![Example Object and Aggregate Queries
• Lucene full text query
GET
/Email/Person/_query?q=FirstName:j*
AND
NOT
Office:[q
TO
z]
• Link path with filtering
GET
/Email/Message/_query?q=
Sender.WHERE(ReceiptDate>'2010-‐06-‐01').Address.Name="*.com"
• Quantifiers
GET
/Email/Message/_aggregate?m=COUNT(*)
&q=ANY(Recipients).ALL(Address).NONE(Person).Department:sales
&f=Tags,TOP(3,TRUNCATE(SendDate,DAY))
• Transitive links
GET
/Email/Person/_query?q=DirectReports^(3).LastName=wilson
&f=DirectReports(Name,DirectReports(Name))](https://image.slidesharecdn.com/overiewofcassandraanddoradus-140717094441-phpapp01/85/Overiew-of-Cassandra-and-Doradus-16-320.jpg)
Overiew of Cassandra and Doradus
- 1. Overview of Cassandra and The Doradus OSS Project Randy Guck Principal Engineer, Dell Software
- 2. Overview • What is No SQL? – Common RDB roadblocks – NoSQL database types • Overview of Cassandra – What's unique – Limitations • Doradus – Architecture – Features – The OLAP and Spider storage managers – What each is good for – Where to get Doradus
- 3. Why RDB Apps Look for Something Else • Performance – B-trees – Locking – One writable copy of each record • Scaling costs – RDBs scale "up" – Big boxes, SANs, fiber channel, etc. • What if you want... – Distributed access – No single points of failure – Instant failover – Sharding – Replication
- 4. NoSQL Data Models Data Model Examples Elastic? Queries? Relationships? Key–Value LevelDB, Kyoto Cabinet, Redis No No No Distributed Key– Value Dynamo, MemcacheDB, Riak, Voldemort Yes No No Column-Oriented Accumulo, Cassandra, HBase Yes Some No Document- Oriented Couchbase, Elasticsearch, MongoDB Yes Yes Some Graph Neo4J, OrientDB, Titan No Yes Yes Sharding + replication AND/OR/ranges/etc. Built-in support
- 5. NoSQL Data Models Data Model Examples Elastic? Queries? Relationships? Key–Value LevelDB, Kyoto Cabinet, Redis No No No Distributed Key– Value Dynamo, MemcacheDB, Riak, Voldemort Yes No No Column-Oriented Accumulo, Cassandra, HBase Yes Some No Document- Oriented Couchbase, Elasticsearch, MongoDB Yes Yes Some Graph Neo4J, OrientDB, Titan No Yes Yes Sharding + replication AND/OR/ranges/etc. Built-in support Doradus goals
- 6. NoSQL Common Traits • Distributed cluster of nodes – Commodity, shared-nothing servers – Scales horizontally – Expands elastically • Replication – Performant local access – Automatic failover • De-normalized data model • Schemaless/dynamic columns • Eventual consistency N=5, RF=3
- 7. Is NoSQL Catching On? Source: db-engines.com
- 8. Overview of Cassandra • Wide column NoSQL database • Open sourced by Facebook • Apache Project with active community • Commercially support by DataStax, Acunu, others • Used by 1,500+ companies • "Pure peer" architecture • Largest known Cassandra cluster: 300+ TB data and 400+ machines.
- 9. What is Cassandra best for? • Continuous data streams – Logs, events, audit records, measurements, ... – Fast data ingestion – Predictable read performance • Partitionable data – "1,000's of little databases in one" • Elastic scalability – Expand/upgrade/repair without downtime • Not good for: – Blob store – Persistent queue – OLTP transactions
- 10. CQL Static Table CREATE TABLE songs ( id uuid PRIMARY KEY, title text, album text, artist text, data blob ); CREATE INDEX ON songs (artist); Row Key Columns: "<column name>"="<column value>" 62c36... "album"="90125" "artist"="Yes" "data"=<audio> "title"="Changes" 837a2... "album"="Crystal Ball" "artist"="Styx" "data"=<audio> "title"="Put Me On" 2de83... "album"="Nevermind" "artist"="Nirvana" "data"=<audio> "title"="Breed" ...
- 11. CQL Clustered Table CREATE TABLE playlists ( id uuid, song_order int, song_id uuid, // copied from songs.id title text, // copied from songs.title album text, // copied from songs.album artist text, // copied from songs.artist PRIMARY KEY (id, song_order) // compound key ); Row Key Columns: "<song_order>:<column name>"="<column value>" 28d23... "1:"="" "1:album"="90125" "1:artist"="Yes" "1:song_id"="62c36..." "1:title"="Changes" "2:"="" "2:album"="Nevermind" "2:artist"="Nirvana" "2:song_id"="2de83..." "2:title"="Breed" "3:"="" ... 2ed91... "1:"="" "1:album"="Crystal Ball" "1:artist"="Styx" "1:song_id"="837a2..." "1:title"="Put Me On" "2:"="" ... ...
- 12. Row Key Columns: "<song_order>:<column name>"="<column value>" 28d23... "1:"="" "1:album"="90125" "1:artist"="Yes" "1:song_id"="62c36..." "1:title"="Changes" "2:"="" "2:album"="Nevermind" "2:artist"="Nirvana" "2:song_id"="2de83..." "2:title"="Breed" "3:"="" ... 2ed91... "1:"="" "1:album"="Crystal Ball" "1:artist"="Styx" "1:song_id"="837a2..." "1:title"="Put Me On" "2:"="" ... ... CQL Clustered Table (cont.) CQL "Rows" CREATE TABLE playlists ( id uuid, song_order int, song_id uuid, // copied from songs.id title text, // copied from songs.title album text, // copied from songs.album artist text, // copied from songs.artist PRIMARY KEY (id, song_order) // compound key );
- 13. Can we make Cassandra more appealing? • Data Model – No direct support for relationships • Indexing – Secondary indexes: single column only – Hash table only: no range searching • Searching – No joins, embedded queries – No aggregate queries – Limited equalities (e.g., SELECT * WHERE <key> IN (<list>)) – No full text search – No OR clauses – ...
- 14. What is Doradus? • Java service that enhances Cassandra • Adds features: – REST API (JSON and XML) – Multi-tenancy – Graph model – Multi-field/full text query language – Automatic data aging – OLAP and Spider storage services • Compatible with NoSQL tenets such as idempotent updates • Under development for ~3 years • Open source: Apache 2.0 License
- 15. Doradus Graph Model • A cluster hosts one of more applications • An application own tables which store objects • An object consists of single- and multi-valued fields • A pair of link fields form a bi-directional relationship Message {Size, SendDate} Participant {ReceiptDate} Address {Name} Person {Name, Department} Attachment {Size, Extension} Managerè çEmployees êPerson Address é êAttachments Messageé Recipientsè çMessageAsRecipient Addressè çParticipants Senderè çMessageAsSender
- 16. Example Object and Aggregate Queries • Lucene full text query GET /Email/Person/_query?q=FirstName:j* AND NOT Office:[q TO z] • Link path with filtering GET /Email/Message/_query?q= Sender.WHERE(ReceiptDate>'2010-‐06-‐01').Address.Name="*.com" • Quantifiers GET /Email/Message/_aggregate?m=COUNT(*) &q=ANY(Recipients).ALL(Address).NONE(Person).Department:sales &f=Tags,TOP(3,TRUNCATE(SendDate,DAY)) • Transitive links GET /Email/Person/_query?q=DirectReports^(3).LastName=wilson &f=DirectReports(Name,DirectReports(Name))
- 17. Doradus: Architecture Application Doradus Cassandra REST API Thrift or CQL Data and Log files
- 18. Doradus: Multi-Data Center Clusters Cassandra Doradus Cassandra Cassandra Doradus Cassandra Doradus Cassandra Cassandra Doradus Node 1 Node 2 Node 3 Node 4 Node 5 Node 6 Rack 1, Data Center 1 Rack 1, Data Center 2 Applications Applications DC=2, N=6, RF=3
- 19. Doradus: Internal Architecture App App App Monitor App Spider Storage Service OLAP Storage Service Cassandra Cluster JMX REST: Embedded Jetty Server Cassandra Interface doradus.yaml REST
- 20. Doradus OLAP Service • Borrows from online analytical processing – Sharding as data "cubes" – Columnar storage • Very dense storage – No indexes! – Value arrays are compressed • Fast load time – Up to 500,000 objects/second/node – Small "data lag" time • Very fast queries – Searches millions of objects/second – Full DQL object and aggregate query support
- 22. OLAP Data Loading T1 EventsEventsEvents EventsEventsPeople EventsEventsComputers EventsEventsDomains T2 T3 T4 T4 Sources Segments … Changes in last n minutes
- 23. OLAP Data Loading T1 EventsEventsEvents EventsEventsPeople EventsEventsComputers EventsEventsDomains T2 T3 T4 T4 2013-03-01 2013-02-28 2013-02-27 Sources Segments Shards … … Changes in last n minutes Date-based shards
- 24. OLAP Data Loading T1 EventsEventsEvents EventsEventsPeople EventsEventsComputers EventsEventsDomains T2 T3 T4 T4 2013-03-01 2013-02-28 2013-02-27 Sources Segments Shards OLAP Store … … Changes in last n minutes Date-based shards
- 25. OLAP Use Case • Data: Windows Events – 115M events • Test parameters – Server: Quad Xeon CPUs, 32GB memory, 3 disks – Cassandra memory: 1GB – Load app/embedded Doradus memory: 4GB – Load threads: 5 – Batch size: 5,000 events – Shard size: 1 day (860 shards total) • Test results – Total objects loaded: ~1 billion – Total time: 32 minutes, 56 seconds – Load rate: 502,991 objects/second – Final database size: ~2GB
- 26. Doradus Spider Service • Analogous to Lucene + NoSQL • Fully inverted field indexing – Configurable analyzers – Stored-only (non-indexed) fields • Unique features: – Automatic table-level sharding – Statistics – Pre-computed aggregate queries – Refreshed in background – Object-level data aging • Use case example: – Indexing a massive number of documents
- 27. OLAP and Spider: When to Use • Spider is best for: – Unstructured/variable- structure data – Configurable indexing – Fine-grained updates with immediate indexing – Document storage and searching – Emphasis on full-text/multi- field searching • OLAP is best for: – High-volume data streams – High performance analytic queries – Dense data storage – Immutable/semi-mutable data – Data that can be loaded in batches – Data that can be partitioned (e.g., time-sharded)
- 28. Summary • What's cool about Doradus? – Bi-directional links with referential integrity – Link paths: simpler than joins – Idempotent updates – Partial object updates – Simple transitive searching – OLAP: dense storage and fast queries – It's free!
- 29. Thank you ! Doradus is available at: https://github.com/dell-oss/Doradus Contact me: randy.guck@dell.software.com