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About Collectors

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Collector server minimum requirements

SQL Server Azure Synapse Requirements

Setting up SQL Server Azure Synapse for metadata extraction is a 2 step processusing a service principal (Application).

Step 1: Establish SQLServer Azure Synapse Access

CREATE LOGIN kadauser WITH password='PASSWORD';
CREATE USER kadauserUSER [<SERVICE_PRINCIPAL_NAME>] FROM LOGINEXTERNAL kadauserPROVIDER; 

CREATE USER kadauser[<SERVICE_PRINCIPAL_NAME>] FROM LOGINEXTERNAL kadauserPROVIDER;
GRANT VIEW DEFINITION TO kadauser[<SERVICE_PRINCIPAL_NAME>];
GRANT VIEW DATABASE STATE to kadauser;
GRANT CONTROL to kadauser;  -- required for extended events sys.fn_xe_file_target_read_fileTO [<SERVICE_PRINCIPAL_NAME>];

The following table should also be available to SELECT by the user created in each database

• INFORMATION_SCHEMA.ROUTINES

• INFORMATION_SCHEMA.VIEWS

• INFORMATION_SCHEMA.TABLE_CONSTRAINTS

• INFORMATION_SCHEMA.CONSTRAINT_COLUMN_USAGE

• INFORMATION_SCHEMA.TABLES

• INFORMATION_SCHEMA.COLUMNS

• INFORMATION_SCHEMA.VIEWS

• sys.foreign_key_columns

• sys.objects

• sys.tables

• sys.schemas

• sys.columns

• sys.databases

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Step

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An Azure SQL Admin will need to setup an extended events process to capture Query Execution in SQLServer.

Some tuning of the logging parameters may be needed depending on event volumes generated on your SQLServer instance.

First create or reuse an existing Azure Storage Account.

Then create a blob in the example the blob is called extended-events

Run the following script to setup Extended Events logging.

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Step 1: Create the Source in K

Create a source in K

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Step 2: Getting Access to the Source Landing Directory

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

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pip install kada_collectors_extractors_sqlserverazure_azuresynapse-x3.x0.x0-py3-none-any.whl

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

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The collector requires a set of parameters to connect to and extract metadata from SQLServer Azure Synapse.

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_sqlserverazure_azuresynapse_extractor_config.json

{
    "client": "",
    "serversecret": "",
    "usernametenant": "",
    "passwordserver": "",
    "databaseshost": [""],
    "driver": "ODBC Driver 17 for SQL Server",
    "databases": [""],
    "output_path": "/tmp/output",
    "mask": true,
    "compress": true,
    "meta_only": true,
    "host": "",
    "events_nameconnection_timeout": "KADA"30
}

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Step 5: Run the Collector

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This code sample uses the kada_sqlserverazure_azuresynapse_extractor.py for handling the configuration details

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

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

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

parser = argparse.ArgumentParser(description='KADA SqlServerAzure AzureSynapse 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(args.name)

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

publish_hwm(_typeargs.name, end_hwm)

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class Extractor(usernameclient: str = None, passwordsecret: str = None, servertenant: str = None, \
     driverserver: str = None, host: str = None, events_pathdriver: str = None, databases: list = [], \
  
 sqlserver_version: str = None, output_path: str = './output', mask: bool = False, compress: bool = False, \
    compressmeta_only: bool = False, eventsconnection_nametimeout: strint = None30) -> None

username: username to sign into sqlserver
password: password to sign into sqlserver
server: sqlserver hostclient: The Client ID for the registered application for access to Azure Synapse
secret: The Secret for the registered application for access to Azure Synapse
tenant: The Tenant ID for the registered application for access to Azure Synapse
server: Azure Synapse server
host: the onboarded host value in K, generally it will be the same as the server
driver: sqlserver driver name
databases: list of databases to extract
output_path: full or relative path to where the outputs should go
mask: To mask the META/DATABASE_LOG files or not
compress: To gzip output files or not
meta_only: To extract without extended events enabledor not
eventsconnection_name: Extended events session nametimeout: Synapse SQL Pool timeout for the connection in seconds

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Step 6: Check the Collector Outputs

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

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Example: Using Airflow to orchestrate the Extract and Push to K

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