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Dsl -> functions, toDF() #9

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Feb 13, 2015
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Dsl -> functions, toDF() #9

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1d767e3
Dsl -> functions, toDF()
Feb 12, 2015
d781e01
schema() -> schema
Feb 12, 2015
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8 changes: 8 additions & 0 deletions python/docs/pyspark.sql.rst
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Expand Up @@ -16,3 +16,11 @@ pyspark.sql.types module
:members:
:undoc-members:
:show-inheritance:


pyspark.sql.functions module
------------------------
.. automodule:: pyspark.sql.functions
:members:
:undoc-members:
:show-inheritance:
3 changes: 1 addition & 2 deletions python/pyspark/sql/__init__.py
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Expand Up @@ -34,9 +34,8 @@

from pyspark.sql.context import SQLContext, HiveContext
from pyspark.sql.types import Row
from pyspark.sql.dataframe import DataFrame, GroupedData, Column, Dsl, SchemaRDD
from pyspark.sql.dataframe import DataFrame, GroupedData, Column, SchemaRDD

__all__ = [
'SQLContext', 'HiveContext', 'DataFrame', 'GroupedData', 'Column', 'Row',
'Dsl',
]
27 changes: 24 additions & 3 deletions python/pyspark/sql/context.py
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Expand Up @@ -38,6 +38,25 @@
__all__ = ["SQLContext", "HiveContext"]


def _monkey_patch_RDD(sqlCtx):
def toDF(self, schema=None, sampleRatio=None):
"""
Convert current :class:`RDD` into a :class:`DataFrame`

This is a shorthand for `sqlCtx.createDataFrame(rdd, schema, sampleRatio)`

:param schema: a StructType or list of names of columns
:param samplingRatio: the sample ratio of rows used for inferring
:return: a DataFrame

>>> rdd.toDF().collect()
[Row(name=u'Alice', age=1)]
"""
return sqlCtx.createDataFrame(self, schema, sampleRatio)

RDD.toDF = toDF


class SQLContext(object):

"""Main entry point for Spark SQL functionality.
Expand Down Expand Up @@ -70,6 +89,7 @@ def __init__(self, sparkContext, sqlContext=None):
self._jsc = self._sc._jsc
self._jvm = self._sc._jvm
self._scala_SQLContext = sqlContext
_monkey_patch_RDD(self)
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in case i forget, can u add to the end of docstring for SQLContext that this adds a toDF method to RDD?


@property
def _ssql_ctx(self):
Expand Down Expand Up @@ -442,7 +462,7 @@ def jsonFile(self, path, schema=None, samplingRatio=1.0):
Row(f1=2, f2=None, f3=Row(field4=22,..., f4=[Row(field7=u'row2')])
Row(f1=None, f2=u'row3', f3=Row(field4=33, field5=[]), f4=None)

>>> df3 = sqlCtx.jsonFile(jsonFile, df1.schema())
>>> df3 = sqlCtx.jsonFile(jsonFile, df1.schema)
>>> sqlCtx.registerRDDAsTable(df3, "table2")
>>> df4 = sqlCtx.sql(
... "SELECT field1 AS f1, field2 as f2, field3 as f3, "
Expand Down Expand Up @@ -495,7 +515,7 @@ def jsonRDD(self, rdd, schema=None, samplingRatio=1.0):
Row(f1=2, f2=None, f3=Row(field4=22..., f4=[Row(field7=u'row2')])
Row(f1=None, f2=u'row3', f3=Row(field4=33, field5=[]), f4=None)

>>> df3 = sqlCtx.jsonRDD(json, df1.schema())
>>> df3 = sqlCtx.jsonRDD(json, df1.schema)
>>> sqlCtx.registerRDDAsTable(df3, "table2")
>>> df4 = sqlCtx.sql(
... "SELECT field1 AS f1, field2 as f2, field3 as f3, "
Expand Down Expand Up @@ -766,7 +786,8 @@ def _test():
Row(field1=2, field2="row2"),
Row(field1=3, field2="row3")]
)
globs['df'] = sqlCtx.createDataFrame(rdd)
_monkey_patch_RDD(sqlCtx)
globs['df'] = rdd.toDF()
jsonStrings = [
'{"field1": 1, "field2": "row1", "field3":{"field4":11}}',
'{"field1" : 2, "field3":{"field4":22, "field5": [10, 11]},'
Expand Down
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