Callers of this function log the returned error and exit.
Let's log the error with the path to the filename and call stack
inside the function. This simplifies the code at callers' side
without reducing the level of debuggability.
Callers of ReadFullData() log the error and then exit.
So let's log the error with the path to the filename and the call stack
inside MustReadData(). This simplifies the code at callers' side,
while leaving the debuggability at the same level.
This commit changes background merge algorithm, so it becomes compatible with Windows file semantics.
The previous algorithm for background merge:
1. Merge source parts into a destination part inside tmp directory.
2. Create a file in txn directory with instructions on how to atomically
swap source parts with the destination part.
3. Perform instructions from the file.
4. Delete the file with instructions.
This algorithm guarantees that either source parts or destination part
is visible in the partition after unclean shutdown at any step above,
since the remaining files with instructions is replayed on the next restart,
after that the remaining contents of the tmp directory is deleted.
Unfortunately this algorithm doesn't work under Windows because
it disallows removing and moving files, which are in use.
So the new algorithm for background merge has been implemented:
1. Merge source parts into a destination part inside the partition directory itself.
E.g. now the partition directory may contain both complete and incomplete parts.
2. Atomically update the parts.json file with the new list of parts after the merge,
e.g. remove the source parts from the list and add the destination part to the list
before storing it to parts.json file.
3. Remove the source parts from disk when they are no longer used.
This algorithm guarantees that either source parts or destination part
is visible in the partition after unclean shutdown at any step above,
since incomplete partitions from step 1 or old source parts from step 3 are removed
on the next startup by inspecting parts.json file.
This algorithm should work under Windows, since it doesn't remove or move files in use.
This algorithm has also the following benefits:
- It should work better for NFS.
- It fits object storage semantics.
The new algorithm changes data storage format, so it is impossible to downgrade
to the previous versions of VictoriaMetrics after upgrading to this algorithm.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3236
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3821
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/70
Previously bytesutil.Resize() was copying the original byte slice contents to a newly allocated slice.
This wasted CPU cycles and memory bandwidth in some places, where the original slice contents wasn't needed
after slize resizing. Switch such places to bytesutil.ResizeNoCopy().
Rename the original bytesutil.Resize() function to bytesutil.ResizeWithCopy() for the sake of improved readability.
Additionally, allocate new slice with `make()` instead of `append()`. This guarantees that the capacity of the allocated slice
exactly matches the requested size. The `append()` could return a slice with bigger capacity as an optimization for further `append()` calls.
This could result in excess memory usage when the returned byte slice was cached (for instance, in lib/blockcache).
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2007
This should reduce disk space usage when scraping targets containing metrics with identical names
such as `node_cpu_seconds_total`, histograms, quantiles, etc.
Expose `vm_timestamps_blocks_merged_total` and `vm_timestamps_bytes_saved_total` metrics for monitoring
the effectiveness of timestamp blocks merging.
