[Original] Superset installation configuration in windows, superset installation Configuration

[Original] Superset installation configuration in windows, superset installation Configuration

Superset is an open-source BI data analysis and visualization platform (formerly Caravel and Panoramix) by Airbnb (a well-known online house short rent company ), the tool provides self-service analysis, custom dashboard, visualized analysis results (export), and user/role permission control. It also integrates an SQL editor to edit and query SQL statements, it was originally used to support visual analysis of Druid. later it was developed to support many relational databases and big data computing frameworks, such as mysql, oracle, S, Presto, sqlite, Redshift, Impala, sparkSQL, Greenplum, MSSQL.

 

Superset official website address:

Http://superset.apache.org/index.html

The official website does not currently provide official support for Windows systems, but it can be installed successfully.

The installation environment is windows 10 64-bit Enterprise Edition.

 

Installation steps:

1. Install Python. We recommend that you install Python 3.4 or later. Python 2.7 has various Encoding Problems on windows.

Https://www.python.org/downloads/release/python-350/

Download a Windows x86-64 executable installer. You can directly use the installation package of exe and add it to the environment variable during installation.

Check: Run python-V and pip-V under CMD respectively. If no command is found, add the python installation directory to the path environment variable.

2. Install virtualenv. (This step is optional. If you install it directly, skip to step 4. Because Superset requires many components to be installed, it is best to use virtualenv to separate a python environment .)

When developing a Python application, the system installs only one version of Python 3. All third-party packages will bepipInstall python on Python 3site-packagesDirectory.

If we want to develop multiple applications at the same time, all these applications share one Python, that is, Python 3 installed on the system. What if application A requires jinja 2.7 and application B requires jinja 2.6?

In this case, each application may have an "independent" Python runtime environment. Virtualenv is used to create an "isolated" Python runtime environment for an application.

Installation command:

pip install virtualenv

3. Use virtualenv.

Create the d: \ python \ myproject directory on drive d.

d:md pythoncd pythonmd myprojectcd myproject

Then activate

Cd d: \ python \ myprojectvirtualenv env // wait until Initialization is complete... // activation: env \ Scripts \ activate

For example, note that there is an env mark on the left side of the command line input, so that subsequent operations will take effect in env without affecting the overall pyhton environment.

4. Install VS2015.

Some libraries dependent on in Superset must be compiled using microsoft visual c ++ 2010.

Follow instructions to install Visual C ++ 2015 Build Tools: http://landinghub.visualstudio.com/visual-cpp-build-tools

5. Install sasl.

This is a big pitfall. I have directly installed superset but it has never been installed successfully. An error is reported (sasl. h cannot be found ).

Solution: via http://www.lfd.uci.edu /~ Gohlke/pythonlibs/# download the corresponding sasl version

For example, we installed python 3.5, the system is 64-bit, download the sasl-0.2.1-cp35-cp35m-win_amd64.whl.
　　

pip install D:\Downloads\sasl-0.2.1-cp35-cp35m-win_amd64.whl 

6. Install superset after the prerequisites are completed.

　　

pip install superset

# Create an administrator account fabmanager create-admin -- app superset

# Initialize the database (in windows, first go to the Python installation directory (or virtual directory of virtualEnv), and under libs \ site-packages \ superset \ bin) Python superset db upgrade

# Loading example (subsequent operations must be performed in libs \ site-packages \ superset \ bin) Python superset load_examples # initialize the role and permission Python superset init # Start the service, port 8088, use-p to change the port number. Python superset runserver-d

 

Then, open localhost: 8088 in the browser to view the logon page.

 

 

7. Superset Localization

(1) Go to the Superset installation directory and run the following command to create the corresponding directory (translations/zh/LC_MESSAGES ):

　　　　

md  translationscd translationsmd zhcd zhmd LC_MESSAGES

 

(2) download the localized mo File
Official github:
Https://github.com/apache/incubator-superset/tree/master/superset/translations/zh/LC_MESSAGES
Download the messages.mo file and put it in the directory created above
You can also download the messages. po file, manually convert it to Chinese, and then compile the po file into a mo file. The compilation method is as follows:
　　　　

msgfmt messages.po -o messages.mo

 

(3) modify the config. py file and restart Superset. The modification part is as follows:

　　

# Setup default language BABEL_DEFAULT_LOCALE = 'zh' # Your application default translation path BABEL_DEFAULT_FOLDER = 'babel/translations' # The allowed translation for you app LANGUAGES = { #'en': {'flag': 'us', 'name': 'English'}, # 'fr': {'flag': 'fr', 'name': 'French'}, 'zh': {'flag': 'cn', 'name': 'Chinese'} }

 

(4) Close the browser and re-open it to see the effect of localization.

 

8. data source.

Superset uses sqllite by default. The following databases are supported:

Database	Pypi package	SQLAlchemy URI prefix
MySQL	pip install mysqlclient	mysql://
Postgres	pip install psycopg2	postgresql+psycopg2://
Presto	pip install pyhive	presto://
Oracle	pip install cx_Oracle	oracle://
Sqlite		sqlite://
Redshift	pip install sqlalchemy-redshift	postgresql+psycopg2://
MSSQL	pip install pymssql	mssql://
Impala	pip install impyla	impala://
SparkSQL	pip install pyhive	jdbc+hive://
Greenplum	pip install psycopg2	postgresql+psycopg2://
Athena	pip install "PyAthenaJDBC>1.0.9"	awsathena+jdbc://
Vertica	pip install sqlalchemy-vertica-python	vertica+vertica_python://
ClickHouse	pip install sqlalchemy-clickhouse	clickhouse://

After installing the database using pip, you can configure the relevant data source on the Web interface.

For the database connection string format, see:

Http://docs.sqlalchemy.org/en/rel_1_0/core/engines.html#database-urls

 

Now, I will paste an example of My SQL Server test. SuperKM testing knowledge classification data is used.

In addition, superset currently only supports single table display.