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authorXiangrui Meng <meng@databricks.com>2015-07-30 17:16:03 -0700
committerReynold Xin <rxin@databricks.com>2015-07-30 17:16:03 -0700
commitdf32669514afc0223ecdeca30fbfbe0b40baef3a (patch)
treea23fde19657010f2245a72ac04450b8d33fe07b7 /python/pyspark/sql/dataframe.py
parentca71cc8c8b2d64b7756ae697c06876cd18b536dc (diff)
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[SPARK-7157][SQL] add sampleBy to DataFrame
This was previously committed but then reverted due to test failures (see #6769). Author: Xiangrui Meng <meng@databricks.com> Closes #7755 from rxin/SPARK-7157 and squashes the following commits: fbf9044 [Xiangrui Meng] fix python test 542bd37 [Xiangrui Meng] update test 604fe6d [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7157 f051afd [Xiangrui Meng] use udf instead of building expression f4e9425 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7157 8fb990b [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7157 103beb3 [Xiangrui Meng] add Java-friendly sampleBy 991f26f [Xiangrui Meng] fix seed 4a14834 [Xiangrui Meng] move sampleBy to stat 832f7cc [Xiangrui Meng] add sampleBy to DataFrame
Diffstat (limited to 'python/pyspark/sql/dataframe.py')
-rw-r--r--python/pyspark/sql/dataframe.py41
1 files changed, 41 insertions, 0 deletions
diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py
index d76e051bd7..0f3480c239 100644
--- a/python/pyspark/sql/dataframe.py
+++ b/python/pyspark/sql/dataframe.py
@@ -441,6 +441,42 @@ class DataFrame(object):
rdd = self._jdf.sample(withReplacement, fraction, long(seed))
return DataFrame(rdd, self.sql_ctx)
+ @since(1.5)
+ def sampleBy(self, col, fractions, seed=None):
+ """
+ Returns a stratified sample without replacement based on the
+ fraction given on each stratum.
+
+ :param col: column that defines strata
+ :param fractions:
+ sampling fraction for each stratum. If a stratum is not
+ specified, we treat its fraction as zero.
+ :param seed: random seed
+ :return: a new DataFrame that represents the stratified sample
+
+ >>> from pyspark.sql.functions import col
+ >>> dataset = sqlContext.range(0, 100).select((col("id") % 3).alias("key"))
+ >>> sampled = dataset.sampleBy("key", fractions={0: 0.1, 1: 0.2}, seed=0)
+ >>> sampled.groupBy("key").count().orderBy("key").show()
+ +---+-----+
+ |key|count|
+ +---+-----+
+ | 0| 3|
+ | 1| 8|
+ +---+-----+
+
+ """
+ if not isinstance(col, str):
+ raise ValueError("col must be a string, but got %r" % type(col))
+ if not isinstance(fractions, dict):
+ raise ValueError("fractions must be a dict but got %r" % type(fractions))
+ for k, v in fractions.items():
+ if not isinstance(k, (float, int, long, basestring)):
+ raise ValueError("key must be float, int, long, or string, but got %r" % type(k))
+ fractions[k] = float(v)
+ seed = seed if seed is not None else random.randint(0, sys.maxsize)
+ return DataFrame(self._jdf.stat().sampleBy(col, self._jmap(fractions), seed), self.sql_ctx)
+
@since(1.4)
def randomSplit(self, weights, seed=None):
"""Randomly splits this :class:`DataFrame` with the provided weights.
@@ -1314,6 +1350,11 @@ class DataFrameStatFunctions(object):
freqItems.__doc__ = DataFrame.freqItems.__doc__
+ def sampleBy(self, col, fractions, seed=None):
+ return self.df.sampleBy(col, fractions, seed)
+
+ sampleBy.__doc__ = DataFrame.sampleBy.__doc__
+
def _test():
import doctest