Christopher Bradford

Replication and consistency in Cassandra... What does it all mean?

Who is this guy?

Christopher BradfordSolutions Architect with DataStax

Built the world’s smallest C* cluster

Twitter: @bradfordcp

GitHub: bradfordcp

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Introduction

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CAP Theorem

Pick 2 of the 3

Consistency

Availability Partition Tolerance

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CAP Theorem

Consistency

Every read receives the most recent write or an error

Consistency

Availability Partition Tolerance

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CAP Theorem

Every request receives a response

Consistency

Availability Partition Tolerance

Availability

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CAP Theorem

Partition Tolerance

The system continues to operate despite arbitrary partitioning

Consistency

Availability Partition Tolerance

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CAP Theorem Evolved

The modern CAP goal should be to maximize combinations of consistency and availability that make sense for the specific application. Such an approach incorporates plans for operation during a partition and for recovery afterward, thus helping designers think about CAP beyond its historically perceived limitations.

- Eric Brewer

C

A P

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CAP Theorem

Cassandra’s View

AP – Availability & Partition tolerance above all else.

Consistency

Availability Partition Tolerance

ReplicationAvailability & Partition Tolerance

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Replication

ClientCoordinator

Replica

Replica

Replica

Write

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Replication

ClientCoordinator

Replica

Replica

Replica

Write

+1 Hint

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Replication

ClientCoordinator

Replica

Replica

Replica

Read

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Configuring Replication

Replication is defined at the keyspace level.

Strategy

Parameters

CREATE KEYSPACE cassandra_summit WITH REPLICATION = { ‘class’: ‘SimpleStrategy’, ‘replication_factor’: 3 };

1 Simple Strategy

2 Network Topology Strategy

Replication Strategies

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Simple Strategy

ClientCoordinator

Replica

Replica

Replica

Request

Class: SimpleStrategyParameters:• replication_factor

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Simple Strategy

ClientCoordinator

Replica

Replica

Replica

Request

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Network Topology Strategy

ClientCoordinator

Replica

Replica

Replica

Request

Class: NetworkTopologyStrategyParameters:• dc_name: replication_factor

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Network Topology Strategy

Client Coordinator

ReplicaRequestRack 1

Rack 2

Replica

Replica

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Network Topology Strategy

ClientCoordinator

ReplicaRequestRack 1

Rack 3

Replica

Replica Rack 2

Tools:nodetool status ksnodetool getendpoints ks table val

ConsistencyBalancing performance and correctness

Tunable Consistency

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Consistency Levels

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Consistent Reads

• ALL• QUORUM• LOCAL_QUORUM• ONE• LOCAL_ONE• SERIAL

Replica

Replica

Replica

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Consistent Writes

• ALL• QUORUM• LOCAL_QUORUM• ONE• LOCAL_ONE• ANY

Replica

Replica

Replica

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Consistency Failures

What happens when the desired consistency level cannot be achieved?

Replica

Replica

Replica

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Failure Recovery

Staying Consistent

In the event of a failure how do replicas get the latest data?

Replica

Replica

Replica

Conclusion

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Questions?