spark-instrumented-optimizer/python/run-tests

#!/usr/bin/env bash

#
# 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.
#


# Figure out where the Spark framework is installed
FWDIR="$(cd `dirname $0`; cd ../; pwd)"

# CD into the python directory to find things on the right path
cd "$FWDIR/python"

FAILED=0

rm -f unit-tests.log

# Remove the metastore and warehouse directory created by the HiveContext tests in Spark SQL
rm -rf metastore warehouse

function run_test() {
    echo "Running test: $1"
    SPARK_TESTING=1 $FWDIR/bin/pyspark $1 2>&1 | tee -a unit-tests.log
    FAILED=$((PIPESTATUS[0]||$FAILED))

    # Fail and exit on the first test failure.
    if [[ $FAILED != 0 ]]; then
        cat unit-tests.log | grep -v "^[0-9][0-9]*" # filter all lines starting with a number.
        echo -en "\033[31m"  # Red
        echo "Had test failures; see logs."
        echo -en "\033[0m"  # No color
        exit -1
    fi
}

echo "Running PySpark tests. Output is in python/unit-tests.log."

# Try to test with Python 2.6, since that's the minimum version that we support:
if [ $(which python2.6) ]; then
    export PYSPARK_PYTHON="python2.6"
fi

echo "Testing with Python version:"
$PYSPARK_PYTHON --version

run_test "pyspark/rdd.py"
run_test "pyspark/context.py"
run_test "pyspark/conf.py"
run_test "pyspark/sql.py"
# These tests are included in the module-level docs, and so must
# be handled on a higher level rather than within the python file.
export PYSPARK_DOC_TEST=1
run_test "pyspark/broadcast.py"
run_test "pyspark/accumulators.py"
run_test "pyspark/serializers.py"
unset PYSPARK_DOC_TEST
run_test "pyspark/shuffle.py"
run_test "pyspark/tests.py"
run_test "pyspark/mllib/_common.py"
run_test "pyspark/mllib/classification.py"
run_test "pyspark/mllib/clustering.py"
run_test "pyspark/mllib/linalg.py"
run_test "pyspark/mllib/random.py"
run_test "pyspark/mllib/recommendation.py"
run_test "pyspark/mllib/regression.py"
run_test "pyspark/mllib/stat.py"
run_test "pyspark/mllib/tests.py"
run_test "pyspark/mllib/tree.py"
run_test "pyspark/mllib/util.py"

if [[ $FAILED == 0 ]]; then
    echo -en "\033[32m"  # Green
    echo "Tests passed."
    echo -en "\033[0m"  # No color
fi

# TODO: in the long-run, it would be nice to use a test runner like `nose`.
# The doctest fixtures are the current barrier to doing this.