Skip to content
Snippets Groups Projects
Select Git revision
  • working
  • baesline-eviction-with-logging
  • evict-by-size
  • master default protected
  • v2.3.0
  • v2.3.0-rc4
  • v2.3.0-rc3
  • v2.3.0-rc2
  • v2.3.0-rc1
  • v2.2.1
  • v2.2.1-rc2
  • v2.2.1-rc1
  • v2.1.2
  • v2.1.2-rc4
  • v2.1.2-rc3
  • v2.1.2-rc2
  • v2.1.2-rc1
  • v2.2.0
  • v2.1.1
  • v2.1.0
  • v2.0.2
  • v1.6.3
  • v2.0.1
  • v2.0.0
24 results
Compare
user avatar
[SPARK-19019] [PYTHON] Fix hijacked `collections.namedtuple` and port...
hyukjinkwon authored 
[SPARK-19019] [PYTHON] Fix hijacked `collections.namedtuple` and port cloudpickle changes for PySpark to work with Python 3.6.0

## What changes were proposed in this pull request?

Currently, PySpark does not work with Python 3.6.0.

Running `./bin/pyspark` simply throws the error as below and PySpark does not work at all:

```
Traceback (most recent call last):
  File ".../spark/python/pyspark/shell.py", line 30, in <module>
    import pyspark
  File ".../spark/python/pyspark/__init__.py", line 46, in <module>
    from pyspark.context import SparkContext
  File ".../spark/python/pyspark/context.py", line 36, in <module>
    from pyspark.java_gateway import launch_gateway
  File ".../spark/python/pyspark/java_gateway.py", line 31, in <module>
    from py4j.java_gateway import java_import, JavaGateway, GatewayClient
  File "<frozen importlib._bootstrap>", line 961, in _find_and_load
  File "<frozen importlib._bootstrap>", line 950, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 646, in _load_unlocked
  File "<frozen importlib._bootstrap>", line 616, in _load_backward_compatible
  File ".../spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 18, in <module>
  File "/usr/local/Cellar/python3/3.6.0/Frameworks/Python.framework/Versions/3.6/lib/python3.6/pydoc.py", line 62, in <module>
    import pkgutil
  File "/usr/local/Cellar/python3/3.6.0/Frameworks/Python.framework/Versions/3.6/lib/python3.6/pkgutil.py", line 22, in <module>
    ModuleInfo = namedtuple('ModuleInfo', 'module_finder name ispkg')
  File ".../spark/python/pyspark/serializers.py", line 394, in namedtuple
    cls = _old_namedtuple(*args, **kwargs)
TypeError: namedtuple() missing 3 required keyword-only arguments: 'verbose', 'rename', and 'module'
```

The root cause seems because some arguments of `namedtuple` are now completely keyword-only arguments from Python 3.6.0 (See https://bugs.python.org/issue25628

).

We currently copy this function via `types.FunctionType` which does not set the default values of keyword-only arguments (meaning `namedtuple.__kwdefaults__`) and this seems causing internally missing values in the function (non-bound arguments).

This PR proposes to work around this by manually setting it via `kwargs` as `types.FunctionType` seems not supporting to set this.

Also, this PR ports the changes in cloudpickle for compatibility for Python 3.6.0.

## How was this patch tested?

Manually tested with Python 2.7.6 and Python 3.6.0.

```
./bin/pyspsark
```

, manual creation of `namedtuple` both in local and rdd with Python 3.6.0,

and Jenkins tests for other Python versions.

Also,

```
./run-tests --python-executables=python3.6
```

```
Will test against the following Python executables: ['python3.6']
Will test the following Python modules: ['pyspark-core', 'pyspark-ml', 'pyspark-mllib', 'pyspark-sql', 'pyspark-streaming']
Finished test(python3.6): pyspark.sql.tests (192s)
Finished test(python3.6): pyspark.accumulators (3s)
Finished test(python3.6): pyspark.mllib.tests (198s)
Finished test(python3.6): pyspark.broadcast (3s)
Finished test(python3.6): pyspark.conf (2s)
Finished test(python3.6): pyspark.context (14s)
Finished test(python3.6): pyspark.ml.classification (21s)
Finished test(python3.6): pyspark.ml.evaluation (11s)
Finished test(python3.6): pyspark.ml.clustering (20s)
Finished test(python3.6): pyspark.ml.linalg.__init__ (0s)
Finished test(python3.6): pyspark.streaming.tests (240s)
Finished test(python3.6): pyspark.tests (240s)
Finished test(python3.6): pyspark.ml.recommendation (19s)
Finished test(python3.6): pyspark.ml.feature (36s)
Finished test(python3.6): pyspark.ml.regression (37s)
Finished test(python3.6): pyspark.ml.tuning (28s)
Finished test(python3.6): pyspark.mllib.classification (26s)
Finished test(python3.6): pyspark.mllib.evaluation (18s)
Finished test(python3.6): pyspark.mllib.clustering (44s)
Finished test(python3.6): pyspark.mllib.linalg.__init__ (0s)
Finished test(python3.6): pyspark.mllib.feature (26s)
Finished test(python3.6): pyspark.mllib.fpm (23s)
Finished test(python3.6): pyspark.mllib.random (8s)
Finished test(python3.6): pyspark.ml.tests (92s)
Finished test(python3.6): pyspark.mllib.stat.KernelDensity (0s)
Finished test(python3.6): pyspark.mllib.linalg.distributed (25s)
Finished test(python3.6): pyspark.mllib.stat._statistics (15s)
Finished test(python3.6): pyspark.mllib.recommendation (24s)
Finished test(python3.6): pyspark.mllib.regression (26s)
Finished test(python3.6): pyspark.profiler (9s)
Finished test(python3.6): pyspark.mllib.tree (16s)
Finished test(python3.6): pyspark.shuffle (1s)
Finished test(python3.6): pyspark.mllib.util (18s)
Finished test(python3.6): pyspark.serializers (11s)
Finished test(python3.6): pyspark.rdd (20s)
Finished test(python3.6): pyspark.sql.conf (8s)
Finished test(python3.6): pyspark.sql.catalog (17s)
Finished test(python3.6): pyspark.sql.column (18s)
Finished test(python3.6): pyspark.sql.context (18s)
Finished test(python3.6): pyspark.sql.group (27s)
Finished test(python3.6): pyspark.sql.dataframe (33s)
Finished test(python3.6): pyspark.sql.functions (35s)
Finished test(python3.6): pyspark.sql.types (6s)
Finished test(python3.6): pyspark.sql.streaming (13s)
Finished test(python3.6): pyspark.streaming.util (0s)
Finished test(python3.6): pyspark.sql.session (16s)
Finished test(python3.6): pyspark.sql.window (4s)
Finished test(python3.6): pyspark.sql.readwriter (35s)
Tests passed in 433 seconds
```

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #16429 from HyukjinKwon/SPARK-19019.

(cherry picked from commit 20e62806)
Signed-off-by: default avatarDavies Liu <davies.liu@gmail.com>
2ff36691
History
user avatar 2ff36691
History
Name Last commit Last update
..
docs
lib
pyspark
test_support
.gitignore
MANIFEST.in
README.md
pylintrc
run-tests
run-tests.py
setup.cfg
setup.py
README.md

Apache Spark

Spark is a fast and general cluster computing system for Big Data. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.

http://spark.apache.org/

Online Documentation

You can find the latest Spark documentation, including a programming guide, on the project web page

Python Packaging

This README file only contains basic information related to pip installed PySpark. This packaging is currently experimental and may change in future versions (although we will do our best to keep compatibility). Using PySpark requires the Spark JARs, and if you are building this from source please see the builder instructions at "Building Spark".

The Python packaging for Spark is not intended to replace all of the other use cases. This Python packaged version of Spark is suitable for interacting with an existing cluster (be it Spark standalone, YARN, or Mesos) - but does not contain the tools required to setup your own standalone Spark cluster. You can download the full version of Spark from the Apache Spark downloads page.

NOTE: If you are using this with a Spark standalone cluster you must ensure that the version (including minor version) matches or you may experience odd errors.

Python Requirements

At its core PySpark depends on Py4J (currently version 0.10.4), but additional sub-packages have their own requirements (including numpy and pandas).