can be executed in any python environment where the whl has been installed. It will produce and read a high water mark file from the same directory as the execution called athenadbt_hwm.txt and produce files according to the configuration JSON.

This is the wrapper script: kada_athenadbt_extractor.py

import os
import argparse
from kada_collectors.extractors.utils import load_config, get_hwm, publish_hwm, get_generic_logger
from kada_collectors.extractors.athenadbt import Extractor

get_generic_logger('root') # Set to use the root logger, you can change the context accordingly or define your own logger

_type = 'athenadbt'
dirname = os.path.dirname(__file__)
filename = os.path.join(dirname, 'kada_{}_extractor_config.json'.format(_type))

parser = argparse.ArgumentParser(description='KADA AthenaDBT Extractor.')
parser.add_argument('--config', '-c', dest='config', default=filename, help='Location of the configuration json, default is the config json in the same directory as the script.')
args = parser.parse_args()

start_hwm, end_hwm = get_hwm(_type)

ext = Extractor(**load_config(args.config))
ext.test_connection()
ext.run(**{"start_hwm": start_hwm, "end_hwm": end_hwm})

publish_hwm(_type, end_hwm)

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If you are handling external arguments of the runner yourself, you’ll need to consider additional items for the run method. Refer to this document for more information https://kadaai.atlassian.net/wiki/spaces/KSL/pages/1902411777/Additional+Notes#The-run-method

from kada_collectors.extractors.snowflake import Extractor

kwargs = {my args} # However you choose to construct your args
hwm_kwrgs = {"start_hwm": "end_hwm": } # The hwm values

ext = Extractor(**kwargs)
ext.run(**hwm_kwrgs)

class Extractor(keytoken: str = None, secretaccount_id: str = None, servermapping: strdict = None{}, \
      buckettimeout: strint = None10, catalogsdry_run: listbool = ['AwsDataCatalog'], \
      region: str = 'ap-southeast-2', role: str = None, \
      False, output_path: str = './output', mask: bool = False, compress: bool = False) -> None

key: AWS Access Key.
secret: AWS Secret.
region: Region.
server: Athena host that was onboarded on K.
role: AWS Role ARN if required to assume a role. bucket: s3 bucket used to temporary store results in the form s3://xxx.
catalogs: list of Catalogs from Athena to extract, by default this is just AwsDataCatalog.ktoken: DBT Cloud Read Only API Token.
account_id: account ID DBT Cloud, should be a numeric ID.
mapping: Dict of project ids to corresponding database hosts
timeout: Timeout for the API call
dry_run: Run the extractor for the purpose of producing
output_path: full or relative path to where the outputs should go
compress: To gzip output files or not

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6: Check the Collector Outputs

K Extracts

A set of files (eg metadata, databaselog, linkages, events etc) will be generated. These files will appear in the output_path directory you set in the configuration details

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A high water mark file is created in the same directory as the execution called athenadbt_hwm.txt and produce files according to the configuration JSON. This file is only produced if you call the publish_hwm method.

If you want prefer file managed hwm, you can edit the location of the hwn by following these instructions https://kadaai.atlassian.net/wiki/spaces/DATKSL/pages/18943181521902411777/Notes+v2.0.0#Storing-HWM-in-another-location

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Additional+Notes#Storing-High-Water-Marks-(HWM)

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Step 7: Push the Extracts to K

Once the files have been validated, you can push the files to the K landing directory.

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