1 files changed, 22 insertions, 16 deletions

diff --git a/python/pyspark/sql.py b/python/pyspark/sql.py
index c3a6938f56..fdd8034c98 100644
--- a/python/pyspark/sql.py
+++ b/python/pyspark/sql.py
@@ -931,7 +931,7 @@ def _parse_schema_abstract(s):
 
 def _infer_schema_type(obj, dataType):
     """
-    Fill the dataType with types infered from obj
+    Fill the dataType with types inferred from obj
 
     >>> schema = _parse_schema_abstract("a b c d")
     >>> row = (1, 1.0, "str", datetime.date(2014, 10, 10))
@@ -2140,7 +2140,7 @@ class DataFrame(object):
             return Column(self._jdf.apply(name))
         raise AttributeError
 
-    def As(self, name):
+    def alias(self, name):
         """ Alias the current DataFrame """
         return DataFrame(getattr(self._jdf, "as")(name), self.sql_ctx)
 
@@ -2216,7 +2216,7 @@ class DataFrame(object):
         """
         return DataFrame(self._jdf.intersect(other._jdf), self.sql_ctx)
 
-    def Except(self, other):
+    def subtract(self, other):
         """ Return a new [[DataFrame]] containing rows in this frame
         but not in another frame.
 
@@ -2234,7 +2234,7 @@ class DataFrame(object):
 
     def addColumn(self, colName, col):
         """ Return a new [[DataFrame]] by adding a column. """
-        return self.select('*', col.As(colName))
+        return self.select('*', col.alias(colName))
 
     def removeColumn(self, colName):
         raise NotImplemented
@@ -2342,7 +2342,7 @@ SCALA_METHOD_MAPPINGS = {
 
 def _create_column_from_literal(literal):
     sc = SparkContext._active_spark_context
-    return sc._jvm.Literal.apply(literal)
+    return sc._jvm.org.apache.spark.sql.api.java.dsl.lit(literal)
 
 
 def _create_column_from_name(name):
@@ -2371,13 +2371,20 @@ def _unary_op(name):
     return _
 
 
-def _bin_op(name):
-    """ Create a method for given binary operator """
+def _bin_op(name, pass_literal_through=False):
+    """ Create a method for given binary operator
+
+    Keyword arguments:
+    pass_literal_through -- whether to pass literal value directly through to the JVM.
+    """
     def _(self, other):
         if isinstance(other, Column):
             jc = other._jc
         else:
-            jc = _create_column_from_literal(other)
+            if pass_literal_through:
+                jc = other
+            else:
+                jc = _create_column_from_literal(other)
         return Column(getattr(self._jc, _scalaMethod(name))(jc), self._jdf, self.sql_ctx)
     return _
 
@@ -2458,10 +2465,10 @@ class Column(DataFrame):
     # __getattr__ = _bin_op("getField")
 
     # string methods
-    rlike = _bin_op("rlike")
-    like = _bin_op("like")
-    startswith = _bin_op("startsWith")
-    endswith = _bin_op("endsWith")
+    rlike = _bin_op("rlike", pass_literal_through=True)
+    like = _bin_op("like", pass_literal_through=True)
+    startswith = _bin_op("startsWith", pass_literal_through=True)
+    endswith = _bin_op("endsWith", pass_literal_through=True)
     upper = _unary_op("upper")
     lower = _unary_op("lower")
 
@@ -2487,7 +2494,7 @@ class Column(DataFrame):
     isNotNull = _unary_op("isNotNull")
 
     # `as` is keyword
-    def As(self, alias):
+    def alias(self, alias):
         return Column(getattr(self._jsc, "as")(alias), self._jdf, self.sql_ctx)
 
     def cast(self, dataType):
@@ -2501,15 +2508,14 @@ class Column(DataFrame):
 
 
 def _aggregate_func(name):
-    """ Creat a function for aggregator by name"""
+    """ Create a function for aggregator by name"""
     def _(col):
         sc = SparkContext._active_spark_context
         if isinstance(col, Column):
             jcol = col._jc
         else:
             jcol = _create_column_from_name(col)
-        # FIXME: can not access dsl.min/max ...
-        jc = getattr(sc._jvm.org.apache.spark.sql.dsl(), name)(jcol)
+        jc = getattr(sc._jvm.org.apache.spark.sql.api.java.dsl, name)(jcol)
         return Column(jc)
     return staticmethod(_)