fix(Dockerfile): install openjdk-17-jre-headless for spark-submit

Spark 4.1.2 requires Java 17 at runtime (it boots a JVM via the
bin/spark-submit shell script). The previous Dockerfile only installed
curl, ca-certificates, and tar — leaving spark-submit unable to find
the 'java' binary.

A JRE is sufficient (not the full JDK) because spark-submit does not
compile Java at runtime — it loads pre-built JARs from $SPARK_HOME/jars/.
JRE-only keeps the image ~160 MB smaller than JDK-headless.

Sets JAVA_HOME=/usr/lib/jvm/java-17-openjdk-amd64 and prepends it to
PATH so spark-submit (which checks JAVA_HOME) finds the right JVM.

Combined with the prior yarn-REST rewrite, the runtime image now needs
exactly three things in addition to python:3.12-slim:
  - uv (from ghcr.io/astral-sh/uv)
  - openjdk-17-jre-headless
  - Spark 4.1.2 from Tsinghua mirror

Dockerfile

@@ -18,7 +18,8 @@ RUN apt-get update && \
     apt-get install -y --no-install-recommends \
         curl \
         ca-certificates \
-        tar && \
+        tar \
+        openjdk-17-jre-headless && \
     curl -L \
       https://mirrors.tuna.tsinghua.edu.cn/apache/spark/spark-${SPARK_VERSION}/spark-${SPARK_VERSION}-bin-hadoop3.tgz \
       -o /tmp/spark.tgz && \
@@ -29,8 +30,9 @@ RUN apt-get update && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/*
 
+ENV JAVA_HOME=/usr/lib/jvm/java-17-openjdk-amd64
 ENV SPARK_HOME=/opt/spark
-ENV PATH=${SPARK_HOME}/bin:${PATH}
+ENV PATH=${JAVA_HOME}/bin:${SPARK_HOME}/bin:${PATH}
 
 # Hadoop/Yarn 配置目录（运行时挂载）
 RUN mkdir -p /etc/hadoop/conf