There was a very small window where it was possible to deadlock during
the close of the Store. When closing, the Store waited on its Waitgroup
under a `Lock`. Naturally, all other goroutines must have been in a
position to call `Done` on the `Waitgroup` before the `Wait` call in
`Close` would return.
For the goroutine running the `monitorShards` method it was possible
that it would be unable to do this. Specifically, if the `monitorShards`
goroutine was jumping into the `t.C` case as the `Close()` goroutine was
acquiring the `Lock` then then `monitorShards` goroutine would be unable
to acquire the `RLock`. Since it would also be unable to progress around
its loop to jump into the `s.closing` case, it would be unable to call
`Done` on the `WaitGroup` and we would have a deadlock.
This was identified during an AppVeyor CI run, though I was unable to
reproduce this locally.
Previously we used the EngineOptions to determine which shard index
type we were using. However, these options are set once at runtime
initialisation. Therefore if you're running with TSI enabled but then
accessing a legacy database with the inmem index, TagValues would not
have taken advantage of the inmem index.
This change ensures we always check the actual index of the shard(s).
This commit adds time support to SHOW TAG VALUES. Time can be used as
both a lower and upper boundary. However, there are some caveats.
For the `inmem` index, filtering by time will still return all results
because the index data is shared across shards.
For the `tsi1` index, filtering by time will only work down to the shard
lever. Specifically, when querying by time all shards within that time
range will be used to generate the results.
When a meta query does not include a time component then it can be
answered exclusively by the index. This should result in a much faster
query execution that if the TSM engine was engaged.
This commit rewrites the following queries such that they make use
of the index where no time component is present:
- SHOW MEASUREMENTS
- SHOW SERIES
- SHOW TAG KEYS
- SHOW FIELD KEYS
Update support in the `toml` package for parsing human-readble byte sizes.
Supported size suffixes are "k" or "K" for kibibytes, "m" or "M" for
mebibytes, and "g" or "G" for gibibytes. If a size suffix isn't specified
then bytes are assumed.
In the config, `cache-max-memory-size` and `cache-snapshot-memory-size` are
now typed as `toml.Size` and support the new syntax.
* Fprint* functions
* No nakedness
* clarify panic messages
* spacing between case statements
* remove break in favor of return
* remove goto in favor of for { continue }
* batch cursors return slices of timestamps and values to reduce call
overhead. Significantly improved iteration.
* added CreateCursor API to Shard, Engine
* moved build*Cursor to code gen
* array has already been sized correctly
* eliminates bounds checking for each element access
* reduces decoding of 30,000,000 points via storage API from
584ms to 540ms on average
Fixes#8989 and #8633.
Previously when issuing commands involving a regex check, walking
through the tags keys/values on a measurement, using the measurement's
index, would be racy.
This commit adds a new `TagKeyValue` type that abstracts away the
multi-layer map we were using as an inverted index from tag keys and
values to series ids. With this abstraction we can also make concurrent
access to this inverted index goroutine safe.
Finally, this commit fixes a very old bug in the index which will affect
any query using a regex. Previously we would always check _every_ tag
against a regex for a measurement, even when we had found a match.
* Introduces EXPLAIN ANALYZE command, which
produces a detailed tree of operations used to
execute the query.
introduce context.Context to APIs
metrics package
* create groups of named measurements
* safe for concurrent access
tracing package
EXPLAIN ANALYZE implementation for OSS
Serialize EXPLAIN ANALYZE traces from remote nodes
use context.Background for tests
group with other stdlib packages
additional documentation and remove unused API
use influxdb/pkg/testing/assert
remove testify reference
If multiple tombstones exists for a series that ended up causing the
full data to be deleted, the blocks were not removed from the offsets
in the index. This causes the TSMReader to report that a key exist
but does not have any data.
During a compaction, every key should have at least one value. Since
this invariant was broken, the compaction aborted early and ends up
dropping all series keys that are lexigraphically greater than where
the breakage occured. This would cause data to be dropped during the
compaction.
This fixes a potential bug where the BlockIterator would skip blocks
if the underlying TSMReader had deletes on it concurrently. This
could possibly occur due to changes in 91eb9de3 that now use the
existing TSMReaders from the FileStore instead of creating new ones
during compaction.
TSI did not check that the max select series limit during planning
the same way that inmem did. This means that the limit could be
set but the planning of a high cardinality query would still OOM
the server. This fixes that limit as well as makes the query interruptible
during planning.
There was a race on the WaitGroup where we could end up calling Add
while another goroutine was still waiting. The functions were confusing
so they have been simplified a bit since the compactions goroutines
have been reworked a lot already.
The scheduling logic ended up favoring more backlogged shards
too much and would starved active, less backed up shards. This
occurred because the scheduling kicks in once a second. When it
runs, it schedules as many compactions as it can. A backed up shard
would end up having more compactions to run during the loop an would
generally get to schedule them more frequently.
This now allows each shard to try and schedule one compaction at a time
which provides a more balanced approach. At some point, we'll probably
want to more directly balanc the each shards backlog vs letting it happen
somewhat randomly.
Some files seem to get orphan behind higher levels. This causes
the compactions to get blocked as the lowere level files will not
get picked up by their lower level planners. This allows the full
plan to identify them and pull them into their plans.
This check doesn't make sense for high cardinality data as the files
typically get big and sparse very quickly. This causes a lot of extra
disk space to be used which is taken up by large indexes and sparse
data.
Edd Robinson
Ben Johnson
Stuart Carnie
Jonathan A. Sternberg
Andrew Hare
Jason Wilder
Jason Wilder
lrita