Scroll ignore | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||||||
About Collectors
Insert excerpt | ||||||
---|---|---|---|---|---|---|
|
...
Pre-requisites
...
Python 3.6 - 3.10
...
Access to the KADA Collector repository that contains the MySQL 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 MySQL whl (e.g. kada_collectors_extractors_mySQL-#.#.#-py3-none-any.whl)
...
Access to K landing directory
...
Collector Server Minimum Requirements
Insert excerpt | ||||||||
---|---|---|---|---|---|---|---|---|
|
MySQL Requirements
Access to MySQL. Supported MySQL versions include:
5.7x
8.0x
Access to the following Information Schema tables
INFORMATION_SCHEMA.VIEWS
INFORMATION_SCHEMA.TABLES
INFORMATION_SCHEMA.COLUMNS
INFORMATION_SCHEMA.KEY_COLUMN_USAGE
...
Step 1: Enabling logging (if desired)
Info |
---|
See more information about logging here - https://dev.mysql.com/doc/refman/8.0/en/log-destinations.html Note this study Impact of General Query Log on MySQL Performance and the performance impact of enabling logging. |
Enable global logging
Code Block |
---|
SET GLOBAL log_output = 'TABLE'; SET GLOBAL general_log = 'ON'; |
...
Code Block |
---|
SET @old_log_state = @@GLOBAL.general_log; SET GLOBAL general_log = 'OFF'; ALTER TABLE mysql.general_log ENGINE = MyISAM; ALTER TABLE mysql.slow_log ENGINE = MyISAM; ALTER TABLE mysql.general_log ADD INDEX (event_time); ALTER TABLE mysql.slow_log ADD INDEX (start_time); SET GLOBAL general_log = @old_log_state; |
Note this study Impact of General Query Log on MySQL Performance and the performance impact of enabling logging.
...
Step 2: Create the Source in K
...
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
Code Block |
---|
pip install kada_collectors_extractors_mysql-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.
Code Block |
---|
pip install kada_collectors_lib-1.0.0-py3<version>-none-any.whl |
...
Step 5: Configure the Collector
...
The MySQL collector only extracts metadata and does not extract or process query usage on the database.
FIELD | FIELD TYPE | DESCRIPTION | EXAMPLE |
---|---|---|---|
username | string | Username to log into MySQL | “myuser” |
password | string | Password to log into MySQL | “password” |
server | string | The server to connect to the MySQL instance, if the MySQL instance uses a port other than the default port, use a comma to indicate the port e.g. local.example.com,3309 | “local.example.com,3309” |
host_name | string | The onboarded host in K for the MySQL Source | “local.example.com” |
database_name | string | The onboarded database name in K for the MySQL Source, this will be the same as the source name for MySQL | “mysqldb” |
meta_only | boolean | If logging is not enabled, set this to true | true |
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 |
compress | boolean | To enable compression or not to .csv.gz | true |
use_ssl | boolean | If the MySQL instances uses SSL | 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.
...
This is the wrapper script: kada_mysql_analytics_extractor.py
Code Block |
---|
import os import argparse from kada_collectors.extractors.utils import load_config, get_hwm, publish_hwm, get_generic_logger from kada_collectors.extractors.oracle_analyticsmysql import Extractor get_generic_logger('root') # Set to use the root logger, you can change the context accordingly or define your own logger _type = 'mysql' dirname = os.path.dirname(__file__) filename = os.path.join(dirname, 'kada_{}_extractor_config.json'.format(_type)) parser = argparse.ArgumentParser(description='KADA MySQL 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) |
...
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 https://kadaai.atlassian.net/wiki/spaces/KSL/pages/1902411777/AdditionalCollector+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 https://kadaai.atlassian.net/wiki/spaces/KSL/pages/1902411777/AdditionalCollector+Integration+General+Notes#The-run-method
Code Block |
---|
from kada_collectors.extractors.mysql 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) |
...
If you want prefer file managed hwm, you can edit the location of the hwn by following these instructions Additional Collector Integration General Notes
...
Step 8: Push the Extracts to K
...