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About Collectors
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Pre-requisites
Python 3.6 - 3.10
Access to the KADA Collector repository that contains the Athena 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 Athena whl (e.g. kada_collectors_extractors_athena-#.#.#-py3-none-any.whl)
Access to K landing directory
Access to Athena
Step 1: Establish Athena Access
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It is advised you create a new Role and a separate s3 bucket for the service user provided to KADA and have a policy that allows the below, see Identity and access management in Athena - Amazon Athena |
The service user/account/role will require permissions to the following
Execute queries against Athena with access to the INFORMATION_SCHEMA in particular the following tables:
information_schema.views
information_schema.tables
information_schema.columns
Executing queries in Athena requires an s3 bucket to temporary store results.
The policy must also allow Read Write Listing access to objects within that bucket, conversely, the bucket must also have policy to allow to do the same.Call the following Athena APIs
list_databases
list_table_metadata
list_query_executions
list_work_groups
batch_get_query_executions
start_query_execution
get_query_execution
The service user/account/role will need permissions to access all workgroups to be able to extract all data, if you omit workgroups, that information will not be extracted and you may not see the complete picture in K.
See IAM policies for accessing workgroups - Amazon Athena on how to add policy entries to have fine grain control at the workgroup level. Note that the extractor runs queries on Athena, If you do choose to restrict workgroup access, ensure that Query based actions (e.g. StartQueryExecution) are allowed for the workgroup the service user/account/role is associated to.
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Note that user usage will be associated to the workgroup level rather than individual users, these workgroups are published as users in K in the form “athena_workgroup_<name>” |
Example Role Policy to allow Athena Access with least privileges for actions, this example allows the ACCOUNT ARN to assume the role. Note the variables ATHENA RESULTS BUCKET NAME. You may also choose to just assign the policy directly to a new user and use that user without assuming roles. In the scenario you do wish to assume a role, please note down the role ARN to be used when onbaording/extracting
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Collector Server Minimum Requirements
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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
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Step 1: Enabling logging (if desired)
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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
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SET GLOBAL log_output = 'TABLE';
SET GLOBAL general_log = 'ON';
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Change logging tables from reading CSV files to MyISAM Engine for performance
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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;
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Step 2: Create the Source in K
Create an Athena MySQL 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. Athena Production MySQLProduction
Add the Host name for the Athena MySQL Server
Click Finish Setup
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Step 3: Getting Access to the Source Landing Directory
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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
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pip install kada_collectors_extractors_athena-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.
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pip install kada_collectors_lib-1.0.0-py3-<version>-none-any.whl |
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Under the covers this uses boto3 and may have OS dependencies see https://boto3.amazonaws.com/v1/documentation/api/latest/guide/quickstart.html |
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Step 5: Configure the Collector
The collector requires a set of parameters to connect to and extract metadata from AthenaMySQL.
The MySQL collector only extracts metadata and does not extract or process query usage on the database.
FIELD | FIELD TYPE | DESCRIPTION | EXAMPLE |
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username | string |
Key for the AWS user
“xcvsdsdfsdf”
secret
string
Secret for the AWS user
Username to log into MySQL | “myuser” | ||
password | string | Password to log into MySQL | “password” |
server | string |
This is the host that was onboarded in K for Athena
“athena.cloud”
bucket
string
Bucket location to temporary store Athena query results, the extractor will use the user to execute queries and store results in this bucket location, it should be the full path starting with s3://
“s3://mybucket/myathenaresults”
catalogs
list<string>
List of catalogs to extract from Athena, most cases this is only AwsDataCatalog unless you have self managed catalogs.
[“AwsDataCatalog”]
region
string
Set the region for AWS for where Athena exists
ap-southeast-2
role
string
If your access requires role assumption, place the full arn value here, otherwise leave it blank
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.
kada_athenamysql_extractor_config.json
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{ "keyusername": "", "secretpassword": "", "server": "athena", "buckethost_name": "s3://examplebucket/examplefolder", "catalogsdatabase_name": ["AwsDataCatalog"], "regionoutput_path": "ap-southeast-2/tmp/output", "rolemask": ""true, "output_path": "/tmp/output", "maskcompress": true, "compressuse_ssl": true } |
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Step 6: Run the Collector
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This can be executed in any python environment where the whl has been installed. It will produce and read a high water mark file from the same directory as the execution called athenamysql_hwm.txt and produce files according to the configuration JSON.
This is the wrapper script: kada_athenamysql_extractor.py
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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.athenamysql import Extractor get_generic_logger('root') # Set to use the root logger, you can change the context accordingly or define your own logger _type = 'athenamysql' dirname = os.path.dirname(__file__) filename = os.path.join(dirname, 'kada_{}_extractor_config.json'.format(_type)) parser = argparse.ArgumentParser(description='KADA AthenaMySQL 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) |
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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
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from kada_collectors.extractors.snowflakemysql 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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class Extractor(keyusername: str = None, secretpassword: str = None, server: str = None, \ bucketdatabase_name: str = None, catalogshost_name: liststr = ['AwsDataCatalog'], \ regionNone, output_path: str = 'ap-southeast-2./output', role: str = None, \ output_pathmask: strbool = './output'False, maskcompress: bool = False, compressmeta_only: bool = False) -> None |
key: AWS Access Key.
secret: AWS Secret.
region: Region.
server: Athena host that was onboarded on K.
role: AWS Role ARN if required to assume a role. bucket: s3 bucket used to temporary store results in the form s3://xxx.
catalogs: list of Catalogs from Athena to extract, by default this is just AwsDataCatalog.username: username to sign into mysql server
password: password to sign into mysql server
server: mysql server host
database_name: The MySQL database name, this should be the name you onboarded or will onboard into K with.
host_name: The MySQL host or address name, this should be the name you onboarded or will onboard into K with.
sql: The list of SQL queries that will be executed by the program
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 metadata only
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Step 7: Check the Collector Outputs
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A high water mark file is created in the same directory as the execution called athenamysql_hwm.txt and produce files according to the configuration JSON. This file is only produced if you call the publish_hwm method.
If you want prefer file managed hwm, you can edit the location of the hwn by following these instructions https://kadaai.atlassian.net/wiki/spaces/DAT/pages/1894318152/Notes+v2.0.0#Storing-HWM-in-another-location Collector Integration General Notes
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Step 8: Push the Extracts to K
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