Thanks for the questions guys! @Jun Kim actually that feature was originally discussed and was put into backlog since proposal was more about tables processed by interpreters and their sharing. However having quick visualisation on the fly for not so large data makes sense indeed, and possibly could be done by importing data into some interpreter by default (Spark, python, etc). So I believe it can be done once initial basics for resource sharing is completed.
@Andrea Santurbano there should be listing of tables with schema info, but i'm not sure exactly what you mean by drop-down feature between tables in the UI. Could you give little more details/example on that as well as enhancements on graph part you meant? On Mon, Jun 12, 2017 at 4:01 PM, Andrea Santurbano <sant...@gmail.com> wrote: > Hi guys, > this is great! I think this can also enable some drop-down feature between > tables in the UI... > Do you think this enhancements can also include the graph part? > > Andrea > > Il giorno lun 12 giu 2017 alle ore 05:47 Jun Kim <i2r....@gmail.com> ha > scritto: > >> All of the enhancements looks great to me! >> >> And I wish a feature which can upload a small CSV file (maybe about >> 20MB..?) and play with it directly. >> It would be great if I can drag a file to Zeppelin and register it as the >> table. >> >> Thanks :) >> >> 2017년 6월 12일 (월) 오전 11:40, Park Hoon <1am...@gmail.com>님이 작성: >> >>> Hi All, >>> >>> Recently, ZEPPELIN-753 >>> <https://issues.apache.org/jira/browse/ZEPPELIN-753> (Tabledata >>> abstraction) and ZEPPELIN-2020 >>> <https://issues.apache.org/jira/browse/ZEPPELIN-2020> (Remote method >>> invocation for resources) were resolved. >>> Based on this work, we can improve Zeppelin with the following >>> enhancements: >>> >>> * register the table result as a shared resource >>> * list all available (registered) tables >>> * preview tables including its meta information (e.g columns, types, ..) >>> * download registered tables as CSV, and other formats. >>> * pivoting/filtering in backend to transforming larger data >>> * cross join tables in different interpreters (e.g Spark interpreter >>> uses a table result generated from JDBC interpreter) >>> >>> You can find the full proposal in Extending Table Data API >>> <https://cwiki.apache.org/confluence/display/ZEPPELIN/Proposal%3A+Extending+TableData+API> >>> which >>> is contributed by @1ambda, @khalidhuseynov, @Leemoonsoo. >>> >>> Any question, feedback or discussion will be welcomed. >>> >>> >>> Thanks. >>> >> -- >> Taejun Kim >> >> Data Mining Lab. >> School of Electrical and Computer Engineering >> University of Seoul >> >
