Github user sun-rui commented on a diff in the pull request:
https://github.com/apache/spark/pull/7280#discussion_r34243718
--- Diff: R/pkg/inst/tests/test_sparkSQL.R ---
@@ -108,6 +108,14 @@ test_that("create DataFrame from RDD", {
expect_equal(count(df), 10)
expect_equal(columns(df), c("a", "b"))
expect_equal(dtypes(df), list(c("a", "int"), c("b", "string")))
+
+ localDF <- data.frame(name=c("John", "Smith", "Sarah"), age=c(19, 23,
18), height=c(164.10, 181.4, 173.7))
+ schema <- structType(structField("name", "string"), structField("age",
"integer"), structField("height", "float"))
+ df <- createDataFrame(sqlContext, localDF, schema)
--- End diff --
@davies, is there any reason that allows user pass in a schema for
createDataFrame(), as we can infer types (R objects have runtime type
information)? Even if in some cases, user-specified schema is needed, I think
only those DataTypes that can map to native R types will be supported, for
long,float, it is not natural to support.
For external sources that has float types , which will be loaded as
java.lang.Float in JVM side, we can support transferring it to double type in R
side.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
