Error from feature-classifier: [Errno 28] No space left on device

Technical Support
1

Hello,

I’m having the same problems listed in this thread and this thread while trying to use the feature-classifier fit-classifier-naive-bayes command after training SILVA132 on my primers. Despite setting my TMPDIR to a path that has plenty of space (over 700GB; it also spits out the correct directory after running the “env” command), and running the code on a machine with 125GB of memory (although it doesn’t seem to be a memory issue), I still get an error. I’m running qiime2-2019.1 in a conda environment on linux.

Command is as follows:

export TMPDIR=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca
echo $TMPDIR
/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca

qiime feature-classifier fit-classifier-naive-bayes \
--i-reference-reads ref-seqs-silva-132_16S.qza \
--i-reference-taxonomy 7_level_taxonomy.qza \
--p-classify--chunk-size 1000 \
--o-classifier 16S_silva-132_classifier.qza \
--verbose

I’ve also tried without the chunk-size line, and with chunk-size of 10; same error.

Behold the error:

/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/q2_feature_classifier/classifier.py:101: UserWarning: The TaxonomicClassifier artifact that results from this method was trained using scikit-learn version 0.20.2. It cannot be used with other versions of scikit-learn. (While the classifier may complete successfully, the results will be unreliable.)

warnings.warn(warning, UserWarning)

Traceback (most recent call last):

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/q2cli/commands.py", line 274, in __call__

results = action(**arguments)

File "</mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/decorator.py:decorator-gen-340>", line 2, in fit_classifier_naive_bayes

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 231, in bound_callable

output_types, provenance)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 393, in _callable_executor_

spec.qiime_type, output_view, spec.view_type, prov)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/qiime2/sdk/result.py", line 265, in _from_view

result = transformation(view)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/qiime2/core/transform.py", line 70, in transformation

new_view = transformer(view)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/q2_feature_classifier/_taxonomic_classifier.py", line 85, in _2

for fn in joblib.dump(data, pf):

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 502, in dump

NumpyPickler(f, protocol=protocol).dump(value)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 409, in dump

self.save(obj)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save

return Pickler.save(self, obj)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 521, in save

self.save_reduce(obj=obj, *rv)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 634, in save_reduce

save(state)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save

return Pickler.save(self, obj)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 476, in save

f(self, obj) # Call unbound method with explicit self

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 821, in save_dict

self._batch_setitems(obj.items())

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 847, in _batch_setitems

save(v)

  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save

return Pickler.save(self, obj)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 476, in save

f(self, obj) # Call unbound method with explicit self

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 781, in save_list

self._batch_appends(obj)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 805, in _batch_appends

save(x)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save

return Pickler.save(self, obj)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 476, in save

f(self, obj) # Call unbound method with explicit self

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 781, in save_list

self._batch_appends(obj)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 805, in _batch_appends

save(x)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save

return Pickler.save(self, obj)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 521, in save

self.save_reduce(obj=obj, *rv)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 634, in save_reduce

save(state)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save

return Pickler.save(self, obj)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 476, in save

f(self, obj) # Call unbound method with explicit self

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 821, in save_dict

self._batch_setitems(obj.items())

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 847, in _batch_setitems

save(v)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 289, in save

wrapper.write_array(obj, self)

File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 104, in write_array

pickler.file_handle.write(chunk.tostring('C'))

OSError: [Errno 28] No space left on device

Plugin error from feature-classifier:

[Errno 28] No space left on device

See above for debug info

Let me know of anything else I can provide to make the issue more clear, if need be. Thank you!

2

Hmm, well, you appear to be running out of disk space somewhere.... How about you run df -h and share those results with us. That command will tell us a bit more about your filesystems and disk partitions. :qiime2:

3

Thanks, @thermokarst

Output:

Filesystem      Size  Used Avail Use% Mounted on

udev             63G     0   63G   0% /dev

tmpfs            13G  9.9M   13G   1% /run

/dev/sda2        28G   19G  7.2G  73% /

tmpfs            63G  1.8M   63G   1% /dev/shm

tmpfs           5.0M  4.0K  5.0M   1% /run/lock

tmpfs            63G     0   63G   0% /sys/fs/cgroup

/dev/sda1       511M  3.5M  508M   1% /boot/efi

/dev/sda4        80G   54G   22G  72% /home

/dev/sdb1       3.6T  1.7T  1.8T  48% /mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1

cgmfs           100K     0  100K   0% /run/cgmanager/fs

tmpfs            13G   36K   13G   1% /run/user/1000
4

Hello there,

Thanks for posting that. OK, let’s compare the drive in the error with the space left on the drives:

Error:
File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca
Drives:
/dev/sdb1 3.6T 1.7T 1.8T 48% /mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1

Wait… that drive is only 48% full, with 1.8T of space left?? :bangbang: How strange?

Colin

5

I think this path is a red-herring, it is where the python code lives, but QIIME 2 will still try to use $TMPDIR which unless otherwise set, will be under /, which according to the table above:

Has only 7.2G available, which is consistent with the error.

If you were to set $TMPDIR to another location, you would probably not run into this issue. Somewhere on /mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1 would likely work well.

EDIT: Sorry, I can't read >_<

2 Likes
7

New idea:

Does setting this variable the same as TMPDIR help?

export JOBLIB_TEMP_FOLDER=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca

Apparently /dev/shm is used by joblib (used by sklearn).

3 Likes
8

Hi,

I succeded to resolve this problem by making my TEMDIR in the Home directory (as you did) and run all commands of feature classifier from the Home directory.

1-Make a TMPDIR in a Home directory

2-Change the path directory of qiime into Home dir

3-Run your classifier commands( do not forget to adjust paths for your input and output files)

Wishing this option will help you

2 Likes
9

Thanks all for your help on this!

Unfortunately, it didn't. I still get the same exact error.

More-detailed commands (including qiime2 paths, etc):

fgplab@FGPGodzila ~ $ source activate /mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2
(/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2) fgplab@FGPGodzila ~ $ cd '/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/Mr. DNA Seq Run (II)/16S/16S_silva-132_train'
(/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2) fgplab@FGPGodzila /mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/Mr. DNA Seq Run (II)/16S/16S_silva-132_train $ export tmpdir=*'/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca'
(/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2) fgplab@FGPGodzila /mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/Mr. DNA Seq Run (II)/16S/16S_silva-132_train $ export JOBLIB_TEMP_FOLDER=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca
(/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2) fgplab@FGPGodzila /mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/Mr. DNA Seq Run (II)/16S/16S_silva-132_train $ env

"env" output:

XDG_VTNR=7
MANPATH=/home/fgplab/perl5/perlbrew/perls/perl-5.20.1/man:$MANPATH:/usr/local/share/man
PERLBREW_VERSION=0.80
SSH_AGENT_PID=1941
XDG_SESSION_ID=c2
JAVA_LD_LIBRARY_PATH=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/server
XDG_GREETER_DATA_DIR=/var/lib/lightdm-data/fgplab
QT_STYLE_OVERRIDE=gtk
PERLBREW_PERL=perl-5.20.1
GPG_AGENT_INFO=/home/fgplab/.gnupg/S.gpg-agent:0:1
TERM=xterm-256color
SHELL=/bin/bash
VTE_VERSION=4205
PYTHONNOUSERSITE=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python*/site-packages/
tmpdir=*/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca
CONDA_SHLVL=1
QT_LINUX_ACCESSIBILITY_ALWAYS_ON=1
CONDA_PROMPT_MODIFIER=(/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2) 
GJS_DEBUG_OUTPUT=stderr
WINDOWID=113246214
OLDPWD=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca
GJS_DEBUG_TOPICS=JS ERROR;JS LOG
GTK_MODULES=gail:atk-bridge
ARBHOME=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/arb
USER=fgplab
LS_COLORS=rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=00:su=37;41:sg=30;43:ca=30;41:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.Z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.jpg=01;35:*.jpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=00;36:*.au=00;36:*.flac=00;36:*.m4a=00;36:*.mid=00;36:*.midi=00;36:*.mka=00;36:*.mp3=00;36:*.mpc=00;36:*.ogg=00;36:*.ra=00;36:*.wav=00;36:*.oga=00;36:*.opus=00;36:*.spx=00;36:*.xspf=00;36:
QT_ACCESSIBILITY=1
CONDA_EXE=/home/fgplab/miniconda3/bin/conda
PERLBREW_BASHRC_VERSION=0.80
XDG_SESSION_PATH=/org/freedesktop/DisplayManager/Session0
XDG_SEAT_PATH=/org/freedesktop/DisplayManager/Seat0
SSH_AUTH_SOCK=/run/user/1000/keyring/ssh
SESSION_MANAGER=local/FGPGodzila:@/tmp/.ICE-unix/1852,unix/FGPGodzila:/tmp/.ICE-unix/1852
DEFAULTS_PATH=/usr/share/gconf/cinnamon.default.path
PERLBREW_ROOT=/home/fgplab/perl5/perlbrew
SSUALIGNDIR=/usr/local/share/ssu-align-0.1.1
XDG_CONFIG_DIRS=/etc/xdg/xdg-cinnamon:/etc/xdg
ARBHOME_BACKUP=
PATH=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/bin:/home/fgplab/miniconda3/condabin:/home/fgplab/perl5/perlbrew/bin:/home/fgplab/perl5/perlbrew/perls/perl-5.20.1/bin:/home/fgplab/bioinformatics/bowtie2:/home/fgplab/bioinformatics/:/home/fgplab/miniconda3/bin:/bin:/usr/bin:/usr/local/bin:/sbin:/usr/sbin
DESKTOP_SESSION=cinnamon
QT_QPA_PLATFORMTHEME=qgnomeplatform
CONDA_PREFIX=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2
XDG_SESSION_TYPE=x11
PWD=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/Mr. DNA Seq Run (II)/16S/16S_silva-132_train
JAVA_HOME=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2
MPLBACKEND=Agg
LANG=en_US.UTF-8
GDM_LANG=en_US
MANDATORY_PATH=/usr/share/gconf/cinnamon.mandatory.path
PERLBREW_HOME=/home/fgplab/.perlbrew
GDMSESSION=cinnamon
CINNAMON_VERSION=3.4.6
XDG_SEAT=seat0
HOME=/home/fgplab
SHLVL=1
LANGUAGE=en_US
PERLBREW_MANPATH=/home/fgplab/perl5/perlbrew/perls/perl-5.20.1/man
GNOME_DESKTOP_SESSION_ID=this-is-deprecated
GTK_OVERLAY_SCROLLING=1
CONDA_PYTHON_EXE=/home/fgplab/miniconda3/bin/python
PERLBREW_PATH=/home/fgplab/perl5/perlbrew/bin:/home/fgplab/perl5/perlbrew/perls/perl-5.20.1/bin
XDG_SESSION_DESKTOP=cinnamon
LOGNAME=fgplab
XDG_DATA_DIRS=/usr/share/cinnamon:/usr/share/gnome:/usr/local/share/:/usr/share/
DBUS_SESSION_BUS_ADDRESS=unix:abstract=/tmp/dbus-6BUmfZk0G2,guid=2065f48e67927ce4e07c52875c883f72
JAVA_HOME_CONDA_BACKUP=
CONDA_DEFAULT_ENV=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2
LESSOPEN=| /usr/bin/lesspipe %s
XDG_RUNTIME_DIR=/run/user/1000
DISPLAY=:0
JAVA_LD_LIBRARY_PATH_BACKUP=
XDG_CURRENT_DESKTOP=X-Cinnamon
R_LIBS_USER=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/R/library/
LESSCLOSE=/usr/bin/lesspipe %s %s
JOBLIB_TEMP_FOLDER=/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca
XAUTHORITY=/home/fgplab/.Xauthority
_=/usr/bin/env

Note there are some lines that point to other paths, which as shown in my reply above from df -h have pretty low space. Perhaps some of them may be the culprit?

Feature-classifer command and output error:

(/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2) fgplab@FGPGodzila /mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/Mr. DNA Seq Run (II)/16S/16S_silva-132_train $ qiime feature-classifier fit-classifier-naive-bayes \
>   --i-reference-reads ref-seqs-silva-132_16S.qza \
>   --i-reference-taxonomy 7_level_taxonomy.qza \
>   --o-classifier 16S_silva-132_classifier.qza \
>   --verbose
/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/q2_feature_classifier/classifier.py:101: UserWarning: The TaxonomicClassifier artifact that results from this method was trained using scikit-learn version 0.20.2. It cannot be used with other versions of scikit-learn. (While the classifier may complete successfully, the results will be unreliable.)
  warnings.warn(warning, UserWarning)
Traceback (most recent call last):
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/q2cli/commands.py", line 274, in __call__
    results = action(**arguments)
  File "</mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/decorator.py:decorator-gen-340>", line 2, in fit_classifier_naive_bayes
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 231, in bound_callable
    output_types, provenance)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 393, in _callable_executor_
    spec.qiime_type, output_view, spec.view_type, prov)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/qiime2/sdk/result.py", line 265, in _from_view
    result = transformation(view)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/qiime2/core/transform.py", line 70, in transformation
    new_view = transformer(view)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/q2_feature_classifier/_taxonomic_classifier.py", line 85, in _2
    for fn in joblib.dump(data, pf):
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 502, in dump
    NumpyPickler(f, protocol=protocol).dump(value)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 409, in dump
    self.save(obj)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save
    return Pickler.save(self, obj)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 521, in save
    self.save_reduce(obj=obj, *rv)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 634, in save_reduce
    save(state)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save
    return Pickler.save(self, obj)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 476, in save
    f(self, obj) # Call unbound method with explicit self
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 821, in save_dict
    self._batch_setitems(obj.items())
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 847, in _batch_setitems
    save(v)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save
    return Pickler.save(self, obj)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 476, in save
    f(self, obj) # Call unbound method with explicit self
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 781, in save_list
    self._batch_appends(obj)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 805, in _batch_appends
    save(x)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save
    return Pickler.save(self, obj)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 476, in save
    f(self, obj) # Call unbound method with explicit self
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 781, in save_list
    self._batch_appends(obj)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 805, in _batch_appends
    save(x)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save
    return Pickler.save(self, obj)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 521, in save
    self.save_reduce(obj=obj, *rv)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 634, in save_reduce
    save(state)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 292, in save
    return Pickler.save(self, obj)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 476, in save
    f(self, obj) # Call unbound method with explicit self
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 821, in save_dict
    self._batch_setitems(obj.items())
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/pickle.py", line 847, in _batch_setitems
    save(v)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 289, in save
    wrapper.write_array(obj, self)
  File "/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca/qiime2/lib/python3.6/site-packages/sklearn/externals/joblib/numpy_pickle.py", line 104, in write_array
    pickler.file_handle.write(chunk.tostring('C'))
OSError: [Errno 28] No space left on device

Plugin error from feature-classifier:

  [Errno 28] No space left on device

See above for debug info.

Thanks so much for the suggestion; unfortunately that's also how I've been running all of my commands. My conda environment, as well as all of my input and output files are in

/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca

Let me know if this is not what you meant.

Going to attempt running this in a different machine (with significantly less space and memory, however). Will report back. Note I've tried it in both of my institution's clusters (following same commands as above) and I get the same error.

1 Like
11

Maybe try to run it directly from Home dir, as I see, you were in something like 16S_silva-132_train file when running feature classifier right?

13

Hey there @BCruz!
It looks like you have a few typos in your post above. Specifically, you have spelled out tmpdir, instead of TMPDIR --- case matters here. Second, there is glob char at the start of that string --- not sure if that is actually a problem or not, but worth removing either way.

export TMPDIR='/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca'
export JOBLIB_TEMP_FOLDER='/mnt/e5514ac8-93d5-4c49-a344-0a016f364cf1/Bianca'

Hope that helps! :t_rex: :qiime2:

1 Like
15

A post was split to a new topic: tmpdir memory error