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Hi mutmurat, unfortunately TFOCS for Spark does not support quadratic programming out of the box. However if your constraints happen to be very simple ranges you may be able to...

Hi BloomSkyTree, since Spark has a general purpose distributed architecture there will definitely be overhead compared to a special purpose application running in memory on a single system. In addition...

Hi Ramon, it's possible that some minor changes will be needed for compatibility with newer spark versions.

Hi Ramon, the sbt build file specifies spark 1.4.1. Generally you can include a git repo in your project using sbt, but if you are making modifications you may want...

Hi AM-DNEGEL, thank you for trying out TFOCS for Spark. Since this is a free open source library we invite you to document the installation procedure you followed and submit...

Hi Bhuvanamitra, thank you for your interest in TFOCS for Spark. I believe you may be able to access the scala interface from java. If you are interested in developing...

Hi gaoyuchris, unfortunately TFOCS for Spark does not contain support for ILP. I do not believe TFOCS (of which TFOCS for Spark is a port) directly supports ILP either.

Hi AM-DNEGEL, TFOCS for Spark was developed for Spark 1.4.1, and some changes may be necessary for compatibility with newer Spark versions. This has been mentioned in https://github.com/databricks/spark-tfocs/issues/26

Hi samiit, Unfortunately MIDCP is not supported. To my knowledge Matlab TFOCS (on which TFOCS for Spark is based) does not support this either.

Hi svishnu88, There is no python interface implemented for Spark for TFOCS, but you may be able to access the scala code with PySpark's java gateway, which uses py4j.