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docs: fix spelling and grammar (#26381)

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Fenil Mehta 2024-01-02 23:36:45 +05:30 committed by GitHub
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RELEASING/release-notes-2-0/README.md
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@ -34,7 +34,7 @@ Superset 2.0 is a big step forward. This release cleans up many legacy code path
- New GitHub workflow to test Storybook Netlify instance nightly ([#19852](https://github.com/apache/superset/pull/19852)) - New GitHub workflow to test Storybook Netlify instance nightly ([#19852](https://github.com/apache/superset/pull/19852))
- Minimum requirement for Superset is now Python 3.8 ([#19017](https://github.com/apache/superset/pull/19017) - Minimum requirement for Superset is now Python 3.8 ([#19017](https://github.com/apache/superset/pull/19017))
## Features ## Features

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docs/docs/frequently-asked-questions.mdx
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@ -154,7 +154,7 @@ Table schemas evolve, and Superset needs to reflect that. It’s pretty common i
dashboard to want to add a new dimension or metric. To get Superset to discover your new columns, dashboard to want to add a new dimension or metric. To get Superset to discover your new columns,
all you have to do is to go to **Data -> Datasets**, click the edit icon next to the dataset all you have to do is to go to **Data -> Datasets**, click the edit icon next to the dataset
whose schema has changed, and hit **Sync columns from source** from the **Columns** tab. whose schema has changed, and hit **Sync columns from source** from the **Columns** tab.
Behind the scene, the new columns will get merged it. Following this, you may want to re-edit the Behind the scene, the new columns will get merged. Following this, you may want to re-edit the
table afterwards to configure the Columns tab, check the appropriate boxes and save again. table afterwards to configure the Columns tab, check the appropriate boxes and save again.
### What database engine can I use as a backend for Superset? ### What database engine can I use as a backend for Superset?
@ -220,7 +220,7 @@ and write your own connector. The only example of this at the moment is the Drui
is getting superseded by Druid’s growing SQL support and the recent availability of a DBAPI and is getting superseded by Druid’s growing SQL support and the recent availability of a DBAPI and
SQLAlchemy driver. If the database you are considering integrating has any kind of of SQL support, SQLAlchemy driver. If the database you are considering integrating has any kind of of SQL support,
it’s probably preferable to go the SQLAlchemy route. Note that for a native connector to be possible it’s probably preferable to go the SQLAlchemy route. Note that for a native connector to be possible
the database needs to have support for running OLAP-type queries and should be able to things that the database needs to have support for running OLAP-type queries and should be able to do things that
are typical in basic SQL: are typical in basic SQL:
- aggregate data - aggregate data

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docs/docs/installation/event-logging.mdx
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@ -56,5 +56,5 @@ from superset.stats_logger import StatsdStatsLogger
STATS_LOGGER = StatsdStatsLogger(host='localhost', port=8125, prefix='superset') STATS_LOGGER = StatsdStatsLogger(host='localhost', port=8125, prefix='superset')
``` ```
Note that it’s also possible to implement you own logger by deriving Note that it’s also possible to implement your own logger by deriving
`superset.stats_logger.BaseStatsLogger`. `superset.stats_logger.BaseStatsLogger`.