diff options
Diffstat (limited to 'python/pyspark/sql/dataframe.py')
| -rw-r--r-- | python/pyspark/sql/dataframe.py | 14 |
1 files changed, 8 insertions, 6 deletions
diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py index 52bd75bf8a..c68c97e926 100644 --- a/python/pyspark/sql/dataframe.py +++ b/python/pyspark/sql/dataframe.py @@ -803,7 +803,7 @@ class GroupedData(object): >>> df.groupBy().mean('age').collect() [Row(AVG(age#0)=3.5)] >>> df3.groupBy().mean('age', 'height').collect() - [Row(AVG(age#4)=3.5, AVG(height#5)=82.5)] + [Row(AVG(age#4L)=3.5, AVG(height#5L)=82.5)] """ @df_varargs_api @@ -814,7 +814,7 @@ class GroupedData(object): >>> df.groupBy().avg('age').collect() [Row(AVG(age#0)=3.5)] >>> df3.groupBy().avg('age', 'height').collect() - [Row(AVG(age#4)=3.5, AVG(height#5)=82.5)] + [Row(AVG(age#4L)=3.5, AVG(height#5L)=82.5)] """ @df_varargs_api @@ -825,7 +825,7 @@ class GroupedData(object): >>> df.groupBy().max('age').collect() [Row(MAX(age#0)=5)] >>> df3.groupBy().max('age', 'height').collect() - [Row(MAX(age#4)=5, MAX(height#5)=85)] + [Row(MAX(age#4L)=5, MAX(height#5L)=85)] """ @df_varargs_api @@ -836,7 +836,7 @@ class GroupedData(object): >>> df.groupBy().min('age').collect() [Row(MIN(age#0)=2)] >>> df3.groupBy().min('age', 'height').collect() - [Row(MIN(age#4)=2, MIN(height#5)=80)] + [Row(MIN(age#4L)=2, MIN(height#5L)=80)] """ @df_varargs_api @@ -847,7 +847,7 @@ class GroupedData(object): >>> df.groupBy().sum('age').collect() [Row(SUM(age#0)=7)] >>> df3.groupBy().sum('age', 'height').collect() - [Row(SUM(age#4)=7, SUM(height#5)=165)] + [Row(SUM(age#4L)=7, SUM(height#5L)=165)] """ @@ -1051,7 +1051,9 @@ def _test(): sc = SparkContext('local[4]', 'PythonTest') globs['sc'] = sc globs['sqlCtx'] = SQLContext(sc) - globs['df'] = sc.parallelize([Row(name='Alice', age=2), Row(name='Bob', age=5)]).toDF() + globs['df'] = sc.parallelize([(2, 'Alice'), (5, 'Bob')])\ + .toDF(StructType([StructField('age', IntegerType()), + StructField('name', StringType())])) globs['df2'] = sc.parallelize([Row(name='Tom', height=80), Row(name='Bob', height=85)]).toDF() globs['df3'] = sc.parallelize([Row(name='Alice', age=2, height=80), Row(name='Bob', age=5, height=85)]).toDF() |