We changed primary key for bucket_bandwidth_rollups table. Now we
need to do some cleanup in places like structs, sorting methods or SQL
queries.
Change-Id: Ida4f874f161356df193379a53507602e04db1668
Sorting by primary key before inserting data into DB is fixed.
Earlier we were sorting input slice of BucketBandwidthRollup but then
we were putting all entries into map to rollup input data. Iteration
over map with a range loop doesn't guarantee any specific order so we
were loosing sorted order when we were creating with this map slices to
use with DB insert.
New code is also using map but when map is full its sorting map keys
separately and iterates over them to get data from map.
https://github.com/storj/storj/issues/5332
Change-Id: I5bf09489b0eecb6858bf854ab387b660124bf53f
bucket_bandwidth_rollups table
We have performance problems with updating bucket_bandwidth_rollups. To
improve situation we can stop storing allocated bandwidth in this table.
This should reduce large number of updates which are comming from
metainfo endpoints, repair workers and audit.
Next step will be to drop `allocated` column completely from
bucket_bandwidth_rollups.
Allocated GET bandwidth is all we need and we are keeping it in
bucket_bandwidth_rollups table.
Change-Id: Ifdd26a89ba8262acbca6d794a6c02883ad0c0c9b
Batching of the order submissions can lead to combining the allocated
traffic totals for two completely different time windows, resulting
in incorrect customer accounting. This change will group the batched
order submissions by projectID as well as time window, leading to
distinct updates of a buckets bandwidth rollup based on the hour
window in which the order was created.
Change-Id: Ifb4d67923eec8a533b9758379914f17ff7abea32
Populate the egress_dead column for taking into account allocated bandwidth that can be removed because orders have been sent by the storage nodes. The bandwidth not used in these orders can be allocated again.
Change-Id: I78c333a03945cd7330aec052edd3562ec671118e
We are not using this table so make no sense to put data there.
This change removes only code that is using this table. Before next
release we need to drop table with migration step.
Change-Id: I80f400aa778c717e70324bd00da502b7032c9d9f
project_bandwidth_daily_rollups table
We want to calculate used bandwidth better so we need to calculate it
from allocated and settled bandwidth. To do this we need first populate
this new table.
https://storjlabs.atlassian.net/browse/PG-56
Change-Id: I308b737bf08ee48ce4e46a3605697ab2095f7257
Initially we duplicated the code to avoid large scale changes to
the packages. Now we are past metainfo refactor we can remove the
duplication.
Change-Id: I9d0b2756cc6e2a2f4d576afa408a15273a7e1cef
Delete satellite order methods and DB tables which aren't used anymore
after we have done a refactoring on the orders to stuck bucket
information in the orders' encrypted metadata.
There are also configuration parameters and a satellite chore that
aren't needed anymore after the orders refactoring.
Change-Id: Ida3682b95921df70792284b42c96d2508bf8ca9c
CRDB doesn't like large deletes. While testing in the POC environment we found that deletes on the serial_numbers table could take hours. This change limits deletes to 1000 at a time (configurable) to avoid blocking other queries.
Change-Id: I08455e25db1574579dd4d7b7125a08e9c913dff1
With the new phase 3 order submission, orders can be added to the
storage and bandwidth rollup tables at timestamps before the most recent
rollup was run. This change shifts the start time of each new rollup
window to account for any unexpired orders that might have been added
since the previous rollup.
A satellitedb migration is necessary to allow upserts in the
accounting_rollups table when entries with identical node_ids and
start_times are inserted.
Change-Id: Ib3022081f4d6be60cfec8430b45867ad3c01da63
It turns out we need to make 2 more changes in order for the new order submission phase 3 to get deployed.
This PR makes 2 changes:
1) when the rollup service deletes tallies, we now keep tallies around until orders expire (vs 1 day like before).
2) the reported rollup chore will now write the storagenode_bandwidth_rollups to a new table _phase2 as an intermediary step so it doesn't conflict with phase 3 order settlement.
These changes need to be deployed for 2 days before we can turn on phase 3 of the new orders settlement workflow.
Change-Id: Iafbff577ba7d55f8f17b7db857311b2ce799de60
Doing it at the ProcessOrders level was insufficient: the endpoints
make multiple database calls. It was a misguided attempt to only
have one spot enter the semaphore. By putting it in the endpoint
we can not only be sure that the concurrency is correctly limited
but it can be configurable easily.
Change-Id: I937149dd077adf9eb87fce52a1a17dc0afe96f64
we have thundering herds of order submissions that take all of the
database connections causing temporary periodic outages. limit
the amount of concurrent order processing to 2.
Change-Id: If3f86cdbd21085a4414c2ff17d9ef6d8839a6c2b
Why: We need a way to cut down on database traffic due to bandwidth
measurement and tracking.
What: This changeset is the Satellite side of settling orders in 1 hr windows.
See design doc for more details: https://review.dev.storj.io/c/storj/storj/+/1732
Change-Id: I2e1c151e2e65516ebe1b7f47b7c5f83a3a220b31
What:
Use the github.com/jackc/pgx postgresql driver in place of
github.com/lib/pq.
Why:
github.com/lib/pq has some problems with error handling and context
cancellations (i.e. it might even issue queries or DML statements more
than once! see https://github.com/lib/pq/issues/939). The
github.com/jackx/pgx library appears not to have these problems, and
also appears to be better engineered and implemented (in particular, it
doesn't use "exceptions by panic"). It should also give us some
performance improvements in some cases, and even more so if we can use
it directly instead of going through the database/sql layer.
Change-Id: Ia696d220f340a097dee9550a312d37de14ed2044
This ensures that rows are closed to avoid leaks.
Also verifies that Err() is called, to ensure that no
error is left behind.
Change-Id: Idd1bec9bf479f40021da67b2c80ce83033149469
this way we don't have to do 2 steps, and by using the ctid, postgres
is going to do two very efficient prefix scans.
Change-Id: Ia9d0546cdf0a1af67ceec9cd508d336a5fdcbdb9
also remove the continuation support from the queue, otherwise
we may end up sequential scanning the entire table to get
a few rows at the end.
then, in the core, instead of looping both to get a big enough
batch inside of the queue, as well as outside of it to ensure
we consume the whole queue, just get a single batch at a time.
also, make the queue size configurable because we'll need to
do some tuning in production.
Change-Id: If1a997c6012898056ace89366a847c4cb141a025
by doing an indexed anti-join we're able to reduce the time to
select the pending orders by over 10x on postgres. this should
help us process pending orders much more quickly.
it probably won't do as good a job on cockroach because it does
not do an indexed anti-join and instead does a hash join after
scanning the entire consumed serials table. we should either
remove orders entirely or try to make that more efficient
when necessary.
Change-Id: I8ca0535acd21c51e74955b24c9b86d20e4f2ff9c
This change adds two new tables to process orders as fast as we used
to but in an asynchronous manner and with hopefully less storage
usage. This should help scale on cockroach, but limits us to one
worker. It lays the groundwork for the order processing pipeline to
be queue rather than database driven.
For more details, see the added fast billing changes blueprint.
It also fixes the orders db so that all the timestamps that are
passed to columns that do not contain a time zone are converted to
UTC at the last possible opportunity, making it less likely to use
the APIs incorrectly. We really should migrate to include timezones
on all of our timestamp columns.
Change-Id: Ibfda8e7a3d5972b7798fb61b31ff56419c64ea35
Enhance the documentation of the UseSerialNumber method (interface and
implementation) and add several missing dots in doc comments of the
methods of the same interface and implementation.
Change-Id: I792cd344f0d2542e060fa2ec288b71231cae69de
A uuid.UUID is an array of bytes, and slicing it refers to the
underlying value, much like taking the address. Because range
in Go reuses the same value for every loop iteration, this means
that later iterations would overwrite earlier stored project
ids. We fix that by making a copy of the value before slicing it
for every loop iteration.
Change-Id: Iae3f11138d11a176ce360bd5af2244307c74fdad
Since incoming times may be in any time zone, and we want the output
to be in UTC and for them to have 00:00:00 hours, minutes and seconds
we first convert the incoming timestamp to UTC before doing the
truncate to the day and adding a day.
Because the old code always returned a timestamp that was in the
future, this is just for efficiency.
Change-Id: Ie692d47bca8691e73852c822d5c56cf8773d99b4
warning: databases migrated to version 77 before this commit
is merged must be manually re-migrated. this should not be a
problem for anything but staging databases.
Change-Id: Ie1631c48379472352014183ee43f1465e22200f7
this commit introduces the reported_serials table. its purpose is
to allow for blind writes into it as nodes report in so that we have
minimal contention. in order to continue to accurately account for
used bandwidth, though, we cannot immediately add the settled amount.
if we did, we would have to give up on blind writes.
the table's primary key is structured precisely so that we can quickly
find expired orders and so that we maximally benefit from rocksdb
path prefix compression. we do this by rounding the expires at time
forward to the next day, effectively giving us storagenode petnames
for free. and since there's no secondary index or foreign key
constraints, this design should use significantly less space than
the current used_serials table while also reducing contention.
after inserting the orders into the table, we have a chore that
periodically consumes all of the expired orders in it and inserts
them into the existing rollups tables. this is as if we changed
the nodes to report as the order expired rather than as soon as
possible, so the belief in correctness of the refactor is higher.
since we are able to process large batches of orders (typically
a day's worth), we can use the code to maximally batch inserts into
the rollup tables to make inserts as friendly as possible to
cockroach.
Change-Id: I25d609ca2679b8331979184f16c6d46d4f74c1a6
everyone was importing it as dbx anyway. why should it be
named satellitedb? so yeah just pass the "-p dbx" flag.
Change-Id: I5efa669f4f00f196b38a9acd0d402009475a936f
This reverts commit 8e242cd012.
Revert because lib/pq has known issues with context cancellation.
These issues need to be resolved before these changes can be merged.
Change-Id: I160af51dbc2d67c5449aafa406a403e5367bb555
this will allow for some nice runtime analysis down the road.
also, this allows for wrapping database handles in a way that
can interact with these contexts
requires https://review.dev.storj.io/c/storj/dbx/+/514
Change-Id: Ib087b7cd73296dd2c1e0331314da34d861f61d2b
