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29 commits

Author SHA1 Message Date
zero323 f0169a1c6a [SPARK-20290][MINOR][PYTHON][SQL] Add PySpark wrapper for eqNullSafe
## What changes were proposed in this pull request?

Adds Python bindings for `Column.eqNullSafe`

## How was this patch tested?

Manual tests, existing unit tests, doc build.

Author: zero323 <zero323@users.noreply.github.com>

Closes #17605 from zero323/SPARK-20290.
2017-05-01 09:43:32 -07:00
hyukjinkwon d228cd0b02 [SPARK-20442][PYTHON][DOCS] Fill up documentations for functions in Column API in PySpark
## What changes were proposed in this pull request?

This PR proposes to fill up the documentation with examples for `bitwiseOR`, `bitwiseAND`, `bitwiseXOR`. `contains`, `asc` and `desc` in `Column` API.

Also, this PR fixes minor typos in the documentation and matches some of the contents between Scala doc and Python doc.

Lastly, this PR suggests to use `spark` rather than `sc` in doc tests in `Column` for Python documentation.

## How was this patch tested?

Doc tests were added and manually tested with the commands below:

`./python/run-tests.py --module pyspark-sql`
`./python/run-tests.py --module pyspark-sql --python-executable python3`
`./dev/lint-python`

Output was checked via `make html` under `./python/docs`. The snapshots will be left on the codes with comments.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #17737 from HyukjinKwon/SPARK-20442.
2017-04-29 13:46:40 -07:00
Michael Patterson 8765bc17d0 [SPARK-20132][DOCS] Add documentation for column string functions
## What changes were proposed in this pull request?
Add docstrings to column.py for the Column functions `rlike`, `like`, `startswith`, and `endswith`. Pass these docstrings through `_bin_op`

There may be a better place to put the docstrings. I put them immediately above the Column class.

## How was this patch tested?

I ran `make html` on my local computer to remake the documentation, and verified that the html pages were displaying the docstrings correctly. I tried running `dev-tests`, and the formatting tests passed. However, my mvn build didn't work I think due to issues on my computer.

These docstrings are my original work and free license.

davies has done the most recent work reorganizing `_bin_op`

Author: Michael Patterson <map222@gmail.com>

Closes #17469 from map222/patterson-documentation.
2017-04-22 19:58:54 -07:00
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
Wenchen Fan 4fa4cf1d4c [SPARK-19706][PYSPARK] add Column.contains in pyspark
## What changes were proposed in this pull request?

to be consistent with the scala API, we should also add `contains` to `Column` in pyspark.

## How was this patch tested?

updated unit test

Author: Wenchen Fan <wenchen@databricks.com>

Closes #17036 from cloud-fan/pyspark.
2017-02-23 13:22:39 -08:00
Sheamus K. Parkes 7b64f7aa03 [SPARK-18541][PYTHON] Add metadata parameter to pyspark.sql.Column.alias()
## What changes were proposed in this pull request?

Add a `metadata` keyword parameter to `pyspark.sql.Column.alias()` to allow users to mix-in metadata while manipulating `DataFrame`s in `pyspark`.  Without this, I believe it was necessary to pass back through `SparkSession.createDataFrame` each time a user wanted to manipulate `StructField.metadata` in `pyspark`.

This pull request also improves consistency between the Scala and Python APIs (i.e. I did not add any functionality that was not already in the Scala API).

Discussed ahead of time on JIRA with marmbrus

## How was this patch tested?

Added unit tests (and doc tests).  Ran the pertinent tests manually.

Author: Sheamus K. Parkes <shea.parkes@milliman.com>

Closes #16094 from shea-parkes/pyspark-column-alias-metadata.
2017-02-14 09:57:43 -08:00
zero323 e02ac303c6 [SPARK-19429][PYTHON][SQL] Support slice arguments in Column.__getitem__
## What changes were proposed in this pull request?

- Add support for `slice` arguments in `Column.__getitem__`.
- Remove obsolete `__getslice__` bindings.

## How was this patch tested?

Existing unit tests, additional tests covering `[]` with `slice`.

Author: zero323 <zero323@users.noreply.github.com>

Closes #16771 from zero323/SPARK-19429.
2017-02-13 15:23:56 -08:00
zero323 06fbc35549 [SPARK-19403][PYTHON][SQL] Correct pyspark.sql.column.__all__ list.
## What changes were proposed in this pull request?

This removes from the `__all__` list class names that are not defined (visible) in the `pyspark.sql.column`.

## How was this patch tested?

Existing unit tests.

Author: zero323 <zero323@users.noreply.github.com>

Closes #16742 from zero323/SPARK-19403.
2017-01-30 18:01:02 +01:00
jiangxingbo 5f02d2e5b4 [SPARK-17215][SQL] Method SQLContext.parseDataType(dataTypeString: String) could be removed.
## What changes were proposed in this pull request?

Method `SQLContext.parseDataType(dataTypeString: String)` could be removed, we should use `SparkSession.parseDataType(dataTypeString: String)` instead.
This require updating PySpark.

## How was this patch tested?

Existing test cases.

Author: jiangxingbo <jiangxb1987@gmail.com>

Closes #14790 from jiangxb1987/parseDataType.
2016-08-24 23:36:04 -07:00
WeichenXu a15ca5533d [SPARK-15464][ML][MLLIB][SQL][TESTS] Replace SQLContext and SparkContext with SparkSession using builder pattern in python test code
## What changes were proposed in this pull request?

Replace SQLContext and SparkContext with SparkSession using builder pattern in python test code.

## How was this patch tested?

Existing test.

Author: WeichenXu <WeichenXu123@outlook.com>

Closes #13242 from WeichenXu123/python_doctest_update_sparksession.
2016-05-23 18:14:48 -07:00
Reynold Xin 40ba87f769 [SPARK-15278] [SQL] Remove experimental tag from Python DataFrame
## What changes were proposed in this pull request?
Earlier we removed experimental tag for Scala/Java DataFrames, but haven't done so for Python. This patch removes the experimental flag for Python and declares them stable.

## How was this patch tested?
N/A.

Author: Reynold Xin <rxin@databricks.com>

Closes #13062 from rxin/SPARK-15278.
2016-05-11 15:12:27 -07:00
Andrew Or fa79d346e1 [SPARK-14896][SQL] Deprecate HiveContext in python
## What changes were proposed in this pull request?

See title.

## How was this patch tested?

PySpark tests.

Author: Andrew Or <andrew@databricks.com>

Closes #12917 from andrewor14/deprecate-hive-context-python.
2016-05-04 17:39:30 -07:00
Reynold Xin 926a93e54b [SPARK-14088][SQL] Some Dataset API touch-up
## What changes were proposed in this pull request?
1. Deprecated unionAll. It is pretty confusing to have both "union" and "unionAll" when the two do the same thing in Spark but are different in SQL.
2. Rename reduce in KeyValueGroupedDataset to reduceGroups so it is more consistent with rest of the functions in KeyValueGroupedDataset. Also makes it more obvious what "reduce" and "reduceGroups" mean. Previously it was confusing because it could be reducing a Dataset, or just reducing groups.
3. Added a "name" function, which is more natural to name columns than "as" for non-SQL users.
4. Remove "subtract" function since it is just an alias for "except".

## How was this patch tested?
All changes should be covered by existing tests. Also added couple test cases to cover "name".

Author: Reynold Xin <rxin@databricks.com>

Closes #11908 from rxin/SPARK-14088.
2016-03-22 23:43:09 -07:00
Reynold Xin 8e0b030606 [SPARK-10380][SQL] Fix confusing documentation examples for astype/drop_duplicates.
## What changes were proposed in this pull request?
We have seen users getting confused by the documentation for astype and drop_duplicates, because the examples in them do not use these functions (but do uses their aliases). This patch simply removes all examples for these functions, and say that they are aliases.

## How was this patch tested?
Existing PySpark unit tests.

Closes #11543.

Author: Reynold Xin <rxin@databricks.com>

Closes #11698 from rxin/SPARK-10380.
2016-03-14 19:25:49 -07:00
Cheng Lian d9efe63ecd [SPARK-12799] Simplify various string output for expressions
This PR introduces several major changes:

1. Replacing `Expression.prettyString` with `Expression.sql`

   The `prettyString` method is mostly an internal, developer faced facility for debugging purposes, and shouldn't be exposed to users.

1. Using SQL-like representation as column names for selected fields that are not named expression (back-ticks and double quotes should be removed)

   Before, we were using `prettyString` as column names when possible, and sometimes the result column names can be weird.  Here are several examples:

   Expression         | `prettyString` | `sql`      | Note
   ------------------ | -------------- | ---------- | ---------------
   `a && b`           | `a && b`       | `a AND b`  |
   `a.getField("f")`  | `a[f]`         | `a.f`      | `a` is a struct

1. Adding trait `NonSQLExpression` extending from `Expression` for expressions that don't have a SQL representation (e.g. Scala UDF/UDAF and Java/Scala object expressions used for encoders)

   `NonSQLExpression.sql` may return an arbitrary user facing string representation of the expression.

Author: Cheng Lian <lian@databricks.com>

Closes #10757 from liancheng/spark-12799.simplify-expression-string-methods.
2016-02-21 22:53:15 +08:00
Reynold Xin cbbcd8e425 [SPARK-12791][SQL] Simplify CaseWhen by breaking "branches" into "conditions" and "values"
This pull request rewrites CaseWhen expression to break the single, monolithic "branches" field into a sequence of tuples (Seq[(condition, value)]) and an explicit optional elseValue field.

Prior to this pull request, each even position in "branches" represents the condition for each branch, and each odd position represents the value for each branch. The use of them have been pretty confusing with a lot sliding windows or grouped(2) calls.

Author: Reynold Xin <rxin@databricks.com>

Closes #10734 from rxin/simplify-case.
2016-01-13 12:44:35 -08:00
Reynold Xin 77ab49b857 [SPARK-12600][SQL] Remove deprecated methods in Spark SQL
Author: Reynold Xin <rxin@databricks.com>

Closes #10559 from rxin/remove-deprecated-sql.
2016-01-04 18:02:38 -08:00
Davies Liu 1d91202010 [SPARK-11836][SQL] udf/cast should not create new SQLContext
They should use the existing SQLContext.

Author: Davies Liu <davies@databricks.com>

Closes #9914 from davies/create_udf.
2015-11-23 13:44:30 -08:00
0x0FFF c34fc19765 [SPARK-9014] [SQL] Allow Python spark API to use built-in exponential operator
This PR addresses (SPARK-9014)[https://issues.apache.org/jira/browse/SPARK-9014]
Added functionality: `Column` object in Python now supports exponential operator `**`
Example:
```
from pyspark.sql import *
df = sqlContext.createDataFrame([Row(a=2)])
df.select(3**df.a,df.a**3,df.a**df.a).collect()
```
Outputs:
```
[Row(POWER(3.0, a)=9.0, POWER(a, 3.0)=8.0, POWER(a, a)=4.0)]
```

Author: 0x0FFF <programmerag@gmail.com>

Closes #8658 from 0x0FFF/SPARK-9014.
2015-09-11 15:19:04 -07:00
Davies Liu 3a11e50e21 [SPARK-10373] [PYSPARK] move @since into pyspark from sql
cc mengxr

Author: Davies Liu <davies@databricks.com>

Closes #8657 from davies/move_since.
2015-09-08 20:56:22 -07:00
0x0FFF 6cd98c1878 [SPARK-10417] [SQL] Iterating through Column results in infinite loop
`pyspark.sql.column.Column` object has `__getitem__` method, which makes it iterable for Python. In fact it has `__getitem__` to address the case when the column might be a list or dict, for you to be able to access certain element of it in DF API. The ability to iterate over it is just a side effect that might cause confusion for the people getting familiar with Spark DF (as you might iterate this way on Pandas DF for instance)

Issue reproduction:
```
df = sqlContext.jsonRDD(sc.parallelize(['{"name": "El Magnifico"}']))
for i in df["name"]: print i
```

Author: 0x0FFF <programmerag@gmail.com>

Closes #8574 from 0x0FFF/SPARK-10417.
2015-09-02 13:36:36 -07:00
Sean Owen 69c9c17716 [SPARK-9613] [CORE] Ban use of JavaConversions and migrate all existing uses to JavaConverters
Replace `JavaConversions` implicits with `JavaConverters`

Most occurrences I've seen so far are necessary conversions; a few have been avoidable. None are in critical code as far as I see, yet.

Author: Sean Owen <sowen@cloudera.com>

Closes #8033 from srowen/SPARK-9613.
2015-08-25 12:33:13 +01:00
Reynold Xin 5e1b0ef079 [SPARK-9659][SQL] Rename inSet to isin to match Pandas function.
Inspiration drawn from this blog post: https://lab.getbase.com/pandarize-spark-dataframes/

Author: Reynold Xin <rxin@databricks.com>

Closes #7977 from rxin/isin and squashes the following commits:

9b1d3d6 [Reynold Xin] Added return.
2197d37 [Reynold Xin] Fixed test case.
7c1b6cf [Reynold Xin] Import warnings.
4f4a35d [Reynold Xin] [SPARK-9659][SQL] Rename inSet to isin to match Pandas function.
2015-08-06 10:39:16 -07:00
Davies Liu 7fb5ae5024 [SPARK-8573] [SPARK-8568] [SQL] [PYSPARK] raise Exception if column is used in booelan expression
It's a common mistake that user will put Column in a boolean expression (together with `and` , `or`), which does not work as expected, we should raise a exception in that case, and suggest user to use `&`, `|` instead.

Author: Davies Liu <davies@databricks.com>

Closes #6961 from davies/column_bool and squashes the following commits:

9f19beb [Davies Liu] update message
af74bd6 [Davies Liu] fix tests
07dff84 [Davies Liu] address comments, fix tests
f70c08e [Davies Liu] raise Exception if column is used in booelan expression
2015-06-23 15:51:16 -07:00
Davies Liu 605ddbb27c [SPARK-8038] [SQL] [PYSPARK] fix Column.when() and otherwise()
Thanks ogirardot, closes #6580

cc rxin JoshRosen

Author: Davies Liu <davies@databricks.com>

Closes #6590 from davies/when and squashes the following commits:

c0f2069 [Davies Liu] fix Column.when() and otherwise()
2015-06-02 13:38:06 -07:00
Davies Liu efe3bfdf49 [SPARK-7322, SPARK-7836, SPARK-7822][SQL] DataFrame window function related updates
1. ntile should take an integer as parameter.
2. Added Python API (based on #6364)
3. Update documentation of various DataFrame Python functions.

Author: Davies Liu <davies@databricks.com>
Author: Reynold Xin <rxin@databricks.com>

Closes #6374 from rxin/window-final and squashes the following commits:

69004c7 [Reynold Xin] Style fix.
288cea9 [Reynold Xin] Update documentaiton.
7cb8985 [Reynold Xin] Merge pull request #6364 from davies/window
66092b4 [Davies Liu] update docs
ed73cb4 [Reynold Xin] [SPARK-7322][SQL] Improve DataFrame window function documentation.
ef55132 [Davies Liu] Merge branch 'master' of github.com:apache/spark into window4
8936ade [Davies Liu] fix maxint in python 3
2649358 [Davies Liu] update docs
778e2c0 [Davies Liu] SPARK-7836 and SPARK-7822: Python API of window functions
2015-05-23 08:30:05 -07:00
kaka1992 699906e538 [SPARK-7394][SQL] Add Pandas style cast (astype)
Author: kaka1992 <kaka_1992@163.com>

Closes #6313 from kaka1992/astype and squashes the following commits:

73dfd0b [kaka1992] [SPARK-7394] Add Pandas style cast (astype)
ad8feb2 [kaka1992] [SPARK-7394] Add Pandas style cast (astype)
4f328b7 [kaka1992] [SPARK-7394] Add Pandas style cast (astype)
2015-05-21 11:50:39 -07:00
Davies Liu 8ddcb25b39 [SPARK-7606] [SQL] [PySpark] add version to Python SQL API docs
Add version info for public Python SQL API.

cc rxin

Author: Davies Liu <davies@databricks.com>

Closes #6295 from davies/versions and squashes the following commits:

cfd91e6 [Davies Liu] add more version for DataFrame API
600834d [Davies Liu] add version to SQL API docs
2015-05-20 23:05:54 -07:00
Davies Liu d7b69946cb [SPARK-7543] [SQL] [PySpark] split dataframe.py into multiple files
dataframe.py is splited into column.py, group.py and dataframe.py:
```
   360 column.py
  1223 dataframe.py
   183 group.py
```

Author: Davies Liu <davies@databricks.com>

Closes #6201 from davies/split_df and squashes the following commits:

fc8f5ab [Davies Liu] split dataframe.py into multiple files
2015-05-15 20:09:15 -07:00