Mastering Apache Cassandra 3.x : an expert guide to improving database scalability and availability without compromising performance / Aaron Ploetz, Tejaswi Malepati, Nishant Neeraj.

Format:

Book

Author/Creator:

Ploetz, Aaron, author.

Malepati, Tejaswi, author.

Neeraj, Nishant, author.

Language:

English

Subjects (All):

Apache Cassandra.

Non-relational databases.

Application software--Development.

Application software.

Physical Description:

1 online resource (348 pages)

Edition:

Third edition.

Other Title:

Mastering Apache Cassandra three point x

Place of Publication:

Birmingham : Packt, 2018.

System Details:

text file

Summary:

Build, manage, and configure high-performing, reliable NoSQL database for your applications with Cassandra Key Features Write programs more efficiently using Cassandra's features with the help of examples Configure Cassandra and fine-tune its parameters depending on your needs Integrate Cassandra database with Apache Spark and build strong data analytics pipeline Book Description With ever-increasing rates of data creation, the demand for storing data fast and reliably becomes a need. Apache Cassandra is the perfect choice for building fault-tolerant and scalable databases. Mastering Apache Cassandra 3.x teaches you how to build and architect your clusters, configure and work with your nodes, and program in a high-throughput environment, helping you understand the power of Cassandra as per the new features. Once you've covered a brief recap of the basics, you'll move on to deploying and monitoring a production setup and optimizing and integrating it with other software. You'll work with the advanced features of CQL and the new storage engine in order to understand how they function on the server-side. You'll explore the integration and interaction of Cassandra components, followed by discovering features such as token allocation algorithm, CQL3, vnodes, lightweight transactions, and data modelling in detail. Last but not least you will get to grips with Apache Spark. By the end of this book, you'll be able to analyse big data, and build and manage high-performance databases for your application. What you will learn Write programs more efficiently using Cassandra's features more efficiently Exploit the given infrastructure, improve performance, and tweak the Java Virtual Machine (JVM) Use CQL3 in your application in order to simplify working with Cassandra Configure Cassandra and fine-tune its parameters depending on your needs Set up a cluster and learn how to scale it Monitor a Cassandra cluster in different ways Use Apache Spark and other big data processing tools Who this book is for Mastering Apache Cassandra 3.x is for you if you are a big data administrator, database administrator, architect, or developer who wants to build a high-performing, scalable, and fault-tolerant database. Prior knowledge of core concepts of databases is required.

Contents:

Cover

Title Page

Copyright and Credits

Packt Upsell

Foreward

Contributors

Table of Contents

Preface

Chapter 1: Quick Start

Introduction to Cassandra

High availability

Distributed

Partitioned row store

Installation

Configuration

cassandra.yaml

cassandra-rackdc.properties

Starting Cassandra

Cassandra Cluster Manager

A quick introduction to the data model

Using Cassandra with cqlsh

Shutting down Cassandra

Summary

Chapter 2: Cassandra Architecture

Why was Cassandra created?

RDBMS and problems at scale

Cassandra and the CAP theorem

Cassandra's ring architecture

Partitioners

ByteOrderedPartitioner

RandomPartitioner

Murmur3Partitioner

Single token range per node

Vnodes

Cassandra's write path

Cassandra's read path

On-disk storage

SSTables

How data was structured in prior versions

How data is structured in newer versions

Additional components of Cassandra

Gossiper

Snitch

Phi failure-detector

Tombstones

Hinted handoff

Compaction

Repair

Merkle tree calculation

Streaming data

Read repair

Security

Authentication

Authorization

Managing roles

Client-to-node SSL

Node-to-node SSL

Chapter 3: Effective CQL

An overview of Cassandra data modeling

[Cassandra storage model for versions 3.0 and beyond]

Cassandra storage model for versions 3.0 and beyond

Data cells

cqlsh

Logging into cqlsh

Problems connecting to cqlsh

Local cluster without security enabled

Remote cluster with user security enabled

Remote cluster with auth and SSL enabled

Connecting with cqlsh over SSL

Converting the Java keyStore into a PKCS12 keyStore

Exporting the certificate from the PKCS12 keyStore

Modifying your cqlshrc file

Testing your connection via cqlsh.

Getting started with CQL

Creating a keyspace

Single data center example

Multi-data center example

Creating a table

Simple table example

Clustering key example

Composite partition key example

Table options

Data types

Type conversion

The primary key

Designing a primary key

Selecting a good partition key

Selecting a good clustering key

Querying data

The IN operator

Writing data

Inserting data

Updating data

Deleting data

Lightweight transactions

Executing a BATCH statement

The expiring cell

Altering a keyspace

Dropping a keyspace

Altering a table

Truncating a table

Dropping a table

Truncate versus drop

Creating an index

Caution with implementing secondary indexes

Dropping an index

Creating a custom data type

Altering a custom type

Dropping a custom type

User management

Creating a user and role

Altering a user and role

Dropping a user and role

Granting permissions

Revoking permissions

Other CQL commands

COUNT

DISTINCT

LIMIT

STATIC

User-defined functions

cqlsh commands

CONSISTENCY

COPY

DESCRIBE

TRACING

Chapter 4: Configuring a Cluster

Evaluating instance requirements

RAM

CPU

Disk

Solid state drives

Cloud storage offerings

SAN and NAS

Network

Public cloud networks

Firewall considerations

Strategy for many small instances versus few large instances

Operating system optimizations

Disable swap

XFS

Limits

limits.conf

sysctl.conf

Time synchronization

Configuring the JVM

Garbage collection

CMS

G1GC

Garbage collection with Cassandra

Installation of JVM

JCE

Configuring Cassandra

cassandra-env.sh

dc

rack

dc_suffix

prefer_local

cassandra-topology.properties.

jvm.options

logback.xml

Managing a deployment pipeline

Orchestration tools

Configuration management tools

Recommended approach

Local repository for downloadable files

Chapter 5: Performance Tuning

Cassandra-Stress

The Cassandra-Stress YAML file

name

size

population

cluster

Cassandra-Stress results

Write performance

Commitlog mount point

Scaling out

Scaling out a data center

Read performance

Compaction strategy selection

Optimizing read throughput for time-series models

Optimizing tables for read-heavy models

Cache settings

Appropriate uses for row-caching

Compression

Chunk size

The bloom filter configuration

Read performance issues

Other performance considerations

JVM configuration

Cassandra anti-patterns

Building a queue

Query flexibility

Querying an entire table

Incorrect use of BATCH

Chapter 6: Managing a Cluster

Revisiting nodetool

A warning about using nodetool

Scaling up

Adding nodes to a cluster

Cleaning up the original nodes

Adding a new data center

Adjusting the cassandra-rackdc.properties file

A warning about SimpleStrategy

Scaling down

Removing nodes from a cluster

Removing a live node

Removing a dead node

Other removenode options

When removenode doesn't work (nodetool assassinate)

Assassinating a node on an older version

Removing a data center

Backing up and restoring data

Taking snapshots

Enabling incremental backups

Recovering from snapshots

Maintenance

Replacing a node

A warning about incremental repairs

Cassandra Reaper

Forcing read repairs at consistency - ALL

Clearing snapshots and incremental backups

Snapshots

Incremental backups

Compaction.

Why you should never invoke compaction manually

Adjusting compaction throughput due to available resources

Chapter 7: Monitoring

JMX interface

MBean packages exposed by Cassandra

JConsole (GUI)

Connection and overview

Viewing metrics

Performing an operation

JMXTerm (CLI)

Connection and domains

Getting a metric

The nodetool utility

Monitoring using nodetool

describecluster

gcstats

getcompactionthreshold

getcompactionthroughput

getconcurrentcompactors

getendpoints

getlogginglevels

getstreamthroughput

gettimeout

gossipinfo

info

netstats

proxyhistograms

status

tablestats

tpstats

verify

Administering using nodetool

cleanup

drain

flush

resetlocalschema

stopdaemon

truncatehints

upgradeSSTable

Metric stack

Telegraf

JMXTrans

InfluxDB

InfluxDB CLI

Grafana

Visualization

Alerting

Custom setup

Log stack

The system/debug/gc logs

Filebeat

Elasticsearch

Kibana

Troubleshooting

High CPU usage

Different garbage-collection patterns

Hotspots

Disk performance

Node flakiness

All-in-one Docker

Creating a database and other monitoring components locally

Web links

Chapter 8: Application Development

Getting started

The path to failure

Is Cassandra the right database?

Good use cases for Apache Cassandra

Use and expectations around application data consistency

Choosing the right driver

Building a Java application

Driver dependency configuration with Apache Maven

Connection class.

Other connection options

Retry policy

Default keyspace

Port

SSL

Connection pooling options

Starting simple - Hello World!

Using the object mapper

Building a data loader

Asynchronous operations

Data loader example

Chapter 9: Integration with Apache Spark

Spark

Architecture

Running custom Spark Docker locally

The web UI

Master

Worker

Application

PySpark

Connection config

Accessing Cassandra data

SparkR

RStudio

Jupyter

Web UI

PYSpark through Juypter

Appendix: References

Chapter 1 - Quick Start

Chapter 2 - Cassandra Architecture

Chapter 3 - Effective CQL

Chapter 4 - Configuring a Cluster

Chapter 5 - Performance Tuning

Chapter 6 - Managing a Cluster

Chapter 7 - Monitoring

Chapter 8 - Application Development

Chapter 9 - Integration with Apache Spark

Other Books You May Enjoy

Index.

Notes:

Includes index.

Includes bibliographical references.

Description based on online resource; title from PDF title page (ebrary, viewed February 20, 2019).

OCLC:

1086104365