[DOP-30579] Allow using SyncMaster worker image as spark.kubernetes.container.image

docker/Dockerfile.worker

@@ -2,6 +2,7 @@ ARG PYTHON_VERSION=3.13
 FROM python:$PYTHON_VERSION-slim-bookworm AS base
 
 RUN apt-get update && apt-get install -y --no-install-recommends \
+        tini \
         openjdk-17-jdk-headless \
         # required for HDFS/Hive with Kerberos enabled
         krb5-user \

docker/entrypoint_worker.sh

@@ -1,8 +1,101 @@
 #!/usr/bin/env bash
-set -e
 
-# https://docs.celeryq.dev/en/stable/userguide/workers.html#max-tasks-per-child-setting
-# Required to start each Celery task in separated process, avoiding issues with global Spark session object
+# Based on https://github.com/apache/spark/blob/v3.5.7/resource-managers/kubernetes/docker/src/main/dockerfiles/spark/entrypoint.sh
 
-# exec is required to forward all signals to the main process
-exec python -m celery -A syncmaster.worker.celery worker --max-tasks-per-child=1 "$@"
+set -ex
+
+if [ -z "$JAVA_HOME" ]; then
+  JAVA_HOME=$(java -XshowSettings:properties -version 2>&1 > /dev/null | grep 'java.home' | awk '{print $3}')
+fi
+if [ -z "$SPARK_HOME" ]; then
+  SPARK_HOME=$(python -c 'import pyspark; import pathlib; print(pathlib.Path(pyspark.__file__).parent.resolve())')
+fi
+
+SPARK_CLASSPATH="$SPARK_CLASSPATH:${SPARK_HOME}/jars/*"
+
+env | grep SPARK_JAVA_OPT_ | sort -t_ -k4 -n | sed 's/[^=]*=\(.*\)/\1/g' > java_opts.txt
+if [ "$(command -v readarray)" ]; then
+  readarray -t SPARK_EXECUTOR_JAVA_OPTS < java_opts.txt
+else
+  SPARK_EXECUTOR_JAVA_OPTS=("${(@f)$(< java_opts.txt)}")
+fi
+
+if [ -n "$SPARK_EXTRA_CLASSPATH" ]; then
+  SPARK_CLASSPATH="$SPARK_CLASSPATH:$SPARK_EXTRA_CLASSPATH"
+fi
+
+if ! [ -z ${PYSPARK_PYTHON+x} ]; then
+    export PYSPARK_PYTHON
+fi
+if ! [ -z ${PYSPARK_DRIVER_PYTHON+x} ]; then
+    export PYSPARK_DRIVER_PYTHON
+fi
+
+# If HADOOP_HOME is set and SPARK_DIST_CLASSPATH is not set, set it here so Hadoop jars are available to the executor.
+# It does not set SPARK_DIST_CLASSPATH if already set, to avoid overriding customizations of this value from elsewhere e.g. Docker/K8s.
+if [ -n "${HADOOP_HOME}"  ] && [ -z "${SPARK_DIST_CLASSPATH}"  ]; then
+  export SPARK_DIST_CLASSPATH="$($HADOOP_HOME/bin/hadoop classpath)"
+fi
+
+if ! [ -z ${HADOOP_CONF_DIR+x} ]; then
+  SPARK_CLASSPATH="$HADOOP_CONF_DIR:$SPARK_CLASSPATH";
+fi
+
+if ! [ -z ${SPARK_CONF_DIR+x} ]; then
+  SPARK_CLASSPATH="$SPARK_CONF_DIR:$SPARK_CLASSPATH";
+elif ! [ -z ${SPARK_HOME+x} ]; then
+  SPARK_CLASSPATH="$SPARK_HOME/conf:$SPARK_CLASSPATH";
+fi
+
+# Place IVY2 jars at the end of classpath to avoid conflicts with Spark and Hadoop jars
+IVY2_HOME=$(realpath ~/.ivy2)
+SPARK_CLASSPATH="$SPARK_CLASSPATH:${IVY2_HOME}/jars/*"
+
+# SPARK-43540: add current working directory into executor classpath
+SPARK_CLASSPATH="$SPARK_CLASSPATH:$PWD"
+
+case "$1" in
+  driver)
+    shift 1
+    CMD=(
+      "$SPARK_HOME/bin/spark-submit"
+      --conf "spark.driver.bindAddress=$SPARK_DRIVER_BIND_ADDRESS"
+      --conf "spark.executorEnv.SPARK_DRIVER_POD_IP=$SPARK_DRIVER_BIND_ADDRESS"
+      --deploy-mode client
+      "$@"
+    )
+    ;;
+  executor)
+    shift 1
+    CMD=(
+      ${JAVA_HOME}/bin/java
+      "${SPARK_EXECUTOR_JAVA_OPTS[@]}"
+      -Xms$SPARK_EXECUTOR_MEMORY
+      -Xmx$SPARK_EXECUTOR_MEMORY
+      -cp "$SPARK_CLASSPATH:$SPARK_DIST_CLASSPATH"
+      org.apache.spark.scheduler.cluster.k8s.KubernetesExecutorBackend
+      --driver-url $SPARK_DRIVER_URL
+      --executor-id $SPARK_EXECUTOR_ID
+      --cores $SPARK_EXECUTOR_CORES
+      --app-id $SPARK_APPLICATION_ID
+      --hostname $SPARK_EXECUTOR_POD_IP
+      --resourceProfileId $SPARK_RESOURCE_PROFILE_ID
+      --podName $SPARK_EXECUTOR_POD_NAME
+    )
+    ;;
+
+  *)
+    # https://docs.celeryq.dev/en/stable/userguide/workers.html#max-tasks-per-child-setting
+    # Required to start each Celery task in separated process, avoiding issues with global Spark session object
+    CMD=(
+      python -m celery
+      -A syncmaster.worker.celery
+      worker
+      --max-tasks-per-child=1
+      "$@"
+    )
+    ;;
+esac
+
+# Execute the container CMD under tini for better hygiene
+exec /usr/bin/tini -s -- "${CMD[@]}"

docs/changelog/next_release/295.feature.rst

@@ -0,0 +1 @@
+Allow using SyncMaster worker image as ``spark.kubernetes.container.image``.

docs/reference/worker/create_spark_session.rst

@@ -23,6 +23,20 @@ It is possible to alter default `Spark Session configuration <https://spark.apac
             spark.sql.pyspark.jvmStacktrace.enabled: true
             spark.ui.enabled: false
 
+For example, to use SyncMaster on Spark + Kubernetes, you can use worker image for Spark executor containers:
+
+.. code-block:: yaml
+    :caption: config.yml
+
+    worker:
+        spark_session_default_config:
+            spark.master: k8s://https://kubernetes.default.svc
+            spark.driver.bindAddress: 0.0.0.0
+            spark.kubernetes.authenticate.driver.serviceAccountName: spark
+            spark.sql.pyspark.jvmStacktrace.enabled: true
+            spark.kubernetes.container.image: mtsrus/syncmaster-worker:{TAG}
+
+
 Custom Spark session factory
 ----------------------------
 

syncmaster/worker/spark.py

@@ -131,12 +131,14 @@ def get_spark_session_conf(
     if spark_master and spark_master.startswith("local"):
         config["spark.master"] = f"local[{tasks}]"
         config["spark.driver.memory"] = f"{memory_mb}M"
-        config["spark.default.parallelism"] = tasks * cores_per_task
     else:
         config["spark.executor.memory"] = f"{memory_mb}M"
-        config["spark.executor.cores"] = cores_per_task
         config["spark.executor.instances"] = tasks
-        config["spark.dynamicAllocation.maxExecutors"] = tasks
+
+    config["spark.executor.cores"] = cores_per_task
+    config["spark.default.parallelism"] = tasks * cores_per_task
+    config["spark.dynamicAllocation.maxExecutors"] = tasks  # yarn
+    config["spark.kubernetes.executor.limit.cores"] = cores_per_task  # k8s
 
     if maven_packages:
         log.debug("Include Maven packages: %s", maven_packages)