I just transferred a ton of data using ExportSnapshot with bandwidth throttling from one Hadoop cluster to another Hadoop cluster, and discovered that ThrottledInputStream does not limit bandwidth.
The problem is that ThrottledInputStream sleeps once, for a fixed time (50 ms), at the start of each read call, disregarding the actual amount of data read.
ExportSnapshot defaults to a buffer size as big as the block size of the outputFs:
In my case, this was 256MB.
Hence, the ExportSnapshot mapper will attempt to read up to 256 MB at a time, each time sleeping only 50ms. Thus, in the worst case where each call to read fills the 256 MB buffer in negligible time, the ThrottledInputStream cannot reduce the bandwidth to under (256 MB) / (5 ms) = 5 GB/s.
Even in a more realistic case where read returns about 1 MB per call, it still cannot throttle the bandwidth to under 20 MB/s.
The issue is exacerbated by the fact that you need to set a low limit because the total bandwidth per host depends on the number of mapper slots as well.
A simple solution would change the if in throttle to a while, so that it keeps sleeping for 50 ms until the rate is finally low enough:
This issue affects the ThrottledInputStream in hadoop as well.
Another way to see this is that for big enough buffer sizes, ThrottledInputStream will be throttling only the number of read calls to 20 per second, disregarding the number of bytes read.