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Merge pull request #5731 from mistercrunch/faq_db_engines
[docs] FAQ entry 'Does Superset work with [database engine]?'
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commit
24a9a39e2d
@ -33,7 +33,6 @@ import sphinx_rtd_theme
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extensions = [
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extensions = [
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'sphinx.ext.autodoc',
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'sphinx.ext.autodoc',
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'sphinx.ext.viewcode',
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'sphinx.ext.viewcode',
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'sphinxcontrib.youtube',
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]
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]
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# Add any paths that contain templates here, relative to this directory.
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# Add any paths that contain templates here, relative to this directory.
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52
docs/faq.rst
52
docs/faq.rst
@ -246,3 +246,55 @@ labels to colors in the ``JSON Metadata`` attribute using the
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"Boys": "#ADD8E6"
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"Boys": "#ADD8E6"
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}
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}
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}
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}
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Does Superset work with [insert database engine here]?
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------------------------------------------------------
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The community over time has curated a list of databases that work well with
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Superset in the :ref:`ref_database_deps` section of the docs. Database
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engines not listed in this page may work too. We rely on the
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community to contribute to this knowledge base.
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.. _SQLAlchemy dialect: http://docs.sqlalchemy.org/en/latest/dialects/
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.. _DBAPI driver: https://www.python.org/dev/peps/pep-0249/
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For a database engine to be supported in Superset through the
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SQLAlchemy connector, it requires having a Python compliant
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`SQLAlchemy dialect`_ as well as a
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`DBAPI driver`_ defined.
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Database that have limited SQL support may
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work as well. For instance it's possible to connect
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to Druid through the SQLAlchemy connector even though Druid does not support
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joins and subqueries. Another key element for a database to be supported is through
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the Superset `Database Engine Specification
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<https://github.com/apache/incubator-superset/blob/master/superset/db_engine_specs.py>`_
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interface. This interface allows for defining database-specific configurations
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and logic
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that go beyond the SQLAlchemy and DBAPI scope. This includes features like:
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* date-related SQL function that allow Superset to fetch different
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time granularities when running time-series queries
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* whether the engine supports subqueries. If false, Superset may run 2-phase
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queries to compensate for the limitation
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* methods around processing logs and inferring the percentage of completion
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of a query
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* technicalities as to how to handle cursors and connections if the driver
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is not standard DBAPI
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* more, read the code for more details
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Beyond the SQLAlchemy connector, it's also possible, though much more
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involved, to extend Superset and write
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your own connector. The only example of this at the moment is the Druid
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connector, which is getting superseded by Druid's growing SQL support and
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the recent availability of a DBAPI and SQLAlchemy driver. If the database
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you are considering integrating has any kind of of SQL support, it's probably
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preferable to go the SQLAlchemy route. Note that for a native connector to
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be possible the database needs to have support for running OLAP-type queries
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and should be able to things that are typical in basic SQL:
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- aggregate data
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- apply filters (==, !=, >, <, >=, <=, IN, ...)
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- apply HAVING-type filters
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- be schema-aware, expose columns and types
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@ -203,7 +203,8 @@ workers this creates a lot of contention and race conditions when defining
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permissions and views.
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permissions and views.
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To alleviate this issue, the automatic updating of permissions can be disabled
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To alleviate this issue, the automatic updating of permissions can be disabled
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by setting the :envvar:`SUPERSET_UPDATE_PERMS` environment variable to `0`.
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by setting the environment variable
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`SUPERSET_UPDATE_PERMS` environment variable to `0`.
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The value `1` enables it, `0` disables it. Note if undefined the functionality
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The value `1` enables it, `0` disables it. Note if undefined the functionality
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is enabled to maintain backwards compatibility.
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is enabled to maintain backwards compatibility.
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@ -298,6 +299,9 @@ auth postback endpoint, you can add them to *WTF_CSRF_EXEMPT_LIST*
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WTF_CSRF_EXEMPT_LIST = ['']
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WTF_CSRF_EXEMPT_LIST = ['']
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.. _ref_database_deps:
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Database dependencies
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Database dependencies
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---------------------
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---------------------
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@ -704,7 +708,7 @@ Note that it's also possible to implement you own logger by deriving
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Install Superset with helm in Kubernetes
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Install Superset with helm in Kubernetes
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--------------
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----------------------------------------
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You can install Superset into Kubernetes with Helm <https://helm.sh/>. The chart is
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You can install Superset into Kubernetes with Helm <https://helm.sh/>. The chart is
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located in ``install/helm``.
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located in ``install/helm``.
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@ -727,7 +731,6 @@ The first step: Configure authorization in Superset ``superset_config.py``.
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.. code-block:: python
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.. code-block:: python
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AUTH_TYPE = AUTH_OAUTH
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AUTH_TYPE = AUTH_OAUTH
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OAUTH_PROVIDERS = [
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OAUTH_PROVIDERS = [
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{ 'name':'egaSSO',
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{ 'name':'egaSSO',
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'token_key':'access_token', # Name of the token in the response of access_token_url
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'token_key':'access_token', # Name of the token in the response of access_token_url
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@ -1,3 +1,2 @@
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sphinx==1.7.1
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sphinx==1.7.1
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sphinx-rtd-theme==0.2.4
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sphinx-rtd-theme==0.2.4
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sphinxcontrib.youtube==0.1.2
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