[
https://issues.apache.org/jira/browse/ARROW-11427?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ali Cetin updated ARROW-11427:
------------------------------
Description:
*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. (Azure VM's are assigned different type of CPU's of same
"class" depending on availability.)
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 bits!?
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}
was:
*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 bits!?
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}
> [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: Blocker
>
> *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. (Azure VM's are assigned different type of
> CPU's of same "class" depending on availability.)
> 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 bits!?
> 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}
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