feat: add Dockerfile

.dockerignore

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+.venv/
+__pycache__/
+*.py[cod]
+.pytest_cache/
+
+# Runtime data (connections, pending jobs, logs) must never be baked in
+data/
+
+# IDE / VCS noise
+.idea/
+.vscode/
+.git/
+
+# Plan + dev-only docs (keep CLAUDE.md is fine; drop the rest)
+docs/
+
+# Note: spark/ and hadoop-conf/ are NOT ignored — the Dockerfile COPYs them
+# as runtime configs. If your environment doesn't have them yet, add a
+# placeholder file in each (e.g. .gitkeep) so COPY doesn't fail with
+# "not a directory" or "no such file or directory".

Dockerfile

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+# syntax=docker/dockerfile:1
+#
+# Spark Executor MCP — runtime image.
+# Build deps with uv (frozen, prod-only), then drop in the source on top of
+# python:3.12-slim with Spark + YARN configs mounted for the spark-submit /
+# yarn CLI calls inside the MCP tools.
+
+FROM python:3.12-slim
+
+# --- uv (official binary) ---
+COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /usr/local/bin/
+
+# --- Spark + Hadoop config (matches the original Dockerfile) ---
+
+ARG SPARK_VERSION=4.1.2
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+        curl \
+        ca-certificates \
+        tar && \
+    curl -L \
+      https://archive.apache.org/dist/spark/spark-${SPARK_VERSION}/spark-${SPARK_VERSION}-bin-hadoop3.tgz \
+      -o /tmp/spark.tgz && \
+    mkdir -p /opt && \
+    tar -xzf /tmp/spark.tgz -C /opt && \
+    mv /opt/spark-${SPARK_VERSION}-bin-hadoop3 /opt/spark && \
+    rm -f /tmp/spark.tgz && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+ENV SPARK_HOME=/opt/spark
+ENV PATH=${SPARK_HOME}/bin:${PATH}
+
+# Hadoop/Yarn 配置目录（运行时挂载）
+RUN mkdir -p /etc/hadoop/conf
+
+# 默认值，可在 docker run 时覆盖
+ENV HADOOP_CONF_DIR=/etc/hadoop/conf
+ENV YARN_CONF_DIR=/etc/hadoop/conf
+
+# --- App ---
+WORKDIR /app
+
+# Install Python deps first so this layer caches independently of source.
+# --frozen pins to uv.lock exactly; --no-dev skips pytest etc. for a slim
+# production image; --no-install-project defers copying the source.
+COPY pyproject.toml uv.lock ./
+RUN uv sync --index-url=https://pypi.tuna.tsinghua.edu.cn/simple/ --frozen --no-dev --no-install-project
+
+# Now copy the source and let uv wire it in.
+COPY main.py ./
+COPY spark_executor ./spark_executor
+COPY common ./common
+RUN uv sync --index-url=https://pypi.tuna.tsinghua.edu.cn/simple/ --frozen --no-dev
+
+# Put the venv on PATH so `python` / `uvicorn` resolve to the project env.
+ENV PATH=/app/.venv/bin:$PATH
+ENV PYTHONUNBUFFERED=1
+
+EXPOSE 8000
+CMD ["python", "main.py"]