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.
* Add defaultPromoTokens to Registry
* Remove flyway files from this PR
* Fix merge conflicts
* Add back flyway file
* Add more info to error messages
* Change to a list
* Fix javadoc
* Change error message
* Add note to field declaration
Switch to using the login email address instead of GAE user ID to
identify console users. The primary use cases are:
1) When the user logged in the registrar console, need to figure out
which registrars they have access to (in
AuthenticatedReigstrarAccess).
2) When a user tries to apply a registry lock, needs to know if they
can (in RegistryLockGetAction).
Both cases are tested in alpha with a personal email address to ensure
it does not get the permission due to being a GAE admin account.
Also verified that the soy templates includes the hidden login email
form field instead of GAE user ID when registrars are displayed on the
console; and consequently when a contact update is posted to the server,
the login email is part of the JSON payload. Even though it does not
look like it is used in any way by RegistrarSettingsAction, which
receives the POST request. Like GAE user ID, the field is hidden, so
cannot be changed by the user from the console, it is also not used to
identify the RegistryPoc entity, whose composite keys are the contact
email and the registrar ID associated with it.
The login email address is backfilled for all RegistrarPocs that have a
non-null GAE user ID. The backfilled addresses converted to the same ID
as stored in the database.
This PR removes all Ofy related cruft around `HistoryEntry` and its three subclasses in order to support dual-write to datastore and SQL. The class structure was refactored to take advantage of inheritance to reduce code duplication and improve clarity.
Note that for the embedded EPP resources, either their columns are all empty (for pre-3.0 entities imported into SQL), including their unique foreign key (domain name, host name, contact id) and the update timestamp; or they are filled as expected (for entities that were written since dual writing was implemented).
Therefore the check for foreign key column nullness in the various `@PostLoad` methods in the original code is an no-op as the EPP resource would have been loaded as null. In another word, there is no case where the update timestamp is null but other columns are not.
See the following query for the most recent entries in each table where the foreign key column or the update timestamp are null -- they are the same.
```
[I]postgres=> select MAX(history_modification_time) from "DomainHistory" where update_timestamp is null;
max
----------------------------
2021-09-27 15:56:52.502+00
(1 row)
[I]postgres=> select MAX(history_modification_time) from "DomainHistory" where domain_name is null;
max
----------------------------
2021-09-27 15:56:52.502+00
(1 row)
[I]postgres=> select MAX(history_modification_time) from "ContactHistory" where update_timestamp is null;
max
----------------------------
2021-09-27 15:56:04.311+00
(1 row)
[I]postgres=> select MAX(history_modification_time) from "ContactHistory" where contact_id is null;
max
----------------------------
2021-09-27 15:56:04.311+00
(1 row)
[I]postgres=> select MAX(history_modification_time) from "HostHistory" where update_timestamp is null;
max
----------------------------
2021-09-27 15:52:16.517+00
(1 row)
[I]postgres=> select MAX(history_modification_time) from "HostHistory" where host_name is null;
max
----------------------------
2021-09-27 15:52:16.517+00
(1 row)
```
Also removed the ability to disable update timestamp auto update as it
was only needed during the migration.
Lastly, rectified the use of raw Coder in RegistryJpaIO.
Also fixed a bug introduced in #1785 where identity checked were performed instead of equality. This resulted in two sets containing the same elements not being regarded as equal and subsequent DNS updated being unnecessarily enqueued.
First, we create a sequence of User IDs in Postgres and assign it to the
User ID field, meaning that Hibernate can autogenerate IDs.
Next, add an update timestamp.
Next, add a constraint that we can't have multiple Users with the same
email address.
Finally, create a DAO since we'll usually want to query by that email
address (at least for now).
- Create a sequence to generate IDs for the user (this allows us to have
Long ID types so that Hibernate can autogenerate IDs)
- Add an update timestamp column so we can extend BackupGroupRoot
- Add a restriction that there can't be multiple users with the same
email address
* Add the PackagePromotion table
* Add long id
* Add NOT NULL
* fix formatting
* make package price non null
* Add not nulls to java file
* Fix broken tests from merge conflicts
Also deletes the autorenew poll message history revision id field in
Domain, which is only needed to recreate the ofy key for the poll
message. The column already contains null values in it, making it
impossible to depend on it. The column itself will be deleted from the
schema after this PR is deployed.
The logic to update autorenew recurrence end time is changed
accordingly: When a poll message already exists, we simply update the
endtime, but when it no longer exists, i. e. when it's deleted
speculatively after a transfer request, we recreate one using the
history entry id that resulted in its creation (e. g. cancelled or rejected
transfer).
This should fix b/240984498. Though the exact reason for that bug is
still unclear to me. Namely, it throws an NPE at this line during an
explicit domain transfer approval:
https://cs.opensource.google/nomulus/nomulus/+/master:core/src/main/java/google/registry/flows/domain/DomainFlowUtils.java;l=603;bpv=1;bpt=0;drc=ede919d7dcdb7f209b074563b3d449ebee19118a
The domain in question has a null autorenewPollMessageHistoryId, but
that in itself should not have caused an NPE because we are not
operating on the null pointer. On that line the only possible way to
throw an NPE is for the domain itself to be null, but if that were the
case, the NPE would have been thrown at line 599 where we called a
method on the domain object.
Regardless of the cause, with this PR we are using an explicitly
provided history id and checking for its nullness before using it. If a
similar issue arises again, we should have a better idea why.
Lastly, the way poll message id is constructed is largely simplified in
PollMessageExternalKeyConverter as a result of the removal ofy parent
keys in PollMessage. This does present a possibility of failure when
immediately before deployment, a registrar requests a poll message and
received the old id, but by the time the registrar acks the id, the new
version is deployed and therefore does not recognize the old key. The
likelihood of this happening should be slim, and we could have prevented
it by letting the converter recognize both the old and the new key.
However, we would like to eventually phase out the old key, and in
theory a registrar could ack a poll message at any time after it was
requested. So, there is not a safe time by which all the old ids are
acked, lest we develop some elaborate scheme to keep track of which
messages were sent with an old id when requested and which of these old
ids are acked. Only then can we be truly safe to phase out the old id.
The benefit does not seem to warrant the effort. If a registrar does
encounter a situation like this, they could open a support bug to have
us manually ack the poll message for them.
This PR turns out to be more massive than I would have liked but it
deals with all billing event related stuff, which are more or link all
intertwined:
* Remove all billing events as Ofy entities.
* Add a temporary annotation to allow BillingEvent's ID to be
auto-allocated by ofy while not lacking the Ofy @Id annotation.
* Remove Modification, which is only used in ofy.
* Remove BillingVKey, as we do not need to store the ofy key parent
information anymore. The VKey for a billing event now just contain
its primary key, and can be converted by VKeyConverter.
* Remove BigQuery related code in the billing pipeline.
Note that after BillingVKey is removed, several columns in
BillingCancellation are no longer needed. The change to database schema
will be handled in https://github.com/google/nomulus/pull/1721 after
this PR is deployed to production.
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* Flyway files for adding allocationToken column to Domain table
* Rename column to current_package_token
* Update er diagram
* Add foreign key to DomainHistory
This is, as of now, unused but we can use it for b/237683906 and
b/237800445 in the future to allow for special behavior dictated by
allocation tokens rather than having to reserve specific domains.
Note that we enforce a tied domain for ANCHOR_TENANT tokens (because
they should be matched to a domain) but not for BYPASS_TLD_STATE tokens.
This deletes LastSqlTransaction and ReplayGap in Datastore, as well as
SqlReplayCheckpoint and TransactionEntity in SQL. These are all related
to replay and are no longer used.
* Remove columns for unused ofy key reconstitution
Remove the columns in Domain, DomainHistory, GracePeriod and
GracePeriodHistory that were only used for Ofy key reconstitution.
All uses of these were removed in #1660.
* Add forgotten flyway file.
This removes the code that converts between ofy fields and SQL fields in DomainContent and a number of related core classes (basically anything that also needed modification to support the removal from DomainContent).
* Add a new recurrenceLastExpansion column to the BillingRecurrence table
This will be used to determine which recurrences are in scope for
expansion. Anything that has already been expanded within the past year is
automatically out of scope.
Note that the default value is set to just over a year ago, so that, initially,
everything is in scope for expansion, and then will gradually be winnowed down
over time so that most recurrences at any given point are out of scope. Newly
created recurrings (after the subsequent code change goes in) will have their
last expansion time set to the same as the event time of when the recurring is
written, such that they'll first be considered in-scope precisely one year
later.
* Use Gradle dependency dynamic versioning
Use dynamic versioning for Gradle dependencies when possible.
Please refer to go/dr-dependency-upgrade for more information about the
automation plan.
This PR calls out all dependencies that must be pinned to specific
versions for various reasons. The remaining ones are converted to
open-ended version ranges ("[version_str,)").
* Add new columns to BillingEvent.java
* Improve PR and modifyJodaMoneyType to handle null currency in override
* Add test cases for edge cases of nullSafeGet in JodaMoneyType
* Improve assertions
These are useful for the purposes of filtering by one-time/multi-use tokens, and
for determining which one-time tokens have been used (and if so, for which
domain).
* Add 3 more SQL indexes to the Host table
These indexes on creationTime, deletionTime, and currentSponsorRegistrarId are
present on the other two EPP resource tables (Domain and Contact), and are
useful for a wide variety of operations/analytics queries.
The query analyzer identified this is a missing index on the BillingEvent table,
and I added it for recurrences and cancellations as well as it's likely to be a
problem for them too. "Give me all the billing events associated with a given
domain by its repo ID" seems like a pretty common use case for the DB (and does
appear to be used by our invoicing pipeline).
This is a follow-up to PR #1545.
These indexes were identified as missing by PostgreSQL's query analyzer in our
sandbox environment (where we get enough realistic EPP traffic to identify these
deficiencies).
Note that a lot of the new indexes being named have to use the DB representation
of the column name because they are either embedded or subclassed entities,
whereas most of the existing ones are able to simply refer to Java field names.
This is the Java schema follow-up PR to PR #1541, which is what added the
actual DB changes through Flyway scripts.
* Reorganize new schema changes
Reorganized new schema changes and make each flyway script update a
single table.
Each flyway script is executed in a single database transaction so that
the script can be rolled back in one shot. It acquires a shared lock on
all tables touched by the script. This is deadlock-prone because in a
busy database, there may be user queries that attempt to lock the same
set of tables, but in different order. By limiting each script to one
table, we avoid the problem.
We should have some a presubmit check to enforce this rule.
All changes have been deployed to Sandbox out-of-band. When doing so,
we changed all CREATE INDEX statements to CREATE INDEX IF NOT EXISTS.
Future deployments should be able to proceed normally.
* Revise Host index on inet_addresses
The index on the 'inet_addresses array column should be of gin or gist
type, which index individual array elements. We use gin for now since
host updates are not often, and gin has better accuracy.
Since flyway script V108__... has not been deployed, we edit the file
in place instead of adding a new script.
This will be followed up with a modified query that can take advantage
of the gin index. Until then we don't expect to see performance
improvement.
The suspected bottlenect query in the whois path is:
select * from "Host" where 'non-ip-string' = any(inet_address) and
deletion_time < now();
It needs to be revised into:
select * from "Host" where array['non-ip-string'] <@ inet_address and
deletion_time < now();
The combined change reduces the query time from 90ms to 30ms in Sandbox,
and from 150ms to 40ms in production.
It is unclear if this solves all problem with whois latency.
