Yuval Tanny created SPARK-11303:
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Summary: sample (without replacement) + filter returns wrong
results in DataFrame
Key: SPARK-11303
URL: https://issues.apache.org/jira/browse/SPARK-11303
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.5.1
Environment: pyspark local mode, linux.
Reporter: Yuval Tanny
When sampling and then filtering DataFrame from python, we get inconsistent
result when not caching the sampled DataFrame. This bug doesn't appear in
spark 1.4.1.
d = sqlContext.createDataFrame(sc.parallelize([[1]] * 50 + [[2]] * 50),['t'])
d_sampled = d.sample(False, 0.1, 1)
print d_sampled.count()
print d_sampled.filter('t = 1').count()
print d_sampled.filter('t != 1').count()
d_sampled.cache()
print d_sampled.count()
print d_sampled.filter('t = 1').count()
print d_sampled.filter('t != 1').count()
output:
14
7
8
14
7
7
Thanks!
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