adaptivescale / rosetta

Declarative Database Management - DDL Transpiler

rosetta

Declarative Database Management - DDL Transpiler

Overview

Rosetta is a declarative data modeler and transpiler that converts database objects from one database to another. Define your database in DBML and rosetta generates the target DDL for you.

Rosetta utilizes JDBC to extract schema metadata from a database and generates declarative DBML models that can be used for conversion to alternate database targets.

Generate DDL from a given source and transpile to the desired target.

Join RosettaDB Slack

Currently, supported databases and translations are shown below in the table.

	BigQuery	Snowflake	MySQL	Postgres	Kinetica	Google Cloud Spanner	SQL Server	DB2	Oracle
BigQuery	/	✅	✅	✅	✅	✅	✅	✅	✅
Snowflake	✅	/	✅	✅	✅	✅	✅	✅	✅
MySQL	✅	✅	/	✅	✅	✅	✅	✅	✅
Postgres	✅	✅	✅	/	✅	✅	✅	✅	✅
Kinetica	✅	✅	✅	✅	/	✅	✅	✅	✅
Google Cloud Spanner	✅	✅	✅	✅	✅	/	✅	✅	✅
SQL Server	✅	✅	✅	✅	✅	✅	/	✅	✅
DB2	✅	✅	✅	✅	✅	✅	✅	/	✅
Oracle	✅	✅	✅	✅	✅	✅	✅	✅	/

Getting Started

Prerequisites

You need the JDBC drivers to connect to the sources/targets that you will use with the rosetta tool. The JDBC drivers for the rosetta supported databases can be downloaded from the following URLs:

• BigQuery JDBC 4.2
• Snowflake JDBC 3.13.19
• Postgresql JDBC 42.3.7
• MySQL JDBC 8.0.30
• Kinetica JDBC 7.1.7.7
• Google Cloud Spanner JDBC 2.6.2
• SQL Server JDBC 12.2.0
• DB2 JDBC jcc4
• Oracle JDBC 23.2.0.0

ROSETTA_DRIVERS Environment

Set the ENV variable ROSETTA_DRIVERS to point to the location of your JDBC drivers.

export ROSETTA_DRIVERS=<path_to_jdbc_drivers>

example:

export ROSETTA_DRIVERS=/Users/adaptivescale/drivers/*

rosetta binary

1. Download the rosetta binary for the supported OS (releases page).

    rosetta-<version>-linux-x64.zip
    rosetta-<version>-mac_aarch64.zip
    rosetta-<version>-mac_x64.zip
    rosetta-<version>-win_x64.zip
   

2. Unzip the downloaded file
3. Run rosetta commands using ./rosetta which is located inside bin directory.
4. Create new project using rosetta init command:

   rosetta init database-migration

The rosetta init command will create a new rosetta project within database-migration directory containing the main.conf (for configuring the connections to data sources).

5. Configure connections in main.conf example: connections for postgres and mysql

# If your rosetta project is linked to a Git repo, during apply you can automatically commit/push the new version of your model.yaml
# The default value of git_auto_commit is false
git_auto_commit: false 
connections:
  - name: mysql
    databaseName: sakila
    schemaName:
    dbType: mysql
    url: jdbc:mysql://root:sakila@localhost:3306/sakila
    userName: root
    password: sakila
  - name: pg
    databaseName: postgres
    schemaName: public
    dbType: postgres
    url: jdbc:postgresql://localhost:5432/postgres?user=postgres&password=sakila
    userName: postgres
    password: sakila

6. Extract the schema from postgres and translate it to mysql:

   rosetta extract -s pg -t mysql

The extract command will create two directories pg and mysql. pg directory will have the extracted schema from Postgres DB. The mysql directory will contain the translated YAML which is ready to be used in MySQL DB.

7. Migrate the translated schema to MySQL DB:

   rosetta apply -s mysql

The apply command will migrate the translated Postgres schema to MySQL.

Rosetta DB YAML Config

YAML Config File

Rosetta by default expects the YAML config file to be named main.conf and looks for it by default in the current folder. The configuration file can be overridden by using the --config, -c command line argument (see Command Line Arguments below for more details).

Here is the list of available configurations in the main.conf file:

connections:
  # The name of the connection
  - name: bigquery_prod
    
    # The name of the default database to use
    databaseName: bigquery-public-data
    
    # The name of the default schema to use
    schemaName: breathe
    
    # The type of the database
    dbType: bigquery
    
    # The connection uri for the database
    url: jdbc:bigquery://[Host]:[Port];ProjectId=[Project];OAuthType= [AuthValue];[Property1]=[Value1];[Property2]=[Value2];...
    
    # The name of the database user
    userName: user

    # The password of the database user
    password: password

    # The name of tables to include which is optional
    tables:
      - table_one
      - table_two

In the YAML config file you can also use environment variables. An example usage of environment variables in config file:

connections:
  - name: snowflake_weather_prod
    databaseName: SNOWFLAKE_SAMPLE_DATA
    schemaName: WEATHER
    dbType: snowflake
    url: jdbc:snowflake://<account_identifier>.snowflakecomputing.com/?<connection_params>
    userName: ${USER}
    password: ${PASSWORD}

Example connection string configurations for databases

BigQuery (service-based authentication OAuth 0)

url: jdbc:bigquery://https://www.googleapis.com/bigquery/v2:443;ProjectId=<PROJECT-ID>;AdditionalProjects=bigquery-public-data;OAuthType=0;OAuthServiceAcctEmail=<EMAIL>;OAuthPvtKeyPath=<SERVICE-ACCOUNT-PATH>

BigQuery (pre-generated token authentication OAuth 2)

jdbc:bigquery://https://www.googleapis.com/bigquery/v2:443;OAuthType=2;ProjectId=<PROJECT-ID>;OAuthAccessToken=<ACCESS-TOKEN>;OAuthRefreshToken=<REFRESH-TOKEN>;OAuthClientId=<CLIENT-ID>;OAuthClientSecret=<CLIENT-SECRET>;

BigQuery (application default credentials authentication OAuth 3)

jdbc:bigquery://https://www.googleapis.com/bigquery/v2:443;OAuthType=3;ProjectId=<PROJECT-ID>;

Snowflake

url: jdbc:snowflake://<HOST>:443/?db=<DATABASE>&user=<USER>&password=<PASSWORD>

PostgreSQL

url: jdbc:postgresql://<HOST>:5432/<DATABASE>?user=<USER>&password=<PASSWORD>

MySQL

url: jdbc:mysql://<USER>:<PASSWORD>@<HOST>:3306/<DATABASE>

Kinetica

url: jdbc:kinetica:URL=http://<HOST>:9191;CombinePrepareAndExecute=1

Google Cloud Spanner

url: jdbc:cloudspanner:/projects/my-project/instances/my-instance/databases/my-db;credentials=/path/to/credentials.json

Google CLoud Spanner (Emulator)

url: jdbc:cloudspanner://localhost:9010/projects/test/instances/test/databases/test?autoConfigEmulator=true

SQL Server

url: jdbc:sqlserver://<HOST>:1433;databaseName=<DATABASE>

DB2

url: jdbc:db2://<HOST>:50000;<DATABASE>

ORACLE

url: jdbc:oracle:thin:<HOST>:1521:<SID>

Translation

This module will read the database structure from the source and map it to a target type. For example, source metadata was BigQuery and we want to convert it to Snowflake. This will be done by using a CSV file that contain mappings like in the following example:

345;;bigquery;;timestamp;;snowflake;;timestamp
346;;bigquery;;int64;;snowflake;;integer
347;;bigquery;;float64;;snowflake;;float
348;;bigquery;;array;;snowflake;;array
349;;bigquery;;date;;snowflake;;date
350;;bigquery;;datetime;;snowflake;;datetime
351;;bigquery;;boolean;;snowflake;;boolean
352;;bigquery;;time;;snowflake;;time
353;;bigquery;;geography;;snowflake;;geography
354;;bigquery;;numeric;;snowflake;;numeric
355;;bigquery;;bignumeric;;snowflake;;number
356;;bigquery;;bytes;;snowflake;;binary
357;;bigquery;;struct;;snowflake;;object

Using external translator

RosettaDB allows users to use their own translator. For the supported databases you can extend or create your version of translation CSV file. To use an external translator you need to set the EXTERNAL_TRANSLATION_FILE ENV variable to point to the external file.

Set the ENV variable EXTERNAL_TRANSLATION_FILE to point to the location of your custom translator CSV file.

export EXTERNAL_TRANSLATION_FILE=<path_to_csv_translator>

example:

export EXTERNAL_TRANSLATION_FILE=/Users/adaptivescale/translation.csv

Make sure you keep the same format as the CSV example given above.

Translation Attributes

Rosetta uses an additional file to maintain translation specific attributes. It stores translation_id, the attribute_name and attribute_value:

1;;302;;columnDisplaySize;;38
2;;404;;columnDisplaySize;;30
3;;434;;columnDisplaySize;;17

The supported attribute names are:

• ordinalPosition
• autoincrement
• nullable
• primaryKey
• primaryKeySequenceId
• columnDisplaySize
• scale
• precision

Set the ENV variable EXTERNAL_TRANSLATION_ATTRIBUTE_FILE to point to the location of your custom translation attribute CSV file.

export EXTERNAL_TRANSLATION_ATTRIBUTE_FILE=<path_to_csv_translator>

example:

export EXTERNAL_TRANSLATION_ATTRIBUTE_FILE=/Users/adaptivescale/translation_attributes.csv

Make sure you keep the same format as the CSV example given above.

Indices (Index)

Indices are supported in Google Cloud Spanner. An example on how they are represented in model.yaml

tables:
- name: "ExampleTable"
  type: "TABLE"
  schema: ""
  indices:
  - name: "PRIMARY_KEY"
    schema: ""
    tableName: "ExampleTable"
    columnNames:
    - "Id"
    - "UserId"
    nonUnique: false
    indexQualifier: ""
    type: 1
    ascOrDesc: "A"
    cardinality: -1
  - name: "IDX_ExampleTable_AddressId_299189FB00FDAFA5"
    schema: ""
    tableName: "ExampleTable"
    columnNames:
    - "AddressId"
    nonUnique: true
    indexQualifier: ""
    type: 2
    ascOrDesc: "A"
    cardinality: -1
  - name: "TestIndex"
    schema: ""
    tableName: "ExampleTable"
    columnNames:
    - "ClientId"
    - "DisplayName"
    nonUnique: true
    indexQualifier: ""
    type: 2
    ascOrDesc: "A"
    cardinality: -1

Rosetta Commands

Available commands

• init
• validate
• extract
• compile
• dbt
• diff
• test
• apply
• generate
• query

init

This command will generate a project (directory) if specified, a default configuration file located in the current directory with example connections for bigquery and snowflake, and the model directory.

rosetta init [PROJECT_NAME]

Parameter	Description
(Optional) PROJECT_NAME	Project name (directory) where the configuration file and model directory will be created.

Example:

#example with 2 connections
connections:
  - name: snowflake_weather_prod
    databaseName: SNOWFLAKE_SAMPLE_DATA
    schemaName: WEATHER
    dbType: snowflake
    url: jdbc:snowflake://<account_identifier>.snowflakecomputing.com/?<connection_params>
    userName: bob
    password: bobPassword
  - name: bigquery_prod
    databaseName: bigquery-public-data
    schemaName: breathe
    dbType: bigquery
    url: jdbc:bigquery://[Host]:[Port];ProjectId=[Project];OAuthType= [AuthValue];[Property1]=[Value1];[Property2]=[Value2];...
    userName: user
    password: password
    tables:
      - bigquery_table

validate

This command validates the configuration and tests if rosetta can connect to the configured source.

rosetta [-c, --config CONFIG_FILE] validate [-h, --help] [-s, --source CONNECTION_NAME]

Parameter	Description
-h, --help	Show the help message and exit.
-c, --config CONFIG_FILE	YAML config file. If none is supplied it will use main.conf in the current directory if it exists.
-s, --source CONNECTION_NAME	The source connection name to extract schema from.

extract

This is the command that extracts the schema from a database and generates declarative DBML models that can be used for conversion to alternate database targets.

rosetta [-c, --config CONFIG_FILE] extract [-h, --help] [-s, --source CONNECTION_NAME] [-t, --convert-to CONNECTION_NAME]

Parameter	Description
-h, --help	Show the help message and exit.
-c, --config CONFIG_FILE	YAML config file. If none is supplied it will use main.conf in the current directory if it exists.
-s, --source CONNECTION_NAME	The source connection name to extract schema from.
-t, --convert-to CONNECTION_NAME (Optional)	The target connection name in which source DBML converts to.

Example:

---
safeMode: false
databaseType: bigquery
operationLevel: database
tables:
- name: "profiles"
  type: "TABLE"
  schema: "breathe"
  columns:
  - name: "id"
    typeName: "INT64"
    jdbcDataType: "4"
    ordinalPosition: 0
    primaryKeySequenceId: 1
    columnDisplaySize: 10
    scale: 0
    precision: 10
    primaryKey: false
    nullable: false
    autoincrement: true
  - name: "name"
    typeName: "STRING"
    jdbcDataType: "12"
    ordinalPosition: 0
    primaryKeySequenceId: 0
    columnDisplaySize: 255
    scale: 0
    precision: 255
    primaryKey: false
    nullable: false
    autoincrement: false

compile

This command generates a DDL for a target database based on the source DBML which was generated by the previous command (extract).

rosetta [-c, --config CONFIG_FILE] compile [-h, --help] [-t, --target CONNECTION_NAME] [-s, --source CONNECTION_NAME]

Parameter	Description
-h, --help	Show the help message and exit.
-c, --config CONFIG_FILE	YAML config file. If none is supplied it will use main.conf in the current directory if it exists.
-s, --source CONNECTION_NAME (Optional)	The source connection name where models are generated.
-t, --target CONNECTION_NAME	The target connection name in which source DBML converts to.
-d, --with-drop	Add query to drop tables when generating ddl.

Example:

CREATE SCHEMA breathe;
CREATE TABLE breathe.profiles(id INTEGER not null AUTO_INCREMENT, name STRING not null);

dbt

This is the command that generates dbt models for a source DBML which was generated by the previous command (extract).

rosetta [-c, --config CONFIG_FILE] dbt [-h, --help] [-s, --source CONNECTION_NAME]

Parameter	Description
-h, --help	Show the help message and exit.
-c, --config CONFIG_FILE	YAML config file. If none is supplied it will use main.conf in the current directory if it exists.
-s, --source CONNECTION_NAME	The source connection name where models are generated.

diff

Show the difference between the local model and the database. Check if any table is removed, or added or if any columns have changed.

rosetta [-c, --config CONFIG_FILE] diff [-h, --help] [-s, --source CONNECTION_NAME]

Parameter	Description
-h, --help	Show the help message and exit.
-c, --config CONFIG_FILE	YAML config file. If none is supplied it will use main.conf in the current directory if it exists.
-s, --source CONNECTION_NAME	The source connection is used to specify which models and connection to use.
-m, --model MODEL_FILE (Optional)	The model file to use for apply. Default is model.yaml

Example:

There are changes between local model and targeted source
Table Changed: Table 'actor' columns changed
Column Changed: Column 'actor_id' in table 'actor' changed 'Precision'. New value: '1', old value: '5'
Column Changed: Column 'actor_id' in table 'actor' changed 'Autoincrement'. New value: 'true', old value: 'false'
Column Changed: Column 'actor_id' in table 'actor' changed 'Primary key'. New value: 'false', old value: 'true'
Column Changed: Column 'actor_id' in table 'actor' changed 'Nullable'. New value: 'true', old value: 'false'
Table Added: Table 'address'

test

This command runs tests for columns using assertions. Then they are translated into query commands, executed, and compared with an expected value. Currently supported assertions are: equals(=), not equals(!=), less than(<), more than(>), less than or equals(<=), more than or equals(>=), contains(in), is null, is not null, like, between. Examples are shown below:

rosetta [-c, --config CONFIG_FILE] test [-h, --help] [-s, --source CONNECTION_NAME]

Parameter	Description
-h, --help	Show the help message and exit.
-c, --config CONFIG_FILE	YAML config file. If none is supplied it will use main.conf in the current directory if it exists.
-s, --source CONNECTION_NAME	The source connection is used to specify which models and connections to use.

Note: Value for BigQuery Array columns should be comma separated value ('a,b,c,d,e').

Example:

---
safeMode: false
databaseType: "mysql"
operationLevel: database
tables:
  - name: "actor"
    type: "TABLE"
    columns:
      - name: "actor_id"
        typeName: "SMALLINT UNSIGNED"
        ordinalPosition: 0
        primaryKeySequenceId: 1
        columnDisplaySize: 5
        scale: 0
        precision: 5
        nullable: false
        primaryKey: true
        autoincrement: false
        tests:
          assertion:
            - operator: '='
              value: 16
              expected: 1
      - name: "first_name"
        typeName: "VARCHAR"
        ordinalPosition: 0
        primaryKeySequenceId: 0
        columnDisplaySize: 45
        scale: 0
        precision: 45
        nullable: false
        primaryKey: false
        autoincrement: false
        tests:
          assertion:
            - operator: '!='
              value: 'Michael'
              expected: 1

Output example:

Running tests for mysql. Found: 2

1 of 2, RUNNING test ('=') on column: 'actor_id'                                                    
1 of 2, FINISHED test on column: 'actor_id' (expected: '1' - actual: '1')  ......................... [PASS in 0.288s]
2 of 2, RUNNING test ('!=') on column: 'first_name'                                                 
2 of 2, FINISHED test on column: 'first_name' (expected: '1' - actual: '219')  ..................... [FAIL in 0.091s]

apply

Gets current model and compares with state of database, generates ddl for changes and applies to database. If you set git_auto_commit to true in main.conf it will automatically push the new model to your Git repo of the rosetta project.

rosetta [-c, --config CONFIG_FILE] apply [-h, --help] [-s, --source CONNECTION_NAME]

Parameter	Description
-h, --help	Show the help message and exit.
-c, --config CONFIG_FILE	YAML config file. If none is supplied it will use main.conf in the current directory if it exists.
-s, --source CONNECTION_NAME	The source connection is used to specify which models and connection to use.
-m, --model MODEL_FILE (Optional)	The model file to use for apply. Default is model.yaml

Example:

(Actual database)

---
safeMode: false
databaseType: "mysql"
operationLevel: database
tables:
  - name: "actor"
    type: "TABLE"
    columns:
      - name: "actor_id"
        typeName: "SMALLINT UNSIGNED"
        ordinalPosition: 0
        primaryKeySequenceId: 1
        columnDisplaySize: 5
        scale: 0
        precision: 5
        nullable: false
        primaryKey: true
        autoincrement: false
        tests:
          assertion:
            - operator: '='
              value: 16
              expected: 1

(Expected database)

---
safeMode: false
databaseType: "mysql"
operationLevel: database
tables:
  - name: "actor"
    type: "TABLE"
    columns:
      - name: "actor_id"
        typeName: "SMALLINT UNSIGNED"
        ordinalPosition: 0
        primaryKeySequenceId: 1
        columnDisplaySize: 5
        scale: 0
        precision: 5
        nullable: false
        primaryKey: true
        autoincrement: false
        tests:
          assertion:
            - operator: '='
              value: 16
              expected: 1
      - name: "first_name"
        typeName: "VARCHAR"
        ordinalPosition: 0
        primaryKeySequenceId: 0
        columnDisplaySize: 45
        scale: 0
        precision: 45
        nullable: false
        primaryKey: false
        autoincrement: false
        tests:
          assertion:
            - operator: '!='
              value: 'Michael'
              expected: 1

Description: Our actual database does not contain first_name so we expect it to alter the table and add the column, inside the source directory there will be the executed DDL and a snapshot of the current database.

generate

This command will generate Spark Python (file) or Spark Scala (file), firstly it extracts a schema from a source database and gets connection properties from the source connection, then it creates a python (file) or scala (file) that translates schemas, which is ready to transfer data from source to target.

rosetta [-c, --config CONFIG_FILE] generate [-h, --help] [-s, --source CONNECTION_NAME] [-t, --target CONNECTION_NAME] [--pyspark] [--scala]

Parameter	Description
-h, --help	Show the help message and exit.
-c, --config CONFIG_FILE	YAML config file. If none is supplied it will use main.conf in the current directory if it exists.
-s, --source CONNECTION_NAME	The source connection name to extract schema from.
-t, --target CONNECTION_NAME	The target connection name where the data will be transfered.
--pyspark	Generates the Spark SQL file.
--scala	Generates the Scala SQL file.

query

The query command allows you to use natural language commands to query your databases, transforming these commands into SQL SELECT statements. By leveraging the capabilities of AI and LLMs, specifically OpenAI models, it interprets user queries and generates the corresponding SQL queries. For effective use of this command, users need to provide their OpenAI API Key and specify the OpenAI model to be utilized. The output will be written to a CSV file. The max number of rows that will be returned is 200. You can overwrite this value, or remove completely the limit. The default openai model that is used is gpt-3.5-turbo.

rosetta [-c, --config CONFIG_FILE] query [-h, --help] [-s, --source CONNECTION_NAME] [-q, --query "Natural language QUERY"] [--output "Output DIRECTORY or FILE"]

Parameter	Description
-h, --help	Show the help message and exit.
-c, --config CONFIG_FILE	YAML config file. If none is supplied it will use main.conf in the current directory if it exists.
-s, --source CONNECTION_NAME	The source connection is used to specify which models and connection to use.
-q --query "Natural language QUERY"	pecifies the natural language query to be transformed into an SQL SELECT statement.
-l --limit Response Row limit (Optional)	Limits the number of rows in the generated CSV file. If not specified, the default limit is set to 200 rows.
--no-limit (Optional)	Specifies that there should be no limit on the number of rows in the generated CSV file.

Example (Setting the key and model) :

(Config file)

openai_api_key: "sk-abcdefghijklmno1234567890"
openai_model: "gpt-4"
connections:
  - name: mysql
    databaseName: sakila
    schemaName:
    dbType: mysql
    url: jdbc:mysql://root:sakila@localhost:3306/sakila
    userName: root
    password: sakila
  - name: pg
    databaseName: postgres
    schemaName: public
    dbType: postgres
    url: jdbc:postgresql://localhost:5432/postgres?user=postgres&password=sakila
    userName: postgres
    password: sakila

Example (Query)

   rosetta query -s mysql -q "Show me the top 10 customers by revenue."

CSV Output Example

customer_name,total_revenue,location,email
John Doe,50000,New York,[email protected]
Jane Smith,45000,Los Angeles,[email protected]
David Johnson,40000,Chicago,[email protected]
Emily Brown,35000,San Francisco,[email protected]
Michael Lee,30000,Miami,[email protected]
Sarah Taylor,25000,Seattle,[email protected]
Robert Clark,20000,Boston,[email protected]
Lisa Martinez,15000,Denver,[email protected]
Christopher Anderson,10000,Austin,[email protected]
Amanda Wilson,5000,Atlanta,[email protected]

Note: When giving a request that will not generate a SELECT statement the query will be generated but will not be executed rather be given to the user to execute on their own.

drivers

This command can list drivers that are listed in a drivers.yaml file and by choosing a driver you can download it to the ROSETTA_DRIVERS directory which will be automatically ready to use.

rosetta drivers [-h, --help] [-f, --file] [--list] <indexToDownload> [-dl, --download]

Parameter	Description
-h, --help	Show the help message and exit.
-f, --file DRIVERS_FILE	YAML drivers file path. If none is supplied it will use drivers.yaml in the current directory and then fallback to our default one.
--list	Used to list all available drivers.
-dl, --download	Used to download selected driver by index.
indexToDownload	Chooses which driver to download depending on the index of the driver.

Example (drivers.yaml)

- name: MySQL 8.0.30
  link: https://dev.mysql.com/get/Downloads/Connector-J/mysql-connector-java-8.0.30.zip
- name: Postgresql 42.3.7
  link: https://jdbc.postgresql.org/download/postgresql-42.3.7.jar

Safety Operation

In model.yaml you can find the attribute safeMode which is by default disabled (false). If you want to prevent any DROP operation during apply command, set safeMode: true.

Operation level

In model.yaml you can find the attribute operationLevel which is by default set to schema. If you want to apply changes on to database level in your model instead of the specific schema in apply command, set operationLevel: schema.

Fallback Type

In model.yaml you can define the attribute fallbackType for columns that are of custom types, not supported for translations or not included in the translation matrix. If a given column type cannot be translated then the fallbackType will be used for the translation. fallbackType is optional.

RosettaDB CLI JAR and RosettaDB Source

Setting Up the CLI JAR (Optional)

1. Download the rosetta CLI JAR (releases page)
2. Create an alias command

alias rosetta='java -cp "<path_to_our_cli_jar>:<path_to_our_drivers>" com.adaptivescale.rosetta.cli.Main'

example:

alias rosetta='java -cp "/Users/adaptivescale/cli-1.0.0.jar:/Users/adaptivescale/drivers/*" com.adaptivescale.rosetta.cli.Main'

Note: If we are using the cli JAR file, we need to specify the location of the JDBC drivers (directory). See the Getting Started section.

Build from the source (Optional)

gradle binary:runtimeZip

Google Cloud Spanner JDBC Fix

Note: If you face one of the following errors with Google Cloud Spanner JDBC

java.sql.SQLException: No suitable driver

or

java.lang.SecurityException: Invalid signature file digest for Manifest main attributes

you can fix it by running the following command where your driver is located:

zip -d google-cloud-spanner-jdbc-2.6.2-single-jar-with-dependencies.jar 'META-INF/.SF' 'META-INF/.RSA' 'META-INF/*SF'

Copyright and License Information

Unless otherwise specified, all content, including all source code files and documentation files in this repository are:

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this tool except in compliance with the License. You may obtain a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0

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