Github user 1ambda commented on the issue:
https://github.com/apache/zeppelin/pull/1952
Sorry for late reply. I was taking a look also recent resource related
commit to understand fully.
1. This PR is well abstracted and shipped with enough unit test.
2. And easy to share table type interpreter results with other
interpreters. The only thing interpreter develop should do is creating it's own
table data class (e.g `JDBCTableData`, `DataFrameTableData` as Leemoonsoo
mentioned.) to be inserted into pool using interpreter specific low-level
result (e.g `JDBCResultSet`, ...)
3. This also enable us to create table data view for shared result in pools.
@Leemoonsoo Now i have a question.
- I can't imagine how one interpreter (e.g JDBC) is able to use shared
table result from another interpreter (e.g spark.sql). I know we have APIs to
get results from pool. But getting doesn't mean using (e.g querying) directly.
Thanks!
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