spark-instrumented-optimizer/python/pyspark/shell.py
Bryan Cutler 021c19702c [SPARK-15456][PYSPARK] Fixed PySpark shell context initialization when HiveConf not present
## What changes were proposed in this pull request?

When PySpark shell cannot find HiveConf, it will fallback to create a SparkSession from a SparkContext.  This fixes a bug caused by using a variable to SparkContext before it was initialized.

## How was this patch tested?

Manually starting PySpark shell and using the SparkContext

Author: Bryan Cutler <cutlerb@gmail.com>

Closes #13237 from BryanCutler/pyspark-shell-session-context-SPARK-15456.
2016-05-20 16:41:57 -07:00

78 lines
2.4 KiB
Python

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""
An interactive shell.
This file is designed to be launched as a PYTHONSTARTUP script.
"""
import atexit
import os
import platform
import py4j
import pyspark
from pyspark.context import SparkContext
from pyspark.sql import SparkSession, SQLContext
from pyspark.storagelevel import StorageLevel
if os.environ.get("SPARK_EXECUTOR_URI"):
SparkContext.setSystemProperty("spark.executor.uri", os.environ["SPARK_EXECUTOR_URI"])
SparkContext._ensure_initialized()
try:
# Try to access HiveConf, it will raise exception if Hive is not added
SparkContext._jvm.org.apache.hadoop.hive.conf.HiveConf()
spark = SparkSession.builder\
.enableHiveSupport()\
.getOrCreate()
except py4j.protocol.Py4JError:
spark = SparkSession.builder.getOrCreate()
except TypeError:
spark = SparkSession.builder.getOrCreate()
sc = spark.sparkContext
atexit.register(lambda: sc.stop())
# for compatibility
sqlContext = spark._wrapped
sqlCtx = sqlContext
print("""Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version %s
/_/
""" % sc.version)
print("Using Python version %s (%s, %s)" % (
platform.python_version(),
platform.python_build()[0],
platform.python_build()[1]))
print("SparkSession available as 'spark'.")
# The ./bin/pyspark script stores the old PYTHONSTARTUP value in OLD_PYTHONSTARTUP,
# which allows us to execute the user's PYTHONSTARTUP file:
_pythonstartup = os.environ.get('OLD_PYTHONSTARTUP')
if _pythonstartup and os.path.isfile(_pythonstartup):
with open(_pythonstartup) as f:
code = compile(f.read(), _pythonstartup, 'exec')
exec(code)