Cassandra High Availability电子书

Cassandra High Availability

Table of Contents

Cassandra High Availability

Credits

About the Author

About the Reviewers

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Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Errata

Piracy

Questions

1. Cassandra's Approach to High Availability

ACID

The monolithic architecture

The master-slave architecture

Sharding

Master failover

Cassandra's solution

Cassandra's architecture

Distributed hash table

Replication

Replication across data centers

Tunable consistency

The CAP theorem

Summary

2. Data Distribution

Hash table fundamentals

Distributing hash tables

Consistent hashing

The mechanics of consistent hashing

Token assignment

Manually assigned tokens

vnodes

How vnodes improve availability

Adding and removing nodes

Node rebuilding

Heterogeneous nodes

Partitioners

Hotspots

Effects of scaling out using ByteOrderedPartitioner

A time-series example

Summary

3. Replication

The replication factor

Replication strategies

SimpleStrategy

NetworkTopologyStrategy

Snitches

Maintaining the replication factor when a node fails

Consistency conflicts

Consistency levels

Repairing data

Balancing the replication factor with consistency

Summary

4. Data Centers

Use cases for multiple data centers

Live backup

Failover

Load balancing

Geographic distribution

Online analysis

Analysis using Hadoop

Analysis using Spark

Data center setup

RackInferringSnitch

PropertyFileSnitch

GossipingPropertyFileSnitch

Cloud snitches

Replication across data centers

Setting the replication factor

Consistency in a multiple data center environment

The anatomy of a replicated write

Achieving stronger consistency between data centers

Summary

5. Scaling Out

Choosing the right hardware configuration

Scaling out versus scaling up

Growing your cluster

Adding nodes without vnodes

Adding nodes with vnodes

How to scale out

Adding a data center

How to scale up

Upgrading in place

Scaling up using data center replication

Removing nodes

Removing nodes within a data center

Decommissioning a data center

Other data migration scenarios

Snitch changes

Summary

6. High Availability Features in the Native Java Client

Thrift versus the native protocol

Setting up the environment

Connecting to the cluster

Executing statements

Prepared statements

Batched statements

Caution with batches

Handling asynchronous requests

Running queries in parallel

Load balancing

Failing over to a remote data center

Downgrading the consistency level

Defining your own retry policy

Token awareness

Tying it all together

Falling back to QUORUM

Summary

7. Modeling for High Availability

How Cassandra stores data

Implications of a log-structured storage

Understanding compaction

Size-tiered compaction

Leveled compaction

Date-tiered compaction

CQL under the hood

Single primary key

Compound keys

Partition keys

Clustering columns

Composite partition keys

The importance of the storage model

Understanding queries

Query by key

Range queries

Denormalizing with collections

How collections are stored

Sets

Lists

Maps

Working with time-series data

Designing for immutability

Modeling sensor data

Queries

Time-based ordering

Using a sentinel value

Satisfying our queries

When time is all that matters

Working with geospatial data

Summary

8. Antipatterns

Multikey queries

Secondary indices

Secondary indices under the hood

Distributed joins

Deleting data

Garbage collection

Resurrecting the dead

Unexpected deletes

The problem with tombstones

Expiring columns

TTL antipatterns

When null does not mean empty

Cassandra is not a queue

Unbounded row growth

Summary

9. Failing Gracefully

Knowledge is power

Monitoring via Java Management Extensions

Using OpsCenter

Choosing a management toolset

Logging

Cassandra logs

Garbage collector logs

Monitoring node metrics

Thread pools

Column family statistics

Finding latency outliers

Communication metrics

When a node goes down

Marking a downed node

Handling a downed node

Handling slow nodes

Backing up data

Taking a snapshot

Incremental backups

Restoring from a snapshot

Summary

Index