apache · dongjoon-hyun · May 15, 2026
diff --git a/.github/workflows/build_infra_images_cache.yml b/.github/workflows/build_infra_images_cache.yml
@@ -32,7 +32,6 @@ on:
     - 'dev/spark-test-image/sparkr/Dockerfile'
     - 'dev/spark-test-image/python-minimum/Dockerfile'
     - 'dev/spark-test-image/python-ps-minimum/Dockerfile'
-    - 'dev/spark-test-image/python-310/Dockerfile'
     - 'dev/spark-test-image/python-311/Dockerfile'
     - 'dev/spark-test-image/python-312/Dockerfile'
     - 'dev/spark-test-image/python-312-classic-only/Dockerfile'
@@ -139,19 +138,6 @@ jobs:
       - name: Image digest (PySpark PS with old dependencies)
         if: hashFiles('dev/spark-test-image/python-ps-minimum/Dockerfile') != ''
         run: echo ${{ steps.docker_build_pyspark_python_ps_minimum.outputs.digest }}
-      - name: Build and push (PySpark with Python 3.10)
-        if: hashFiles('dev/spark-test-image/python-310/Dockerfile') != ''
-        id: docker_build_pyspark_python_310
-        uses: docker/build-push-action@bcafcacb16a39f128d818304e6c9c0c18556b85f
-        with:
-          context: ./dev/spark-test-image/python-310/
-          push: true
-          tags: ghcr.io/apache/spark/apache-spark-github-action-image-pyspark-python-310-cache:${{ github.ref_name }}-static
-          cache-from: type=registry,ref=ghcr.io/apache/spark/apache-spark-github-action-image-pyspark-python-310-cache:${{ github.ref_name }}
-          cache-to: type=registry,ref=ghcr.io/apache/spark/apache-spark-github-action-image-pyspark-python-310-cache:${{ github.ref_name }},mode=max
-      - name: Image digest (PySpark with Python 3.10)
-        if: hashFiles('dev/spark-test-image/python-310/Dockerfile') != ''
-        run: echo ${{ steps.docker_build_pyspark_python_310.outputs.digest }}
       - name: Build and push (PySpark with Python 3.11)
         if: hashFiles('dev/spark-test-image/python-311/Dockerfile') != ''
         id: docker_build_pyspark_python_311

diff --git a/.github/workflows/build_python_3.10.yml b/.github/workflows/build_python_3.10.yml
diff --git a/.github/workflows/build_python_minimum.yml b/.github/workflows/build_python_minimum.yml
@@ -38,7 +38,7 @@ jobs:
       envs: >-
         {
           "PYSPARK_IMAGE_TO_TEST": "python-minimum",
-          "PYTHON_TO_TEST": "python3.10"
+          "PYTHON_TO_TEST": "python3.11"
         }
       jobs: >-
         {

diff --git a/.github/workflows/build_python_ps_minimum.yml b/.github/workflows/build_python_ps_minimum.yml
@@ -38,7 +38,7 @@ jobs:
       envs: >-
         {
           "PYSPARK_IMAGE_TO_TEST": "python-ps-minimum",
-          "PYTHON_TO_TEST": "python3.10"
+          "PYTHON_TO_TEST": "python3.11"
         }
       jobs: >-
         {

diff --git a/README.md b/README.md
@@ -42,7 +42,6 @@ This README file only contains basic setup instructions.
 |            | [![GitHub Actions Build](https://github.com/apache/spark/actions/workflows/build_maven_java21_macos26.yml/badge.svg)](https://github.com/apache/spark/actions/workflows/build_maven_java21_macos26.yml)         |
 |            | [![GitHub Actions Build](https://github.com/apache/spark/actions/workflows/build_maven_java21_arm.yml/badge.svg)](https://github.com/apache/spark/actions/workflows/build_maven_java21_arm.yml)                 |
 |            | [![GitHub Actions Build](https://github.com/apache/spark/actions/workflows/build_coverage.yml/badge.svg)](https://github.com/apache/spark/actions/workflows/build_coverage.yml)                                 |
-|            | [![GitHub Actions Build](https://github.com/apache/spark/actions/workflows/build_python_3.10.yml/badge.svg)](https://github.com/apache/spark/actions/workflows/build_python_3.10.yml)                           |
 |            | [![GitHub Actions Build](https://github.com/apache/spark/actions/workflows/build_python_3.11.yml/badge.svg)](https://github.com/apache/spark/actions/workflows/build_python_3.11.yml)                           |
 |            | [![GitHub Actions Build](https://github.com/apache/spark/actions/workflows/build_python_3.12_classic_only.yml/badge.svg)](https://github.com/apache/spark/actions/workflows/build_python_3.12_classic_only.yml) |
 |            | [![GitHub Actions Build](https://github.com/apache/spark/actions/workflows/build_python_3.12_arm.yml/badge.svg)](https://github.com/apache/spark/actions/workflows/build_python_3.12_arm.yml)                   |

diff --git a/binder/Dockerfile b/binder/Dockerfile
@@ -15,7 +15,7 @@
 # limitations under the License.
 #
 
-FROM python:3.10-slim
+FROM python:3.11-slim
 # install the notebook package
 RUN  pip install --no-cache notebook jupyterlab
 

diff --git a/dev/infra/Dockerfile b/dev/infra/Dockerfile
@@ -61,7 +61,7 @@ RUN apt-get update && apt-get install -y \
     openjdk-17-jdk-headless \
     pandoc \
     pkg-config \
-    python3.10 \
+    python3.11 \
     python3-psutil \
     qpdf \
     r-base \
@@ -94,14 +94,14 @@ ARG BASIC_PIP_PKGS="numpy pyarrow>=18.0.0 six==1.16.0 pandas==2.3.3 scipy plotly
 # Python deps for Spark Connect
 ARG CONNECT_PIP_PKGS="grpcio==1.76.0 grpcio-status==1.76.0 protobuf==6.33.5 googleapis-common-protos==1.71.0 graphviz==0.20.3"
 
-# Install Python 3.10 packages
-RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.10
-RUN python3.10 -m pip install --ignore-installed 'blinker>=1.6.2' # mlflow needs this
-RUN python3.10 -m pip install --ignore-installed 'six==1.16.0'  # Avoid `python3-six` installation
-RUN python3.10 -m pip install $BASIC_PIP_PKGS unittest-xml-reporting $CONNECT_PIP_PKGS && \
-    python3.10 -m pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu && \
-    python3.10 -m pip install deepspeed torcheval && \
-    python3.10 -m pip cache purge
+# Install Python 3.11 packages
+RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.11
+RUN python3.11 -m pip install --ignore-installed 'blinker>=1.6.2' # mlflow needs this
+RUN python3.11 -m pip install --ignore-installed 'six==1.16.0'  # Avoid `python3-six` installation
+RUN python3.11 -m pip install $BASIC_PIP_PKGS unittest-xml-reporting $CONNECT_PIP_PKGS && \
+    python3.11 -m pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu && \
+    python3.11 -m pip install deepspeed torcheval && \
+    python3.11 -m pip cache purge
 
 # Install Python 3.9
 RUN add-apt-repository ppa:deadsnakes/ppa

diff --git a/dev/spark-test-image/python-310/Dockerfile b/dev/spark-test-image/python-310/Dockerfile
diff --git a/dev/spark-test-image/python-minimum/Dockerfile b/dev/spark-test-image/python-minimum/Dockerfile
@@ -49,22 +49,22 @@ RUN apt-get update && apt-get install -y \
     software-properties-common \
     zlib1g-dev
 
-# Install Python 3.10
+# Install Python 3.11
 RUN add-apt-repository ppa:deadsnakes/ppa
 RUN apt-get update && apt-get install -y \
-    python3.10 \
-    python3.10-venv \
+    python3.11 \
+    python3.11-venv \
     && apt-get autoremove --purge -y \
     && apt-get clean \
     && rm -rf /var/lib/apt/lists/*
 
 # Setup virtual environment
 ENV VIRTUAL_ENV=/opt/spark-venv
-RUN python3.10 -m venv $VIRTUAL_ENV
+RUN python3.11 -m venv $VIRTUAL_ENV
 ENV PATH="$VIRTUAL_ENV/bin:$PATH"
 
 ARG BASIC_PIP_PKGS="numpy==1.22.4 pyarrow==18.0.0 pandas==2.2.0 six==1.16.0 scipy scikit-learn coverage unittest-xml-reporting psutil"
 ARG CONNECT_PIP_PKGS="grpcio==1.76.0 grpcio-status==1.76.0 googleapis-common-protos==1.71.0 zstandard==0.25.0 graphviz==0.20 protobuf==6.33.5"
 
-RUN python3.10 -m pip install --force $BASIC_PIP_PKGS $CONNECT_PIP_PKGS && \
-    python3.10 -m pip cache purge
+RUN python3.11 -m pip install --force $BASIC_PIP_PKGS $CONNECT_PIP_PKGS && \
+    python3.11 -m pip cache purge
diff --git a/dev/spark-test-image/python-ps-minimum/Dockerfile b/dev/spark-test-image/python-ps-minimum/Dockerfile
@@ -49,22 +49,22 @@ RUN apt-get update && apt-get install -y \
     software-properties-common \
     zlib1g-dev
 
-# Install Python 3.10
+# Install Python 3.11
 RUN add-apt-repository ppa:deadsnakes/ppa
 RUN apt-get update && apt-get install -y \
-    python3.10 \
-    python3.10-venv \
+    python3.11 \
+    python3.11-venv \
     && apt-get autoremove --purge -y \
     && apt-get clean \
     && rm -rf /var/lib/apt/lists/*
 
 # Setup virtual environment
 ENV VIRTUAL_ENV=/opt/spark-venv
-RUN python3.10 -m venv $VIRTUAL_ENV
+RUN python3.11 -m venv $VIRTUAL_ENV
 ENV PATH="$VIRTUAL_ENV/bin:$PATH"
 
 ARG BASIC_PIP_PKGS="pyarrow==18.0.0 pandas==2.2.0 six==1.16.0 numpy scipy coverage unittest-xml-reporting psutil"
 ARG CONNECT_PIP_PKGS="grpcio==1.76.0 grpcio-status==1.76.0 googleapis-common-protos==1.71.0 zstandard==0.25.0 graphviz==0.20 protobuf==6.33.5"
 
-RUN python3.10 -m pip install --force $BASIC_PIP_PKGS $CONNECT_PIP_PKGS && \
-    python3.10 -m pip cache purge
+RUN python3.11 -m pip install --force $BASIC_PIP_PKGS $CONNECT_PIP_PKGS && \
+    python3.11 -m pip cache purge
diff --git a/docs/index.md b/docs/index.md
@@ -34,7 +34,7 @@ source, visit [Building Spark](building-spark.html).
 
 Spark runs on both Windows and UNIX-like systems (e.g. Linux, Mac OS), and it should run on any platform that runs a supported version of Java. This should include JVMs on x86_64 and ARM64. It's easy to run locally on one machine --- all you need is to have `java` installed on your system `PATH`, or the `JAVA_HOME` environment variable pointing to a Java installation.
 
-Spark runs on Java 17/21/25, Scala 2.13, Python 3.10+, and R 3.5+ (Deprecated).
+Spark runs on Java 17/21/25, Scala 2.13, Python 3.11+, and R 3.5+ (Deprecated).
 Java 25 prior to version 25.0.3 support is deprecated as of Spark 4.2.0.
 When using the Scala API, it is necessary for applications to use the same version of Scala that Spark was compiled for. Since Spark 4.0.0, it's Scala 2.13.
 

diff --git a/docs/rdd-programming-guide.md b/docs/rdd-programming-guide.md
@@ -39,7 +39,7 @@ along with if you launch Spark's interactive shell -- either `bin/spark-shell` f
 
 <div data-lang="python"  markdown="1">
 
-Spark {{site.SPARK_VERSION}} works with Python 3.10+. It can use the standard CPython interpreter,
+Spark {{site.SPARK_VERSION}} works with Python 3.11+. It can use the standard CPython interpreter,
 so C libraries like NumPy can be used.
 
 Spark applications in Python can either be run with the `bin/spark-submit` script which includes Spark at runtime, or by including it in your setup.py as:

diff --git a/python/docs/source/development/contributing.rst b/python/docs/source/development/contributing.rst
@@ -129,8 +129,8 @@ If you are using Conda, the development environment can be set as follows.
 
 .. code-block:: bash
 
-    # Python 3.10+ is required
-    conda create --name pyspark-dev-env python=3.10
+    # Python 3.11+ is required
+    conda create --name pyspark-dev-env python=3.11
     conda activate pyspark-dev-env
     pip install --upgrade -r dev/requirements.txt
 
@@ -149,15 +149,15 @@ You can use Python's built-in ``venv`` module to create an isolated environment:
 
 .. code-block:: bash
 
-    # Python 3.10+ is required
+    # Python 3.11+ is required
     python3 -m venv .venv
     source .venv/bin/activate
     pip install --upgrade -r dev/requirements.txt
 
 pip
 ~~~
 
-With Python 3.10+, pip can be used as below to install and set up the development environment.
+With Python 3.11+, pip can be used as below to install and set up the development environment.
 
 .. code-block:: bash
 

diff --git a/python/docs/source/getting_started/install.rst b/python/docs/source/getting_started/install.rst
@@ -30,7 +30,7 @@ and building from the source.
 Python Versions Supported
 -------------------------
 
-Python 3.10 and above.
+Python 3.11 and above.
 
 
 Using PyPI
@@ -143,7 +143,7 @@ the same session as pyspark (you can install in several steps too).
 
 .. code-block:: bash
 
-    conda install -c conda-forge pyspark  # can also add "python=3.10 some_package [etc.]" here
+    conda install -c conda-forge pyspark  # can also add "python=3.11 some_package [etc.]" here
 
 Note that `PySpark for conda <https://anaconda.org/conda-forge/pyspark>`_ is maintained
 separately by the community; while new versions generally get packaged quickly, the

diff --git a/python/docs/source/tutorial/pandas_on_spark/typehints.rst b/python/docs/source/tutorial/pandas_on_spark/typehints.rst
@@ -62,7 +62,7 @@ it as a Spark schema. As an example, you can specify the return type hint as bel
 Notice that the function ``pandas_div`` actually takes and outputs a pandas DataFrame instead of
 pandas-on-Spark :class:`DataFrame`. So, technically the correct types should be of pandas.
 
-With Python 3.10+, you can specify the type hints by using pandas instances as follows:
+With Python 3.11+, you can specify the type hints by using pandas instances as follows:
 
 .. code-block:: python
 

diff --git a/python/packaging/classic/setup.py b/python/packaging/classic/setup.py
@@ -382,10 +382,9 @@ def run(self):
                 "pyyaml>=%s" % _minimum_pyyaml_version,
             ],
         },
-        python_requires=">=3.10",
+        python_requires=">=3.11",
         classifiers=[
             "Development Status :: 5 - Production/Stable",
-            "Programming Language :: Python :: 3.10",
             "Programming Language :: Python :: 3.11",
             "Programming Language :: Python :: 3.12",
             "Programming Language :: Python :: 3.13",

diff --git a/python/packaging/client/setup.py b/python/packaging/client/setup.py
@@ -217,10 +217,9 @@
             "numpy>=%s" % _minimum_numpy_version,
             "pyyaml>=%s" % _minimum_pyyaml_version,
         ],
-        python_requires=">=3.10",
+        python_requires=">=3.11",
         classifiers=[
             "Development Status :: 5 - Production/Stable",
-            "Programming Language :: Python :: 3.10",
             "Programming Language :: Python :: 3.11",
             "Programming Language :: Python :: 3.12",
             "Programming Language :: Python :: 3.13",

diff --git a/python/packaging/connect/setup.py b/python/packaging/connect/setup.py
@@ -127,10 +127,9 @@
             "numpy>=%s" % _minimum_numpy_version,
             "pyyaml>=%s" % _minimum_pyyaml_version,
         ],
-        python_requires=">=3.10",
+        python_requires=">=3.11",
         classifiers=[
             "Development Status :: 5 - Production/Stable",
-            "Programming Language :: Python :: 3.10",
             "Programming Language :: Python :: 3.11",
             "Programming Language :: Python :: 3.12",
             "Programming Language :: Python :: 3.13",