On my cluster, I've enabled emrfs consistent view and it's working fine when running spark jobs. 

However, I find tedious to manually sync/delete/import metadata after generic s3 operations.

For instance, after a copy, s3 becomes inconsistent:

```
aws s3 cp localfile1 s3://bucket/path/
emrfs sync s3://bucket/path/
emrfs diff s3://bucket/path/

BOTH | MANIFEST ONLY | S3 ONLY
DIR  bucket/path/           (BOTH)
FILE bucket/path/localfile1 (BOTH)

```

Here, localfile1 and metadata are in sync.

```
aws s3 cp localfile2 s3://bucket/path/
emrfs diff s3://bucket/path/

BOTH | MANIFEST ONLY | S3 ONLY
DIR  bucket/path/           (BOTH)
FILE bucket/path/localfile1 (BOTH)
FILE bucket/path/localfile2 (S3 ONLY)

```

Is there a way to keep metadata in sync with s3 when performing operations like that directly from the EMR cluster where consistent view is enabled?

Thanks