The chief segment health models we've come up with are the "immediate
danger" model and the "survivability" model. The former calculates the
chance of losing a segment becoming lost in the next time period (using
the CDF of the binomial distribution to estimate the chance of x nodes
failing in that period), while the latter estimates the number of
iterations for which a segment can be expected to survive (using the
mean of the negative binomial distribution). The immediate danger model
was a promising one for comparing segment health across segments with
different RS parameters, as it is more precisely what we want to
prevent, but it turns out that practically all segments in production
have infinite health, as the chance of losing segments with any
reasonable estimate of node failure rate is smaller than DBL_EPSILON,
the smallest possible difference from 1.0 representable in a float64
(about 1e-16).
Leaving aside the wisdom of worrying about the repair of segments that
have less than a 1e-16 chance of being lost, we want to be extremely
conservative and proactive in our repair efforts, and the health of the
segments we have been repairing thus far also evaluates to infinity
under the immediate danger model. Thus, we find ourselves reaching for
an alternative.
Dr. Ben saves the day: the survivability model is a reasonably close
approximation of the immediate danger model, and even better, it is
far simpler to calculate and yields manageable values for real-world
segments. The downside to it is that it requires as input an estimate
of the total number of active nodes.
This change replaces the segment health calculation to use the
survivability model, and reinstates the call to SegmentHealth() where it
was reverted. It gets estimates for the total number of active nodes by
leveraging the reliability cache.
Change-Id: Ia5d9b9031b9f6cf0fa7b9005a7011609415527dc
WHAT:
added brotli compression for wasm files and added copying of those files to static/wasm folder in Dockerfile
WHY:
those files are a part of web worker webpack bundle and I didn't find a way to compress them separately using webpack.
I'm open to any other ideas if they come up
Change-Id: I105cc1582e9816fd9b63052ba48358525c85a164
WHAT:
web worker is initialized during onlogin loading screen now
WHY:
removed unnecessary initializations and increased UX experience
Change-Id: I734f194f862c15b3fb08e436a161da32d8d4a8ac
Currently node id in access grant is '1' and it cannot be parsed to
valid node id. This change update access grant satellite address with
randomly generated node id.
Change-Id: Id1684ac71509bc5a8177b069a914355be3c72d43
A few weeks ago it was discovered that the segment health function
was not working as expected with production values. As a bandaid,
we decided to insert the number of healthy pieces into the segment
health column. This should have effectively reverted our means of
prioritizing repair to the previous implementation.
However, it turns out that the bandaid was placed into the code which
removes items from the irreparable db and inserts them into the repair
queue.
This change: insert number of healthy pieces into the repair queue in the
method, RemoteSegment
Change-Id: Iabfc7984df0a928066b69e9aecb6f615253f1ad2
there were two changes to this package: one that modified
some things and renamed access.go to main.go, and one that
reduced the binary sizes against main.go.
somehow the latter change was included on this branch but
the former was not, which made the folder contain both
main.go and access.go. building the package then fails
with duplicate definitions.
the easiest fix is to remove access.go which makes the folder
match the contents of the current master branch.
Change-Id: I7070a0d25a0399cef3166b8b2189427bc55587e0
There is a new checker field called statsCollector. This contains
a map of stats pointers where the key is a stringified redundancy
scheme. stats contains all tagged monkit metrics. These metrics exist
under the key name, "tagged_repair_stats", which is tagged with the
name of each metric and a corresponding rs scheme.
As the metainfo observer works on a segment, it checks statsCollector
for a stats corresponding to the segment's redundancy scheme. If one
doesn't exist, it is created and chained to the monkit scope. Now we can call
Observe, Inc, etc on the fields just like before, and they have tags!
durabilityStats has also been renamed to aggregateStats.
At the end of the metainfo loop, we insert the aggregateStats totals into the
corresponding stats fields for metric reporting.
Change-Id: I8aa1918351d246a8ef818b9712ed4cb39d1ea9c6
and replaces access grant with access
uplink share <path> --> creates access grant
uplink share --register <path> --> registers access grant
uplink share --url <path> --> creates URL, implies register and public
uplink share --dns <hostname> <path> --> creates dns info, implies register and public
Change-Id: I7930c4973a602d3d721ec6f77170f90957dad8c0
Make changes so that we only import the necessary files from the console package so that the generated wasm code is as small as possible.
This change gets the compiled wasm code down to 8.6MB uncompressed and 2MB when compressed with `gzip --best`.
https://review.dev.storj.io/c/storj/storj/+/3396
Change-Id: Ifdd4be285810757b46bbbe43327c0d0139e5f8f7
Remove a declared variable that's set by never read nor passed to any
function so it's unused code.
Change-Id: I8daf9d1f71d29ab39d7a80011d1b4813ada1c67d
We need to be able to update just remote_pieces column in DB. This is
needed at least for repair process.
Change-Id: I20dcc9b06babfefbbf102f32b1d14946379f26c2
It was designed to detect and remove zombie segments in the PointerDB.
This tool should be not relevant with the MetabaseDB anymore.
Change-Id: I112552203b1329a5a659f69a0043eb1f8dadb551
We migrated satelliteDB off of Postgres and over to CockroachDB (crdb), but there was way too high contention for the injuredsegments table so we had to rollback to Postgres for the repair queue. A couple things contributed to this problem:
1) crdb doesn't support `FOR UPDATE SKIP LOCKED`
2) the original crdb Select query was doing 2 full table scans and not using any indexes
3) the SLC Satellite (where we were doing the migration) was running 48 repair worker processes, each of which run up to 5 goroutines which all are trying to select out of the repair queue and this was causing a ton of contention.
The changes in this PR should help to reduce that contention and improve performance on CRDB.
The changes include:
1) Use an update/set query instead of select/update to capitalize on the new `UPDATE` implicit row locking ability in CRDB.
- Details: As of CRDB v20.2.2, there is implicit row locking with update/set queries (contention reduction and performance gains are described in this blog post: https://www.cockroachlabs.com/blog/when-and-why-to-use-select-for-update-in-cockroachdb/).
2) Remove the `ORDER BY` clause since this was causing a full table scan and also prevented the use of the row locking capability.
- While long term it is very important to `ORDER BY segment_health`, the change here is only suppose to be a temporary bandaid to get us migrated over to CRDB quickly. Since segment_health has been set to infinity for some time now (re: https://review.dev.storj.io/c/storj/storj/+/3224), it seems like it might be ok to continue not making use of this for the short term. However, long term this needs to be fixed with a redesign of the repair workers, possible in the trusted delegated repair design (https://review.dev.storj.io/c/storj/storj/+/2602) or something similar to what is recommended here on how to implement a queue on CRDB https://dev.to/ajwerner/quick-and-easy-exactly-once-distributed-work-queues-using-serializable-transactions-jdp, or migrate to rabbit MQ priority queue or something similar..
This PRs improved query uses the index to avoid full scans and also locks the row its going to update and CRDB retries for us if there are any lock errors.
Change-Id: Id29faad2186627872fbeb0f31536c4f55f860f23
