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About Collectors

Collectors are extractors that are developed and managed by you (A customer of K).

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1. Deploying and orchestrating the extract code

2. Managing a high water mark so the extract only pull the latest metadata

3. Storing and pushing the extracts to your K instance.

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Pre-requisites

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Collector Server Minimum Requirements

SSRS Requirements

• Support SQL SSRS 2016+ where the database is called ReportServer$RS

  • if your SSRS databases differs from this, please Advise KADA of the SSRS version and what the database is called.

  • The collector will need access to the underlying SQLServer Database with permissions to read the following tables:

    • ReportServer$RS.DBO.CATALOG

    • ReportServer$RS.DBO.EXECUTIONLOG3

    • ReportServer$RS.DBO.USERS

• Access to K landing directory

• Access to the KADA Collector repository that contains the SSRS 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 SSRS whl (e.g. kada_collectors_extractors_ssrs-#.#.#-py3-none-any.whl)

Known SSRS Collector limitations

The following connection types are NOT currently supported:

1. Teradata IP Reference Only Data Source

2. SAP NetWeaver Data Source

3. XML Data Source

4. Web Service Data Source

5. XML Document Data Source

6. Sharepoint Data Source

The following catalog item types are currently NOT supported:

1. Linked Reports

2. Files

3. Power BI Desktop Files

4. Report Models

Parameter resolution is not supported.

SSAS query syntax is not supported

Some TSQL syntax is not support. These are mostly statements that contain not standard ANSI SQL constructs. Examples include:

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Variables (DECLARE)

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• Check your SSRS instance port

  • Run the following query and note the local tcp port.

    Code Block
    SELECT local_tcp_port FROM sys.dm_exec_connections WHERE session_id = @@SPID GO

Known SSRS Collector limitations

The following connection types are NOT currently supported:

1. Teradata IP Reference Only Data Source

2. SAP NetWeaver Data Source

3. XML Data Source

4. Web Service Data Source

5. XML Document Data Source

6. Sharepoint Data Source

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Step 1: Create the Source in K

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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_ssrs-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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The collector requires a set of parameters to connect to and extract metadata from SSRS.

{
        "myDSN": {
            "host": "myhost",
            "database": "mydatabase"
        }
    }

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.ssrs import Extractor

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

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

parser = argparse.ArgumentParser(description='KADA SSRS 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 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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If you are handling external arguments of the runner yourself, you’ll need to consider the following for the run method https://kadaai.atlassian.net/wiki/spaces/DATKSL/pages/18943181521902411777/Notes+v2.0.0#TheAdditional+Notes#Extractor-run-method

from kada_collectors.extractors.ssrs 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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A high water mark file is created in the same directory as the execution called ssrs_hwm.txt and produce files according to the configuration JSON. This file is only produced if you call the publish_hwm method. https://kadaai.atlassian.net/wiki/spaces/KSL/pages/1902411777/Additional+Notes#Storing-the-HWM-using-the-K-Landing-Area

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Step 7: Push the Extracts to K

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