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Posted to issues@mahout.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2026/01/15 10:13:00 UTC
[jira] [Work logged] (MAHOUT-827) Another version of RecommenderJob that broadcasts the similarity matrix
[ https://issues.apache.org/jira/browse/MAHOUT-827?focusedWorklogId=1000225&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-1000225 ]
ASF GitHub Bot logged work on MAHOUT-827:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 15/Jan/26 10:12
Start Date: 15/Jan/26 10:12
Worklog Time Spent: 10m
Work Description: ryankert01 opened a new pull request, #833:
URL: https://github.com/apache/mahout/pull/833
### Purpose of PR
- Consolidate dev dependencies in root `pyproject.toml`
- Add `qdp-dev` dependency group for QDP build tools (maturin, patchelf, torch, numpy)
- Align pytest version to `>=9.0.1` (matching qdp-python)
- Add pytest markers configuration for `gpu` and `slow`
- `pyproject.toml`: Add `qdp-dev` group, bump pytest, add markers
## Usage
```bash
uv sync --group dev # Base dev tools
uv sync --group dev --group qdp-dev # Include QDP build tools
```
### Related Issues or PRs
Closes #827
### Changes Made
<!
Issue Time Tracking
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Worklog Id: (was: 1000225)
Remaining Estimate: 0h
Time Spent: 10m
> Another version of RecommenderJob that broadcasts the similarity matrix
> -----------------------------------------------------------------------
>
> Key: MAHOUT-827
> URL: https://issues.apache.org/jira/browse/MAHOUT-827
> Project: Mahout
> Issue Type: New Feature
> Affects Versions: 0.6
> Reporter: Sebastian Schelter
> Assignee: Sebastian Schelter
> Priority: Major
> Attachments: MAHOUT-827-2.patch, MAHOUT-827-3.patch, MAHOUT-827.patch
>
> Time Spent: 10m
> Remaining Estimate: 0h
>
> Add another version of RecommenderJob that computes the item similarities via RowSimilarityJob but assumes that the resulting similarity matrix fits into the memory of the mappers in the cluster. After the item similarity computation is done, the similarities are broadcasted via Hadoop's distributed cache and the recommendations are computed in a map-only pass over the data afterwards.
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