Previously the interval between item addition and its conversion to searchable in-memory part
could vary significantly because of too coarse per-second precision. Switch from fasttime.UnixTimestamp()
to time.Now().UnixMilli() for millisecond precision. It is OK to use time.Now() for tracking
the time when buffered items must be converted to searchable in-memory parts, since time.Now()
calls aren't located in hot paths.
Increase the flush interval for converting buffered samples to searchable in-memory parts
from one second to two seconds. This should reduce the number of blocks, which are needed
to be processed during high-frequency alerting queries. This, in turn, should reduce CPU usage.
While at it, hardcode the maximum size of rawRows shard to 8Mb, since this size gives the optimal
data ingestion pefromance according to load tests. This reduces memory usage and CPU usage on systems
with big amounts of RAM under high data ingestion rate.
Callers of OpenStorage() log the returned error and exit.
The error logging and exit can be performed inside MustOpenStorage()
alongside with printing the stack trace for better debuggability.
This simplifies the code at caller side.
Callers of these functions log the returned error and then exit. The returned error already contains the path
to directory, which was failed to be created. So let's just log the error together with the call stack
inside these functions. This leaves the debuggability of the returned error at the same level
while allows simplifying the code at callers' side.
While at it, properly use MustMkdirFailIfExist instead of MustMkdirIfNotExist inside inmemoryPart.MustStoreToDisk().
It is expected that the inmemoryPart.MustStoreToDick() must fail if there is already a directory under the given path.
The main purpose of this command-line flag is to increase the lifetime of low-end flash storage
with the limited number of write operations it can perform. Such flash storage is usually
installed on Raspberry PI or similar appliances.
For example, `-inmemoryDataFlushInterval=1h` reduces the frequency of disk write operations
to up to once per hour if the ingested one-hour worth of data fits the limit for in-memory data.
The in-memory data is searchable in the same way as the data stored on disk.
VictoriaMetrics automatically flushes the in-memory data to disk on graceful shutdown via SIGINT signal.
The in-memory data is lost on unclean shutdown (hardware power loss, OOM crash, SIGKILL).
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3337
This eliminates the need for storing block data into temporary files on a single-node VictoriaMetrics
during heavy queries, which touch big number of time series over long time ranges.
This improves single-node VM performance on heavy queries by up to 2x.
