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Gracefully handle duplicate name with unique MD5 #3355

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merged 3 commits into from
Mar 22, 2023

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@dbutenhof dbutenhof commented Mar 20, 2023

PBENCH-1112

In testing we're seeing duplicate tarball names with distinct MD5 values. We have reduced the importance of duplicate tarball names, relying on the dataset resource ID (MD5) for "uniqueness" internally. However the cache manager still maintains tarball files and MD5 companions on disk, and the upload API has to temporarily store the API payload somewhere. When the duplicate tarballs are uploaded concurrently, the .open() fails, leading to an internal server error.

Instead, move temporary upload files into an MD5-based subdirectory, and clean up that directory after upload completes.

NOTE: I'm pushing this early as a draft for testing and exposure. I still need to write some unit tests this afternoon before it's formally ready for review.

@dbutenhof dbutenhof added Server API Of and relating to application programming interfaces to services and functions labels Mar 20, 2023
@dbutenhof dbutenhof self-assigned this Mar 20, 2023
webbnh
webbnh previously approved these changes Mar 21, 2023
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LGTM

lib/pbench/server/api/resources/upload_api.py Outdated Show resolved Hide resolved
PBENCH-1112

In testing we're seeing duplicate tarball names with distinct MD5 values. We
have reduced the importance of duplicate tarball names, relying on the dataset
resource ID (MD5) for "uniqueness" internally. However the cache manager still
maintains tarball files and MD5 companions on disk, and the upload API has to
temporarily store the API payload somewhere. When the duplicate tarballs are
uploaded concurrently, the `.open()` fails, leading to an internal server
error.

Instead, move temporarily upload files into an MD5-based subdirectory, and
clean up that directory after upload completes.
I removed unused fixtures (particularly supporting the obsolete "controller"
header).

Also slightly rearranged some code in upload: I removed a new exception handler
that's not really necessary and realized that some post-upload checks were
unnecessarily inside the `with` block.
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👍

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@siddardh-ra siddardh-ra left a comment

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LGTM 👍

@dbutenhof dbutenhof merged commit 97e17ca into distributed-system-analysis:main Mar 22, 2023
@dbutenhof dbutenhof deleted the uniquerer branch March 22, 2023 11:46
@portante portante added this to the v0.73 milestone Mar 28, 2023
dbutenhof added a commit to dbutenhof/pbench that referenced this pull request May 18, 2023
…analysis#3355)

* Gracefully handle duplicate name with unique MD5

PBENCH-1112

In testing we're seeing duplicate tarball names with distinct MD5 values. We
have reduced the importance of duplicate tarball names, relying on the dataset
resource ID (MD5) for "uniqueness" internally. However the cache manager still
maintains tarball files and MD5 companions on disk, and the upload API has to
temporarily store the API payload somewhere. When the duplicate tarballs are
uploaded concurrently, the `.open()` fails, leading to an internal server
error. We want to minimize the chance of reporting internal server errors where
possible.

Instead, move temporarily upload files into an MD5-based subdirectory, and
clean up that directory after upload completes.
dbutenhof added a commit that referenced this pull request May 22, 2023
* Gracefully handle duplicate name with unique MD5

PBENCH-1112
PBENCH-1150

In testing we're seeing duplicate tarball names with distinct MD5 values. We
have reduced the importance of duplicate tarball names, relying on the dataset
resource ID (MD5) for "uniqueness" internally. However the cache manager still
maintains tarball files and MD5 companions on disk, and the upload API has to
temporarily store the API payload somewhere. When the duplicate tarballs are
uploaded concurrently, the `.open()` fails, leading to an internal server
error. We want to minimize the chance of reporting internal server errors where
possible.

Instead, move temporarily upload files into an MD5-based subdirectory, and
clean up that directory after upload completes.
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4 participants