spark-instrumented-optimizer/python/pyspark
hyukjinkwon 224e0e785b [SPARK-19701][SQL][PYTHON] Throws a correct exception for 'in' operator against column
## What changes were proposed in this pull request?

This PR proposes to remove incorrect implementation that has been not executed so far (at least from Spark 1.5.2) for `in` operator and throw a correct exception rather than saying it is a bool. I tested the codes above in 1.5.2, 1.6.3, 2.1.0 and in the master branch as below:

**1.5.2**

```python
>>> df = sqlContext.createDataFrame([[1]])
>>> 1 in df._1
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File ".../spark-1.5.2-bin-hadoop2.6/python/pyspark/sql/column.py", line 418, in __nonzero__
    raise ValueError("Cannot convert column into bool: please use '&' for 'and', '|' for 'or', "
ValueError: Cannot convert column into bool: please use '&' for 'and', '|' for 'or', '~' for 'not' when building DataFrame boolean expressions.
```

**1.6.3**

```python
>>> 1 in sqlContext.range(1).id
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File ".../spark-1.6.3-bin-hadoop2.6/python/pyspark/sql/column.py", line 447, in __nonzero__
    raise ValueError("Cannot convert column into bool: please use '&' for 'and', '|' for 'or', "
ValueError: Cannot convert column into bool: please use '&' for 'and', '|' for 'or', '~' for 'not' when building DataFrame boolean expressions.
```

**2.1.0**

```python
>>> 1 in spark.range(1).id
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File ".../spark-2.1.0-bin-hadoop2.7/python/pyspark/sql/column.py", line 426, in __nonzero__
    raise ValueError("Cannot convert column into bool: please use '&' for 'and', '|' for 'or', "
ValueError: Cannot convert column into bool: please use '&' for 'and', '|' for 'or', '~' for 'not' when building DataFrame boolean expressions.
```

**Current Master**

```python
>>> 1 in spark.range(1).id
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File ".../spark/python/pyspark/sql/column.py", line 452, in __nonzero__
    raise ValueError("Cannot convert column into bool: please use '&' for 'and', '|' for 'or', "
ValueError: Cannot convert column into bool: please use '&' for 'and', '|' for 'or', '~' for 'not' when building DataFrame boolean expressions.
```

**After**

```python
>>> 1 in spark.range(1).id
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File ".../spark/python/pyspark/sql/column.py", line 184, in __contains__
    raise ValueError("Cannot apply 'in' operator against a column: please use 'contains' "
ValueError: Cannot apply 'in' operator against a column: please use 'contains' in a string column or 'array_contains' function for an array column.
```

In more details,

It seems the implementation intended to support this

```python
1 in df.column
```

However, currently, it throws an exception as below:

```python
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File ".../spark/python/pyspark/sql/column.py", line 426, in __nonzero__
    raise ValueError("Cannot convert column into bool: please use '&' for 'and', '|' for 'or', "
ValueError: Cannot convert column into bool: please use '&' for 'and', '|' for 'or', '~' for 'not' when building DataFrame boolean expressions.
```

What happens here is as below:

```python
class Column(object):
    def __contains__(self, item):
        print "I am contains"
        return Column()
    def __nonzero__(self):
        raise Exception("I am nonzero.")

>>> 1 in Column()
I am contains
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 6, in __nonzero__
Exception: I am nonzero.
```

It seems it calls `__contains__` first and then `__nonzero__` or `__bool__` is being called against `Column()` to make this a bool (or int to be specific).

It seems `__nonzero__` (for Python 2), `__bool__` (for Python 3) and `__contains__` forcing the the return into a bool unlike other operators. There are few references about this as below:

https://bugs.python.org/issue16011
http://stackoverflow.com/questions/12244074/python-source-code-for-built-in-in-operator/12244378#12244378
http://stackoverflow.com/questions/38542543/functionality-of-python-in-vs-contains/38542777

It seems we can't overwrite `__nonzero__` or `__bool__` as a workaround to make this working because these force the return type as a bool as below:

```python
class Column(object):
    def __contains__(self, item):
        print "I am contains"
        return Column()
    def __nonzero__(self):
        return "a"

>>> 1 in Column()
I am contains
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: __nonzero__ should return bool or int, returned str
```

## How was this patch tested?

Added unit tests in `tests.py`.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #17160 from HyukjinKwon/SPARK-19701.
2017-03-05 18:04:52 -08:00
..
ml [SPARK-19348][PYTHON] PySpark keyword_only decorator is not thread-safe 2017-03-03 16:43:45 -08:00
mllib [SPARK-17645][MLLIB][ML][FOLLOW-UP] document minor change 2017-01-10 13:09:58 +00:00
sql [SPARK-19701][SQL][PYTHON] Throws a correct exception for 'in' operator against column 2017-03-05 18:04:52 -08:00
streaming [SPARK-19405][STREAMING] Support for cross-account Kinesis reads via STS 2017-02-22 11:32:36 -05:00
__init__.py [SPARK-19348][PYTHON] PySpark keyword_only decorator is not thread-safe 2017-03-03 16:43:45 -08:00
accumulators.py [SPARK-8652] [PYSPARK] Check return value for all uses of doctest.testmod() 2015-06-26 08:12:22 -07:00
broadcast.py [SPARK-17472] [PYSPARK] Better error message for serialization failures of large objects in Python 2016-09-14 13:37:35 -07:00
cloudpickle.py [SPARK-19019] [PYTHON] Fix hijacked collections.namedtuple and port cloudpickle changes for PySpark to work with Python 3.6.0 2017-01-17 09:53:20 -08:00
conf.py [SPARK-18447][DOCS] Fix the markdown for Note:/NOTE:/Note that across Python API documentation 2016-11-22 11:40:18 +00:00
context.py [SPARK-13330][PYSPARK] PYTHONHASHSEED is not propgated to python worker 2017-02-24 15:04:42 -08:00
daemon.py [SPARK-4897] [PySpark] Python 3 support 2015-04-16 16:20:57 -07:00
files.py [SPARK-3309] [PySpark] Put all public API in __all__ 2014-09-03 11:49:45 -07:00
find_spark_home.py [SPARK-1267][SPARK-18129] Allow PySpark to be pip installed 2016-11-16 14:22:15 -08:00
heapq3.py [SPARK-8652] [PYSPARK] Check return value for all uses of doctest.testmod() 2015-06-26 08:12:22 -07:00
java_gateway.py [SPARK-1267][SPARK-18129] Allow PySpark to be pip installed 2016-11-16 14:22:15 -08:00
join.py [SPARK-14202] [PYTHON] Use generator expression instead of list comp in python_full_outer_jo… 2016-03-28 14:51:36 -07:00
profiler.py [SPARK-8652] [PYSPARK] Check return value for all uses of doctest.testmod() 2015-06-26 08:12:22 -07:00
rdd.py [SPARK-13330][PYSPARK] PYTHONHASHSEED is not propgated to python worker 2017-02-24 15:04:42 -08:00
rddsampler.py [SPARK-4897] [PySpark] Python 3 support 2015-04-16 16:20:57 -07:00
resultiterable.py [SPARK-3074] [PySpark] support groupByKey() with single huge key 2015-04-09 17:07:23 -07:00
serializers.py [SPARK-19019] [PYTHON] Fix hijacked collections.namedtuple and port cloudpickle changes for PySpark to work with Python 3.6.0 2017-01-17 09:53:20 -08:00
shell.py [SPARK-16536][SQL][PYSPARK][MINOR] Expose sql in PySpark Shell 2016-07-13 22:24:26 -07:00
shuffle.py [SPARK-10710] Remove ability to disable spilling in core and SQL 2015-09-19 21:40:21 -07:00
statcounter.py [SPARK-6919] [PYSPARK] Add asDict method to StatCounter 2015-09-29 13:38:15 -07:00
status.py [SPARK-4172] [PySpark] Progress API in Python 2015-02-17 13:36:43 -08:00
storagelevel.py [SPARK-13992][CORE][PYSPARK][FOLLOWUP] Update OFF_HEAP semantics for Java api and Python api 2016-04-12 23:06:55 -07:00
taskcontext.py [SPARK-18576][PYTHON] Add basic TaskContext information to PySpark 2016-12-20 15:51:21 -08:00
tests.py [SPARK-19348][PYTHON] PySpark keyword_only decorator is not thread-safe 2017-03-03 16:43:45 -08:00
traceback_utils.py [SPARK-1087] Move python traceback utilities into new traceback_utils.py file. 2014-09-15 19:28:17 -07:00
version.py [SPARK-1267][SPARK-18129] Allow PySpark to be pip installed 2016-11-16 14:22:15 -08:00
worker.py [SPARK-18576][PYTHON] Add basic TaskContext information to PySpark 2016-12-20 15:51:21 -08:00