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Wes McKinney commented on ARROW-11427: -------------------------------------- Didn't we start bundling the Visual Studio runtime in this release but not beforehand? > [Python] Windows Server 2012 w/ Xeon Platinum 8171M crashes after upgrading > to pyarrow 3.0 > ------------------------------------------------------------------------------------------ > > Key: ARROW-11427 > URL: https://issues.apache.org/jira/browse/ARROW-11427 > Project: Apache Arrow > Issue Type: Bug > Components: Python > Environment: Windows Server 2012 Datacenter, Azure VM (D2_v2), Intel > Xeon Platinum 8171m > Reporter: Ali Cetin > Priority: Major > > *Update*: Azure (D2_v2) VM no longer spins-up with Xeon Platinum 8171m, so > I'm unable to test it with other OS's. We resolved the issue by changing VM > SKU's, so no longer an issue for us per se. So, its up to you to follow it up > further if necessary I guess. > VM's w/ Xeon Platinum 8171m running on Azure (D2_v2) start crashing after > upgrading from pyarrow 2.0 to pyarrow 3.0. However, this only happens when > reading parquet files larger than 4096 bytes!? > Windows closes Python with exit code 255 and produces this: > > {code:java} > Faulting application name: python.exe, version: 3.8.3150.1013, time stamp: > 0x5ebc7702 Faulting module name: arrow.dll, version: 0.0.0.0, time stamp: > 0x60060ce3 Exception code: 0xc000001d Fault offset: 0x000000000047aadc > Faulting process id: 0x1b10 Faulting application start time: > 0x01d6f4a43dca3c14 Faulting application path: > D:\SvcFab\_App\SomeApp.FabricType_App32\SomeApp.Fabric.Executor.ProcessActorPkg.Code.1.0.218-prod\Python38\python.exe > Faulting module path: > D:\SvcFab\_App\SomeApp.FabricType_App32\temp\Executions\50cfffe8-9250-4ac7-8ba8-08d8c2bb3edf\.venv\lib\site-packages\pyarrow\arrow.dll{code} > > Tested on: > ||OS||Xeon Platinum 8171m||Other CPUs|| > |Windows Server 2012 Data Center|Fail|OK| > |Windows Server 2016 Data Center| |OK| > |Windows Server 2019 Data Center| | | > |Windows 10| |OK| > > Example code (Python): > {code:java} > import numpy as np > import pandas as pd > data_len = 2**5 > data = pd.DataFrame( > {"values": np.arange(0., float(data_len), dtype=float)}, > index=np.arange(0, data_len, dtype=int) > ) > data.to_parquet("test.parquet") > data = pd.read_parquet("test.parquet", engine="pyarrow") # fails here! > {code} -- This message was sent by Atlassian Jira (v8.3.4#803005)