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GH action to generate report #199
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.github/workflows/report.yaml
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pull_request: | ||
branches: | ||
- main |
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Should we also run this on a weekly basis?
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It's on PR push just so I can test easily, but yes, 1/week sounds good to me. @kabilar Do you have a preference for what day/time?
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Great, thank you. How about Mondays at 6am EST? We can then review the report on Monday mornings.
Hi @asmacdo, just checking in to see how this report generation is going? Thanks. |
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Ran into some problems The du script ran for about 50 minutes and then the pod disappeared without logs. Worse it kicked my jupyterhub pod as well as another user.
I think this means we need to take a different approach. By setting resource limits, we should have isolated our job from the other pods, but since I have no other logs about what happened here I think we need to take a more conservative approach that is completely isolated from user pods. I did it this way because I thought it would be simpler, but if theres any chance that we affect a running user pod, we would be better off directly deploying a separate EC2 instance and bind the EFS directly, avoiding Kubernetes altogether. |
Thanks @asmacdo. That makes sense. |
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#!/usr/bin/env bash | |||
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set -e |
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set -e | |
set -eu |
@@ -0,0 +1,133 @@ | |||
#!/usr/bin/env bash | |||
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set -e |
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set -e | |
set -eu |
LOCAL_SCRIPTS_DIR=".github/scripts" | ||
REMOTE_SCRIPTS_DIR="/home/ec2-user/scripts" | ||
MOUNT_POINT="/mnt/efs" | ||
ENV_FILE=".ec2-session.env" |
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I dislike the fact that it would be just dumping into some hidden file in my current directory.
Could we make it dumped into some tmpdir and may be establish there env variable with its path so cleanup script could take it from that environment
ENV_FILE=".ec2-session.env" | |
ENV_FILE="/run/user/$(id -u)/ec2-session.env" |
but then we might want to add logic to react if file already exist -- since that would mean likely that cleanup did not remove it and instance might still be running etc.
set -e | ||
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# Load environment variables from the file if they are not already set | ||
ENV_FILE=".ec2-session.env" |
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ENV_FILE=".ec2-session.env" | |
ENV_FILE="/run/user/$(id -u)/ec2-session.env" |
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left comments on the report and walking.
The plan:
- see if more recent AMI with newer than 3.7 python available (e.g. 3.10 to be future proof somewhat)
- run the
create-file-index.py
across all the users- could be done in parallel and under duct following http://www.oneukrainian.com/tmp/run_manifests.sh example
- scp those reports somewhere
- while running develop produce-report.py further:
- change logic so we compute sizes for all directories
- go through the list of folders and match to the desired to be monitored/informed about https://github.com/dandi/dandi-hub/pull/188/files#diff-b7bf13dc481c474b9080a061c3154f0e645619658cb9bd469383938de07a7439R16
- ideally compose a dict/json record with those, do not render immediately. e.g.
{
"total":
{
"file_size": 123123123123,
"file_count":123
},
"caches": {
"__pycache__": { # count directories which last path component is `__pycache__`
"file_size": 12123123,
"file_count": 12,
"directories": [
"a/e/__pycache__"
"a/b/d/e/__pycache__"
"a/e/__pycache__/c/__pycache__" # should not happen in the wild
],
"pip_cache": {
"file_size": 13,
"file_count": 1,
"directories": [
"blah/.cache/pip
]
}
.github/scripts/create-file-index.py
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import gzip | ||
from datetime import datetime | ||
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def list_files_with_metadata(directory, output_file): |
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write a simple test, could even probably be in this file, where you populate directory with nested folders and symlinks and you know the ground truth to aim for and compare against.
.github/scripts/create-file-index.py
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files_metadata = [] | ||
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for root, dirs, files in os.walk(directory): |
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FTR. walk seems to be already doing desired (right) thing and does not follow symlinked folders. We get
In [14]: list(os.walk('/tmp/1234'))
Out[14]:
[('/tmp/1234', ['infinitum', 'subdir', 'linkgood'], []),
('/tmp/1234/subdir', ['subdir2'], ['file']),
('/tmp/1234/subdir/subdir2', [], ['file2'])]
for
❯ tree /tmp/1234
/tmp/1234
├── infinitum -> /tmp/1234
├── linkgood -> subdir
└── subdir
├── file
└── subdir2
└── file2
note: we do not monitor empty folders below
Amazon Linux 2023 comes with 3.9, which is sufficient. I briefly tried ubuntu 22.04, (with 3.12) but that would add complexity, requiring |
Update:
Heres an example of the json output produced by the report generator:{
"total_size": 238294213,
"file_count": 3639,
"caches": {
"pycache": {
"total_size": 22782820,
"file_count": 1431,
"directories": [
"asmacdo/venvs/my_venv/lib/python3.11/site-packages/pkg_resources/extern/__pycache__",
"asmacdo/venvs/my_venv/lib/python3.11/site-packages/pkg_resources/__pycache__",
"asmacdo/venvs/my_venv/lib/python3.11/site-packages/pkg_resources/_vendor/jaraco/__pycache__",
"asmacdo/venvs/my_venv/lib/python3.11/site-packages/pkg_resources/_vendor/jaraco/text/__pycache__",
"asmacdo/venvs/my_venv/lib/python3.11/site-packages/pkg_resources/_vendor/importlib_resources/__pycache__",
"asmacdo/venvs/my_venv/lib/python3.11/site-packages/pkg_resources/_vendor/__pycache__",
"asmacdo/venvs/my_venv/lib/python3.11/site-packages/pkg_resources/_vendor/packaging/__pycache__",
"asmacdo/venvs/my_venv/lib/python3.11/site-packages/pkg_resources/_vendor/pyparsing/__pycache__",
"asmacdo/venvs/my_venv/lib/python3.11/site-packages/pkg_resources/_vendor/pyparsing/diagram/__pycache__",
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"asmacdo/venvs/myenv/lib/python3.11/site-packages/pip/_vendor/pyproject_hooks/_in_process/__pycache__",
"asmacdo/venvs/myenv/lib/python3.11/site-packages/pip/_vendor/pyproject_hooks/__pycache__",
"asmacdo/venvs/myenv/lib/python3.11/site-packages/pip/_vendor/distlib/__pycache__",
"asmacdo/venvs/myenv/lib/python3.11/site-packages/pip/_vendor/chardet/cli/__pycache__",
"asmacdo/venvs/myenv/lib/python3.11/site-packages/pip/_vendor/chardet/metadata/__pycache__",
"asmacdo/venvs/myenv/lib/python3.11/site-packages/pip/_vendor/chardet/__pycache__",
"asmacdo/venvs/myenv/lib/python3.11/site-packages/pip/_vendor/resolvelib/compat/__pycache__",
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"asmacdo/venvs/myenv/lib/python3.11/site-packages/con_duct/__pycache__",
"asmacdo/dandi-notebooks/000971/lernerlab/seiler_2024/__pycache__"
]
},
"user_cache": {
"total_size": 10852503,
"file_count": 81,
"directories": [
"asmacdo/.cache"
]
},
"yarn_cache": {
"total_size": 0,
"file_count": 0,
"directories": []
},
"pip_cache": {
"total_size": 10852503,
"file_count": 80,
"directories": [
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"nwb_cache": {
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}
} Notably, the total size 238294213 is less than reported by |
(Also increase timeout)
Python 3.9 is new enough. Ubuntu was not ideal because the EFS mounting require amazonl-efs-utils which is available via package manage for amazon linux, but requires building from source on Ubuntu.
gzip will only be needed if we want to upload to s3
=== Do not change lines below === { "chain": [], "cmd": "black .github/scripts/calculate-directory-stats.py", "exit": 0, "extra_inputs": [], "inputs": [], "outputs": [ ".github/scripts/calculate-directory-stats.py" ], "pwd": "." } ^^^ Do not change lines above ^^^
Holding the entire file index in memory would be risky, especially with zarr files
Whether there is an error or not, write all fields for each file. This allows us to read the tsv file and unpack the same number of values for each line.
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Fixes #177
Step 1: Create Skeleton
I've verified that when a user-node is available (created by running a
tiny
jupyterhub), the job pod schedules on that node. I then shut down my jupyterhub and all user-nodes scaled down. I reran this job, and Karpenter successfully scaled up a new spot node, the pod was scheduled on it, ran successfully, was deleted, and the node cleaned up. Step 1 complete!Step 2 Generate Report
Step 3 Push Report
Questions to answer: