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  1. .github/PULL_REQUEST_TEMPLATE.md

    - [ ] Bug fix (non-breaking change which fixes an issue)
    - [ ] New feature (non-breaking change which adds functionality)
    - [ ] Optimization (provides speedup with no functional changes)
    - [ ] Breaking change (fix or feature that would cause existing functionality to change)
    
    ## Checklist:
    - [ ] Fixes a regression (If yes, please add `commit-id` or `PR #` here)
    - [ ] Unit tests added/updated
    - [ ] Internal documentation updated
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  2. docs/metrics/v3.md

    `test1` and `test2`, make a scrape request to `/minio/metrics/v3/api/bucket?buckets=test1,test2`. 
    
    Instead of a metrics scrape, it is also possible to list the metrics that would be returned by a path. This is done by adding a `?list` query parameter. The MinIO server will then list all possible metrics that could be returned. During an actual metrics scrape, only available metrics are returned - not all of them. With the `list` query parameter, the output format can be selected - just set...
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  3. docs/distributed/CONFIG.md

    - Each pool expects each host in this pool has the same number of drives specified as any other host.
    - Mixing `local-path` and `distributed-path` is not allowed, doing so would cause MinIO to refuse starting the server.
    - Ellipses notation (e.g. `{1...10}`) or bracket notations are fully allowed (e.g. `{a,c,f}`) to have multiple entries in one line.
    
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  4. docs/bucket/versioning/README.md

    MinIO versioning is designed to keep multiple versions of an object in one bucket. For example, you could store `spark.csv` (version `ede336f2`) and `spark.csv` (version `fae684da`) in a single bucket. Versioning protects you from unintended overwrites, deletions, protect objects with retention policies.
    
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  5. docs/iam/access-management-plugin.md

    mc cp /etc/issue myminio/test
    mc admin user add myminio foo foobar123
    export MC_HOST_foo=http://foo:foobar123@localhost:9000
    mc ls foo
    mc cp /etc/issue myminio/test/issue2
    ```
    
    Only the last operation would fail with a permissions error.
    
    ## Configuration
    
    Access Management Plugin can be configured with environment variables:
    
    ```sh
    $ mc admin config set myminio policy_plugin --env
    KEY:
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  6. docs/bucket/notifications/README.md

    ```
    
    Here we see that MinIO performed `HSET` on `minio_events` key.
    
    In case, `access` format was used, then `minio_events` would be a list, and the MinIO server would have performed an `RPUSH` to append to the list. A consumer of this list would ideally use `BLPOP` to remove list items from the left-end of the list.
    
    ## Publish MinIO events via NATS
    
    Install NATS from [here](http://nats.io/).
    
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  7. docs/select/README.md

    ### 3. Example
    
    As an example, let us take a gzip compressed CSV file. Without S3 Select, we would need to download, decompress and process the entire CSV to get the data you needed. With Select API, can use a simple SQL expression to return only the data from the CSV you’re interested in, instead of retrieving the entire object. Following Python example shows how to retrieve the first column `Location` from an object containing data in CSV format.
    
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  8. docs/bucket/replication/DESIGN.md

    An additional header `X-Minio-Replication-Delete-Status` is returned which would show `PENDING` or `FAILED` status if the replication is still not caught up.
    
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  9. docs/distributed/README.md

    ### High availability
    
    A stand-alone MinIO server would go down if the server hosting the drives goes offline. In contrast, a distributed MinIO setup with _m_ servers and _n_ drives will have your data safe as long as _m/2_ servers or _m*n_/2 or more drives are online.
    
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  10. docs/distributed/DESIGN.md

    number erasure sets to provide for uniform distribution across nodes*. This is to ensure that same number of drives are pariticipating in any erasure set. For example if you have 2 nodes with 180 drives then GCD is 15 but this would lead to uneven distribution, one of the nodes would participate more drives. To avoid this the affinity is given towards nodes which leads to next best GCD factor of 12 which provides uniform distribution.
    
    - In this algorithm, we also make sure that we spread the drives...
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