* Allow replicateToDatastore to skip gaps
As it turns out, gaps in the transaction id sequence number are expected
because rollbacks do not rollback sequence numbers.
To deal with this, stop checking these.
This change is not adequate in and of itself, as it is possible for a gap to
be introduced if two transactions are committed out of order of their sequence
number. We are currently discussing several strategies to mitigate this.
* Remove println, add a record verification
* Fix hanging test
Tests using the TestServerExtension may hang forever if an underlying
component (e.g., testcontainer for psql) fails. This may be the cause
of the some kokoro runs that timeed out after three hours.
* Add a tools command to launch SQL validation job
Stopping using Pipeline.run().waitUntilFinish in
ValidateDatastorePipeline. Flex-templalate does not support blocking
wait in the main thread.
This PR adds a new ValidateSqlCommand that launches the pipeline and
maintains the SQL snapshot while the pipeline is running.
This PR also added more parameters to both ValidateSqlCommand and
ValidateDatastoreCommand:
- The -c option to supply an optional incremental comparison start time
- The -r option to supply an optional release tag that is not 'live',
e.g., nomulus-DDDDYYMM-RC00
If the manual launch option (-m) is enabled, the commands will print the
gcloud command that can launch the pipeline.
Tested with sandbox, qa and the dev project.
* Don't reset the update time for TLD updates
It turns out that the reason that the Registrar update timestamp isn't updated
for some of the tests is because the record is updated unchanged. We can
avoid this problem by not trying to update the registrar to the same value.
So in this case, if the registrar alreay contains the TLD we're adding, don't
try to add it.
* Fix entity delete replication, compare db @ replay
Replay tests currently only verify that the contents of a transaction are
can be successfully replicated to the other database. They do not verify that
the contents of both databases are equivalent. As a result, we miss any
changes omitted from the transaction (as was the case with entity deletions).
This change adds a final database comparison to ReplayExtension so we can
safely say that the databases are in the same state.
This comparison is introduced in part as a unit test for the one-line fix for
replication of an "entity delete" operation (where we delete using an entity
object instead of the object's key) which so far has only affected PollMessage
deletion. The fix is also included in this commit within
JpaTransactionManagerImpl.
* Exclude tests and entities with failing comparisons
* Get all tests to pass and fix more timestamp
Fix most of the unit tests that were broken by this change.
- Fix timestamp updates after grace period changes in DomainContent and for
TLD changes in Registrar.
- Reenable full database comparison for most DomainCreateFlowTest's.
- Make some test entities NonReplicated so they don't break when used with
jpaTm().delete()
- Diable checking of a few more entity types that are failing comparisons.
- Add some formatting fixes.
* Remove unnecessary "NoDatabaseCompare"
I turns out that after other fixes/elisions we no longer need these for
any tests in DomainCreateFlowTest.
* Changes for review
* Remove old "compare" flag.
* Reformatted.
* Make a few quality-of-life improvements in CloudTasksUtils
1. Update the method names. There are too many overloaded methods and it
is hard to figure out which one does which without checking the
javadoc.
2. Added a method in the task matcher to specify the delay time in
DateTime, so the caller does not need to convert it to Timestamp.
3. Remove the expilict dependency on a clock when enqueueing a task with
delay, the clock is now injected directly into the util instance
itself.
* Disable prober data deletion cron job in prod & sandbox
This is going to unnecessarily make the database migration more complex, and we
don't need them that badly. We'll re-enable these cron jobs once we've written
the new version of this action that handles Cloud SQL correctly (the current
version only does Datastore anyway).
* Ignore prober data when comparing databases
Completely ignore prober data when comparing Datastore and SQL.
Prober data deletions are not propagated from Datastore to SQL. It is
difficult to distinguish soft-deletes from normal updates, therefore
difficult to avoid false positives when looking for differences.
This is necessary because the Cloud Tasks API is not transactionally enrolled,
so it's possible that multiple tasks might end up being enqueued. We need to be
able to handle them.
* Fix update timestamps for DomainContent types
We expect update timestamps to be updated whenever a containing entity is
modified and persisted, but unfortunately Hibernate doesn't seem to do this --
instead it appears to regard such an entity as unchanged.
To work around this, we explicitly reset the update timestamp whenever a
nested collection is modified in the Builder.
Note that this change only solves the problem for DomainContent. All other
entitities containing UpdateAutoTimestamp will need to be audited and
instrumented with a similar change.
* Fix a handful of tests broken by this change
* Reformatted.
* Use CloudTaskUtils to enqueue
* Add CloudTasksUtilsModule to FrontendComponent
* Fix Uri query issue
* Remove header and check service in matcher
* Use a ThreadLocal boolean in TestServer to determine enqueueing
* Extract enqueuing and email sending from tm().transact()
* Add action to DB comparison pipeline
Add a backend Action in Nomulus server that lanuches the pipeline for
comparing datastore (secondary) with Cloud SQL (primary).
* Save progress
* Revert test changes
* Add pipeline launching
* Fix create/update timestamp replay problems
When CreateAutoTimestamp and UpdateAutoTimestamp are inserted into a
Transaction, their values are not populated in the same way as when they are
stored in the course of an SQL commit. This results in different timestamp
values between SQL and datastore during the SQL -> DS replay.
Fix this by providing these values from the JPA transaction time when we're
doing transaction serialization.
This change also removes the initialization of the Ofy clock in
ExpandRecurringBillingEventsActionTest. It's not necessary as the
ReplayExtension already takes care of this and doing it after the
ReplayExtension as we were breaks a test now that the update timestamps are
correct.
* Remove ReportingUtils and use CloudTaskUtil to enqueue
* Use schedule time helper to enqueue and update schedule time comparison
* Fix comment, indentation in gradle file and improve time comparison
* Change from TaskQueueUtils to CloudTasksUtils in LoadTestAction
* Put X_CSRF_TOKEN in task headers
* Fix schedule time and gradle issue
* Remove TaskQueue constant dependency
* Double run seconds
* Add comment for X_CSRF_TOKEN
* Fix flaky RdeStagingActionDatastoreTest
Fixed the most common cause that makes one method flaky (Clock and
timestamp problem). Added a TODO to rethink test case.
Also added notes on tasks potentially enqueued multiple times.
* Add an index on Host.host_name column
This field is queried during host creation and needs an index to speed
up the query.
Since Hibernate does not explicitly refer to indexes, we can change the
code and schema in one PR.
* Use the built-in replicaJpaTm() in RDAP
This includes a test for the replica-simulating transaction manager and
removal of any replica-specific code in RDAP tests, because it's
unnecessary due to the existing tests.
* Add DS validation to match Cloud DNS
* Add checks to flows
* Add some flow tests
* Add tests for DomainCreateFlow
* Add tests for UpdateDomainCommand
* Fix docs test
* Small fixes
* Remove builder from tests
Standard mode will determine the watermarks based on the cursors and
kick off subsequent uploading steps. In order to run both the Beam and
the Mapreduce pipeline in parallel, we need to allow setting the beam
parameter when in standard mode. This changes should have been part of
https://github.com/google/nomulus/pull/1500.
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The cached methods are only used in situations where we don't really
care about being 100% synchronously up to date (e.g. whois), and they're
not used frequently anyway, so it's safe to use the replica in these
locations.
* Compare migration data with SQL as primary DB
Add a BEAM pipeline that compares the secondary Datastore against SQL.
This is a dumb pipeline to be launched by a driver (in a followup PR).
Manually tested pipeline in sandbox.
Also updated the ValidateSqlPipeline and the snapshot finder class so
that an appropriate Datastore export is found (one that ends before the
replay checkpoint value).
We can use it more places later but this can serve as a template. We
should inject the connection to the read-only replica (only created
once) to the constructor of the action, then use that instead of the
regular transaction manager.
We add a transaction manager that simulates the read-only-replica
behavior for testing purposes as well.
In addition, we set the transaction isolation level to READ COMMITTED
for this transaction manager (this is fine since we're never writing to
it). Postgres requires this for replica SQL access (it fails if we try
to use SERIALIZABLE) transactions. We didn't see this with the pipelines
before since those already had transaction isolation level overrides
* CommitLog handling code should call ofyTm
The tm() call will use JPA transaction manager after the switch-over to
SQL. These calls would lose their transaction semantics.
Both actions are to be invoked after the switchover in case we have to
switch back to Datastore as primary.
* Only compare recent changes in Datastore and SQL
When comparing Datastore and SQL, ignore older History and EPP resource
objects. This cuts the run time in half compared with a full comparison.
The intention is to run a full comparison before the switch-over from
Datastore and SQL, and run this incremental comparison during the down
time.
The incremental comparison takes about 25 minutes in production.
Performance can be improved further by filtering out older billing
events (OneTime and Cancellation). However, we don't think further
optimization is worth the effort (considering that Recurring events
cannot be filtered since they are mutable but without lastUpdateTime).
Verified in Sandbox and prod with and without time filter.
We already have ValidateEscrowDepositCommand to check for internal
reference consistency of two deposits, i. e. making sure that all
contacts and hosts referenced by domains exist in the same deposit.
Therefore to compare whether two deposits are equal we only need to make
sure that they contain the same domains and registrars, assuming they
both pass the validation. We don't compare their contents directly
because the MapReduce deposit contains all contacts and domains whereas
the Beam deposit only contains referenced ones, making a direct
comparison impossible.
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