When a time zone shift happened at the edge of a time bucket, the logic
was incorrect. When we added an hour to the day with a time grouping of
2 hours, we took the hour away from the previous bucket instead of the
next bucket so the first bucket of the day would be from midnight to 1
AM and the second bucket would include 1 AM to 4 AM (2 AM to 3 AM does
not exist when shifting forwards). The correct buckets should have been
12 AM to 2 AM for the first bucket of the day and 3 AM to 4 AM for the
second (since 2 AM to 3 AM does not exist).
This also modifies the tests to use table tests and sub tests.
This calculates the start and end time along with any time zones shifts
so that continuous queries are run at the correct time when a time zone
is included in the query.
Removing the forced `Connection: close` header from the `/query`
endpoint. This was originally added because of golang/go#13165, but it
seems like it's possible to use pipelining with go 1.8 and http 1.1,
just not recommended.
After some testing, it appears that the channel returned by
`ResponseWriter.CloseNotify()` will not send a value if the connection
was not interrupted. We already account for this in /query by exiting
from the goroutine if the request has finished by signaling another
channel.
Since the handler already accounts for the possibility that the channel
will not signal and since `CloseNotify()` doesn't interfere with a
pipelined request, we can remove the forced `Connection: close` that was
added to force clients to establish a new connection.
The Go timestamp leads Truncate to start a week on Monday, but the query
engine uses unix timestamps which has the week start on a Thursday.
Updating the service so it uses a custom truncate method that uses the
unix timestamp instead of `time.Time`.
Fixes#8569.
The sortedSeriesIds slice was not getting reset to 0 which caused
the same series ids to exist in the slice more than once. Since
the size of the slice never matched the size of the seriesID map,
it kept appendending to the slice and sorting it which cause multiple
cursor to get created for the same series.
Fixes#8531
This adds a v3 format that is a gzip compressed version of the v2
format. It reduces the size of tombstone files substantially without
having to support a more feature rich file format for tombstones.
This commit adds a new environment variable INFLUXDB_PANIC_CRASH, which
when set to a truthy value, e.g., true, TRUE, 1, will prevent the server
from recovering from a panic.
Recover currently occurs in two places: the HTTP handler and the
QueryExecutor. INFLUXDB_PANIC_CRASH will control both.
Further, this commit adds _internal stats that will monitor the
occurrence of panics all the time (regardless of if INFLUXDB_PANIC_CRASH
has been set to true or not).
The recovered panic frequency can be inspected with the following
queries:
SELECT "recoveredPanics" FROM "_internal"."monitor"."httpd";
SELECT "recoveredPanics" FROM "_internal"."monitor"."queryExecutor";
Currently two write locks in `inmem` are obtained and then
manually unlocked at function exit points. However, we have
reports that the `inmem` index is hanging on a write lock and
cannot track the issue down to anything else besides a lock
that could have been left unlocked because of a panic.
This commit changes the two locks to always defer their unlocks
to prevent these hangs.
The new algorithm uses only one formula and needs no additional bias corrections for the entire range of cardinalities,
therefore, it is more efficient and simpler to implement. Our simulations show that the accuracy provided by the new
algorithm is as good as or better than the accuracy provided by either of HyperLogLog or HyperLogLog++. The sparse
representation was kept in to provide better low cardinality accuracy. However the linear counting and range estimations
are replaced.
This fixes the case where log files are compacted out of order
and cause non-contiguous sets of index files to be compacted.
Previously, the compaction planner would fetch a list of index files
for each level and compact them in order starting with the oldest
ones. This can be a problem for level 1 because level 0 (log files)
are compacted individually and in some cases a log file can finish
compacting before older log files are finished compacting. This
causes there to be a gap in the list of level 1 files that is
ignored when fetching a list of index files.
Now, the planner reads the list of index files starting from the
oldest but stops once it hits a log file. This prevents that gap
from being ignored.
* off by default, enabled by `query-stats-enabled`
* writes to cq_query measurement of configured monitor database
* see CHANGELOG for schema of individual points
This check was previously in a different section of code which
was lost during a refactor to the new compaction strategy. The
compaction planning now makes a check to ensure at least two
files are available for compaction in a level.
When a `SELECT ... INTO ...` is used with `top()` or `bottom()` used
with tags, the points will be written with the tags still intact instead
of converted to fields.
The previous version of `top()` and `bottom()` would gather all of the
points to use in a slice, filter them (if necessary), then use a
slightly modified heap sort to retrieve the top or bottom values.
This performed horrendously from the standpoint of memory. Since it
consumed so much memory and spent so much time in allocations (along
with sorting a potentially very large slice), this affected speed too.
These calls have now been modified so they keep the top or bottom points
in a min or max heap. For `top()`, a new point will read the minimum
value from the heap. If the new point is greater than the minimum point,
it will replace the minimum point and fix the heap with the new value.
If the new point is smaller, it discards that point. For `bottom()`, the
process is the opposite.
It will then sort the final result to ensure the correct ordering of the
selected points.
When `top()` or `bottom()` contain a tag to select, they have now been
modified so this query:
SELECT top(value, host, 2) FROM cpu
Essentially becomes this query:
SELECT top(value, 2), host FROM (
SELECT max(value) FROM cpu GROUP BY host
)
This should drastically increase the performance of all `top()` and
`bottom()` queries.
Writing points outside of a retention policy range were silently dropped. They
are dropped to prevent creating a shard that will be immediately deleted. These
dropped points were silent and did not return an error respone to the caller.
Fixes#8392
Currently, when debugging issues with InfluxDB we often ask for the
following profiles:
curl -o block.txt "http://localhost:8086/debug/pprof/block?debug=1"
curl -o goroutine.txt
"http://localhost:8086/debug/pprof/goroutine?debug=1"
curl -o heap.txt "http://localhost:8086/debug/pprof/heap?debug=1"
curl -o cpu.txt "http://localhost:8086/debug/pprof/profile
This can be bothersome for users, or even difficult if they're
unfamiliar with cURL (or it's not on their system).
This commit adds a new endpoint: /debug/pprof/all which will return a
single compressed archive of all of the above profiles. The CPU profile
is optional, and not returned by default. To include a CPU profile the
URL to request should be: /debug/pprof/all?cpu=true. It's also possible
to vary the length of the CPU profile by adding a `seconds=x` parameter,
where x defaults to 30, if absent.
The new command for gathering profiles from users should now be:
curl -o profiles.tar.gz "http://localhost:8086/debug/pprof/all"
Or, if we need to see a CPU profile:
curl -o profiles.tar.gz
"http://localhost:8086/debug/pprof/all?cpu=true"
It's important to remember that a CPU profile is a blocking operation
and by default it will take 30 seconds for the response to be returned
to the user.
Finally, if the user is unfamiliar with cURL, they will now be able to
visit http://localhost:8086/debug/pprof/all in a web browser, and the
archive will be downloaded to their machine.