One question is where will the list of capability strings be defined?
________________________________ From: Ryan Blue <rb...@netflix.com.invalid> Sent: Thursday, November 8, 2018 2:09 PM To: Reynold Xin Cc: Spark Dev List Subject: Re: DataSourceV2 capability API Yes, we currently use traits that have methods. Something like “supports reading missing columns” doesn’t need to deliver methods. The other example is where we don’t have an object to test for a trait (scan.isInstanceOf[SupportsBatch]) until we have a Scan with pushdown done. That could be expensive so we can use a capability to fail faster. On Thu, Nov 8, 2018 at 1:54 PM Reynold Xin <r...@databricks.com<mailto:r...@databricks.com>> wrote: This is currently accomplished by having traits that data sources can extend, as well as runtime exceptions right? It's hard to argue one way vs another without knowing how things will evolve (e.g. how many different capabilities there will be). On Thu, Nov 8, 2018 at 12:50 PM Ryan Blue <rb...@netflix.com.invalid> wrote: Hi everyone, I’d like to propose an addition to DataSourceV2 tables, a capability API. This API would allow Spark to query a table to determine whether it supports a capability or not: val table = catalog.load(identifier) val supportsContinuous = table.isSupported("continuous-streaming") There are a couple of use cases for this. First, we want to be able to fail fast when a user tries to stream a table that doesn’t support it. The design of our read implementation doesn’t necessarily support this. If we want to share the same “scan” across streaming and batch, then we need to “branch” in the API after that point, but that is at odds with failing fast. We could use capabilities to fail fast and not worry about that concern in the read design. I also want to use capabilities to change the behavior of some validation rules. The rule that validates appends, for example, doesn’t allow a write that is missing an optional column. That’s because the current v1 sources don’t support reading when columns are missing. But Iceberg does support reading a missing column as nulls, so that users can add a column to a table without breaking a scheduled job that populates the table. To fix this problem, I would use a table capability, like read-missing-columns-as-null. Any comments on this approach? rb -- Ryan Blue Software Engineer Netflix -- Ryan Blue Software Engineer Netflix
