Add first/last ignoreNulls in python

python/pyspark/sql/functions.py

@@ -81,8 +81,6 @@ def _():
 
     'max': 'Aggregate function: returns the maximum value of the expression in a group.',
     'min': 'Aggregate function: returns the minimum value of the expression in a group.',
-    'first': 'Aggregate function: returns the first value in a group.',
-    'last': 'Aggregate function: returns the last value in a group.',
     'count': 'Aggregate function: returns the number of items in a group.',
     'sum': 'Aggregate function: returns the sum of all values in the expression.',
     'avg': 'Aggregate function: returns the average of the values in a group.',
@@ -277,6 +275,13 @@ def countDistinct(col, *cols):
     jc = sc._jvm.functions.countDistinct(_to_java_column(col), _to_seq(sc, cols, _to_java_column))
     return Column(jc)
 
+@since(1.3)
+def first(col, ignorenulls=False):
+    """Aggregate function: returns the first value in a group.
+    """
+    sc = SparkContext._active_spark_context
+    jc = sc._jvm.functions.first(_to_java_column(col), ignorenulls)
+    return Column(jc)
 
 @since(1.6)
 def input_file_name():
@@ -309,6 +314,13 @@ def isnull(col):
     sc = SparkContext._active_spark_context
     return Column(sc._jvm.functions.isnull(_to_java_column(col)))
 
+@since(1.3)
+def last(col, ignorenulls=False):
+    """Aggregate function: returns the last value in a group.
+    """
+    sc = SparkContext._active_spark_context
+    jc = sc._jvm.functions.last(_to_java_column(col), ignorenulls)
+    return Column(jc)
 
 @since(1.6)
 def monotonically_increasing_id():

python/pyspark/sql/tests.py

@@ -641,6 +641,16 @@ def test_aggregator(self):
         self.assertTrue(95 < g.agg(functions.approxCountDistinct(df.key)).first()[0])
         self.assertEqual(100, g.agg(functions.countDistinct(df.value)).first()[0])
 
+    def test_first_last_ignorenulls(self):
+        from pyspark.sql import functions
+        df = self.sqlCtx.range(0, 100)
+        df2 = df.select(functions.when(df.id % 3 == 0, None).otherwise(df.id).alias("id"))
+        df3 = df2.select(functions.first(df2.id, False).alias('a'),
+                         functions.first(df2.id, True).alias('b'),
+                         functions.last(df2.id, False).alias('c'),
+                         functions.last(df2.id, True).alias('d'))
+        self.assertEqual([Row(a=None, b=1, c=None, d=98)], df3.collect())
+
     def test_corr(self):
         import math
         df = self.sc.parallelize([Row(a=i, b=math.sqrt(i)) for i in range(10)]).toDF()