This commit changes the logic around selecting jobs to run. Before this,
Boundary used a view "job_jobs_to_run" which was a collation of all jobs
that were not running and scheduled to run. When jobs were requested to
run, Boundary would look at this view, grab a certain amount of jobs and
insert them into the "job_run" table. Importantly, while the amount of
jobs to be scheduled at once defaulted to 1 in the scheduler package,
this was entirely overriden in the controller package to -1 (no limit,
run all jobs that the query would return).
With this commit, Boundary now looks at the "job" table directly for
jobs to run, regardless of job run status. This was done to improve DB
performance as the view (which queried all "job_run" rows) was causing
significant DB contention.
Additionally, the option to limit job runs is now removed since it was
already hardcoded to -1 and not user-configurable anyways.
Should the need arise to implement this limit again, this will have to
be done in a different way since the new query does not account for
running jobs and limiting the rows returned after jobs are already
running would yield a no-op (the new query inserts nothing into
"job_run" if any given job is already running).
Before this change, upon the completion of a job run, the scheduler
would update a job_run entry with the completed status as well as the
number of objects affected by the run. Additionally, we then had a
cleaner job whose scope was deleting these completed entries from
job_run.
This commit changes this design to drop the cleaner job the and rolls
its functionality directly into the scheduler. Now, when any given job
run is complete, the scheduler will automatically delete it from the
job_run table itself.
In addition, the completed status has been removed as a valid status as
it is not set anymore.
This change follows a decision that given the data in these job_run
entries is already being deleted by the cleaner job, updating its state
when a job completes just to have it deleted is not efficient.
Additionally, no use-case for this data was surfaced.
This changes the periodic job that deletes terminated sessions to delete
the those sessions in batches. Prior to this, a single SQL DELETE
command was used to delete all qualifying terminated sessions. In
systems under heavy load, the statement could timeout leading to a
situation where no qualifying terminated sessions were ever being
deleted.
This adds retries as an attribute to JobStatus allowing a job to
indicate liveness to the scheduler when work has not progressed.
A job could use this and the statusThreshold passed into the Run method
to break work up into batches that would otherwise timeout if all the
work was attempted at once, for example a long running SQL delete
command.
When a resource relating to a session is deleted,
notably a target, host, or auth_token, the corresponding sessions are
marked as canceled via a database trigger that calls the cancel_session
function. This function was performing a select as part of the insert
call to ensure that it would not attempt to insert a session_sate of
canceled if it was an invalid state transition. However, since this
function was first introduced, there has been additional constraints
added that would prevent an invalid state transition. In addition,
performing a select as part of an insert increases the chances for
contention with other queries that interact with the session_state
table, especially since a large number of sessions and session_state
rows can be included in a single transaction when things like
auth_tokens or targets get deleted.
Now, the cancel_function will perform the insert, and catch any of the
potential violations, allowing the query to continue without needing to
perform the select, thus reduction the potential for contention.
This replaces the start_time, end_time, and previous_end_time columns on
the session_state table with a time range column that records when the
state was active. This allowed for dropping several constraints on the
session_state table that were used to ensure that states for a session
did not overlap. Instead this can be ensured with a single exclusion
constraint. By reducing the number of constraints, it improves the
performance for a number of queries involved with session state. Most
notably when resolving delete cascades of resources related to sessions,
such as targets, where as part of the delete transaction large numbers
of sessions get canceled. Similarly, when sessions get deleted, and the
corresponding session_state rows are deleted, these constraints all must
be checked during the transaction.
The domain layer continues to expose StartTime and EndTime fields on
session.State. However it drops PreviousEndTime, which was never used by
anything calling the domain layer.
See:
https://www.postgresql.org/docs/current/ddl-constraints.html#DDL-CONSTRAINTS-EXCLUSIONhttps://www.postgresql.org/docs/current/rangetypes.html
This function was returning the set of deletion tables. A view seems
better suited for this task since it would allow for applying additional
filters of the result set. This was particularly necessary to easily
make changes to some sqltests due to switching the delete trigger for
the session table.
(cherry picked from commit 32d41639892950b21fafc39b50c10b997c6d5121)
When sessions are deleted, a trigger is used to insert records into the
session_deleted table. This table is utilized by the sessions list
endpoint when using a refresh token to inform a client of the sessions
that have been deleted since the last request. We delete sessions in
bulk via a controller job to delete sessions that have been terminated
over an hour ago, which results in the trigger running a large number of
separate insert statements while processing the delete statement.
This changes the trigger to run once for the delete statement, instead
of for each row, resulting in a single bulk insert statement to the
session_deleted table.
This new trigger function also avoids the use of `on conflict`. When
testing this function, while the single statement was still faster than
running multiple inserts, the `on conflict` still added significant
overhead, even when there were no conflicts. It should be safe to
perform the insert without the `on conflict`, since the same ID should
never be deleted more than once if it is successfully deleted.
(cherry picked from commit 3569b36c6eb2bee7a4e36e7584fcc6bbf1124f95)
When processing a controller API request, system uses a query to fetch
the grants for the requesting user. This query requires pulling together
information from several tables, and is currently performing many
sequential scans to do so. For a number of the tables involved, there
are indexes from multi-column primary keys, however, due to the order of
the columns in the index, the postgres planner would need to do a full
scan of the index, which can be less efficient than a sequential scan,
so instead it will perform a sequential scan of the table.
This recreates the primary keys while swapping the order of the columns
in the primary key definition, and thus the order in the index. By doing
so, the planner will not need to perform a full index scan, and will be
more likely to use the index when executing the grants query.
(cherry picked from commit 5577b3c358e9d45cd7ec02fc951e45d52e50595e)
This adds indexes for a few categories:
1. Foreign keys on the session table. These are set to `null` when the
referenced row is deleted. These indexes will help to more
efficiently set these `null` values in the case where a target is
deleted, or and auth token is deleted.
2. Foreign keys from other tables to the session table. These are either
set to `null` or cascade deleted when a session is deleted. These
indexes help with these update/deletes when a session is deleted.
3. A multi-column index on session_state. This helps with the query that
is used to delete all terminated sessions that have been terminated
for over an hour.
(cherry picked from commit 263a96e9ddd197cb36f2c4c74e91ac034112321e)
* refact: to use go-dbw CreateItems, DeleteItems
Latest version of go-dbw updated the signature of
CreateItems(...) and DeleteItems(...) on a happy
note this latest version of go-dbw actually does
batch inserts and updates for this functions.
* all: regenerate protos with new protoc-gen-go version
The worker_filter column was dropped from the
credential_vault_credential_private view in the
56/02_add_data_key_foreign_key_references.up.sql migration.
Any credential renewal/revocations that relied on the worker filter
would not successfully renew.
- Add new `local_storage_state` column to `server_worker` table which keeps track of the state of the local disk space.
- The valid values for `local_storage_state` are:
-- `available`: The worker local storage state is at an acceptable state
-- `lowStorage`: The worker is below the minimum threshold for local storage
-- `criticallyLowStorage`: The worker local storage state is below the critical minimum threshold for local storage
-- `outOfStorage`: The worker is out of local disk space
-- `notConfigured`: The worker does not have a local storage path configured
-- `unknown`: The default local storage state of a worker. Used when the local storage state of a worker is not yet known
This adds two sql functions that can be used to access the views to
retrieve monthly active user counts. The functions ensure that any time
calculates are performed in UTC, so that the month bounds align with the
start of the month in UTC.
1. hcp_billing_monthly_active_users_last_2_months() will return monthly
active users for the current and previous month.
2. hcp_billing_monthly_active_users_all() will return monthly active
users for all months. This function can also be provided a start time
and or end time to filter the results to a specific range.
This adds a function and after delete trigger to the auth_token table to
ensure that a corresponding auth token fact is updated with the deleted
time and sets the auth token valid time range. The data warehouse will
only be updated if the token that was deleted is in the 'token issued'
status.
This adds a function and update trigger to auth_token to ensure that:
1. If the auth token is updated to the issued state, a auth token fact
is added to the warehouse.
2. If the auth token's approximate last access time is updated, the
corresponding auth token fact is updated with the new time.
Previously the function used to upsert into the user dimension required
both an auth token id, and a user id. However, the user id can be
determined from the auth token, in fact it already was via the
whx_user_dimension_source view. This refactor removes the user id as an
argument, since it is not needed and will not be directly available when
this function is used when populating the new auth token accumulating
fact.
Hugo
Michael Gaffney
Timothy Messier
Louis Ruch
Damian Debkowski
Jim
Irena Rindos
Elim Tsiagbey
Todd
Jeff MitchellandDamian Debkowski
Johan Brandhorst-Satzkorn
Danielle Miu