Metadata-Version: 2.1
Name: google-datacatalog-sqlserver-connector
Version: 0.10.0
Summary: Library for ingesting SQLServer metadata into Google Cloud Data Catalog
Home-page: UNKNOWN
Author: Google LLC
License: UNKNOWN
Description: # google-datacatalog-sqlserver-connector
        
        Library for ingesting SQLServer metadata into Google Cloud Data Catalog.
        Currently supports SQL Server 2017 Standard.
        
        [![Python package][2]][2] [![PyPi][3]][4] [![License][5]][5] [![Issues][6]][7]
        
        **Disclaimer: This is not an officially supported Google product.**
        
        <!--
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          run `npx markdown-toc -i README.md`.
        
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        ## Table of Contents
        
        <!-- toc -->
        
        - [1. Installation](#1-installation)
          * [1.1. Mac/Linux](#11-maclinux)
          * [1.2. Windows](#12-windows)
          * [1.3. Install from source](#13-install-from-source)
            + [1.3.1. Get the code](#131-get-the-code)
            + [1.3.2. Create and activate a *virtualenv*](#132-create-and-activate-a-virtualenv)
            + [1.3.3. Install the library](#133-install-the-library)
        - [2. Environment setup](#2-environment-setup)
          * [2.1. Auth credentials](#21-auth-credentials)
            + [2.1.1. Create a service account and grant it below roles](#211-create-a-service-account-and-grant-it-below-roles)
            + [2.1.2. Download a JSON key and save it as](#212-download-a-json-key-and-save-it-as)
          * [2.2 Set up SQL Server Driver (Optional)](#22-set-up-sql-server-driver--optional)
          * [2.3. Set environment variables](#23-set-environment-variables)
        - [3. Adapt user configurations](#3-adapt-user-configurations)
        - [4. Run entry point](#4-run-entry-point)
          * [4.1. Run Python entry point](#41-run-python-entry-point)
          * [4.2. Run the Python entry point with a user-defined entry resource URL prefix](#42-run-the-python-entry-point-with-a-user-defined-entry-resource-url-prefix)
          * [4.3. Run Docker entry point](#43-run-docker-entry-point)
        - [5 Scripts inside tools](#5-scripts-inside-tools)
          * [5.1. Run clean up](#51-run-clean-up)
        - [6. Developer environment](#6-developer-environment)
          * [6.1. Install and run Yapf formatter](#61-install-and-run-yapf-formatter)
          * [6.2. Install and run Flake8 linter](#62-install-and-run-flake8-linter)
          * [6.3. Run Tests](#63-run-tests)
        - [7. Metrics](#7-metrics)
        - [8. Troubleshooting](#8-troubleshooting)
        
        <!-- tocstop -->
        
        -----
        
        ## 1. Installation
        
        Install this library in a [virtualenv][1] using pip. [virtualenv][1] is a tool to
        create isolated Python environments. The basic problem it addresses is one of
        dependencies and versions, and indirectly permissions.
        
        With [virtualenv][1], it's possible to install this library without needing system
        install permissions, and without clashing with the installed system
        dependencies. Make sure you use Python 3.6+.
        
        
        ### 1.1. Mac/Linux
        
        ```bash
        pip3 install virtualenv
        virtualenv --python python3.6 <your-env>
        source <your-env>/bin/activate
        <your-env>/bin/pip install google-datacatalog-sqlserver-connector
        ```
        
        ### 1.2. Windows
        
        ```bash
        pip3 install virtualenv
        virtualenv --python python3.6 <your-env>
        <your-env>\Scripts\activate
        <your-env>\Scripts\pip.exe install google-datacatalog-sqlserver-connector
        ```
        
        ### 1.3. Install from source
        
        #### 1.3.1. Get the code
        
        ````bash
        git clone https://github.com/GoogleCloudPlatform/datacatalog-connectors-rdbms/
        cd datacatalog-connectors-rdbms/google-datacatalog-sqlserver-connector
        ````
        
        #### 1.3.2. Create and activate a *virtualenv*
        
        ```bash
        pip3 install virtualenv
        virtualenv --python python3.6 <your-env>
        source <your-env>/bin/activate
        ```
        
        #### 1.3.3. Install the library
        
        ```bash
        pip install .
        ```
        
        ## 2. Environment setup
        
        ### 2.1. Auth credentials
        
        #### 2.1.1. Create a service account and grant it below roles
        
        - Data Catalog Admin
        
        #### 2.1.2. Download a JSON key and save it as
        - `<YOUR-CREDENTIALS_FILES_FOLDER>/sqlserver2dc-credentials.json`
        
        > Please notice this folder and file will be required in next steps.
        
        ### 2.2 Set up SQL Server Driver  (Optional)
        This is step is needed when you are running the connector on a machine that does not have the SQLServer installation.
        
        https://docs.microsoft.com/en-us/sql/connect/odbc/linux-mac/installing-the-microsoft-odbc-driver-for-sql-server?view=sql-server-2017
        
        ### 2.3. Set environment variables
        
        Replace below values according to your environment:
        
        ```bash
        export GOOGLE_APPLICATION_CREDENTIALS=data_catalog_credentials_file
        
        export SQLSERVER2DC_DATACATALOG_PROJECT_ID=google_cloud_project_id
        export SQLSERVER2DC_DATACATALOG_LOCATION_ID=google_cloud_location_id
        export SQLSERVER2DC_SQLSERVER_SERVER=sqlserver_server
        export SQLSERVER2DC_SQLSERVER_USERNAME=sqlserver_username
        export SQLSERVER2DC_SQLSERVER_PASSWORD=sqlserver_password
        export SQLSERVER2DC_SQLSERVER_DATABASE=sqlserver_database
        export SQLSERVER2DC_RAW_METADATA_CSV=sqlserver_raw_csv (If supplied ignores the SQLSERVER server credentials)
        
        ```
        
        ## 3. Adapt user configurations
        
        Along with default metadata, the connector can enrich metadata with user provided values as well,
         such as adding a prefix to each schema and tables name. 
         
         The table below shows what metadata is scraped by default, and what is configurable.
        
        | Metadata                     | Description                                        | Scraped by default | Config option                                |                    
        | ---                          | ---                                                | ---                | ---                                          |                       
        | schema_name                  | Name of the Schema                                 | Y                  | ---                                          | 
        | table_name                   | Name of a table                                    | Y                  | ---                                          | 
        | table_type                   | Type of a table (BASE, VIEW, etc)                  | Y                  | ---                                          | 
        | column_name                  | Name of a column                                   | Y                  | ---                                          | 
        | column_type                  | Column data type                                   | Y                  | ---                                          | 
        | column_default_value         | Default value of a column                          | Y                  | ---                                          | 
        | column_nullable              | Whether a column is nullable                       | Y                  | ---                                          | 
        | column_char_length           | Char length of values in a column                  | Y                  | ---                                          | 
        | column_numeric_precision     | Numeric precision of values in a column            | Y                  | ---                                          |
        | prefix                       | Prefix to be added to schema and tables name       | N/A                | enrich_metadata.entry_prefix                 | 
        | entry_id_pattern_for_prefix  | Entry ID pattern which the prefix will be applied  | N/A                | enrich_metadata.entry_id_pattern_for_prefix  | 
         
         
         `prefix` should comply with Data Catalog `entryId`: 
         ```text
        The ID must begin with a letter or underscore, contain only English letters, numbers and underscores, and have at most 64 characters (combined the prefix + the entryId).
        ```   
        
        if the `entry_id_pattern_for_prefix` is supplied, the prefix will only be applied to this pattern.
         
        Sample configuration file [ingest_cfg.yaml](https://github.com/GoogleCloudPlatform/datacatalog-connectors-rdbms/blob/master/google-datacatalog-sqlserver-connector/ingest_cfg.yaml) in the repository root shows what kind of configuration is expected. 
        
        **If you want to enable the user defined config, please add ingest_cfg.yaml to the directory from which you execute the connector and adapt it to your needs.** 
        
        ## 4. Run entry point
        
        ### 4.1. Run Python entry point
        
        - Virtualenv
        
        ```bash
        google-datacatalog-sqlserver-connector \
        --datacatalog-project-id=$SQLSERVER2DC_DATACATALOG_PROJECT_ID \
        --datacatalog-location-id=$SQLSERVER2DC_DATACATALOG_LOCATION_ID \
        --sqlserver-host=$SQLSERVER2DC_SQLSERVER_SERVER \
        --sqlserver-user=$SQLSERVER2DC_SQLSERVER_USERNAME \
        --sqlserver-pass=$SQLSERVER2DC_SQLSERVER_PASSWORD \
        --sqlserver-database=$SQLSERVER2DC_SQLSERVER_DATABASE  \
        --raw-metadata-csv=$SQLSERVER2DC_RAW_METADATA_CSV      
        ```
        
        ### 4.2. Run the Python entry point with a user-defined entry resource URL prefix
        
        This option is useful when the connector cannot accurately determine the database hostname.
        For example when running under proxies, load balancers or database read replicas,
        you can specify the prefix of your master instance so the resource URL will point
        to the exact database where the data is stored.
        
        - Virtualenv
        
        ```bash
        google-datacatalog-sqlserver-connector \
        --datacatalog-project-id=$SQLSERVER2DC_DATACATALOG_PROJECT_ID \
        --datacatalog-location-id=$SQLSERVER2DC_DATACATALOG_LOCATION_ID \
        --datacatalog-entry-resource-url-prefix project/database-instance \
        --sqlserver-host=$SQLSERVER2DC_SQLSERVER_SERVER \
        --sqlserver-user=$SQLSERVER2DC_SQLSERVER_USERNAME \
        --sqlserver-pass=$SQLSERVER2DC_SQLSERVER_PASSWORD \
        --sqlserver-database=$SQLSERVER2DC_SQLSERVER_DATABASE  \
        --raw-metadata-csv=$SQLSERVER2DC_RAW_METADATA_CSV 
        ```
        
        ### 4.3. Run Docker entry point
        
        ```bash
        docker build -t sqlserver2datacatalog .
        docker run --rm --tty -v YOUR-CREDENTIALS_FILES_FOLDER:/data sqlserver2datacatalog \
        --datacatalog-project-id=$SQLSERVER2DC_DATACATALOG_PROJECT_ID \
        --datacatalog-location-id=$SQLSERVER2DC_DATACATALOG_LOCATION_ID \
        --sqlserver-host=$SQLSERVER2DC_SQLSERVER_SERVER \
        --sqlserver-user=$SQLSERVER2DC_SQLSERVER_USERNAME \
        --sqlserver-pass=$SQLSERVER2DC_SQLSERVER_PASSWORD \
        --sqlserver-database=$SQLSERVER2DC_SQLSERVER_DATABASE  \
        --raw-metadata-csv=$SQLSERVER2DC_RAW_METADATA_CSV       
        ```
        
        ## 5 Scripts inside tools
        
        ### 5.1. Run clean up
        
        ```bash
        # List of projects split by comma. Can be a single value without comma
        export SQLSERVER2DC_DATACATALOG_PROJECT_IDS=my-project-1,my-project-2
        ```
        
        ```bash
        # Run the clean up
        python tools/cleanup_datacatalog.py --datacatalog-project-ids=$SQLSERVER2DC_DATACATALOG_PROJECT_IDS 
        
        ```
        
        ## 6. Developer environment
        
        ### 6.1. Install and run Yapf formatter
        
        ```bash
        pip install --upgrade yapf
        
        # Auto update files
        yapf --in-place --recursive src tests
        
        # Show diff
        yapf --diff --recursive src tests
        
        # Set up pre-commit hook
        # From the root of your git project.
        curl -o pre-commit.sh https://raw.githubusercontent.com/google/yapf/master/plugins/pre-commit.sh
        chmod a+x pre-commit.sh
        mv pre-commit.sh .git/hooks/pre-commit
        ```
        
        ### 6.2. Install and run Flake8 linter
        
        ```bash
        pip install --upgrade flake8
        flake8 src tests
        ```
        
        
        ### 6.3. Run Tests
        
        ```bash
        python setup.py test
        ```
        
        ## 7. Metrics
        
        [Metrics README.md](docs/README.md)
        
        ## 8. Troubleshooting
        
        In the case a connector execution hits Data Catalog quota limit, an error will be raised and logged with the following detailement, depending on the performed operation READ/WRITE/SEARCH: 
        ```
        status = StatusCode.RESOURCE_EXHAUSTED
        details = "Quota exceeded for quota metric 'Read requests' and limit 'Read requests per minute' of service 'datacatalog.googleapis.com' for consumer 'project_number:1111111111111'."
        debug_error_string = 
        "{"created":"@1587396969.506556000", "description":"Error received from peer ipv4:172.217.29.42:443","file":"src/core/lib/surface/call.cc","file_line":1056,"grpc_message":"Quota exceeded for quota metric 'Read requests' and limit 'Read requests per minute' of service 'datacatalog.googleapis.com' for consumer 'project_number:1111111111111'.","grpc_status":8}"
        ```
        For more info about Data Catalog quota, go to: [Data Catalog quota docs](https://cloud.google.com/data-catalog/docs/resources/quotas).
        
        [1]: https://virtualenv.pypa.io/en/latest/
        [2]: https://github.com/GoogleCloudPlatform/datacatalog-connectors-rdbms/workflows/Python%20package/badge.svg?branch=master
        [3]: https://img.shields.io/pypi/v/google-datacatalog-sqlserver-connector.svg
        [4]: https://pypi.org/project/google-datacatalog-sqlserver-connector/
        [5]: https://img.shields.io/github/license/GoogleCloudPlatform/datacatalog-connectors-rdbms.svg
        [6]: https://img.shields.io/github/issues/GoogleCloudPlatform/datacatalog-connectors-rdbms.svg
        [7]: https://github.com/GoogleCloudPlatform/datacatalog-connectors-rdbms/issues
        
Platform: Posix; MacOS X; Windows
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
