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Felix Cheung commented on SPARK-11167: -------------------------------------- Another error from PR 8984 I can have this > e <- new.env() > e[["abd"]] <- 1276 > e[["84798"]] <- "abc" > l <- list(e) > df <- createDataFrame(sqlContext, list(l)) > df DataFrame[_1:map<string,string>] So env supports mixed type values they are mapped to map<string, string> on JVM. In fact, this DataFrame doesn't seem to work properly > head(df) 15/10/27 19:02:02 ERROR Executor: Exception in task 0.0 in stage 6.0 (TID 6) scala.MatchError: 1276.0 (of class java.lang.Double) at org.apache.spark.sql.catalyst.CatalystTypeConverters$StringConverter$.toCatalystImpl(CatalystTypeConverters.scala:295) > Incorrect type resolution on heterogeneous data structures > ---------------------------------------------------------- > > Key: SPARK-11167 > URL: https://issues.apache.org/jira/browse/SPARK-11167 > Project: Spark > Issue Type: Bug > Components: SparkR > Affects Versions: 1.6.0 > Reporter: Maciej Szymkiewicz > > If structure contains heterogeneous incorrectly assigns type of the > encountered element as type of a whole structure. This problem affects both > lists: > {code} > SparkR:::infer_type(list(a=1, b="a") > ## [1] "array<double>" > SparkR:::infer_type(list(a="a", b=1)) > ## [1] "array<string>" > {code} > and environments: > {code} > SparkR:::infer_type(as.environment(list(a=1, b="a"))) > ## [1] "map<string,double>" > SparkR:::infer_type(as.environment(list(a="a", b=1))) > ## [1] "map<string,string>" > {code} > This results in errors during data collection and other operations on > DataFrames: > {code} > ldf <- data.frame(row.names=1:2) > ldf$foo <- list(list("1", 2), list(3, 4)) > sdf <- createDataFrame(sqlContext, ldf) > collect(sdf) > ## 15/10/17 17:58:57 ERROR Executor: Exception in task 0.0 in stage 9.0 (TID > 9) > ## scala.MatchError: 2.0 (of class java.lang.Double) > ## ... > {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org