Right now - if there's an error during DnsWriter.publish*, all the publish from
before that error will be committed, while all the publish after that error
will not.
More than that - in some writers partial publishes can be committed, depending
on implementation.
This defines a new contract that publish* are only committed when .commit is
called. That way any error will simply mean no publish is committed.
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Created by MOE: https://github.com/google/moe
MOE_MIGRATED_REVID=165708063
Attending to this old bug will improve our ability to perform zone comparisons between Datastore and the DNS provider. Right now, zone comparison finds some bogus differences, because the TTL we send to the DNS subsystem doesn't match the TTL we use when generating our local dump files.
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Created by MOE: https://github.com/google/moe
MOE_MIGRATED_REVID=164635557
We're now using java_import_external instead of maven_jar. This allows
us to specify the relationships between jars, thereby allowing us to
eliminate scores of vendor BUILD files that did nothing but re-export
@foo//jar targets, thus addressing the concerns of djhworld on Hacker
News: https://news.ycombinator.com/item?id=12738072
We now have redundant failover mirrors, which is a feature I added to
Bazel 0.4.2 in ed7ced0018
A new standard naming convention is now being used for all Maven repos.
Those names are calculated from the group_artifact name using the
following algorithm that eliminates redundancy:
https://gist.github.com/jart/41bfd977b913c2301627162f1c038e55
The JSR330 dep has been removed from java targets if they also depend
on Dagger, since Dagger always exports JSR330.
Annotation processor dependencies should now be leaner and meaner, by
more appropriately managing what needs to be on the classpath at
runtime. This should trim down the production jar by >1MB. As it stands
currently in the open source world:
- backend_jar_deploy.jar: 50MB
- frontend_jar_deploy.jar: 30MB
- tools_jar_deploy.jar: 45MB
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Created by MOE: https://github.com/google/moe
MOE_MIGRATED_REVID=143487929
This change replaces all Ref objects in the code with Key objects. These are
stored in datastore as the same object (raw datastore keys), so this is not
a model change.
Our best practices doc says to use Keys not Refs because:
* The .get() method obscures what's actually going on
- Much harder to visually audit the code for datastore loads
- Hard to distinguish Ref<T> get()'s from Optional get()'s and Supplier get()'s
* Implicit ofy().load() offers much less control
- Antipattern for ultimate goal of making Ofy injectable
- Can't control cache use or batch loading without making ofy() explicit anyway
* Serialization behavior is surprising and could be quite dangerous/incorrect
- Can lead to serialization errors. If it actually worked "as intended",
it would lead to a Ref<> on a serialized object being replaced upon
deserialization with a stale copy of the old value, which could potentially
break all kinds of transactional expectations
* Having both Ref<T> and Key<T> introduces extra boilerplate everywhere
- E.g. helper methods all need to have Ref and Key overloads, or you need to
call .key() to get the Key<T> for every Ref<T> you want to pass in
- Creating a Ref<T> is more cumbersome, since it doesn't have all the create()
overloads that Key<T> has, only create(Key<T>) and create(Entity) - no way to
create directly from kind+ID/name, raw Key, websafe key string, etc.
(Note that Refs are treated specially by Objectify's @Load method and Keys are not;
we don't use that feature, but it is the one advantage Refs have over Keys.)
The direct impetus for this change is that I am trying to audit our use of memcache,
and the implicit .get() calls to datastore were making that very hard.
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Created by MOE: https://github.com/google/moe
MOE_MIGRATED_REVID=131965491
