It's fairly common for adapters (Calcite's abstraction of a data source) to push down predicates. However, the API certainly looks a lot different than Catalyst's. -- Michael Mior mm...@apache.org
Le lun. 13 janv. 2020 à 09:45, Jason Nerothin <jasonnerot...@gmail.com> a écrit : > > The implementation they chose supports push down predicates, Datasets and > other features that are not available in Calcite: > > https://databricks.com/glossary/catalyst-optimizer > > On Mon, Jan 13, 2020 at 8:24 AM newroyker <newroy...@gmail.com> wrote: >> >> Was there a qualitative or quantitative benchmark done before a design >> decision was made not to use Calcite? >> >> Are there limitations (for heuristic based, cost based, * aware optimizer) >> in Calcite, and frameworks built on top of Calcite? In the context of big >> data / TCPH benchmarks. >> >> I was unable to dig up anything concrete from user group / Jira. Appreciate >> if any Catalyst veteran here can give me pointers. Trying to defend >> Spark/Catalyst. >> >> >> >> >> >> -- >> Sent from: http://apache-spark-user-list.1001560.n3.nabble.com/ >> >> --------------------------------------------------------------------- >> To unsubscribe e-mail: user-unsubscr...@spark.apache.org >> > > > -- > Thanks, > Jason --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org
