Cassandra has always been a highly performant distributed database, but not always simple to use though. Apache Cassandra 1.2 introduces some new features such as a Binary Protocol and Collections datatype that together with the now finalized CQL3 query language provide a new interface to communicate with Cassandra that dramatically shrink its learning curve and simplify its daily use while still relying on its highly scalable architecture and storage engine. This presentation will iterate over all these new features including an overview of CQL3 query language, a look at the new client architecture, and an update on data modeling best practices. Then we'll see how to implement an enterprise application using this new interface so that the audience can realize that a number of design principles are inspired from those commonly used with relational databases while some other entirely different, due to Cassandra partitioning approach.

1. The new face of Cassandra
Michaël Figuière
@mfiguiere

2. Speaker
Michaël Figuière
@mfiguiere
©2012 DataStax 2

3. Ring Architecture
Node Node
Node Cassandra Node
Node
Node
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4. Ring Architecture
Node Replica
Node
Replica
Node
Replica
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5. Linear Scalability
Client Writes/s by Node Count - Replication Factor = 3
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6. Client / Server Communication
Client ? Node Replica
Client
Node
Replica
Client
Node
Client Replica
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7. Client / Server Communication
Client Node Replica
Client
Node
Replica
Client
Node
Client Replica
Coordinator node:
Forwards all R/W requests
to corresponding replicas
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8. Tunable Consistency
Time
A A A
3 replicas
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9. Tunable Consistency
Time
A A A
B A A
Write ‘B’
Write and wait for
acknowledge from one node
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10. Tunable Consistency
Time
R +W < N
A A A
B A A
B A A
Read waiting for one node Write and wait for
to answer acknowledge from one node
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11. Tunable Consistency
Time
R +W = N
A A A
B B A
B B A
Read waiting for one node Write and wait for
to answer acknowledges from two nodes
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12. Tunable Consistency
Time
R +W > N
A A A
B B A
B B A
Read waiting for two nodes Write and wait for
to answer acknowledges from two nodes
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13. Tunable Consistency
Time
R = W = QUORUM
A A A
B B A
B B A
QUORUM = (N / 2) + 1
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14. Request Path
1
Client Node Replica
2
3
Client
4 2
Node
Replica
3
Client
2
3
Node
Client Replica
Coordinator node
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15. Multi-Datacenter
Datacenter A
Node 1
Node Node Node 2
1 2
Datacenter B
Node 3
Node
6 Node
3 Node 4
Datacenter C
Node
Node
5 Node 5
4
Node 6
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16. Column Family Data Model
address email name state
jbellis
123 main jb@ds.com Jonathan TX
address email name state
dhutch
45 2nd st dh@ds.com Daria CA
email name
egilmore
eg@ds.com Eric
Row Key Columns = List of K/V pairs sorted by Key
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17. Column Family Data Model
datastax dhutch egilmore mzcassie
jbellis
egilmore
dhutch
datastax mzcassie
egilmore
Row Key Columns = List of K/V pairs sorted by Key
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18. Storage Engine
Memtable Memtable
Commit
SSTable
Log SSTable SSTable
SSTable
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19. CQL3 Denormalized Model
CQL3 Query Language comes with a new Data Model abstraction made of
denormalized, statically defined tables
Data duplicated over several tables
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20. CQL3 Data Model
Timeline Table
user_id tweet_id author body
gmason 1735 phenry Give me liberty or give me death
gmason 1742 gwashington I chopped down the cherry tree
ahamilton 1767 jadams A government of laws, not men
ahamilton 1794 gwashington I chopped down the cherry tree
Partition Clustering
Key Key
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21. CQL3 Data Model
Timeline Table
user_id tweet_id author body
gmason 1735 phenry Give me liberty or give me death
gmason 1742 gwashington I chopped down the cherry tree
ahamilton 1767 jadams A government of laws, not men
ahamilton 1794 gwashington I chopped down the cherry tree
CQL
CREATE TABLE timeline (
user_id varchar,
tweet_id timeuuid,
author varchar,
body varchar,
PRIMARY KEY (user_id, tweet_id));
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22. CQL3 Data Model
Timeline Table
user_id tweet_id author body
gmason 1735 phenry Give me liberty or give me death
gmason 1742 gwashington I chopped down the cherry tree
ahamilton 1767 jadams A government of laws, not men
ahamilton 1794 gwashington I chopped down the cherry tree
Timeline Physical Layout
[1735, author] [1735, body] [1742, author] [1742, body]
gmason
gwashington I chopped down the... phenry Give me liberty or give...
[1767, author] [1767, body] [1794, author] [1794, body]
ahamilton
gwashington I chopped down the... jadams A government of laws...
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23. Current Drivers Architecture
CQL API Thrift API OO API DB API
Thrift RPC Thrift RPC
Client Library CQL Driver
* This is a simplified view of drivers architecture. Details vary from one language to another.
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24. New Drivers Architecture
DB API CQL API OO API
CQL Native Protocol
Next Generation Driver
* This is a simplified view of drivers architecture. Details vary from one language to another.
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25. DataStax Java Driver
• Reference Implementation
• Asynchronous architecture based on Netty
• Prepared Statements Support
• Automatic Fail-over
• Node Discovery
• Cassandra Tracing Support
• Tunable policies
• LoadBalancingPolicy
• ReconnectionPolicy
•
©2012 DataStax
RetryPolicy
25

26. Connect and Write
Cluster cluster = new Cluster.Builder()
.addContactPoints("10.0.0.1", "10.0.0.2")
.build();
Session session = cluster.connect("myKeyspace");
session.execute(
"INSERT INTO user (user_id, name, email)
VALUES (12345, 'johndoe', 'john@doe.com')"
);
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27. Read
ResultSet rs = session.execute("SELECT * FROM test");
List<Row> rows = rs.fetchAll();
for (Row row : rows) {
String userId = row.getString("user_id");
String name = row.getString("name");
String email = row.getString("email");
}
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28. Asynchronous Read
ResultSet.Future future =
session.executeAsync("SELECT * FROM test");
for (Row row : future.get()) {
String userId = row.getString("user_id");
String name = row.getString("name");
String email = row.getString("email");
}
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29. Object Mapping
@Table(name = "user")
public class User { public enum Gender {
@PartitionKey @EnumValue("m")
@Column(name = "user_id") MALE,
private String userId;
@EnumValue("f")
private String name; FEMALE;
}
private String email;
private Gender gender;
}
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30. Inheritance
@Table(name = "catalog")
@Inheritance(
@InheritanceValue("tv")
subClasses = {Phone.class, TV.class},
public class TV
column = "product_type"
extends Product {
)
public abstract class Product {
private float size;
}
@Column(name = "product_id")
private String productId;
private float price;
private String vendor;
private String model;
}
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31. Now Available!
https://github.com/datastax/java-driver

32. Stay Tuned!
blog.datastax.com
@mfiguiere