Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/3431#discussion_r21939982
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala ---
@@ -49,6 +48,15 @@ private[sql] class DDLParser extends
StandardTokenParsers with PackratParsers wi
protected implicit def asParser(k: Keyword): Parser[String] =
lexical.allCaseVersions(k.str).map(x => x : Parser[String]).reduce(_ |
_)
+ protected val STRING = Keyword("STRING")
+ protected val SHORT = Keyword("SHORT")
+ protected val DOUBLE = Keyword("DOUBLE")
+ protected val BOOLEAN = Keyword("BOOLEAN")
+ protected val BYTE = Keyword("BYTE")
+ protected val FLOAT = Keyword("FLOAT")
+ protected val INT = Keyword("INT")
+ protected val INTEGER = Keyword("INTEGER")
+ protected val LONG = Keyword("LONG")
--- End diff --
We also need to handle nested types and arrays. Another decision is if we
want to support the standard SQL types as well (`TINYINT`, etc) as aliases for
the JVM type names. We could do this like Hive does unless there is another
way?
Thoughts @matez and @rxin?
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