Cassandra Plugins for Akka Persistence

Replicated Akka Persistence journal and snapshot store backed by Apache Cassandra.

Dependencies

Latest release

To include the latest release of the Cassandra plugins for Akka 2.5.x into your sbt project, add the following lines to your build.sbt file:

libraryDependencies += Seq(
  "com.typesafe.akka" %% "akka-persistence-cassandra" % "0.80-RC3",
  "com.typesafe.akka" %% "akka-persistence-cassandra-launcher" % "0.80-RC3" % Test
)

This version of akka-persistence-cassandra depends on Akka 2.5.6. It has been published for Scala 2.11 and 2.12. The launcher artifact is a utility for starting an embedded Cassandra, useful for running tests. It can be removed if not needed.

To include the latest release of the Cassandra plugins for Akka 2.4.x into your sbt project, add the following lines to your build.sbt file:

libraryDependencies += "com.typesafe.akka" %% "akka-persistence-cassandra" % "0.30"

This version of akka-persistence-cassandra depends on Akka 2.4.20. It has been published for Scala 2.11 and 2.12.

Those versions are compatible with Cassandra 3.0.0 or higher, and it is also compatible with Cassandra 2.1.6 or higher (versions < 2.1.6 have a static column bug) if you configure cassandra-journal.cassandra-2x-compat=on in your application.conf.

Journal plugin

Features

• All operations required by the Akka Persistence journal plugin API are fully supported.
• The plugin uses Cassandra in a pure log-oriented way i.e. data are only ever inserted but never updated (deletions are made on user request only).
• Writes of messages are batched to optimize throughput for persistAsync. See batch writes for details how to configure batch sizes. The plugin was tested to work properly under high load.
• Messages written by a single persistent actor are partitioned across the cluster to achieve scalability with data volume by adding nodes.
• Persistence Query support by CassandraReadJournal

Configuration

To activate the journal plugin, add the following line to your Akka application.conf:

akka.persistence.journal.plugin = "cassandra-journal"

This will run the journal with its default settings. The default settings can be changed with the configuration properties defined in reference.conf:

Caveats

• Detailed tests under failure conditions are still missing.
• Range deletion performance (i.e. deleteMessages up to a specified sequence number) depends on the extend of previous deletions
  • linearly increases with the number of tombstones generated by previous permanent deletions and drops to a minimum after compaction
• For versions prior to 0.80 events by tag uses Cassandra Materialized Views which are a new feature that has yet to stabilise Use at your own risk, see here for a recent discussion on the Cassandra dev mailing list. Version 0.80 and on migrated away from Materialized Views and maintain a separate table for events by tag queries.

These issues are likely to be resolved in future versions of the plugin.

Snapshot store plugin

Features

• Implements the Akka Persistence snapshot store plugin API.

Configuration

To activate the snapshot-store plugin, add the following line to your Akka application.conf:

akka.persistence.snapshot-store.plugin = "cassandra-snapshot-store"

This will run the snapshot store with its default settings. The default settings can be changed with the configuration properties defined in reference.conf:

Persistence Queries

It implements the following Persistence Queries:

• persistenceIds, currentPersistenceIds
• eventsByPersistenceId, currentEventsByPersistenceId
• eventsByTag, currentEventsByTag

Persistence Query usage example to obtain a stream with all events tagged with "someTag" with Persistence Query:

val queries = PersistenceQuery(system).readJournalFor[CassandraReadJournal](CassandraReadJournal.Identifier)
queries.eventsByTag("someTag", Offset.noOffset)

Cleanup of tag_views table

By default the tag_views table keeps tagged events indefinitely, even when the original events have been removed. Depending on the volume of events this may not be suitable for production.

Before going live decide a time to live (TTL) and, if small enough, consider using the Time Window Compaction Strategy. See events-by-tag.time-to-live in reference.conf for how to set this.

Migrations

Migrations to 0.80-RC3

0.80 introduces a completely different way to manage tags for events.

It is very important that you test this migration in a pre-production environment as once you drop the materialized view and tag columns you can not roll back.

Most of the migration can be done while the old version of your application is running. The remaining steps happen automatically when a persistent actor is recovered which may slow down actor recovery but only by a small amount if you follow the offline steps.

The EventsByTagMigration class provides a set of tools to assist in the migration.

The first two are schema changes that should be performed once on a single node and can be done while your application is running with the old version of this plugin:

• createTables creates the two new tables required
• addTagsColumn adds a set<text> column to the messages table

For example you could put the following in a main method to do the schema migrations:

val system = ActorSystem()

val migrator = EventsByTagMigration(system)

val schemaMigration: Future[Done] = for {
  _ <- migrator.createTables()
  done <- migrator.addTagsColumn().recover { case i: ExecutionException if i.getMessage.contains("conflicts with an existing column") => Done}
} yield done

The recover makes the adding of the tags column idempotent as cql does not include a IF NOT EXISTS for adding a column

Next is the data migration into a new table that stores events indexed by tag. This will be a slow process as it needs to scan over all existing events. It can be run while your application is running but beware that it will produce a lot of writes to your C* cluster so should be done during a quiet period.

• migrateToTagViews scans over all your persistence ids and writes the tagged events to the tag_views table. At the same time it keeps track of its progress in the tag_write_progress table so if this were to fail due to say a C* issue you can resume and it won't start from scratch.
• If you have an efficient way of getting all the persistenceIds pass them into this method. Otherwise a select distinct query is used which is likely to time out. You can also use this method to stagger your migration.

You do not need to worry if a small number of events are missed by migrateToTagViews as they will be fixed during your PersistentActor recovery. However do not rely on this for full migration as only active PersistentActors will be recovered and it will mean the start up time for your PersistentActors will be very long.

After you have migrated your data you can now remove the materialized view and tagN columns from the messages table. It is highly recommended you do this as maintaining a materialized view is expensive and uses a large amount of capacity in your cluster:

• Drop the materialized view

DROP MATERIALIZED VIEW akka.eventsbytag;

• Drop the tag columns on the messages table

ALTER TABLE akka.messages DROP tag1;
ALTER TABLE akka.messages DROP tag2;
ALTER TABLE akka.messages DROP tag3;

Note that the new tags column won't be back filled for old events. This won't affect your eventsByTag queries as they come from a different table. This column is used for recovering any missed writes to the tag_views table when running persistent actors with the new version.

The following configuration changes. See reference.conf for full details:

• pubsub-minimum-interval has been removed. If using DistributedPubsub notifications for tag writes then set pubsub-notification to on
• delayed-event-timeout has been replaces by events-by-tag.gap-timeout with the restriction removed that all events have to be tagged.
• first-time-bucket format has changed to: yyyyMMddTHH:mm e.g. 20151120T00:00
• eventual-consistency has been removed. It may be re-added see #263

Migrations from 0.54 to 0.59

In version 0.55 additional columns were added to be able to store meta data about an event without altering the actual domain event.

The new columns meta_ser_id, meta_ser_manifest, and meta are defined in the new journal table definition and new snapshot table definition.

You can add the to existing tables by executing the following in cqlsh:

alter table akka.messages add meta_ser_id int;
alter table akka.messages add meta_ser_manifest text;
alter table akka.messages add meta blob;
alter table akka_snapshot.snapshots add meta_ser_id int;
alter table akka_snapshot.snapshots add meta_ser_manifest text;
alter table akka_snapshot.snapshots add meta blob;

These columns are used when the event is wrapped in akka.persistence.cassandra.EventWithMetaData or snapshot is wrapped in akka.persistence.cassandra.SnapshotWithMetaData. It is optional to alter the table and add the columns. It's only required to add the columns if such meta data is used.

It is also not required to add the materialized views, not even if the meta data is stored in the journal table. If the materialized view is not changed the plain events are retrieved with the eventsByTag query and they are not wrapped in EventWithMetaData. Note that Cassandra does not support adding columns to an existing materialized view.

If you don't alter existing messages table and still use tables-autocreate=on you have to set config:

cassandra-journal.meta-in-events-by-tag-view = off

When trying to create the materialized view (tables-autocreate=on) with the meta columns before corresponding columns have been added the messages table an exception "Undefined column name meta_ser_id" is raised, because Cassandra validates the "CREATE MATERIALIZED VIEW IF NOT EXISTS" even though the view already exists and will not be created. To work around that issue you can disable the meta columns in the materialized view by setting meta-in-events-by-tag-view=off.

Migrations from 0.51 to 0.52

CassandraLauncher has been pulled out into its own artifact, and now bundles Cassandra into a single fat jar, which is bundled into the launcher artifact. This has allowed Cassandra to be launched without it being on the classpath, which prevents classpath conflicts, but it also means that Cassandra can't be configured by changing files on the classpath, for example, a custom logback.xml in src/test/resources is no longer sufficient to configure Cassandra's logging. To address this, CassandraLauncher.start now accepts a list of classpath elements that will be added to the classpath, and provides a utility for locating classpath elements based on resource name.

To depend on the new CassandraLauncher artifact, remove any dependency on cassandra-all itself, and add:

"com.typesafe.akka" %% "akka-persistence-cassandra-launcher" % "0.52"

to your build. To modify the classpath that Cassandra uses, for example, if you have a logback.xml file in your src/test/resources directory that you want Cassandra to use, you can do this:

CassandraLauncher.start(
   cassandraDirectory,
   CassandraLauncher.DefaultTestConfigResource,
   clean = true,
   port = 0,
   CassandraLauncher.classpathForResources("logback.xml")
)

Migrations from 0.23 to 0.50

The Persistence Query API changed slightly, see migration guide for Akka 2.5.

Migrations from 0.11 to 0.12

Dispatcher configuration was changed, see reference.conf:

Migrations from 0.9 to 0.10

The event data, snapshot data and meta data are stored in a separate columns instead of being wrapped in blob. Run the following statements in cqlsh:

drop materialized view if exists akka.eventsbytag1;
drop materialized view if exists akka.eventsbytag2;
drop materialized view if exists akka.eventsbytag3;
alter table akka.messages add writer_uuid text;
alter table akka.messages add ser_id int;
alter table akka.messages add ser_manifest text;
alter table akka.messages add event_manifest text;
alter table akka.messages add event blob;
alter table akka_snapshot.snapshots add ser_id int;
alter table akka_snapshot.snapshots add ser_manifest text;
alter table akka_snapshot.snapshots add snapshot_data blob;

Migrations from 0.6 to 0.7

Schema changes mean that you can't upgrade from version 0.6 for Cassandra 2.x of the plugin to the 0.7 version and use existing data without schema migration. You should be able to export the data and load it to the new table definition.

Migrating from 0.3.x (Akka 2.3.x)

Schema and property changes mean that you can't currently upgrade from 0.3 to 0.4 SNAPSHOT and use existing data without schema migration. You should be able to export the data and load it to the new table definition.