A tool to compare data from different sources.
Project description
A utility to compare tables, espacially useful to perform validations for migration projects.
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Functionality
The basic functionality of tulona is to compare datasets, write them into Excel files and highlight the mismatches.
Connection Profiles
Connection profiles is a yaml file that will store credentials and other details to connect to the databases/data sources.
It must be setup in profiles.yml file and it must be placed under $HOME/.tulona dierctory. Create a directory named .tulona under your home directory and place profiles.yml under it.
This is what a sample profiles.yml looks like:
integration_project: # project_name
profiles:
pgdb:
type: postgres
host: localhost
port: 5432
database: postgres
username: postgres
password: postgres
mydb:
type: mysql
host: localhost
port: 3306
database: db
username: user
password: password
snowflake:
type: snowflake
account: snowflake_account
warehouse: dev_x_small
role: dev_role
database: dev_stage
schema: user_schema
user: dev_user
private_key: 'rsa_key.p8'
private_key_passphrase: 444444
mssql:
type: mssql
connection_string: 'DRIVER={ODBC Driver 18 for SQL Server};SERVER=dagger;DATABASE=test;UID=user;PWD=password'
Project Config File
Project config file stores the properties of the tables that need to be compared. It must be created in tulona-project.yml file and this file can be placed anywhere and that directory will be considered project root directory. Which means that the output` folder will be created under that directory where all results will be stored. It’s always a good idea to create an empty directory and store tulona-project.yml under it.
This is how a tulona-project.yml file looks like:
version: '2.0'
name: integration_project
config_version: 1
outdir: output # optional
# Datasource names must be unique
datasources:
employee_postgres:
connection_profile: pgdb
database: postgresdb
schema: corporate
table: employee
primary_key: Employee_ID
exclude_columns:
- Email
- Name
compare_column: Employee_ID
employee_mysql:
connection_profile: mydb
schema: corporate
table: employee
primary_key: Employee_ID
exclude_columns:
- Phone_Number
compare_column: Employee_ID
person_postgres:
connection_profile: pgdb
database: postgresdb
schema: corporate
table: people_composite_key
primary_key:
- ID_1
- ID_2
# exclude_columns:
# - name
compare_column:
- ID_1
- ID_2
person_mysql:
connection_profile: mydb
schema: corporate
table: people_composite_key
primary_key:
- ID_1
- ID_2
# exclude_columns:
# - phone_number
compare_column:
- ID_1
- ID_2
postgresdb_postgres:
connection_profile: pgdb
database: postgresdb
none_mysql:
connection_profile: mydb
postgresdb_postgres_schema:
connection_profile: pgdb
database: postgresdb
schema: corporate_copy
none_mysql_schema:
connection_profile: mydb
schema: corporate
employee_postgres_query:
connection_profile: pgdb
database: postgresdb
schema: corporate
query: select * from postgresdb.corporate.employee
primary_key: Employee_ID
exclude_columns:
- name
compare_column: Employee_ID
employee_mysql_query:
connection_profile: mydb
schema: corporate
query: select * from corporate.employee
primary_key: Employee_ID
exclude_columns:
- phone_number
compare_column: Employee_ID
employee_postgres_query_tab:
connection_profile: pgdb
database: postgresdb
schema: corporate
table: employee
query: select * from postgresdb.corporate.employee
primary_key: Employee_ID
exclude_columns:
- name
compare_column: Employee_ID
employee_mysql_query_tab:
connection_profile: mydb
schema: corporate
table: employee
query: select * from corporate.employee
primary_key: Employee_ID
exclude_columns:
- phone_number
compare_column: Employee_ID
# List of task configs(Dict)
# Depending on the accepted params, task config can have different params
# The value for that `task` key is the name of the command you want to run
task_config:
- task: ping
datasources:
- person_postgres
- none_mysql
- employee_mysql_query
- task: profile
datasources:
- employee_postgres
- employee_mysql
compare: true
- task: profile
datasources:
- person_postgres
- person_mysql
- task: compare-row
datasources:
- employee_postgres
- employee_mysql
sample_count: 30
- task: compare-row
datasources:
- employee_postgres
- employee_mysql
- task: compare-row
datasources:
- employee_postgres_query
- employee_mysql_query
- task: compare-column
datasources:
- employee_postgres
- employee_mysql
- task: compare-column
datasources:
- person_postgres
- person_mysql
composite: false # If it's false, specifying it is optional
- task: compare-column
datasources:
- person_postgres
- person_mysql
composite: true
- task: compare
datasources:
- employee_postgres
- employee_mysql
composite: true
- task: compare
datasources:
- person_postgres
- person_mysql
composite: true
sample_count: 30
- task: scan
datasources:
- postgresdb_postgres_schema
- task: scan
datasources:
- postgresdb_postgres
- none_mysql
compare: false
- task: scan
datasources:
- postgresdb_postgres_schema
- none_mysql_schema
compare: true
- task: scan
datasources:
- postgresdb_postgres
- none_mysql
compare: true
- task: compare
datasources:
- employee_postgres_query_tab
- employee_mysql_query_tab
Features
Executing tulona or tulona -h or tulona –help returns available commands. If you don’t setup task_config, all commands take one mandatory parameter, –datasources, a comma separated list of names of datasources from project config file (tulona-project.yml).
Tulona has following commands available:
ping: To test connectivity to the databases for the datasources. Sample command:
To ping one data source pass the name to the –datasources parameter:
tulona ping --datasources employee_postgres
More than one datasources can be passed to the –datasources parameter separated by commas:
tulona ping --datasources employee_postgres,employee_mysql
To ping all the datasources, just skip the –datasources parameter:
tulona ping
profile: To extract and compare metadata of two sources/tables. It includes metadata from information_schema related to the tables and some column level metrics (min, max, average, count & distinct_count). Note that specifying database, schema and table is required for profile to work regardless the use of query. Sample commands:
Profiling without –compare flag. It will write metadata and metrics about different sources/tables in different sheets/tabs in the excel file (not a comparison view):
tulona profile --datasources employee_postgres,employee_mysql
Profiling with –compare flag. It will produce a comparison view (side by side):
tulona profile --compare --datasources employee_postgres,employee_mysql
Sample output will be something like this:
compare-row: To compare sample data from two sources/tables/queries. It will create a comparative view of all common columns from both sources/tables side by side (like: id_ds1 <-> id_ds2) and highlight mismatched values in the output excel file. By default it compares 20 common rows from both tables (subject to availabillity) but the number can be overridden with the command line argument –sample-count. Command samples:
Command without –sample-count parameter:
tulona compare-row --datasources employee_postgres,employee_mysql
Command with –sample-count parameter:
tulona compare-row --sample-count 50 --datasources employee_postgres,employee_mysql
Compare queries instead of tables, useful when you want to compare resutls of two queries:
tulona compare-row --datasources employee_postgres_query,employee_mysql_query
Sample output will be something like this:
compare-column: To compare columns from tables from two sources/tables. This is expecially useful when you want see if all the rows from one table/source is present in the other one by comparing the primary/unique key. The result will be an excel file with extra primary/unique keys from both sides. If both have the same set of primary/unique keys, essentially means they have the same rows, excel file will be empty. Command samples:
Column[s] to compare is[are] specified in tulona-project.yml file as part of datasource configs, with compare_column property. Sample command:
tulona compare-column --datasources employee_postgres,employee_mysql
Compare multiples columns as composite key (combination of column values will be compared) with additional –composite flag:
tulona compare-column --composite --datasources employee_postgres,employee_mysql
Sample output will be something like this:
compare: To prepare a comparison report for evrything together. To executed this command just swap the command from any of the above commands with compare. It will prepare comparison of everything and write them into different sheets of a single excel file. Sample command:
tulona compare --datasources employee_postgres,employee_mysql
scan: To scan and compare databases or schemas in terms of metadata and tables present if you want to compare all tables and don’t want to set up datasource config for all of them. Sample commands:
Scan without comparing:
tulona scan --datasources postgresdb_postgres_schema,none_mysql_schema
Scan and compare:
tulona scan --compare --datasources postgresdb_postgres_schema,none_mysql_schema
run: To execute all the tasks defined in the task_config section. Sample command:
tulona run
If you setup task_config, there is no need to pass the –datasources parameter. In that case the following command (to compare some datasoruces):
tulona compare --datasources employee_postgres,employee_mysql
will become this:
tulona compare
and it will run all the compare tasks defined in the task_config section. From our example project config file above, it will run 2 compare tasks.
Also setting up task_config can be greatly benificial as you can set up different instance of same/different tasks with different config to execute in one go with the run command.
Please look at the sample project config from above to understand how to set up task_config property.
To know more about any specific command, execute tulona <command> -h.
Supported Data Platforms
Platform |
Adapter Name |
Supported Auth Mechanism |
---|---|---|
Postgres |
postgres |
Connection string, Password |
MySQL |
mysql |
Connection string, Password |
Snowflake |
snowflake |
Password, Key pair, SSO (Externalbrowser) |
Microsoft SQL Server |
mssql |
Connection string |
Development Environment Setup
For live installation execute pip install -e “.[dev]”.
Build Wheel Executable
Execute python -m build.
Install Wheel Executable File
Execute pip install <wheel-file.whl>
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