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Author SHA1 Message Date
hyukjinkwon 71cfba04ae [SPARK-23319][TESTS] Explicitly specify Pandas and PyArrow versions in PySpark tests (to skip or test)
## What changes were proposed in this pull request?

This PR proposes to explicitly specify Pandas and PyArrow versions in PySpark tests to skip or test.

We declared the extra dependencies:

b8bfce51ab/python/setup.py (L204)

In case of PyArrow:

Currently we only check if pyarrow is installed or not without checking the version. It already fails to run tests. For example, if PyArrow 0.7.0 is installed:

```
======================================================================
ERROR: test_vectorized_udf_wrong_return_type (pyspark.sql.tests.ScalarPandasUDF)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/.../spark/python/pyspark/sql/tests.py", line 4019, in test_vectorized_udf_wrong_return_type
    f = pandas_udf(lambda x: x * 1.0, MapType(LongType(), LongType()))
  File "/.../spark/python/pyspark/sql/functions.py", line 2309, in pandas_udf
    return _create_udf(f=f, returnType=return_type, evalType=eval_type)
  File "/.../spark/python/pyspark/sql/udf.py", line 47, in _create_udf
    require_minimum_pyarrow_version()
  File "/.../spark/python/pyspark/sql/utils.py", line 132, in require_minimum_pyarrow_version
    "however, your version was %s." % pyarrow.__version__)
ImportError: pyarrow >= 0.8.0 must be installed on calling Python process; however, your version was 0.7.0.

----------------------------------------------------------------------
Ran 33 tests in 8.098s

FAILED (errors=33)
```

In case of Pandas:

There are few tests for old Pandas which were tested only when Pandas version was lower, and I rewrote them to be tested when both Pandas version is lower and missing.

## How was this patch tested?

Manually tested by modifying the condition:

```
test_createDataFrame_column_name_encoding (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 1.19.2 must be installed; however, your version was 0.19.2.'
test_createDataFrame_does_not_modify_input (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 1.19.2 must be installed; however, your version was 0.19.2.'
test_createDataFrame_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 1.19.2 must be installed; however, your version was 0.19.2.'
```

```
test_createDataFrame_column_name_encoding (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
test_createDataFrame_does_not_modify_input (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
test_createDataFrame_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
```

```
test_createDataFrame_column_name_encoding (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 1.8.0 must be installed; however, your version was 0.8.0.'
test_createDataFrame_does_not_modify_input (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 1.8.0 must be installed; however, your version was 0.8.0.'
test_createDataFrame_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 1.8.0 must be installed; however, your version was 0.8.0.'
```

```
test_createDataFrame_column_name_encoding (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 0.8.0 must be installed; however, it was not found.'
test_createDataFrame_does_not_modify_input (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 0.8.0 must be installed; however, it was not found.'
test_createDataFrame_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 0.8.0 must be installed; however, it was not found.'
```

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #20487 from HyukjinKwon/pyarrow-pandas-skip.
2018-02-07 23:28:10 +09:00
Takuya UESHIN 12d20dd75b [SPARK-22874][PYSPARK][SQL][FOLLOW-UP] Modify error messages to show actual versions.
## What changes were proposed in this pull request?

This is a follow-up pr of #20054 modifying error messages for both pandas and pyarrow to show actual versions.

## How was this patch tested?

Existing tests.

Author: Takuya UESHIN <ueshin@databricks.com>

Closes #20074 from ueshin/issues/SPARK-22874_fup1.
2017-12-25 20:29:10 +09:00
Takuya UESHIN 13190a4f60 [SPARK-22874][PYSPARK][SQL] Modify checking pandas version to use LooseVersion.
## What changes were proposed in this pull request?

Currently we check pandas version by capturing if `ImportError` for the specific imports is raised or not but we can compare `LooseVersion` of the version strings as the same as we're checking pyarrow version.

## How was this patch tested?

Existing tests.

Author: Takuya UESHIN <ueshin@databricks.com>

Closes #20054 from ueshin/issues/SPARK-22874.
2017-12-22 20:09:51 +09:00
Bryan Cutler 59d52631eb [SPARK-22324][SQL][PYTHON] Upgrade Arrow to 0.8.0
## What changes were proposed in this pull request?

Upgrade Spark to Arrow 0.8.0 for Java and Python.  Also includes an upgrade of Netty to 4.1.17 to resolve dependency requirements.

The highlights that pertain to Spark for the update from Arrow versoin 0.4.1 to 0.8.0 include:

* Java refactoring for more simple API
* Java reduced heap usage and streamlined hot code paths
* Type support for DecimalType, ArrayType
* Improved type casting support in Python
* Simplified type checking in Python

## How was this patch tested?

Existing tests

Author: Bryan Cutler <cutlerb@gmail.com>
Author: Shixiong Zhu <zsxwing@gmail.com>

Closes #19884 from BryanCutler/arrow-upgrade-080-SPARK-22324.
2017-12-21 20:43:56 +09:00
Niranjan Padmanabhan a1e40b1f5d
[MINOR][DOCS] Remove consecutive duplicated words/typo in Spark Repo
## What changes were proposed in this pull request?
There are many locations in the Spark repo where the same word occurs consecutively. Sometimes they are appropriately placed, but many times they are not. This PR removes the inappropriately duplicated words.

## How was this patch tested?
N/A since only docs or comments were updated.

Author: Niranjan Padmanabhan <niranjan.padmanabhan@gmail.com>

Closes #16455 from neurons/np.structure_streaming_doc.
2017-01-04 15:07:29 +00:00
Tathagata Das 9a5071996b [SPARK-15953][WIP][STREAMING] Renamed ContinuousQuery to StreamingQuery
Renamed for simplicity, so that its obvious that its related to streaming.

Existing unit tests.

Author: Tathagata Das <tathagata.das1565@gmail.com>

Closes #13673 from tdas/SPARK-15953.
2016-06-15 10:46:07 -07:00
Reynold Xin a71d1364ae [SPARK-15686][SQL] Move user-facing streaming classes into sql.streaming
## What changes were proposed in this pull request?
This patch moves all user-facing structured streaming classes into sql.streaming. As part of this, I also added some since version annotation to methods and classes that don't have them.

## How was this patch tested?
Updated tests to reflect the moves.

Author: Reynold Xin <rxin@databricks.com>

Closes #13429 from rxin/SPARK-15686.
2016-06-01 10:14:40 -07:00
gatorsmile ef7a5e0bca [SPARK-14603][SQL][FOLLOWUP] Verification of Metadata Operations by Session Catalog
#### What changes were proposed in this pull request?
This follow-up PR is to address the remaining comments in https://github.com/apache/spark/pull/12385

The major change in this PR is to issue better error messages in PySpark by using the mechanism that was proposed by davies in https://github.com/apache/spark/pull/7135

For example, in PySpark, if we input the following statement:
```python
>>> l = [('Alice', 1)]
>>> df = sqlContext.createDataFrame(l)
>>> df.createTempView("people")
>>> df.createTempView("people")
```
Before this PR, the exception we will get is like
```
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/dataframe.py", line 152, in createTempView
    self._jdf.createTempView(name)
  File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py", line 933, in __call__
  File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py", line 312, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o35.createTempView.
: org.apache.spark.sql.catalyst.analysis.TempTableAlreadyExistsException: Temporary table 'people' already exists;
    at org.apache.spark.sql.catalyst.catalog.SessionCatalog.createTempView(SessionCatalog.scala:324)
    at org.apache.spark.sql.SparkSession.createTempView(SparkSession.scala:523)
    at org.apache.spark.sql.Dataset.createTempView(Dataset.scala:2328)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:280)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:211)
    at java.lang.Thread.run(Thread.java:745)
```
After this PR, the exception we will get become cleaner:
```
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/dataframe.py", line 152, in createTempView
    self._jdf.createTempView(name)
  File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py", line 933, in __call__
  File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/utils.py", line 75, in deco
    raise AnalysisException(s.split(': ', 1)[1], stackTrace)
pyspark.sql.utils.AnalysisException: u"Temporary table 'people' already exists;"
```

#### How was this patch tested?
Fixed an existing PySpark test case

Author: gatorsmile <gatorsmile@gmail.com>

Closes #13126 from gatorsmile/followup-14684.
2016-05-19 11:46:11 -07:00
gatorsmile 5c6b085578 [SPARK-14603][SQL] Verification of Metadata Operations by Session Catalog
Since we cannot really trust if the underlying external catalog can throw exceptions when there is an invalid metadata operation, let's do it in SessionCatalog.

- [X] The first step is to unify the error messages issued in Hive-specific Session Catalog and general Session Catalog.
- [X] The second step is to verify the inputs of metadata operations for partitioning-related operations. This is moved to a separate PR: https://github.com/apache/spark/pull/12801
- [X] The third step is to add database existence verification in `SessionCatalog`
- [X] The fourth step is to add table existence verification in `SessionCatalog`
- [X] The fifth step is to add function existence verification in `SessionCatalog`

Add test cases and verify the error messages we issued

Author: gatorsmile <gatorsmile@gmail.com>
Author: xiaoli <lixiao1983@gmail.com>
Author: Xiao Li <xiaoli@Xiaos-MacBook-Pro.local>

Closes #12385 from gatorsmile/verifySessionAPIs.
2016-05-10 11:25:55 -07:00
Burak Yavuz 78c8aaf849 [SPARK-14555] Second cut of Python API for Structured Streaming
## What changes were proposed in this pull request?

This PR adds Python APIs for:
 - `ContinuousQueryManager`
 - `ContinuousQueryException`

The `ContinuousQueryException` is a very basic wrapper, it doesn't provide the functionality that the Scala side provides, but it follows the same pattern for `AnalysisException`.

For `ContinuousQueryManager`, all APIs are provided except for registering listeners.

This PR also attempts to fix test flakiness by stopping all active streams just before tests.

## How was this patch tested?

Python Doc tests and unit tests

Author: Burak Yavuz <brkyvz@gmail.com>

Closes #12673 from brkyvz/pyspark-cqm.
2016-04-28 15:22:28 -07:00
Herman van Hovell a9b93e0739 [SPARK-14211][SQL] Remove ANTLR3 based parser
### What changes were proposed in this pull request?

This PR removes the ANTLR3 based parser, and moves the new ANTLR4 based parser into the `org.apache.spark.sql.catalyst.parser package`.

### How was this patch tested?

Existing unit tests.

cc rxin andrewor14 yhuai

Author: Herman van Hovell <hvanhovell@questtec.nl>

Closes #12071 from hvanhovell/SPARK-14211.
2016-03-31 09:25:09 -07:00
Herman van Hovell 600c0b69ca [SPARK-13713][SQL] Migrate parser from ANTLR3 to ANTLR4
### What changes were proposed in this pull request?
The current ANTLR3 parser is quite complex to maintain and suffers from code blow-ups. This PR introduces a new parser that is based on ANTLR4.

This parser is based on the [Presto's SQL parser](https://github.com/facebook/presto/blob/master/presto-parser/src/main/antlr4/com/facebook/presto/sql/parser/SqlBase.g4). The current implementation can parse and create Catalyst and SQL plans. Large parts of the HiveQl DDL and some of the DML functionality is currently missing, the plan is to add this in follow-up PRs.

This PR is a work in progress, and work needs to be done in the following area's:

- [x] Error handling should be improved.
- [x] Documentation should be improved.
- [x] Multi-Insert needs to be tested.
- [ ] Naming and package locations.

### How was this patch tested?

Catalyst and SQL unit tests.

Author: Herman van Hovell <hvanhovell@questtec.nl>

Closes #11557 from hvanhovell/ngParser.
2016-03-28 12:31:12 -07:00
Jeff Zhang 3a6807fdf0 [SPARK-11804] [PYSPARK] Exception raise when using Jdbc predicates opt…
…ion in PySpark

Author: Jeff Zhang <zjffdu@apache.org>

Closes #9791 from zjffdu/SPARK-11804.
2015-11-18 08:18:54 -08:00
Liang-Chi Hsieh 3dfa4ea526 [SPARK-11322] [PYSPARK] Keep full stack trace in captured exception
JIRA: https://issues.apache.org/jira/browse/SPARK-11322

As reported by JoshRosen in [databricks/spark-redshift/issues/89](https://github.com/databricks/spark-redshift/issues/89#issuecomment-149828308), the exception-masking behavior sometimes makes debugging harder. To deal with this issue, we should keep full stack trace in the captured exception.

Author: Liang-Chi Hsieh <viirya@appier.com>

Closes #9283 from viirya/py-exception-stacktrace.
2015-10-28 21:45:00 -07:00
Liang-Chi Hsieh 9b644c4130 [SPARK-9166][SQL][PYSPARK] Capture and hide IllegalArgumentException in Python API
JIRA: https://issues.apache.org/jira/browse/SPARK-9166

Simply capture and hide `IllegalArgumentException` in Python API.

Author: Liang-Chi Hsieh <viirya@appier.com>

Closes #7497 from viirya/hide_illegalargument and squashes the following commits:

8324dce [Liang-Chi Hsieh] Fix python style.
9ace67d [Liang-Chi Hsieh] Also check exception message.
8b2ce5c [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into hide_illegalargument
7be016a [Liang-Chi Hsieh] Capture and hide IllegalArgumentException in Python.
2015-07-19 00:32:56 -07:00
Davies Liu f958f27e20 [SPARK-8766] support non-ascii character in column names
Use UTF-8 to encode the name of column in Python 2, or it may failed to encode with default encoding ('ascii').

This PR also fix a bug when there is Java exception without error message.

Author: Davies Liu <davies@databricks.com>

Closes #7165 from davies/non_ascii and squashes the following commits:

02cb61a [Davies Liu] fix tests
3b09d31 [Davies Liu] add encoding in header
867754a [Davies Liu] support non-ascii character in column names
2015-07-01 16:43:18 -07:00
Davies Liu 58ee2a2e47 [SPARK-8738] [SQL] [PYSPARK] capture SQL AnalysisException in Python API
Capture the AnalysisException in SQL, hide the long java stack trace, only show the error message.

cc rxin

Author: Davies Liu <davies@databricks.com>

Closes #7135 from davies/ananylis and squashes the following commits:

dad7ae7 [Davies Liu] add comment
ec0c0e8 [Davies Liu] Update utils.py
cdd7edd [Davies Liu] add doc
7b044c2 [Davies Liu] fix python 3
f84d3bd [Davies Liu] capture SQL AnalysisException in Python API
2015-06-30 16:17:46 -07:00