I want to do the below query that I run in impala calling a c++ UDF in spark sql. In which pnl_flat_pp and pfh_flat are both impala table with partitioned.
Can Spark Sql does that? select a.pnl_type_code,percentile_udf_cloudera(cast(90.0 as double),sum(pnl_vector1),sum(pnl_vector2),sum(pnl_vector3),sum(pnl_vector4),sum(pnl_vector5),sum(pnl_vector6),sum(pnl_vector7),sum(pnl_vector8),sum(pnl_vector9),sum(pnl_vector10),sum(pnl_vector11),sum(pnl_vector12),sum(pnl_vector13),sum(pnl_vector14)) FROM ibrisk.pnl_flat_pp a JOIN(select portfolio_code from ibrisk.pfh_flat where pl0_code = '"3"') b ON a.portfolio_code = b.portfolio_code where rf_level = '"0"' and calc_ref = "7020704" and excl_pnl != '"1"' group by a.pnl_type_code -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/spark-sql-can-it-call-impala-udf-tp11878.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
