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Posted to commits@spark.apache.org by ru...@apache.org on 2025/10/16 05:27:10 UTC
(spark) branch master updated: [SPARK-53931][INFRA][PYTHON] Fix scheduled job for numpy 2.1.3
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ruifengz pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/spark.git
The following commit(s) were added to refs/heads/master by this push:
new 9823daf2cf90 [SPARK-53931][INFRA][PYTHON] Fix scheduled job for numpy 2.1.3
9823daf2cf90 is described below
commit 9823daf2cf90f7c0b4978c0ae574b580a54ef8c2
Author: Ruifeng Zheng <ru...@apache.org>
AuthorDate: Thu Oct 16 13:26:56 2025 +0800
[SPARK-53931][INFRA][PYTHON] Fix scheduled job for numpy 2.1.3
### What changes were proposed in this pull request?
Fix scheduled job for numpy 2.1.3
### Why are the changes needed?
to fix https://github.com/apache/spark/actions/runs/18538043179/job/52838303733
it was caused by a bug in 19.0.0, see https://github.com/apache/arrow/issues/45283
### Does this PR introduce _any_ user-facing change?
no, infra-only
### How was this patch tested?
PR builder with
```
default: '{"PYSPARK_IMAGE_TO_TEST": "numpy-213", "PYTHON_TO_TEST": "python3.11"}'
```
see https://github.com/zhengruifeng/spark/actions/runs/18527303212/job/52801019275
### Was this patch authored or co-authored using generative AI tooling?
no
Closes #52633 from zhengruifeng/restore_numpy_213.
Authored-by: Ruifeng Zheng <ru...@apache.org>
Signed-off-by: Ruifeng Zheng <ru...@apache.org>
---
dev/spark-test-image/numpy-213/Dockerfile | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/dev/spark-test-image/numpy-213/Dockerfile b/dev/spark-test-image/numpy-213/Dockerfile
index af1a19c4859c..116154b663b0 100644
--- a/dev/spark-test-image/numpy-213/Dockerfile
+++ b/dev/spark-test-image/numpy-213/Dockerfile
@@ -68,7 +68,7 @@ RUN apt-get update && apt-get install -y \
# Pin numpy==2.1.3
-ARG BASIC_PIP_PKGS="numpy==2.1.3 pyarrow==19.0.0 six==1.16.0 pandas==2.2.3 scipy plotly<6.0.0 mlflow>=2.8.1 coverage matplotlib openpyxl memory-profiler>=0.61.0 scikit-learn>=1.3.2"
+ARG BASIC_PIP_PKGS="numpy==2.1.3 pyarrow>=21.0.0 six==1.16.0 pandas==2.2.3 scipy plotly<6.0.0 mlflow>=2.8.1 coverage matplotlib openpyxl memory-profiler>=0.61.0 scikit-learn>=1.3.2"
# Python deps for Spark Connect
ARG CONNECT_PIP_PKGS="grpcio==1.67.0 grpcio-status==1.67.0 protobuf==5.29.5 googleapis-common-protos==1.65.0 graphviz==0.20.3"
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