Thanks for catching this. Please feel free to submit a PR. I do not think Vanzin wants to introduce the behavior changes in that PR. We should do the code review more carefully.
Xiao 2018-06-14 9:18 GMT-07:00 Li Jin <ice.xell...@gmail.com>: > Are there objection to restore the behavior for PySpark users? I am happy > to submit a patch. > > On Thu, Jun 14, 2018 at 12:15 PM Reynold Xin <r...@databricks.com> wrote: > >> The behavior change is not good... >> >> On Thu, Jun 14, 2018 at 9:05 AM Li Jin <ice.xell...@gmail.com> wrote: >> >>> Ah, looks like it's this change: >>> https://github.com/apache/spark/commit/b3417b731d4e323398a0d7ec6e8640 >>> 5f4464f4f9#diff-3b5463566251d5b09fd328738a9e9bc5 >>> >>> It seems strange that by default Spark doesn't build with Hive but by >>> default PySpark requires it... >>> >>> This might also be a behavior change to PySpark users that build Spark >>> without Hive. The old behavior is "fall back to non-hive support" and the >>> new behavior is "program won't start". >>> >>> On Thu, Jun 14, 2018 at 11:51 AM, Sean Owen <sro...@gmail.com> wrote: >>> >>>> I think you would have to build with the 'hive' profile? but if so that >>>> would have been true for a while now. >>>> >>>> >>>> On Thu, Jun 14, 2018 at 10:38 AM Li Jin <ice.xell...@gmail.com> wrote: >>>> >>>>> Hey all, >>>>> >>>>> I just did a clean checkout of github.com/apache/spark but failed to >>>>> start PySpark, this is what I did: >>>>> >>>>> git clone g...@github.com:apache/spark.git; cd spark; build/sbt >>>>> package; bin/pyspark >>>>> >>>>> And got this exception: >>>>> >>>>> (spark-dev) Lis-MacBook-Pro:spark icexelloss$ bin/pyspark >>>>> >>>>> Python 3.6.3 |Anaconda, Inc.| (default, Nov 8 2017, 18:10:31) >>>>> >>>>> [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)] on darwin >>>>> >>>>> Type "help", "copyright", "credits" or "license" for more information. >>>>> >>>>> 18/06/14 11:34:14 WARN NativeCodeLoader: Unable to load native-hadoop >>>>> library for your platform... using builtin-java classes where applicable >>>>> >>>>> Using Spark's default log4j profile: org/apache/spark/log4j- >>>>> defaults.properties >>>>> >>>>> Setting default log level to "WARN". >>>>> >>>>> To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use >>>>> setLogLevel(newLevel). >>>>> >>>>> /Users/icexelloss/workspace/upstream2/spark/python/pyspark/shell.py:45: >>>>> UserWarning: Failed to initialize Spark session. >>>>> >>>>> warnings.warn("Failed to initialize Spark session.") >>>>> >>>>> Traceback (most recent call last): >>>>> >>>>> File >>>>> "/Users/icexelloss/workspace/upstream2/spark/python/pyspark/shell.py", >>>>> line 41, in <module> >>>>> >>>>> spark = SparkSession._create_shell_session() >>>>> >>>>> File >>>>> "/Users/icexelloss/workspace/upstream2/spark/python/pyspark/sql/session.py", >>>>> line 564, in _create_shell_session >>>>> >>>>> SparkContext._jvm.org.apache.hadoop.hive.conf.HiveConf() >>>>> >>>>> TypeError: 'JavaPackage' object is not callable >>>>> >>>>> I also tried to delete hadoop deps from my ivy2 cache and reinstall >>>>> them but no luck. I wonder: >>>>> >>>>> >>>>> 1. I have not seen this before, could this be caused by recent >>>>> change to head? >>>>> 2. Am I doing something wrong in the build process? >>>>> >>>>> >>>>> Thanks much! >>>>> Li >>>>> >>>>> >>>
