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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 DBT Cloud 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 DBT whl (e.g. kada_collectors_extractors_athenadbt-#.#.#-py3-none-any.whl)
Access to K landing directory
Access to Athena
Step 1: Establish Athena Access
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It is advised you create a new Role and a separate s3 bucket for the service user provided to KADA and have a policy that allows the below, see Identity and access management in Athena - Amazon Athena |
The service user/account/role will require permissions to the following
Execute queries against Athena with access to the INFORMATION_SCHEMA in particular the following tables:
information_schema.views
information_schema.tables
information_schema.columns
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.Call the following Athena APIs
list_databases
list_table_metadata
list_query_executions
list_work_groups
batch_get_query_executions
start_query_execution
get_query_execution
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.
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.
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Note that user usage will be associated to the workgroup level rather than individual users, these workgroups are published as users in K in the form “athena_workgroup_<name>” |
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
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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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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
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.
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pip install kada_collectors_extractors_athenadbt-3.0.0-py3-none-any.whl |
You will also need to install the common library kada_collectors_lib-1.0.0 for this collector to function properly.
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pip install kada_collectors_lib-1.0.0-py3-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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These are some known possible packages you may require depending on your OS, this is not exhaustive and only serves as a guide. |
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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
FIELD | FIELD TYPE | DESCRIPTION | EXAMPLE | ||
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keyaccount_id | string | Key for the AWS user | “xcvsdsdfsdf” | ||
secret | string | Secret for the AWS user | “sgsdfdsfg” | ||
server | string | This is the host that was onboarded in K for Athena | “athena.cloud” | ||
bucket | string | Bucket location to temporary store Athena query results, the extractor will use the user to execute queries and store results in this bucket location, it should be the full path starting with s3:// | “s3://mybucket/myathenaresults” | ||
catalogs | list<string> | List of catalogs to extract from Athena, most cases this is only AwsDataCatalog unless you have self managed catalogs. | [“AwsDataCatalog”] | ||
region | string | Set the region for AWS for where Athena exists | ap-southeast-2 | ||
role | string | If your access requires role assumption, place the full arn value here, otherwise leave it blank | “” | ||
output_path | string | Absolute path to the output location where files are to be written | “/tmp/output” | ||
mask | boolean | To enable masking or not | trueDBT cloud account Id | “xxxxx.australia-east.azure” | |
token | string | Generated token from the DBT console |
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output_path | string | Absolute path to the output location where files are to be written | “/tmp/output” | ||
timeout | integer | By default we allow 20 seconds for the API to respond, for slower connections it may take longer, so adjust accordingly. | 20 | ||
mapping | JSON | Mapping between DBT project ids and their corresponding database host value in K. | The keys are DBT project ids where as the host is corresponding onboarded host in K
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dry_run | boolean | If you enable dry run, the extractor will simply produce the mapping.json file only which helps you map all your projects to a corresponding database host. | false | ||
compress | boolean | To gzip the output or not | true |
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
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{ "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
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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
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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) |
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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/DAT/pages/1894318152/Notes+v2.0.0#Storing-HWM-in-another-location
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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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