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13 changes: 9 additions & 4 deletions images/pyspark-notebook/Dockerfile
Original file line number Diff line number Diff line change
Expand Up @@ -15,10 +15,10 @@ USER root
# Spark dependencies
# Default values can be overridden at build time
# (ARGS are in lower case to distinguish them from ENV)
ARG spark_version="3.4.1"
ARG spark_version="3.5.0"
ARG hadoop_version="3"
ARG scala_version
ARG spark_checksum="5a21295b4c3d1d3f8fc85375c711c7c23e3eeb3ec9ea91778f149d8d321e3905e2f44cf19c69a28df693cffd536f7316706c78932e7e148d224424150f18b2c5"
ARG spark_checksum="8883c67e0a138069e597f3e7d4edbbd5c3a565d50b28644aad02856a1ec1da7cb92b8f80454ca427118f69459ea326eaa073cf7b1a860c3b796f4b07c2101319"
ARG openjdk_version="17"

ENV APACHE_SPARK_VERSION="${spark_version}" \
Expand Down Expand Up @@ -66,9 +66,14 @@ RUN fix-permissions "/etc/ipython/"
USER ${NB_UID}

# Install pyarrow
# Temporarily pin pandas to version 1.5.3, see: https://github.com/jupyter/docker-stacks/issues/1924
# NOTE: It's important to ensure compatibility between Pandas versions.
# The pandas version in this Dockerfile should match the version
# on which the Pandas API for Spark is built.
# To find the right version:
# 1. Check out the Spark branch you are on.
# 2. Find the pandas version in the file spark/dev/infra/Dockerfile.
RUN mamba install --yes \
'pandas>=1.5.3,<2.0.0' \
'pandas=2.0.3' \
'pyarrow' && \
mamba clean --all -f -y && \
fix-permissions "${CONDA_DIR}" && \
Expand Down
2 changes: 1 addition & 1 deletion tests/pyspark-notebook/units/unit_pandas_version.py
Original file line number Diff line number Diff line change
Expand Up @@ -2,4 +2,4 @@
# Distributed under the terms of the Modified BSD License.
import pandas

assert pandas.__version__ == "1.5.3"
assert pandas.__version__ == "2.0.3"