Build / Spark Connect Python-only (master-server, 35-client, Python 3.11) #66
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# 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. | |
# | |
name: Build / Spark Connect Python-only (master-server, 35-client, Python 3.11) | |
on: | |
schedule: | |
- cron: '0 21 * * *' | |
jobs: | |
# Build: build Spark and run the tests for specified modules using SBT | |
build: | |
name: "Build modules: pyspark-connect" | |
runs-on: ubuntu-latest | |
timeout-minutes: 100 | |
if: github.repository == 'apache/spark' | |
steps: | |
- name: Checkout Spark repository | |
uses: actions/checkout@v4 | |
with: | |
fetch-depth: 0 | |
- name: Cache SBT and Maven | |
uses: actions/cache@v4 | |
with: | |
path: | | |
build/apache-maven-* | |
build/*.jar | |
~/.sbt | |
key: build-spark-connect-python-only-${{ hashFiles('**/pom.xml', 'project/build.properties', 'build/mvn', 'build/sbt', 'build/sbt-launch-lib.bash', 'build/spark-build-info') }} | |
restore-keys: | | |
build-spark-connect-python-only- | |
- name: Cache Coursier local repository | |
uses: actions/cache@v4 | |
with: | |
path: ~/.cache/coursier | |
key: coursier-build-spark-connect-python-only-${{ hashFiles('**/pom.xml') }} | |
restore-keys: | | |
coursier-build-spark-connect-python-only- | |
- name: Install Java 17 | |
uses: actions/setup-java@v4 | |
with: | |
distribution: zulu | |
java-version: 17 | |
- name: Install Python 3.11 | |
uses: actions/setup-python@v5 | |
with: | |
python-version: '3.11' | |
architecture: x64 | |
- name: Build Spark | |
run: | | |
./build/sbt -Phive Test/package | |
- name: Install Python dependencies | |
run: | | |
pip install 'numpy==1.25.1' 'pyarrow==12.0.1' 'pandas<=2.0.3' scipy unittest-xml-reporting plotly>=4.8 'mlflow>=2.3.1' coverage 'matplotlib==3.7.2' openpyxl 'memory-profiler==0.60.0' 'scikit-learn==1.1.*' | |
# Add Python deps for Spark Connect. | |
pip install 'grpcio==1.67.0' 'grpcio-status==1.67.0' 'protobuf==5.28.3' 'googleapis-common-protos==1.65.0' 'graphviz==0.20.3' | |
# Add torch as a testing dependency for TorchDistributor | |
pip install 'torch==2.0.1' 'torchvision==0.15.2' torcheval | |
- name: Run tests | |
env: | |
SPARK_TESTING: 1 | |
SPARK_SKIP_CONNECT_COMPAT_TESTS: 1 | |
SPARK_CONNECT_TESTING_REMOTE: sc://localhost | |
run: | | |
# Make less noisy | |
cp conf/log4j2.properties.template conf/log4j2.properties | |
sed -i 's/rootLogger.level = info/rootLogger.level = warn/g' conf/log4j2.properties | |
# Start a Spark Connect server for local | |
PYTHONPATH="python/lib/pyspark.zip:python/lib/py4j-0.10.9.7-src.zip:$PYTHONPATH" ./sbin/start-connect-server.sh \ | |
--driver-java-options "-Dlog4j.configurationFile=file:$GITHUB_WORKSPACE/conf/log4j2.properties" \ | |
--jars "`find connector/protobuf/target -name spark-protobuf-*SNAPSHOT.jar`,`find connector/avro/target -name spark-avro*SNAPSHOT.jar`" | |
# Checkout to branch-3.5 to use the tests in branch-3.5. | |
cd .. | |
git clone --single-branch --branch branch-3.5 $GITHUB_SERVER_URL/$GITHUB_REPOSITORY spark-3.5 | |
cd spark-3.5 | |
# Several tests related to catalog requires to run them sequencially, e.g., writing a table in a listener. | |
# Run branch-3.5 tests | |
./python/run-tests --parallelism=1 --python-executables=python3 --modules pyspark-connect | |
# None of tests are dependent on each other in Pandas API on Spark so run them in parallel | |
./python/run-tests --parallelism=1 --python-executables=python3 --modules pyspark-pandas-connect,pyspark-pandas-slow-connect | |
- name: Upload test results to report | |
if: always() | |
uses: actions/upload-artifact@v4 | |
with: | |
name: test-results-spark-connect-python-only | |
path: "**/target/test-reports/*.xml" | |
- name: Upload Spark Connect server log file | |
if: ${{ !success() }} | |
uses: actions/upload-artifact@v4 | |
with: | |
name: unit-tests-log-spark-connect-python-only | |
path: logs/*.out |