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| <h5 class="page-header text-uppercase">Documentation |
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| <h1 id="aurora-scheduler-storage">Aurora Scheduler Storage</h1> |
| |
| <ul> |
| <li><a href="#overview">Overview</a></li> |
| <li><a href="#reads-writes-modifications">Reads, writes, modifications</a> |
| |
| <ul> |
| <li><a href="#read-lifecycle">Read lifecycle</a></li> |
| <li><a href="#write-lifecycle">Write lifecycle</a></li> |
| </ul></li> |
| <li><a href="#atomicity-consistency-and-isolation">Atomicity, consistency and isolation</a></li> |
| <li><a href="#population-on-restart">Population on restart</a></li> |
| </ul> |
| |
| <h2 id="overview">Overview</h2> |
| |
| <p>Aurora scheduler maintains data that need to be persisted to survive failovers and restarts. |
| For example:</p> |
| |
| <ul> |
| <li>Task configurations and scheduled task instances</li> |
| <li>Job update configurations and update progress</li> |
| <li>Production resource quotas</li> |
| <li>Mesos resource offer host attributes</li> |
| </ul> |
| |
| <p>Aurora solves its persistence needs by leveraging the Mesos implementation of a Paxos replicated |
| log <a href="https://ramcloud.stanford.edu/~ongaro/userstudy/paxos.pdf">[1]</a> |
| <a href="http://en.wikipedia.org/wiki/State_machine_replication">[2]</a> with a key-value |
| <a href="https://github.com/google/leveldb">LevelDB</a> storage as persistence media.</p> |
| |
| <p>Conceptually, it can be represented by the following major components:</p> |
| |
| <ul> |
| <li>Volatile storage: in-memory cache of all available data. Implemented via in-memory |
| <a href="http://www.h2database.com/html/main.html">H2 Database</a> and accessed via |
| <a href="http://mybatis.github.io/mybatis-3/">MyBatis</a>.</li> |
| <li>Log manager: interface between Aurora storage and Mesos replicated log. The default schema format |
| is <a href="https://github.com/apache/thrift">thrift</a>. Data is stored in serialized binary form.</li> |
| <li>Snapshot manager: all data is periodically persisted in Mesos replicated log in a single snapshot. |
| This helps establishing periodic recovery checkpoints and speeds up volatile storage recovery on |
| restart.</li> |
| <li>Backup manager: as a precaution, snapshots are periodically written out into backup files. |
| This solves a <a href="/documentation/0.6.0-incubating/storage-config/#recovering-from-a-scheduler-backup">disaster recovery problem</a> |
| in case of a complete loss or corruption of Mesos log files.</li> |
| </ul> |
| |
| <p><img alt="Storage hierarchy" src="../images/storage_hierarchy.png" /></p> |
| |
| <h2 id="reads-writes-modifications">Reads, writes, modifications</h2> |
| |
| <p>All services in Aurora access data via a set of predefined store interfaces (aka stores) logically |
| grouped by the type of data they serve. Every interface defines a specific set of operations allowed |
| on the data thus abstracting out the storage access and the actual persistence implementation. The |
| latter is especially important in view of a general immutability of persisted data. With the Mesos |
| replicated log as the underlying persistence solution, data can be read and written easily but not |
| modified. All modifications are simulated by saving new versions of modified objects. This feature |
| and general performance considerations justify the existence of the volatile in-memory store.</p> |
| |
| <h3 id="read-lifecycle">Read lifecycle</h3> |
| |
| <p>There are two types of reads available in Aurora: consistent and weakly-consistent. The difference |
| is explained <a href="#atomicity-and-isolation">below</a>.</p> |
| |
| <p>All reads are served from the volatile storage making reads generally cheap storage operations |
| from the performance standpoint. The majority of the volatile stores are represented by the |
| in-memory H2 database. This allows for rich schema definitions, queries and relationships that |
| key-value storage is unable to match.</p> |
| |
| <h3 id="write-lifecycle">Write lifecycle</h3> |
| |
| <p>Writes are more involved operations since in addition to updating the volatile store data has to be |
| appended to the replicated log. Data is not available for reads until fully ack-ed by both |
| replicated log and volatile storage.</p> |
| |
| <h2 id="atomicity-consistency-and-isolation">Atomicity, consistency and isolation</h2> |
| |
| <p>Aurora uses <a href="http://en.wikipedia.org/wiki/Write-ahead_logging">write-ahead logging</a> to ensure |
| consistency between replicated and volatile storage. In Aurora, data is first written into the |
| replicated log and only then updated in the volatile store.</p> |
| |
| <p>Aurora storage uses read-write locks to serialize data mutations and provide consistent view of the |
| available data. The available <code>Storage</code> interface exposes 3 major types of operations: |
| * <code>consistentRead</code> - access is locked using reader’s lock and provides consistent view on read |
| * <code>weaklyConsistentRead</code> - access is lock-less. Delivers best contention performance but may result |
| in stale reads |
| * <code>write</code> - access is fully serialized by using writer’s lock. Operation success requires both |
| volatile and replicated writes to succeed.</p> |
| |
| <p>The consistency of the volatile store is enforced via H2 transactional isolation.</p> |
| |
| <h2 id="population-on-restart">Population on restart</h2> |
| |
| <p>Any time a scheduler restarts, it restores its volatile state from the most recent position recorded |
| in the replicated log by restoring the snapshot and replaying individual log entries on top to fully |
| recover the state up to the last write.</p> |
| |
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| <p class="disclaimer">© 2014-2017 <a href="http://www.apache.org/">Apache Software Foundation</a>. Licensed under the <a href="http://www.apache.org/licenses/">Apache License v2.0</a>. The <a href="https://www.flickr.com/photos/trondk/12706051375/">Aurora Borealis IX photo</a> displayed on the homepage is available under a <a href="https://creativecommons.org/licenses/by-nc-nd/2.0/">Creative Commons BY-NC-ND 2.0 license</a>. Apache, Apache Aurora, and the Apache feather logo are trademarks of The Apache Software Foundation.</p> |
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