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Task #4290

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Investigate performance of Pulp with UUID PKs

Added by dalley over 5 years ago. Updated about 5 years ago.

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CLOSED - COMPLETE
Priority:
Normal
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-
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0%

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Groomed:
Yes
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Yes
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Sprint 49
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Description

On the pulp-dev mailing list, we discussed how the way we are using bulk_create only works on certain databases, such as Postgres, and not on others, such as MySQL.

https://www.redhat.com/archives/pulp-dev/2018-November/msg00019.html

The summary of this issue is that - when we use bulk_create(), we need to get back the PKs of the created objects. With database-generated autoincrement integer IDs, Postgres can do this but MySQL cannot.

A proposed solution to this problem is to use UUID PKs, which can be generated in the application and therefore do not need to be returned from the database, because we already have them.

However, using UUIDs as PKs in a database often carries performance implications. It inflates the size of the database (due to being 128 bits, vs a 32 or 64 bit integer), and the randomness and lack of natural ordering makes them difficult to properly index.

We should verify that this will not cause performance issues.

We should test the following:

  • Size of the database/database indexes
  • Memory usage while running?
  • Insert performance, and the degree to which it gets progressively worse with database size
  • Query performance, and the degree to which it gets progressively worse with database size

For the following suggested procedure, use additive sync, NOT mirror sync, and lazy sync, NOT immediate sync.

Suggested procedure:

  • Create 5 file fixture repositories, each with 100,000 random file content units, using the script below (modifications needed)
  • Create 5 file fixture repositories, each with 1,000 random file content units, using the same script
  • Create 2 Pulp repositories
  • With the first repository, repeat the following process 4 times using different fixture repositories and record the results
  • Sync a 100,000 unit repository
  • Sync a 1,000 unit repository
  • Inside a Python shell, time how long it takes execute FileContent.objects.get(pk=.....) using the PK of a unit present in the DB
  • Inside a Python shell, time how long it takes to execute the following script for the latest repository version {c['_type']: c['count'] for c in repo_version.content.values('_type').annotate(count=Count('_type'))}
  • Inside a Python shell, time how long it takes to execute Content.objects.filter(pk__in=repo_version.content)
  • Then repeat that process once, but using the second repository, and only the last (one) set of fixtures and record the results
  • Sync EPEL using the RPM plugin and record the results
  • Measure the total size of the database and record the results

If neither insert/query/storage performance is impacted significantly enough to be a blocking issue, there are additional tests we can run as well.

Bonus Task: Perform these same tests on MySQL / MariaDB, to see how performance compares against PostgreSQL.

Bonus Task: UUID PKs may make it possible to implement a smarter version of "bulk_create()" which can speed up saving Content models with multi-table inheritance. We could attempt to implement this.

Basic testing script

sudo dnf install nginx
sudo systemctl start nginx
cd /usr/share/nginx/html
mkdir large_repository
chmod -R 777 large_repository
cd large_repository

for i in {1..70000}; do echo `uuidgen` > $i; done
for file in `ls`; do echo $file,`sha256sum $file | awk '{ print $1 }'`,`stat -L -c '%s' $file`; done > PULP_MANIFEST

# open up PULP_MANIFEST and remove the line for PULP_MANIFEST
vim PULP_MANIFEST

# now try to fetch PULP_MANIFEST just to make sure everything's working
curl http://localhost/large_repository/PULP_MANIFEST

http POST :8000/pulp/api/v3/repositories/ name=foo
http POST :8000/pulp/api/v3/remotes/file/ name=bar url=http://localhost/large_repository/PULP_MANIFEST policy='on_demand'
http POST :8000/pulp/api/v3/remotes/file/1/sync/ repository=/pulp/api/v3/repositories/1/

Files


Related issues

Blocks Pulp - Task #4270: Add support for MariaDB and MySQLCLOSED - CURRENTRELEASEdaviddavis

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