[
https://issues.apache.org/jira/browse/SPARK-8408?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Felix Maximilian Möller updated SPARK-8408:
-------------------------------------------
Description:
h3. Given
{code}
d = [{'name': 'Alice', 'age': 1},{'name': 'Bob', 'age': 2}]
person_df = sqlContext.createDataFrame(d)
{code}
h3. When
{code}
person_df.filter(person_df.age==1 or person_df.age==2).collect()
{code}
h3. Expected
[Row(age=1, name=u'Alice'), Row(age=2, name=u'Bob')]
h3. Actual
[Row(age=1, name=u'Alice')]
h3. While
{code}
person_df.filter("age = 1 or age = 2").collect()
{code}
yields the correct result:
[Row(age=1, name=u'Alice'), Row(age=2, name=u'Bob')]
was:
Given
=====
.. code:: python
d = [{'name': 'Alice', 'age': 1},{'name': 'Bob', 'age': 2}]
person_df = sqlContext.createDataFrame(d)
When
====
.. code:: python
person_df.filter(person_df.age==1 or person_df.age==2).collect()
Expected
========
[Row(age=1, name=u'Alice'), Row(age=2, name=u'Bob')]
Actual
======
[Row(age=1, name=u'Alice')]
While
=====
.. code:: python
person_df.filter("age = 1 or age = 2").collect()
yields the correct result:
[Row(age=1, name=u'Alice'), Row(age=2, name=u'Bob')]
> Python OR operator is not considered while creating a column of boolean type
> ----------------------------------------------------------------------------
>
> Key: SPARK-8408
> URL: https://issues.apache.org/jira/browse/SPARK-8408
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.4.0
> Environment: OSX Apache Spark 1.4.0
> Reporter: Felix Maximilian Möller
> Priority: Minor
> Attachments: bug_report.ipynb.json
>
>
> h3. Given
> {code}
> d = [{'name': 'Alice', 'age': 1},{'name': 'Bob', 'age': 2}]
> person_df = sqlContext.createDataFrame(d)
> {code}
> h3. When
> {code}
> person_df.filter(person_df.age==1 or person_df.age==2).collect()
> {code}
> h3. Expected
> [Row(age=1, name=u'Alice'), Row(age=2, name=u'Bob')]
> h3. Actual
> [Row(age=1, name=u'Alice')]
> h3. While
> {code}
> person_df.filter("age = 1 or age = 2").collect()
> {code}
> yields the correct result:
> [Row(age=1, name=u'Alice'), Row(age=2, name=u'Bob')]
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