Oracle Database (via Collector method) - v.3.0.0

About Collectors

Collector Method

Pre-requisites

Python 3.6 - 3.10
Access to K Landing Directory
Access to Oracle (see section below)

Oracle Access

Create an Oracle user with read access to following tables

dba_hist_active_sess_history
dba_hist_snapshot
dba_users
dba_hist_sqltext
dba_mviews
dba_views
dba_procedures
dba_constraints
dba_cons_columns
dba_tab_columns
dba_audit_trail (If you do not have Auditing configured, speak to KADA about it.)
dba_tab_privs
dba_role_privs
dba_roles
proxy_users_and_roles
dba_synonyms

Check the MAX_STRING_SIZE option in the database , if it is not of type EXTENDED and you are unable to change it, you will need to alter the DDL_SQL used by the extractor and change from 32767 to the maximum supported value in MAX_STRING_SIZE instead. If this is not aligned you will see an ORA-00910: specified length is too long for its datatype will be thrown.

You have the option to create a wallet if you are using Oracle Cloud for authentication, otherwise this integration will use a username and password.

If you are using TNSNAMES ensure the tnsnames.ora file is up to date with the correct entries to be referenced.

You can connect 3 ways.

Host/servicename
TNSNAME in the tnsnames.ora file
A connection descriptor

Step 1: Create the Source in K

Create a Oracle source in K

Go to Settings, Select Sources and click Add Source
Select “Load from File” option
Give the source a Name - e.g. Oracle Production
Add the Host name for the Oracle Server
Click Finish Setup

Step 2: Getting Access to the Source Landing Directory

Collector Method

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 may require an ODBC package for the OS to be installed as well as an oracle client library package if do you not have one already, see https://www.oracle.com/au/database/technologies/instant-client.html

Step 4: Configure the Collector

The collector requires a set of parameters to connect to and extract metadata from Oracle

FIELD	FIELD TYPE	DESCRIPTION	EXAMPLE

FIELD	FIELD TYPE	DESCRIPTION	EXAMPLE
username	string	Username to log into Oracle	“myuser”
password	string	Password to log into Oracle
dsn	string	Datasource Name for Oracle, this can be one of the following forms <tnsname> <host/servicename>	“preprod” “local.example.com/oraservice”
oracle_client_path	string	Full path to the location of the Oracle Client libraries	“/tmp/drivers/lib/oracleinstantclient_11_9”
oracle_major_version	string	We currently support 11g and 12c, 11g has different SQL scripts so be very careful when setting this value	12c
database_name	string	The database name as onboarded in K, it is important that it matches so the objects are created correctly	“mykdatabase”
host_name	string	The host name as onboarded in K, it is important that it matches so the objects are created correctly	“mykhost”
wallet_path	string	If you use Oracle wallets, then this is the location of the wallet, ensure that the sqlora.net file references the wallet locaton correctly. If you do not use wallets, leave this blank.	“/tmp/drivers/oracle/wallet”
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

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_oracle_extractor_config.json

{
    "username": "",
    "password": "",
    "dsn": "",
    "oracle_client_path": "",
    "oracle_major_version": "12c",
    "database_name": "",
    "host_name": "",
    "wallet_path": "",
    "output_path": "/tmp/output",
    "mask": true
    "compress": true
}

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 code sample uses the kada_oracle_extractor_config.json for handling the configuration details

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

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 oracle_hwm.txt and produce files according to the configuration JSON. This file is only produced if you call the publish_hwm method.

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

Collector Method