bees Gotchas

C++ Exceptions

bees is very paranoid about the data it gets from btrfs, and if btrfs does anything bees does not expect, bees will throw an exception and move on without touching the offending data. This will trigger a stack trace to the log containing data which is useful for developers to understand what happened.

In all cases C++ exceptions in bees are harmless to data on the filesystem. bees handles most exceptions by aborting processing of the current extent and moving to the next extent. In some cases an exception may occur in a critical bees thread, which will stop the bees process from making any further progress; however, these cases are rare and are typically caused by unusual filesystem conditions (e.g. freshly formatted filesystem with no data) or lack of memory or other resources.

The following are common cases that users may encounter:

• If a snapshot is deleted, bees will generate a burst of exceptions for references to files in the snapshot that no longer exist. This lasts until the FD caches are cleared, usually a few minutes with default btrfs mount options. These generally look like:

  std::system_error: BTRFS_IOC_TREE_SEARCH_V2: [path] at fs.cc:844: No such file or directory

• If data is modified at the same time it is being scanned, bees will get an inconsistent version of the data layout in the filesystem, causing the ExtentWalker class to throw various constraint-check exceptions. The exception causes bees to retry the extent in a later filesystem scan (hopefully when the file is no longer being modified). The exception text is similar to:

  std::runtime_error: fm.rbegin()->flags() = 776 failed constraint check (fm.rbegin()->flags() & FIEMAP_EXTENT_LAST) at extentwalker.cc:229

  but the line number or specific code fragment may vary.

• If there are too many possible matching blocks within a pair of extents, bees will loop billions of times considering all possibilities. This is a waste of time, so an exception is currently used to break out of such loops early. The exception text in this case is:

  FIXME: too many duplicate candidates, bailing out here

Terminating bees with SIGTERM

bees is designed to survive host crashes, so it is safe to terminate bees using SIGKILL; however, when bees next starts up, it will repeat some work that was performed between the last bees crawl state save point and the SIGKILL (up to 15 minutes), and a large hash table may not be completely written back to disk, so some duplicate matches will be lost.

If bees is stopped and started less than once per week, then this is not a problem as the proportional impact is quite small; however, users who stop and start bees daily or even more often may prefer to have a clean shutdown with SIGTERM so bees can restart faster.

The shutdown procedure performs these steps:

1. Crawl state is saved to $BEESHOME. This is the most important bees state to save to disk as it directly impacts restart time, so it is done as early as possible

2. Hash table is written to disk. Normally the hash table is trickled back to disk at a rate of about 128KiB per second; however, SIGTERM causes bees to attempt to flush the whole table immediately. The time spent here depends on the size of RAM, speed of disks, and aggressiveness of competing filesystem workloads. It can trigger vm.dirty_bytes limits and block other processes writing to the filesystem for a while.

3. The bees process calls _exit, which terminates all running worker threads, closes and deletes all temporary files. This can take a while after the bees process exits, especially on slow spinning disks.

Balances

A btrfs balance relocates data on disk by making a new copy of the data, replacing all references to the old data with references to the new copy, and deleting the old copy. To bees, this is the same as any other combination of new and deleted data (e.g. from defrag, or ordinary file operations): some new data has appeared (to be scanned) and some old data has disappeared (to be removed from the hash table when it is detected).

As bees scans the newly balanced data, it will get hits on the hash table pointing to the old data (it’s identical data, so it would look like a duplicate). These old hash table entries will not be valid any more, so when bees tries to compare new data with old data, it will not be able to find the old data at the old address, and bees will delete the hash table entries. If no other duplicates are found, bees will then insert new hash table entries pointing to the new data locations. The erase is performed before the insert, so the new data simply replaces the old and there is (little or) no impact on hash table entry lifetimes (depending on how overcommitted the hash table is). Each block is processed one at a time, which can be slow if there are many of them.

Routine btrfs maintenance balances rarely need to relocate more than 0.1% of the total filesystem data, so the impact on bees is small even after taking into account the extra work bees has to do.

If the filesystem must undergo a full balance (e.g. because disks were added or removed, or to change RAID profiles), then every data block on the filesystem will be relocated to a new address, which invalidates all the data in the bees hash table at once. In such cases it is a good idea to:

1. Stop bees before the full balance starts,
2. Wipe the $BEESHOME directory (or delete and recreate beeshash.dat),
3. Restart bees after the full balance is finished.

bees will perform a full filesystem scan automatically after the balance since all the data has “new” btrfs transids. bees won’t waste any time invalidating stale hash table data after the balance if the hash table is empty. This can considerably improve the performance of both bees (since it has no stale hash table entries to invalidate) and btrfs balance (since it’s not competing with bees for iops).

Snapshots

bees can dedupe filesystems with many snapshots, but bees only does well in this situation if bees was running on the filesystem from the beginning.

Each time bees dedupes an extent that is referenced by a snapshot, the entire metadata page in the snapshot subvol (16KB by default) must be CoWed in btrfs. Since all references must be removed at the same time, this CoW operation is repeated in every snapshot containing the duplicate data. This can result in a substantial increase in btrfs metadata size if there are many snapshots on a filesystem.

Normally, metadata is small (less than 1% of the filesystem) and dedupe hit rates are large (10-40% of the filesystem), so the increase in metadata size is offset by much larger reductions in data size and the total space used by the entire filesystem is reduced.

If a subvol is deduped before a snapshot is created, the snapshot will have the same deduplication as the subvol. This does not result in unusually large metadata sizes. If a snapshot is made after bees has fully scanned the origin subvol, bees can avoid scanning most of the data in the snapshot subvol, as it will be provably identical to the origin subvol that was already scanned.

If a subvol is deduped after a snapshot is created, the origin and snapshot subvols must be deduplicated separately. In the worst case, this will double the amount of reading the bees scanner must perform, and will also double the amount of btrfs metadata used for the snapshot; however, the “worst case” is a dedupe hit rate of 1% or more, so a doubling of metadata size is certain for all but the most unique data sets. Also, bees will not be able to free any space until the last snapshot has been scanned and deduped, so payoff in data space savings is deferred until the metadata has almost finished expanding.

If a subvol is deduped after many snapshots have been created, all subvols must be deduplicated individually. In the worst case, this will multiply the scanning work and metadata size by the number of snapshots. For 100 snapshots this can mean a 100x growth in metadata size and bees scanning time, which typically exceeds the possible savings from reducing the data size by dedupe. In such cases using bees will result in a net increase in disk space usage that persists until the snapshots are deleted.

Snapshot case studies

• bees running on an empty filesystem
  • filesystem is mkfsed
  • bees is installed and starts running
  • data is written to the filesystem
  • bees dedupes the data as it appears
  • a snapshot is made of the data
    • The snapshot will already be 99% deduped, so the metadata will not expand very much because only 1% of the data in the snapshot must be deduped.
  • more snapshots are made of the data
    • as long as dedupe has been completed on the origin subvol, bees will quickly scan each new snapshot because it can skip all the previously scanned data. Metadata usage remains low (it may even shrink because there are fewer csums).
• bees installed on a non-empty filesystem with snapshots
  • filesystem is mkfsed
  • data is written to the filesystem
  • multiple snapshots are made of the data
  • bees is installed and starts running
  • bees dedupes each snapshot individually
    • The snapshot metadata will no longer be shared, resulting in substantial growth of metadata usage.
    • Disk space savings do not occur until bees processes the last snapshot reference to data.

Other Gotchas

• bees avoids the slow backrefs kernel bug by measuring the time required to perform LOGICAL_INO operations. If an extent requires over 5.0 kernel CPU seconds to perform a LOGICAL_INO ioctl, then bees blacklists the extent and avoids referencing it in future operations. In most cases, fewer than 0.1% of extents in a filesystem must be avoided this way. This results in short write latency spikes as btrfs will not allow writes to the filesystem while LOGICAL_INO is running. Generally the CPU spends most of the runtime of the LOGICAL_INO ioctl running the kernel, so on a single-core CPU the entire system can freeze up for a second during operations on toxic extents. Note this only occurs on older kernels. See the slow backrefs kernel bug section.

• If a process holds a directory FD open, the subvol containing the directory cannot be deleted (btrfs sub del will start the deletion process, but it will not proceed past the first open directory FD). btrfs-cleaner will simply skip over the directory and all of its children until the FD is closed. bees avoids this gotcha by closing all of the FDs in its directory FD cache every btrfs transaction.

• If a file is deleted while bees is caching an open FD to the file, bees continues to scan the file. For very large files (e.g. VM images), the deletion of the file can be delayed indefinitely. To limit this delay, bees closes all FDs in its file FD cache every btrfs transaction.