b3417b731d
Currently, in spark-shell, if the session fails to start, the
user sees a bunch of unrelated errors which are caused by code
in the shell initialization that references the "spark" variable,
which does not exist in that case. Things like:
```
<console>:14: error: not found: value spark
import spark.sql
```
The user is also left with a non-working shell (unless they want
to just write non-Spark Scala or Python code, that is).
This change fails the whole shell session at the point where the
failure occurs, so that the last error message is the one with
the actual information about the failure.
For the python error handling, I moved the session initialization code
to session.py, so that traceback.print_exc() only shows the last error.
Otherwise, the printed exception would contain all previous exceptions
with a message "During handling of the above exception, another
exception occurred", making the actual error kinda hard to parse.
Tested with spark-shell, pyspark (with 2.7 and 3.5), by forcing an
error during SparkContext initialization.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes #21368 from vanzin/SPARK-16451.
77 lines
2.3 KiB
Python
77 lines
2.3 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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"""
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An interactive shell.
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This file is designed to be launched as a PYTHONSTARTUP script.
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"""
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import atexit
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import os
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import platform
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import warnings
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import py4j
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from pyspark import SparkConf
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from pyspark.context import SparkContext
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from pyspark.sql import SparkSession, SQLContext
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if os.environ.get("SPARK_EXECUTOR_URI"):
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SparkContext.setSystemProperty("spark.executor.uri", os.environ["SPARK_EXECUTOR_URI"])
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SparkContext._ensure_initialized()
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try:
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spark = SparkSession._create_shell_session()
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except Exception:
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import sys
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import traceback
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warnings.warn("Failed to initialize Spark session.")
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traceback.print_exc(file=sys.stderr)
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sys.exit(1)
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sc = spark.sparkContext
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sql = spark.sql
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atexit.register(lambda: sc.stop())
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# for compatibility
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sqlContext = spark._wrapped
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sqlCtx = sqlContext
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print("""Welcome to
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____ __
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/ __/__ ___ _____/ /__
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_\ \/ _ \/ _ `/ __/ '_/
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/__ / .__/\_,_/_/ /_/\_\ version %s
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/_/
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""" % sc.version)
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print("Using Python version %s (%s, %s)" % (
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platform.python_version(),
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platform.python_build()[0],
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platform.python_build()[1]))
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print("SparkSession available as 'spark'.")
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# The ./bin/pyspark script stores the old PYTHONSTARTUP value in OLD_PYTHONSTARTUP,
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# which allows us to execute the user's PYTHONSTARTUP file:
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_pythonstartup = os.environ.get('OLD_PYTHONSTARTUP')
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if _pythonstartup and os.path.isfile(_pythonstartup):
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with open(_pythonstartup) as f:
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code = compile(f.read(), _pythonstartup, 'exec')
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exec(code)
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