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About Collectors

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• Python 3.6 - 3.10

• Access to the KADA Collector repository that contains the Athena 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 Athena MySQL whl (e.g. kada_collectors_extractors_athenamySQL-#.#.#-py3-none-any.whl)

• Access to K landing directory

• Access to Athena

Step 1: Establish Athena Access

The service user/account/role will require permissions to the following

1. Execute queries against Athena with access to the INFORMATION_SCHEMA in particular the following tables:

   1. information_schema.views

   2. information_schema.tables

   3. information_schema.columns

2. 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.

3. Call the following Athena APIs

   1. list_databases

   2. list_table_metadata

   3. list_query_executions

   4. list_work_groups

   5. batch_get_query_executions

   6. start_query_execution

   7. get_query_execution

4. 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.

5. 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.

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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• MySQL. Supported MySQL versions include:

  • 5.7x

  • 8.0x

• Access to the following Information Schema tables

  1. INFORMATION_SCHEMA.VIEWS

  2. INFORMATION_SCHEMA.TABLES

  3. INFORMATION_SCHEMA.COLUMNS

  4. INFORMATION_SCHEMA.KEY_COLUMN_USAGE

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Step 1: Enabling logging (if desired)

https://dev.mysql.com/doc/refman/8.0/en/log-destinations.html

Enable global logging

SET GLOBAL log_output = 'TABLE';
SET GLOBAL general_log = 'ON';

Change logging tables from reading CSV files to MyISAM Engine for performance

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.

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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
  

  Image RemovedImage Added

• 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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pip install kada_collectors_extractors_athenamysql-3.0.0-py3-none-any.whl

You will also need to install the common library kada_collectors_lib-1.0.0 for this collector to function properly.

pip install kada_collectors_lib-1.0.0-py3-none-any.whl

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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.

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

{
    "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_mysql_athenaanalytics_extractor.py

import os
import argparse
from kada_collectors.extractors.utils import load_config, get_hwm, publish_hwm, get_generic_logger
from kada_collectors.extractors.athenaoracle_analytics 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.')
args = parser.parse_args()

start_hwm, end_hwm = get_hwm(_type)

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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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', role: str = None./output', \
      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 Additional Notes

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Step 8: Push the Extracts to K

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