SSIS (Collector method) - v3.1.0
About Collectors
Collectors are extractors that are developed and managed by you (A customer of K).
KADA provides python libraries that customers can use to quickly deploy a Collector.
Why you should use a Collector
There are several reasons why you may use a collector vs the direct connect extractor:
You are using the KADA SaaS offering and it cannot connect to your sources due to firewall restrictions
You want to push metadata to KADA rather than allow it pull data for Security reasons
You want to inspect the metadata before pushing it to K
Using a collector requires you to manage
Deploying and orchestrating the extract code
Managing a high water mark so the extract only pull the latest metadata
Storing and pushing the extracts to your K instance.
Pre-requisites
Collector Server Minimum Requirements
SSIS Requirements
MSDB database / SQLServer DB access
if using SSISDB to store package you will need to download each project via SQL Server Management Studio. See SSIS (Collector method) - v3.1.0 | Downloading SSISDB packages
The collector will need access to the underlying SQLServer Database with permissions to read the following tables is the SSIS main databases:
MSDB.DBO.SYSSSISPACKAGES
<SSIS Logging Database>.DBO.SYSSSISLOG where <SSIS Logging Database> is the database configured for SSIS logging
Check your SSIS instance port
Run the following query and note the local tcp port.
SELECT local_tcp_port FROM sys.dm_exec_connections WHERE session_id = @@SPID GO
Downloading SSISDB packages
In SQL Server Studio Manager Go to Integration Services Catalog > Projects.
Right click on a Project > Export…
Save project file
Change the file extraction from
.ispac
to.zip
Repeat for each project.
Step 1: Create the Source in K
Create a SSIS 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. SSIS Production
Add the Host name for the SSIS Server
Click Finish Setup
Step 2: Getting Access to the Source Landing Directory
Step 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.
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
Run the following command to install the collector
pip install kada_collectors_extractors_<version>-none-any.whl
You will also need to install the common library kada_collectors_lib for this collector to function properly.
pip install kada_collectors_lib-<version>-none-any.whl
You will also need an ODBC package installed at the OS level for pyodbc to use as well as a SQLServer ODBC driver, refer to Download ODBC Driver for SQL Server - ODBC Driver for SQL Server
Step 4: Configure the Collector
The collector requires a set of parameters to connect to and extract metadata from SSIS.
FIELD | FIELD TYPE | DESCRIPTION | EXAMPLE |
---|---|---|---|
server | string | SQLServer server host Note if the default port is not used append the port to the server name. Example
| “10.1.18.19” |
username | string | Username to log into the SQLServer account | “myuser” |
password | string | Password to log into the SQLServer account |
|
logging_database | string | Database where the SSIS Logging has been setup | “ssis_logging” |
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 |
driver | string | This is the ODBC driver, generally its ODBC Driver 17 for SQL Server, if you another driver installed please use that instead | “ODBC Driver 17 for SQL Server” |
output_path | string | Absolute path to the output location where files are to be written | “/tmp/output” |
input_path | string | Absolute path to the input folder where SSISDB project zips are extract to. See SSIS (Collector method) - v3.1.0 | Downloading SSISDB packages Note that within this folder there should be seperate folders for each project and the .manifest/.dtsx/.conmgr (conmgr may or may nor be applicable) files should sit within this folder, for e.g.
| “/tmp/input” |
mask | boolean | To enable masking or not | true |
compress | boolean | To gzip the output or not | true |
uses_ssissdb | boolean | Are packages deployed to ssisdb or msdb? | false |
meta_only | boolean | Do you wish to extract metadata only and don’t want to set up logging for SSIS packages? | false |
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_ssis_extractor_config.json
Step 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.
This is the wrapper script: kada_ssis_extractor.py
This code will produce and read a high water mark file from the same directory as the execution called ssis_hwm.txt and produce files according to the configuration JSON.
Advance options:
If you wish to maintain your own high water mark files elsewhere you can use the above section’s script as a guide on how to call the extractor. The configuration file is simply the keyword arguments in JSON format. Refer to this document for more information Collector Integration General Notes | Storing HWM in another location
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 Collector Integration General Notes | The run method
username: username to sign into sqlserver
password: password to sign into sqlserver
server: sqlserver host
driver: sqlserver driver name
logging_database: Logging Database name for SSIS
mapping: Dict of DNS to database and hostnames
output_path: full or relative path to where the outputs should go
input_path: full or relative path to where the dstx files should be
mask: To mask the META/DATABASE_LOG files or not
compress: To gzip output files or not
uses_ssisdb: Are packages published to ssisdb or msdb?
meta_only: Option to extract metadata only
Step 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
High Water Mark File
A high water mark file is created in the same directory as the execution called ssis_hwm.txt and produce files according to the configuration JSON. This file is only produced if you call the publish_hwm method. Collector Integration General Notes | Storing the HWM using the K Landing Area
Step 7: Push the Extracts to K
Once the files have been validated, you can push the files to the K landing directory.
You can use Azure Storage Explorer if you want to initially do this manually. You can push the files using python as well (see Airflow example below)
Example: Using Airflow to orchestrate the Extract and Push to K