This includes renaming the billing classes to match the SQL table names,
as well as splitting them out into their own separate top-level classes.
The rest of the changes are mostly renaming variables and comments etc.
We now use `BillingBase` as the name of the common billing superclass,
because one-time events are called BillingEvents
Because we need to check if a contact history is the most recent for its
underlying contact resource, the query-wipe out-repeat loop no longer works
ideally due to the added overhead with the query.
Instead, we refactor the logic into a Beam pipeline where the query only
needs to be performed once and history entries eligible for wipe out are
handled individually in their own transforms. Because history entries
are otherwise immutable, we can run the pipeline in relatively relaxed
repeatable read isolation level. We also do not worry about batching for
performance, as we do not anticipate this operation to put a lot of
strains on the particular table.
This will replace the ExpandRecurringBillingEventsAction, which has a
couple of issues:
1) The action starts with too many Recurrings that are later filtered out
because their expanded OneTimes are not actually in scope. This is due
to the Recurrings not recording its latest expanded event time, and
therefore many Recurrings that are not yet due for renewal get included
in the initial query.
2) The action works in sequence, which exacerbated the issue in 1) and
makes it very slow to run if the window of operation is wider than
one day, which in turn makes it impossible to run any catch-up
expansions with any significant gap to fill.
3) The action only expands the recurrence when the billing times because
due, but most of its logic works on event time, which is 45 days
before billing time, making the code hard to reason about and
error-prone. This has led to b/258822640 where a premature
optimization intended to fix 1) caused some autorenwals to not be
expanded correctly when subsequent manual renews within the autorenew
grace period closed the original recurrece.
As a result, the new pipeline addresses the above issues in the
following way:
1) Update the recurrenceLastExpansion field on the Recurring when a new
expansion occurs, and narrow down the Recurrings in scope for
expansion by only looking for the ones that have not been expanded for
more than a year.
2) Make it a Beam pipeline so expansions can happen in parallel. The
Recurrings are grouped into batches in order to not overwhelm the
database with writes for each expansion.
3) Create new expansions when the event time, as opposed to billing
time, is within the operation window. This streamlines the logic and
makes it clearer and easier to reason about. This also aligns with
how other (cancelllable) operations for which there are accompanying
grace periods are handled, when the corresponding data is always
speculatively created at event time. Lastly, doing this negates the
need to check if the expansion has finished running before generating
the monthly invoices, because the billing events are now created not
just-in-time, but 45 days in advance.
Note that this PR only adds the pipeline. It does not switch the default
behavior to using the pipeline, which is still done by
ExpandRecurringBillingEventsAction. We will first use this pipeline to
generate missing billing events and domain histories caused by
b/258822640. This also allows us to test it in production, as it
backfills data that will not affect ongoing invoice generation. If
anything goes wrong, we can always delete the generated billing events
and domain histories, based on the unique "reason" in them.
This pipeline can only run after we switch to use SQL sequence based ID
allocation, introduced in #1831.
Some retriers are no longer needed because transactions are
automatically retried by the JPA transaction manager when there's a
transient exception.
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So long, farewell, adios, ciao, sayonara, 再见!
TESTED=deployed to alpha and used `nomulus list_tlds` to confirm that the web app can receive and serve requests.
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* Fix Gradle dependency version pinning
In Gradle 7, version labels require '!!' at the end to be free from
any forced upgrade.
Hibernate min version needs to be advanced past 5.6.12, which is buggy.
Upgraded most dependencies to the latest version.
* Remove Cloud KMS from Nomulus Server
Removed Cloud KMS from the Nomulus (:core) since it is no longer used.
Renamed remaining classes to reflect their use of the SecretManager.
Updated the config instructions to use a new codename for the keyring:
KMS to CSM. This PR works with both codenames. Will drop 'KMS' after
the internal repo is updated.
This runs over all domains that weren't deleted as of September 5. This
will fix most of b/248112997, which is itself caused by b/245940594 --
creating synthetic history objects means that the RDE pipeline will look
at those instead of the potentially-no-longer-valid data in the old
history objects.
* Convert to gradle 7.
* More fixes, regenerated lockfiles.
* Update lockfiles for dependency update.
* Fix show_upgrade_diff for new lockfile format
* Add property for allowInsecureProtocol
Allow us to override the restriction against use of plain HTTP for
communication to dependency repositories. We need this to be able to use a
local proxy for dependency gathering.
* Checking in missing gradle.lockfile
Fortunately this no longer requires a log-in, we can just send a GET
request and receive a CSV result in return.
This also adds the apache-commons CSV parser to the dependencies
See https://b.corp.google.com/issues/237784559 for more details
This includes:
- deletion of helper DB methods in tests
- deletion of various old Datastore-only classes and removal of any
endpoints
- removal of the dual-database test concept
- removal of 'ofy' from the AppEngineExtension
One of the more significant changes introduced in this PR is that we use
SQL as the backing database in all tests unless otherwise specified,
e.g. by using the TmOverrideExtension. We change various ofy-related
tests to use this.
This includes various changes:
- Deletion of SqlEntity/DatastoreEntity and related classes. Includes
any necessary changes because of that (e.g. getting a nice SQL key on
error in RegistryJpaIO).
- Deletion of classes that used libraries from the init-sql code
(RefreshDnsOnHostRenameAction)
- Removal of the JpaTransactionManager's backup implementation
- Modification of RegistryJpaWriteTest to not use init-sql code
- Removal of the Transaction class and related classes, however it does
not remove the TransactionEntity class as that would require DB
changes
- Removal of anything related to the actual usage of the database
migration schedule or read-only phases
- Various test changes and fixes to account for the differences in SQL
(like how foreign keys need to exist)
This deliberately doesn't do anything to alter the objects actually
stored in the DB yet, just how we use them
This includes:
- removing the actions that do the replay
- removing the tests for the replay
- removing the ReplayExtension and adjusting the various tests that used
it appropriately
- removing functionality relating to "things that happen during replay",
e.g. beforeSqlSaveOnReplay
This does not include:
- removing the InitSqlPipeline or similar tasks
- removing e.g. SqlEntity (it's used in other places)
- removing Transforms/RegistryJpaIO and other SQL-pipeline-creation code
This included removing ofy-specific code from various tests. Also, some
of the other tests (e.g. RdapDomainActionTest) had to be configured to
use only SQL -- otherwise, as it currently stands, they were trying to
use ofy.
We also delete the CreateSyntheticHistoryEntriesAction and pipeline
because they're no longer relevant, and impossible to test (the goal of
the actions were to create objects in ofy which doesn't happen any
more).
* Create a Dataflow pipeline to resave EPP resources
This has two modes.
If `fast` is false, then we will just load all EPP resources, project them to the current time, and save them.
If `fast` is true, we will attempt to intelligently load and save only resources that we expect to have changes applied when we project them to the current time. This means resources with pending transfers that have expired, domains with expired grace periods, and non-deleted domains that have expired (we expect that they autorenewed).
* Begin migration from Guava Cache to Caffeine
Caffeine is apparently strictly superior to the older Guava Cache (and is even
recommended in lieu of Guava Cache on Guava Cache's own documentation).
This adds the relevant dependencies and switch over just a single call site to
use the new Caffeine cache. It also implements a new pattern, asynchronously
refreshing the cache value starting from half of our configuration time. For
frequently accessed entities this will allow us to NEVER block on a load, as it
will be asynchronously refreshed in the background long before it ever expires
synchronously during a read operation.
* 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.
* 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
* 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 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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This version of Beam does not have an explicit dependency on log4j.
There are a couple of other things that need to change due to the
upgrade.
1) The new version pulls in a dependency that is not on Maven Central
but on packages.confluent.io, so we need to explicitly add this repo.
2) The new version has a dependency on flogger 0.6 anb above , which removed
the LoggerConfig class (see google/flogger#142).
We therefore backported the class. In the long term we should do what
was suggested in the issue and use the normal JDK Logger config
directly.
3) The intSqlPipeline dependency graph also needs to be updated.
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* Validate SQL with Datastore being primary
Validates the data asynchronously replicated from Datastore to SQL.
This is a short term tool optimized for the current production database.
Tested in production.
BSD sed requires a parameter to -i to indicate the backup suffix. By
adding a blank suffix the sed command works on both Linux and macOS.
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* Add a beam pipeline to create synthetic history entries in SQL
The logic is mostly lifted from CreateSyntheticHistoryEntriesAction. We
do not need to test for the existence of an embedded EPP resource in the
history entry before create a synthetic one because after
InitSqlPipeline runs it is guaranteed that no embedded resource exists.
This PR adds the final step in RDE pipeline (enqueueing the next action
to Cloud Tasks) and makes some necessary changes, namely by making all
CloudTasksUtils related classes serializable, so that they can be used
on Beam.
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* Make :core:cleanTest depend on FilterTests
The "cleanTest" target doesn't work for our specialized tests derived from
FilterTest. Make them all explicit dependencies of cleanTest so we can reset
the tests from a single target.
* Fix javadoc problems with SoyInfo and subprojects
The *SoyInfo.java files generated by the soy compiler contain deprecation
warnings with links to files that are not imported. This causes a javadoc
warning. Temporarily fix this by replacing the link tags with "LINK". This
also allows us to remove the exclusion of these files, which is a bit nicer.
Also disable javadoc tasks from subprojects. These just break because they
don't have access to the legacy javadoc classes in the root.
* Implement a util class to manage push queues using Cloud Tasks API
Push queues were part of App Engine when they debuted. As a result the
Task Queue API were part of the App Engine SDK and can only be used in
App Engine classic runtime. The new Cloud Tasks API can be used in any
runtime but it only supports push queues. In this PR we implement a util
class (CloudTasksUtils) like TaskQueueUtils to handle enqueuing tasks to
push queues using Cloud Tasks. One action (TldFanoutAction) was
converted to use the new API as a demo. Mass migration of other call sites of
the old API will follow in a separate PR.
TESTED=deployed to alpha and verified that tasks are corrected enqueued
and executed.
* Remove KmsSecret model entities
Now that we have been using the SecretManager for almost a month now,
remove the KmsSecret and KmsSecretRevision entities from Java code base.
A follow-up PR will drop the relevant tables in the schema.
Also removed a few unused classes in the beam package.
The API provided by the GAE SDK will not be available outside GAE
runtime. This presents a problem when we migrate off of GAE. More
pressingly, the RDE pipeline migration to Beam requires that we write to
GCS on GCE. Previously we were able to sidestep the issue by delegating
the writes to FileIO provided by Beam, which knows how to write to GCS.
However the RDE pipeline cannot use FileIO directly as it needs to write
to multiple files in one go and explicit use of GCS API is needed.
An unfortunate side effect of the API migration is that the new testing
library contains a bug which makes serializing GcsUtils impossible. It
is fixed upstream but not released yet. The fix has been backported for
the time being.
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This is the first part of the RdeStagingAction SQL migration where the
mapper logic is implemented in Beam.
A few helper methods are added to convert the DomainContent, HostBase
and ContactBase to their respective terminal child classes. This is
necessary and possible because the child classes do not have extra
fields and the base classes exist only to be embedded to other entities
(such as the various HistoryEntry entities). The conversion is necessary
because most of our code expects the terminal classes, such as the
RdeMarshaller's various marshallXXX() methods. The alternative would be
to change all the call sites, which seems to be much more disruptive.
Unfortunately there is is no good way to do this conversion than just
creating a builder and setting every fields there is.
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* Support testing SQL -> DS replication in ReplayExt
Support testing of Postgres -> Datastore replication in the ReplayExtension
when running in SQL mode in a DualDatabaseTest.
This is currently only enabled for one test (HostInfoFlowTest) since this form
of replication is likely to be problematic in many cases.
As part of this change:
- Add a thread-local flag so that we don't attempt to do certain data
transformations when serializing entities for storage in a Transaction
record. (These typically need to be called in a datastore transaction).
- Replace tm() in datastore translators with ofyTm() (these should only be
called from within an ofy transaction) and also in the replay system itself.
- Add a transactWithoutBackup() method for use within the replay itself.
- Prevent replication of entities that are not intended to be replicated.
- Make some of the ReplicateToDatastoreAction methods public so we can invoke
them from ReplayExtension.
- Change the way that the test type is stored in the extension context in a
DualDatabaseTest so that we can check for it from the ReplayExtension.
* Limit number of tests and show output
Trying to debug why these are failing in kokoro.
* Move HostInfoFlowTest to fragile for now
The test now manipulates a globel variable that causes problems for other
tests. There's likely a better fix for this, but for purposes of this PR we
can just move it to "fragile."
* Fix a few more problems
- "replay" flag should have been initialized to false -- as it stands,
replay wasn't happening.
- disable "always save with backup" in the datastore helper, we were
apparently getting some unwanted commit log entries that were causing
timestamp inversions in other tests. Also clear out the replay queue
just for good hygiene.
- Check for a null replicator in replayToOfy before proceeding.
- Use a local inOfyContext flag to track whether we're in ofy context, as
the tm() function is less reliable in dual-database tests.
This is useful when we expect a specific subtype in the return value so
that we can set the parent resource (e. g. DomainContent for
DomainHistory) on it, or when a specific subtype is needed from the call
site.
This PR also fixes some use of generic return values. It is always better to
return <HistoryEntry> than a wildcard <? extends HistoryEntry>, because for
immutable collections, <? extends HistoryEntry> is no different than
<HistoryEntry> as return value -- you can only get a HistoryEntry from it.
The wildcard return value means that even if you are indeed getting a
<DomainHistory> from the query, the call site has no compile time knowledge of
it and can only assume it is a <HistoryEntry>.
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* Update GCL dependency to avoid security alert
This required a few changes in addition to the dependency update.
- a few transitive / required dependency updates as well
- updating soyutils_usegoog.js and adding checks.js because they're
necessary as part of the Soy compilation process
- Using a trustedResourceUri in the buildSrc Soy compilation instead of
a string
- changing the arguments to the Soy-to-Java compiler to comply with the
new version
- Moving all Soy UI files to be in the registrar directory. This was
not the case before due to previous thinking that we'd have separate
admin and registrar consoles -- this is no longer the case so it's no
longer necessary. This necessitated various refactorings and reference
changes.
- The new soy-to-javascript compiler requires this, as it removes the
"deps" param that we were previously using to say "use the general UI
utils as dependencies for the registrar-console files".
- Creating a SQL environment and loading test data in the test server
main method -- previously, the local test server did not work.
- Fix some JS code that was referencing now-deleted library functions
- Removal of the Karma tests, as the karma-closure library hasn't been
updated since 2018 and it no longer works. We never noticed any errors
from the Karma tests, we never change the JS, and we have the
Java+Selenium screenshot differ tests to test the UI anyway.
This also forces the karma test to use the Gradle-installed version of
node instead of the global version. The global version installed on the
Kokoro machines is too old to function with some of the newer libraries.
This is similar to the migration of the spec11 pipeline in #1073. Also removed
a few Dagger providers that are no longer needed.
TESTED=tested the dataflow job on alpha.
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