commit | 49346050439d66179e1de19c0bffa4ced3a8dbe6 | [log] [tgz] |
---|---|---|
author | Maxime Beauchemin <maximebeauchemin@gmail.com> | Thu Nov 08 09:38:10 2018 -0800 |
committer | GitHub <noreply@github.com> | Thu Nov 08 09:38:10 2018 -0800 |
tree | f950d6fb6632f15c21c72b3c3adb5903ab8ec9b4 | |
parent | 1fcfda4fdc4df78c38b650fb308bebabb0be0855 [diff] |
Make stacktraces available in many more cases (#6299) * Wrap <LoadableRenderer /> with <ErrorBoundary /> It appears that since the introduction of <SuperChart />, errors in the visualization javascript (which are somewhat common and expected, especially as we'll support plugins) were not handled and the whole page would throw and go missing. Here I'm introducing a new <ErrorBoundary /> component that elegantly wraps other components and handles errors. It's inspired by: https://reactjs.org/docs/error-boundaries.html The default behavior of the component is to simply surface the error as an <Alert bsStyle="danger" /> and exposes the React stacktrace when clicking on the error. It's also possible to use component and pass an onError handler and not show the default message. This also fixes some minor bugs in TimeTable. * Addressing comments * Getting more stack traces * Adressing comments
Apache Superset (incubating) is a modern, enterprise-ready business intelligence web application
[this project used to be named Caravel, and Panoramix in the past]
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Apache Superset is a data exploration and visualization web application.
Superset provides:
Superset speaks many SQL dialects through SQLAlchemy, a Python ORM that is compatible with most common databases.
Superset can be used to visualize data out of most databases:
On top of having the ability to query your relational databases, Superset ships with deep integration with Druid (a real time distributed column-store). When querying Druid, Superset can query humongous amounts of data on top of real time dataset. Note that Superset does not require Druid in any way to function, it's simply another database backend that it can query.
Here's a description of Druid from the http://druid.io website:
Druid is an open-source analytics data store designed for business intelligence (OLAP) queries on event data. Druid provides low latency (real-time) data ingestion, flexible data exploration, and fast data aggregation. Existing Druid deployments have scaled to trillions of events and petabytes of data. Druid is best used to power analytic dashboards and applications.
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