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* Chinese page * Using react-intl-universal to improve multi language in react page * Using react-intl-universal to improve multi language in react page * react_intl_universal * change * change * change * change * change * change * change * merge * multiple page in js * merge * merge * merge * merge * Js Translations * JS Translation * JS Translations * Js translation * JS translations * JS translations * Js translaion * JS en Translation * JS Translation * upgrade document Fixing the damn build (#3179) * Fixing the build * Going deeper [bugfix] only filterable columns should show up in FilterBox list (#3105) * [bugfix] only filterable columns should show up in FilterBox list * Touchups Datasource cannot be empty (#3035) add title description to model view (#3045) * add title description to model view * add missing import Add 'show/hide totals' option to pivot table vis (#3101) [bugfix] numeric value for date fields in table viz (#3036) Bug was present only when using the NOT GROUPED BY option fixes https://github.com/ApacheInfra/superset/issues/3027 fix hive.fetch_logs (#2968) add Zalando to the list of organizations (#3171) docs: fixup installation examples code indentation (#3169) [bugfix] fix bar order (#3180) [bugfix] visualize flow error: 'Metric x is not valid' (#3181) The metric name in the frontend doesn't match the one generated on the backend. It turns out the explore view will default to the first metric so specifying one isn't needed. Fix the segment interval for pulling metadata (#3174) The end of the interval would be on the truncated today date, which means that you will exclude today. If your realtime ingestion job runs shorter than a day, the metadata cannot be pulled from the druid cluster. Bump cryptography to 1.9 (#3065) As 1.7.2 doesn't compile here with openssl 1.1.0f Escaping the user's SQL in the explore view (#3186) * Escaping the user's SQL in the explore view When executing SQL from SQL Lab, we use a lower level API to the database which doesn't require escaping the SQL. When going through the explore view, the stack chain leading to the same method may need escaping depending on how the DBAPI driver is written, and that is the case for Presto (and perhaps other drivers). * Using regex to avoid doubling doubles [sqllab] improve Hive support (#3187) * [sqllab] improve Hive support * Fix "Transport not open" bug * Getting progress bar to show * Bump pyhive to 0.4.0 * Getting [Track Job] button to show * Fix testzz Add BigQuery engine specifications (#3193) As contributed by @mxmzdlv on issue #945 [bugfix] fix merge conflict that broke Hive support (#3196) Adding 'apache' to docs (#3194) [druid] Allow custom druid postaggregators (#3146) * [druid] Allow custom druid postaggregators Also, fix the postaggregation for approxHistogram quantiles so it adds the dependent field and that can show up in the graphs/tables. In general, postAggregators add significant power, we should probably support including custom postAggregators. Plywood has standard postAggregators here, and a customAggregator escape hatch that allows you to define custom postAggregators. This commit adds a similar capability for Superset and a additional field/fields/fieldName breakdown of the typical naming for dependent aggregations, which should make it significantly easier to develop approxHistogram and custom postAggregation-required dashboards. * [druid] Minor style cleanup in tests file. * [druid] Apply code review suggestions * break out CustomPostAggregator into separate class. This just cleans up the creation of the postaggregator a little bit. * minor style issues. * move the function around so the git diff is more readable add combine config for metrics in pivot table (#3086) * add combine config for metrics in pivot table * change method to stack/unstack * update backendSync Autofocus search input in VizTypeControl modal onEnter (#2929) Speed up JS build time (#3203) Also bumping a few related libs JS Translation JS translations js translation fix issue 3204 (#3205) [bugfix] capture Hive job_id pre-url transformation (#3213) js translation fix issue 3204 (#3205) [bugfix] capture Hive job_id pre-url transformation (#3213) [docs] update url in CONTRIBUTING.md (#3212) [sqllab/cosmetics] add margin-top for labels in query history (#3222) [explore] nvd3 sort values in rich tooltip (#3197) [sqllab] fix UI shows 'The query returned no results' momentarily (#3214) this is visible when running async queries between the fetching and success state as the rows are getting cached in the component [explore] DatasourceControl to pick datasource in modal (#3210) * [explore] DatasourceControl to pick datasource in modal Makes it easier to change datasource, also makes it such that the list of all datasources doesn't need to be loaded upfront. * Adding more metadata * Js translation * js tran * js trans * js trans * js tran * js trans * js trans * js tran * js translation * js trans * js translation * try load language pack async * Backend translations things * create language pack inside common data * performance improvement for js i18n. - js bundle should not contain localized content - we populate translation content from server-side, in boostrap.common.language_pack - in client-side, use promise to wrap around translation content. text will be translated after translation content arrived/parsed. - fix linting * fix Timer unit test * 1. add global hook for all tests, to make translation pack avaialble before each test starts. 2. fix unit test for Timer component 3. remove noused method get_locale, and modules 4. fix page reload after user change page language * parse and build i18n dictionary as a module * fix sync-backend task, which should run without DOM |
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README.md
Superset
Apache Superset (incubating) is a modern, enterprise-ready business intelligence web application
[this project used to be named Caravel, and Panoramix in the past]
Screenshots & Gifs
View Dashboards
View/Edit a Slice
Query and Visualize with SQL Lab
Apache Superset
Apache Superset is a data exploration and visualization web application.
Superset provides:
- An intuitive interface to explore and visualize datasets, and create interactive dashboards.
- A wide array of beautiful visualizations to showcase your data.
- Easy, code-free, user flows to drill down and slice and dice the data underlying exposed dashboards. The dashboards and charts acts as a starting point for deeper analysis.
- A state of the art SQL editor/IDE exposing a rich metadata browser, and an easy workflow to create visualizations out of any result set.
- An extensible, high granularity security model allowing intricate rules on who can access which product features and datasets. Integration with major authentication backends (database, OpenID, LDAP, OAuth, REMOTE_USER, ...)
- A lightweight semantic layer, allowing to control how data sources are exposed to the user by defining dimensions and metrics
- Out of the box support for most SQL-speaking databases
- Deep integration with Druid allows for Superset to stay blazing fast while slicing and dicing large, realtime datasets
- Fast loading dashboards with configurable caching
Database Support
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:
- MySQL
- Postgres
- Vertica
- Oracle
- Microsoft SQL Server
- SQLite
- Greenplum
- Firebird
- MariaDB
- Sybase
- IBM DB2
- Exasol
- MonetDB
- Snowflake
- Redshift
- more! look for the availability of a SQLAlchemy dialect for your database to find out whether it will work with Superset
Druid!
On top of having the ability to query your relational databases, Superset has 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.
Installation & Configuration
More screenshots
Resources
- Superset Google Group
- Gitter (live chat) Channel
- Docker image (community contributed)
- Slides from Strata (March 2016)
Contributing
Interested in contributing? Casual hacking? Check out Contributing.MD
Who uses Apache Superset (incubating)?
Here's a list of organizations who have taken the time to send a PR to let the world know they are using Superset. Join our growing community!