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About Collectors
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Pre-requisites
Python 3.6 8 - 3.1011
Access to K landing directory
Access to Power BI (see section below)
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The collector requires a set of parameters to connect to and extract metadata from Power BI
FIELD | FIELD TYPE | DESCRIPTION | EXAMPLE | ||
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client | string | Onboarded client in Azure to access powerbi | |||
secret | string | Onboarded client secret in Azure to access powerbi | |||
tenant | string | Tenant ID of where powerbi exists | |||
output_path | string | Absolute path to the output location where files are to be written | “/tmp/output” | ||
mask | boolean | To enable masking or not | true | ||
timeout | integer | Timeout in seconds allowed against the powerbi APIs, for slower connections we recommend 30, default is 20 | 20 | ||
export_timeout | integer | Timeout in seconds allowed against the powerbi export pbix APIs, we recommend not setting this lower than 120 | 120 | ||
mapping | JSON | Mapping file of data source names against the onboarded host and database name in K | Assuming I have a “myDSN” data source name in powerbi, I’ll map it to host “myhost” and database “mydatabase” onboarded in K, snowflake type references are handled automatically
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filter_flag | boolean | Should we be filtering out workspaces based on filter_workspaces as a whitelist? | false | ||
filter_workspaces | list<string> | List of workspace names that should be processed, this is case insensitive. Note that personal workspaces are excluded globally and will never be included even if you include it here. | [“data lab”, “analysis models”] | ||
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.powerbi import Extractor
get_generic_logger('root') # Set to use the root logger, you can change the context accordingly or define your own logger
_type = 'powerbi'
dirname = os.path.dirname(__file__)
filename = os.path.join(dirname, 'kada_{}_extractor_config.json'.format(_type))
parser = argparse.ArgumentParser(description='KADA PowerBI 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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