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About Collectors
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Pre-requisites
Python 3.6 8 - 3.10
Access to the KADA Collector repository that contains the 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 DBT whl (e.g. kada_collectors_extractors_dbt-#.#.#-py3-none-any.whl)Access to K landing directory
Access toDBT Cloud
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You can download the Latest Core Library and Athena whl via Platform Settings → Sources → Download Collectors
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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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The collector requires a set of parameters to connect to and extract metadata from DBT Cloud
FIELD | FIELD TYPE | DESCRIPTION | EXAMPLE | ||
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account_id | string | DBT cloud account Id | “xxxxx.australia-east.azure” | ||
environment_ids | list<string> | List of environment Ids to extract | 12345,234234 | ||
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.
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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.dbt import Extractor
get_generic_logger('root') # Set to use the root logger, you can change the context accordingly or define your own logger
_type = 'dbt'
dirname = os.path.dirname(__file__)
filename = os.path.join(dirname, 'kada_{}_extractor_config.json'.format(_type))
parser = argparse.ArgumentParser(description='KADA DBT 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.')
parser.add_argument('--name', '-n', dest='name', default=_type, help='Name of the collector instance.')
args = parser.parse_args()
start_hwm, end_hwm = get_hwm(_typeargs.name)
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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