* 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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* Speed up updating of premium lists
There are two parts to this:
1. Don't load the premium entries in the command prompt (this isn't
necessary and we didn't display that information anyway).
2. Set a proper batch size (rather than just 1) when saving all the
premium entries. This means that we generate only one INSERT statement
rather than N statements.
* Allow usage of a read-only Postgres replica
This adds the Dagger provider code for both the regular and the BEAM
environments, which are similar but not quite the same.
In addition, this demonstrates usage of the replica DB in the
RdePipeline. I tested this on alpha with a modified version of the
RdePipeline that attempts to write some dummy values to the database and
it failed with the expected message that one cannot write to a replica.
* Resolve ResaveEntityAction related conflicts
* Replace string with existing constants
* Remove solved TODOs related to ofy string to new vkey string
* Add a TODO for clean up
* Fix missing annotation
* Make not logged in errors take precedence over extension errors
This is the right order to do the checks in, because if the registrar isn't
logged in (or their login failed) then they will have an empty set of declared
extensions, so any attempt to use an extension will throw a "Service
extension(s) must be declared at login" error. This is potentially misleading
because the actual error in this situation is that the registrar isn't logged
in at all.
This also fixes some flows that weren't declared final (but should be), or
methods declared final on final classes, which is superfluous.
* Don't throw errors when existing premium list is empty
This state is possible to get into when things go wrong and it shouldn't prevent
saving new revisions of the list. Note that it will continue to throw errors if
you attempt to save a new revision that is blank (which is usually a mistake).
See http://b/211774375
* Make premium list saving run as a single transaction
This fixes the bug where the new revision is saved, but then execution gets
halted for some reason (e.g. request timeout) before the entries finish saving,
which leaves the DB in a bad state with a new top revision containing zero
entries, thus making everything standard.
* Add pending action extension to server update poll messages
This is necessary for the poll messages to contain the necessary context
explaining what domain name the relevant statuses were being added/removed
to/from.
* Always use JPA TM on Beam
Beam does not have access to datastore. Using ofy on Beam always results
in an error. Normally we should use database migration state schedule to
determine which TM to use, but on Beam there's no point in doing so. By
hard-coding the TM on beam to be SQL we can start testing features before
we migrate to SQL mode, for example the new RDE pipeline.
Also made a change to where the manual deposits are stored. It made more
sense to store them under manual/[direcitory]/[jobname]/ instead of
[jobname]/manual/[directory]/.
TESTED=deployed the pipeline on production and ran a job.
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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* Ignore Prober related entities when comparing db
Deletion of prober entities are not propagated to SQL, resulting in two
types of mismatches: entity only exists in SQL, or copies of an entity
differ in deleteTime. Both cases should not count as erros.
* Make ImmutableObject.toString deterministic
Remove the identity hash from the output. There is no use case
(including debugging) for it.
Removing it allows us to also remove some overriding implementations in
subclasses, and may also simplify tests.
* Improve logging/comments for commit log forks
It looks like the diff file lister is doing a second constructDiffSequence()
when a commit diff file is missing from the final sequence for purely
informational purposes. However, this purpose wasn't clear when investigating
an actual case of this.
This PR adds another warning to hopefully make the log output a bit more
useful, and also promotes the "gap" log message to a warning and adds a
comment indicating the purpose of the second constructDiffSequence().
This adds two new options:
1) An option to run RDE in lenient mode.
2) An option to run RDE with the new Beam pipeline regardless of the datastore setting.
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