The panic may trigger during data blocks' processing received
from vmstorage nodes when some of vmstorage nodes return an error
or when `-replicationFactor` is set to values higher than 2 at `vmselect`.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3058
The bug results in `duplicate output time series` error
because the same time series is added two times into the orderedMetricNames list
inside the tmpBlocksFileWrapper.Finalize().
While at it, properly release all the tmpBlocksFile structs on tbf.Finalize() error.
Previously only the remaining tbf entries were released. This could result in resource leak.
This should improve vmselect performance scalability on systems with many CPU cores.
The following tasks were done:
- Use separate temporary files for storing the data read from each vmstorage node.
This may result in the following potential issues:
- Up to N times higher memory usage for performing each query where N is the number
of vmstorage nodes known to vmselect.
This issue shouldn't increase chances of out of memory errors in most cases,
since per-query memory overhead is quite low comparing to the overall vmselect memory usage.
- Up to N times higher number of open temporary files where N is the number
of vmstorage nodes known to vmselect.
This issue should be fixed by increasing the limit on the number of open files.
- Use separate counters per each vmstorage node for various stats calculation
when reading the data from vmstorage nodes.
Previously a single syncwg.WaitGroup was used for tracking the lifetime of processBlock callbacks
across all the per-vmstorage goroutines. This could be slow on systems with many CPU cores
because of inter-CPU synchronization overhead.
Use a separate per-vmstorage sync.WaitGroup instead in order to reduce inter-CPU synchronization overhead.
This should imrpove performance for heavy queries over big number of blocks on multi-CPU systems.
Reduce inter-CPU communications when processing the query over big number of time series.
This should improve performance for queries over big number of time series
on systems with many CPU cores.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2896
Based on b596ac3745
Thanks to @zqyzyq for the idea.
- Use binary search instead of linear scan when locating the run of smallest timestamps
in blocks with intersected time ranges. This should improve performance
when merging blocks with big number of samples
- Skip samples with duplicate timestamps. This should increase query performance
in cluster version of VictoriaMetrics with the enabled replication.
Previously SearchMetricNames was returning unmarshaled metric names.
This wasn't great for vmstorage, which should spend additional CPU time
for marshaling the metric names before sending them to vmselect.
While at it, remove possible duplicate metric names, which could occur when
multiple samples for new time series are ingested via concurrent requests.
Also sort the metric names before returning them to the client.
This simplifies debugging of the returned metric names across repeated requests to /api/v1/series
Metrics `vm_partial_results_total` and `vm_requests_total` serving
the similar purpose, but contain inconsistent set of labels.
This change updates `vm_partial_results_total` labels to be consistent
with `vm_requests_total`.
The change breaks backward compatibility with assumption that
`vm_partial_results_total` wasn't widely used, since it is
not documented and absent in the alerts and dashboards.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
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
