Disruptive Code; September 22, 2010; Stockholm Sweden.

1. Cassandra Explained
Berlin Buzzwords
June 6, 2010
Eric Evans
eevans@rackspace.com
@jericevans
http://blog.sym-link.com

2. Outline
● Background
● Description
● API
● Examples

3. Background

4. Influential Papers
● BigTable
● Strong consistency
● Sparse map data model
● GFS, Chubby, et al
● Dynamo
● O(1) distributed hash table (DHT)
● BASE (aka eventual consistency)
● Client tunable consistency/availability

5. NoSQL
● HBase ● Hypertable
● MongoDB ● HyperGraphDB
● Riak ● Memcached
● Voldemort ● Tokyo Cabinet
● Neo4J ● Redis
● Cassandra ● CouchDB

6. NoSQL Big data
● HBase ● Hypertable
● MongoDB ● HyperGraphDB
● Riak ● Memcached
● Voldemort ● Tokyo Cabinet
● Neo4J ● Redis
● Cassandra ● CouchDB

7. Bigtable / Dynamo
Bigtable Dynamo
● HBase ● Riak
● Hypertable ● Voldemort
Cassandra ??

8. Dynamo-Bigtable Lovechild

9. CAP Theorem “Pick Two”
● CP ● AP
● Bigtable ● Dynamo
● Hypertable ● Voldemort
● HBase ● Cassandra

10. CAP Theorem “Pick Two”
● Consistency
● Availability
● Partition Tolerance

11. Description

12. Properties
● Symmetric
● No single point of failure
● Linearly scalable
● Ease of administration
● Flexible partitioning, replica placement
● Automated provisioning
● High availability (eventual consistency)

13. P2P Routing

14. P2P Routing

15. Partitioning
● Random
● 128bit namespace, (MD5)
● Good distribution
● Order Preserving
● Tokens determine namespace
● Natural order (lexicographical)
● Range / cover queries
● Yours ??

16. Replica Placement
● SimpleSnitch
● Default
● N-1 successive nodes
● RackInferringSnitch
● Infers DC/rack from IP
● PropertyFileSnitch
● Configured w/ a properties file

17. Bootstrap

18. Bootstrap

19. Bootstrap

20. Choosing Consistency
Write Read
Level Description Level Description
ZERO Hail Mary ZERO N/A
ANY 1 replica (HH) ANY N/A
ONE 1 replica ONE 1 replica
QUORUM (N / 2) +1 QUORUM (N / 2) +1
ALL All replicas ALL All replicas
R+W>N

21. Quorum ((N/2) + 1)

22. Quorum ((N/2) + 1)

23. Data Model

24. Overview
● Keyspace
● Uppermost namespace
● Typically one per application
● ColumnFamily
● Associates records of a similar kind
● Record-level Atomicity
● Indexed
● Column
● Basic unit of storage

25. Sparse Table

26. Column
● name
● byte[]
● Queried against (predicates)
● Determines sort order
● value
● byte[]
● Opaque to Cassandra
● timestamp
● long
● Conflict resolution (Last Write Wins)

27. Column Comparators
● Bytes
● UTF8
● TimeUUID
● Long
● LexicalUUID
● Composite (third-party)
http://github.com/edanuff/CassandraCompositeType

28. API

29. Low / High
● Thrift
● Compact binary RPC framework
● 12 different languages
● Idiomatic
● Hector (Java)
● Pycassa (Python)
● Others...
http://wiki.apache.org/cassandra/ClientOptions

30. Thrift Read Methods
● get() → Column
● get_slice() → list<Column>
● mulitget_slice() → map<key, list<Column>>
● get_count() → int
● multiget_count() → map<key, int>
● get_range_slices()

31. Thrift Write Methods
● insert()
● batch_insert()
● remove()
● batch_mutate()

32. Examples

33. Pycassa – Python Client API
● connect() → Thrift proxy
● cf = ColumnFamily(proxy, ksp, cfname)
● cf.insert() → long
● cf.get() → dict
● cf.get_range() → dict
http://github.com/vomjom/pycassa

34. Address Book – Setup
<!-- conf/storage-conf.xml -->
<Keyspace Name=”AddressBook”>
<ColumnFamily Name=”Addresses”
CompareWith=”BytesType”
RowsCached=”10000”
KeysCached=”50%”
Comment=”Too lame” />
</Keyspace>

35. Adding an entry
key = uuid()
columns = {
'first': 'Eric',
'last': 'Evans',
'email': 'eevans@rackspace.com',
'city': 'Austin',
'zip': 78250
}
addresses.insert(key, columns)

36. Fetching a record
# fetching the record by key
record = addresses.get(key)
# accessing columns by name
zipcode = record['zip']
city = record['city']

37. Indexing
<!-- conf/storage-conf.xml -->
<Keyspace Name=”AddressBook”>
<ColumnFamily Name=”Addresses”
CompareWith=”BytesType”
RowsCached=”10000”
KeysCached=”50%”
Comment=”Too lame” />
<ColumnFamily Name=”ByCity”
CompareWith=”UTF8Type” />
</Keyspace>

38. Updating the index
key = uuid()
columns = {
'first': 'Eric',
'last': 'Evans',
'email': 'eevans@rackspace.com',
'city': 'Austin',
'zip': 78250
}
addresses.insert(key, columns)
byCity.insert('Austin', {key: ''})

39. Timeseries
<!-- conf/storage-conf.xml -->
<Keyspace Name=”Sites”>
<ColumnFamily Name=”Stats”
CompareWith=”LongType”/>
</Keyspace>

40. Logging values
# time as a long, binary, network-order
ts = pack('>d', long(time() * 1e6))
stats.insert('org.apache', {ts: value})

41. Slicing
begin = pack('>d', long(s * 1e6))
stats.get_range('org.apache',
column_start=begin)
end = pack('>d', long((s + 86400) * 1e6))
stats.get_range(start='org.apache',
finish='org.debian',
column_start=begin,
column_finish=end)

42. Questions?