kkraus14
commented
4 years ago Closing as duplicate of #5615
Closed rjzamora closed 4 years ago
kkraus14
commented
4 years ago Closing as duplicate of #5615
rjzamora
commented
4 years ago Closing as duplicate of #5615
Ah - Completely forgot about that.
Describe the bug The data written to disk during
to_parquetis incorrect if the method is called on a sliced DataFrame (e.gdf.iloc[10:]) containg string data. For now, the only workaround is to explicity copy any data that needs to be written to disk.Steps/Code to reproduce bug
Trace:
Expected behavior Ideally, the data view should be written to disk as expected.
Environment overview (please complete the following information)
Environment details
Click here to see environment details
**git*** commit fc1bbdbf042c4fc84e2d562a9927fed3404aeee5 (HEAD -> fix-multi-file-io, origin/fix-multi-file-io) Author: rjzamora
Date: Wed Aug 5 10:29:08 2020 -0700
remove pdb statement
**git submodules***
***OS Information***
DGX_NAME="DGX Server"
DGX_PRETTY_NAME="NVIDIA DGX Server"
DGX_SWBUILD_DATE="2020-03-04"
DGX_SWBUILD_VERSION="4.4.0"
DGX_COMMIT_ID="ee09ebc"
DGX_PLATFORM="DGX Server for DGX-1"
DGX_SERIAL_NUMBER="QTFCOU8220024"
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NAME="Ubuntu"
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ID=ubuntu
ID_LIKE=debian
PRETTY_NAME="Ubuntu 18.04.4 LTS"
VERSION_ID="18.04"
HOME_URL="https://www.ubuntu.com/"
SUPPORT_URL="https://help.ubuntu.com/"
BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
VERSION_CODENAME=bionic
UBUNTU_CODENAME=bionic
Linux dgx14 4.15.0-76-generic #86-Ubuntu SMP Fri Jan 17 17:24:28 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux
***GPU Information***
Wed Aug 5 12:54:12 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.64.00 Driver Version: 440.64.00 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla V100-SXM2... On | 00000000:06:00.0 Off | 0 |
| N/A 31C P0 56W / 300W | 691MiB / 32510MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 Tesla V100-SXM2... On | 00000000:07:00.0 Off | 0 |
| N/A 32C P0 41W / 300W | 12MiB / 32510MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 2 Tesla V100-SXM2... On | 00000000:0A:00.0 Off | 0 |
| N/A 30C P0 43W / 300W | 12MiB / 32510MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 3 Tesla V100-SXM2... On | 00000000:0B:00.0 Off | 0 |
| N/A 29C P0 41W / 300W | 12MiB / 32510MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 4 Tesla V100-SXM2... On | 00000000:85:00.0 Off | 0 |
| N/A 30C P0 43W / 300W | 12MiB / 32510MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 5 Tesla V100-SXM2... On | 00000000:86:00.0 Off | 0 |
| N/A 30C P0 41W / 300W | 12MiB / 32510MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 6 Tesla V100-SXM2... On | 00000000:89:00.0 Off | 0 |
| N/A 32C P0 43W / 300W | 12MiB / 32510MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 7 Tesla V100-SXM2... On | 00000000:8A:00.0 Off | 0 |
| N/A 28C P0 42W / 300W | 12MiB / 32510MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 70083 C ...ora/miniconda3/envs/cudf_dev/bin/python 679MiB |
+-----------------------------------------------------------------------------+
***CPU***
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 80
On-line CPU(s) list: 0-79
Thread(s) per core: 2
Core(s) per socket: 20
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
CPU family: 6
Model: 79
Model name: Intel(R) Xeon(R) CPU E5-2698 v4 @ 2.20GHz
Stepping: 1
CPU MHz: 3064.612
CPU max MHz: 3600.0000
CPU min MHz: 1200.0000
BogoMIPS: 4390.04
Virtualization: VT-x
L1d cache: 32K
L1i cache: 32K
L2 cache: 256K
L3 cache: 51200K
NUMA node0 CPU(s): 0-19,40-59
NUMA node1 CPU(s): 20-39,60-79
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single pti intel_ppin ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdt_a rdseed adx smap intel_pt xsaveopt cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts md_clear flush_l1d
***CMake***
/datasets/rzamora/miniconda3/envs/cudf_dev/bin/cmake
cmake version 3.17.0
CMake suite maintained and supported by Kitware (kitware.com/cmake).
***g++***
/usr/bin/g++
g++ (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Copyright (C) 2017 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
***nvcc***
/usr/local/cuda/bin/nvcc
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Wed_Oct_23_19:24:38_PDT_2019
Cuda compilation tools, release 10.2, V10.2.89
***Python***
/datasets/rzamora/miniconda3/envs/cudf_dev/bin/python
Python 3.7.6
***Environment Variables***
PATH : /home/nfs/rzamora/.vscode-server/bin/cd9ea6488829f560dc949a8b2fb789f3cdc05f5d/bin:/home/nfs/rzamora/bin:/home/nfs/rzamora/.local/bin:/datasets/rzamora/miniconda3/envs/cudf_dev/bin:/datasets/rzamora/miniconda3/condabin:/usr/local/cuda/bin:/opt/bin:/home/nfs/rzamora/.vscode-server/bin/cd9ea6488829f560dc949a8b2fb789f3cdc05f5d/bin:/home/nfs/rzamora/bin:/home/nfs/rzamora/.local/bin:/usr/local/cuda/bin:/opt/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin
LD_LIBRARY_PATH :
NUMBAPRO_NVVM :
NUMBAPRO_LIBDEVICE :
CONDA_PREFIX : /datasets/rzamora/miniconda3/envs/cudf_dev
PYTHON_PATH :
***conda packages***
/datasets/rzamora/miniconda3/condabin/conda
# packages in environment at /datasets/rzamora/miniconda3/envs/cudf_dev:
#
# Name Version Build Channel
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Additional context The need for an explicit copy of the data view may affect NVTabular perfomance cc @benfred