Added libffi-dev build dependency

nigel.stanger / docker-analytics

Browse code Added libffi-dev build dependency master spark3
1 parent a98b2d1 commit 762caf633063166a349378d3f8f8033166b4be96 Nigel Stanger authored on 19 Sep 2020

Patch

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# Don't use the official jupyter/pyspark-notebook image because it's massive! FROM nstanger/spark ARG NB_USER="pyspark" ARG NB_UID="1000" ARG NB_GID="1000" USER root RUN adduser -D -u $NB_UID $NB_USER RUN apk add --no-cache --virtual .build-deps \ build-base \ zeromq-dev \ python3-dev \ libffi-dev \ py3-zmq RUN pip install --upgrade \ pip \ && pip install \ # Tornado 6 breaks sparkmonitor tornado==5.1 \ jupyter \ kafka-python \ pyspark \ sparkmonitor \ tini RUN apk del .build-deps ENV PYSPARK_PYTHON="/usr/local/bin/python3" ENV KERNEL_NAME="PySpark" \ KERNELS_TEMPLATE_PATH="/tmp" \ KERNELS_DIR_PATH="/home/$NB_USER/.local/share/jupyter/kernels" \ PYTHONPATH="$SPARK_HOME/python:$SPARK_HOME/python/lib/py4j-0.10.7-src.zip" \ PYSPARK_DRIVER_PYTHON="$PYSPARK_PYTHON" \ PYSPARK_SUBMIT_ARGS="--master $SPARK_MASTER pyspark-shell" \ PYTHONSTARTUP="$SPARK_HOME/python/pyspark/shell.py" # ENV SPARKMONITOR_UI_PORT 8080 USER $NB_UID RUN ipython kernel install --user --name $KERNEL_NAME # kernel.json is based on the template from <https://github.com/Anchormen/pyspark-jupyter-kernels>. COPY kernel.json pyspark-kernel.sh $KERNELS_DIR_PATH/$KERNEL_NAME/ RUN jupyter nbextension install sparkmonitor --py --user --symlink \ && jupyter nbextension enable sparkmonitor --py --user \ && jupyter serverextension enable --py --user sparkmonitor \ && ipython profile create \ && echo "c.InteractiveShellApp.extensions.append('sparkmonitor.kernelextension')" >> $(ipython profile locate default)/ipython_kernel_config.py RUN mkdir -p /home/$NB_USER/work WORKDIR /home/$NB_USER/work ENTRYPOINT ["/sbin/tini", "--"] # pyspark-kernel.sh will automatically set up the PySpark context when # the kernel is loaded. CMD ["jupyter", "notebook", "--ip=0.0.0.0", "--port=8888"] # debugging # CMD ["bash"] # Don't use the official jupyter/pyspark-notebook image because it's massive! FROM nstanger/spark ARG NB_USER="pyspark" ARG NB_UID="1000" ARG NB_GID="1000" USER root RUN adduser -D -u $NB_UID $NB_USER RUN apk add --no-cache --virtual .build-deps \ build-base \ zeromq-dev \ python3-dev \ py3-zmq RUN pip install --upgrade \ pip \ && pip install \ # Tornado 6 breaks sparkmonitor tornado==5.1 \ jupyter \ kafka-python \ pyspark \ sparkmonitor \ tini RUN apk del .build-deps ENV PYSPARK_PYTHON="/usr/local/bin/python3" ENV KERNEL_NAME="PySpark" \ KERNELS_TEMPLATE_PATH="/tmp" \ KERNELS_DIR_PATH="/home/$NB_USER/.local/share/jupyter/kernels" \ PYTHONPATH="$SPARK_HOME/python:$SPARK_HOME/python/lib/py4j-0.10.7-src.zip" \ PYSPARK_DRIVER_PYTHON="$PYSPARK_PYTHON" \ PYSPARK_SUBMIT_ARGS="--master $SPARK_MASTER pyspark-shell" \ PYTHONSTARTUP="$SPARK_HOME/python/pyspark/shell.py" # ENV SPARKMONITOR_UI_PORT 8080 USER $NB_UID RUN ipython kernel install --user --name $KERNEL_NAME # kernel.json is based on the template from <https://github.com/Anchormen/pyspark-jupyter-kernels>. COPY kernel.json pyspark-kernel.sh $KERNELS_DIR_PATH/$KERNEL_NAME/ RUN jupyter nbextension install sparkmonitor --py --user --symlink \ && jupyter nbextension enable sparkmonitor --py --user \ && jupyter serverextension enable --py --user sparkmonitor \ && ipython profile create \ && echo "c.InteractiveShellApp.extensions.append('sparkmonitor.kernelextension')" >> $(ipython profile locate default)/ipython_kernel_config.py RUN mkdir -p /home/$NB_USER/work WORKDIR /home/$NB_USER/work ENTRYPOINT ["/sbin/tini", "--"] # pyspark-kernel.sh will automatically set up the PySpark context when # the kernel is loaded. CMD ["jupyter", "notebook", "--ip=0.0.0.0", "--port=8888"] # debugging # CMD ["bash"]

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pyspark/Dockerfile

# Don't use the official jupyter/pyspark-notebook image because it's massive!
FROM nstanger/spark

ARG NB_USER="pyspark"
ARG NB_UID="1000"
ARG NB_GID="1000"

USER root

RUN adduser -D -u $NB_UID $NB_USER

RUN apk add --no-cache --virtual .build-deps \
        build-base \
        zeromq-dev \
        python3-dev \
        libffi-dev \
        py3-zmq

RUN pip install --upgrade \
        pip \
    && pip install \
        # Tornado 6 breaks sparkmonitor
        tornado==5.1 \
        jupyter \
        kafka-python \
        pyspark \
        sparkmonitor \
        tini

RUN apk del .build-deps

ENV PYSPARK_PYTHON="/usr/local/bin/python3"

ENV KERNEL_NAME="PySpark" \
    KERNELS_TEMPLATE_PATH="/tmp" \
    KERNELS_DIR_PATH="/home/$NB_USER/.local/share/jupyter/kernels" \
    PYTHONPATH="$SPARK_HOME/python:$SPARK_HOME/python/lib/py4j-0.10.7-src.zip" \
    PYSPARK_DRIVER_PYTHON="$PYSPARK_PYTHON" \
    PYSPARK_SUBMIT_ARGS="--master $SPARK_MASTER pyspark-shell" \
    PYTHONSTARTUP="$SPARK_HOME/python/pyspark/shell.py"

# ENV SPARKMONITOR_UI_PORT 8080

USER $NB_UID

RUN ipython kernel install --user --name $KERNEL_NAME
# kernel.json is based on the template from <https://github.com/Anchormen/pyspark-jupyter-kernels>.
COPY kernel.json pyspark-kernel.sh $KERNELS_DIR_PATH/$KERNEL_NAME/

RUN jupyter nbextension install sparkmonitor --py --user --symlink \
    && jupyter nbextension enable sparkmonitor --py --user \
    && jupyter serverextension enable --py --user sparkmonitor \
    && ipython profile create \
    && echo "c.InteractiveShellApp.extensions.append('sparkmonitor.kernelextension')" >> $(ipython profile locate default)/ipython_kernel_config.py

RUN mkdir -p /home/$NB_USER/work
WORKDIR /home/$NB_USER/work

ENTRYPOINT ["/sbin/tini", "--"]

# pyspark-kernel.sh will automatically set up the PySpark context when
# the kernel is loaded.
CMD ["jupyter", "notebook", "--ip=0.0.0.0", "--port=8888"]

# debugging
# CMD ["bash"]