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Home > Programming > Programming Language > Getting Started with Hazelcast, Second Edition
Getting Started with Hazelcast, Second Edition
Getting Started with Hazelcast, Second Edition

Getting Started with Hazelcast, Second Edition: Get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application

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Getting Started with Hazelcast, Second Edition

Chapter 2. Getting off the Ground

We can think of Hazelcast as a library technology—a JAR file that we bring into our application's classpath and integrate with in order to harness its data distribution capabilities. Now, we can go about setting up an application in the many ways that allow us to use various third-party libraries and dependencies. Most modern IDEs can do this for you. Dependency management or build tools such as Maven, Ant, or Gradle can automate these IDEs, and we can manually sort it out ourselves. However, it's now time to jump in at the deep end. In this chapter, we shall study the following topics:

  • Downloading Hazelcast
  • Creating a basic application with Hazelcast
  • Exploring the various simple storage collections
  • Fetching and searching stored data
  • Setting limits and understanding what happens when we reach the limits

Let's get started

First things first, let's create a working directory for our project.

Navigate to Hazelcast's download page. To download Hazelcast, visit www.hazelcast.org/download/.

The following image shows what the download page looks like:

Let's get started

We will use the latest version, in this case, Version 3.5.

Note

While there is nothing stopping you from working with Hazelcast Enterprise, there is nothing within this book that requires it. For our purposes, the community version will do just fine.

When you unzip the archive, you will find a lib/ directory. This contains the various library JAR files that we can use within our application. For now, let's copy lib/hazelcast-3.5.jar to the working directory.

Showing off straightaway

Within the Hazelcast JAR file, there is a very useful ConsoleApp utility class (this class was previously known as TestApp, but the name was a little deceptive as it can be used for operations beyond just testing). It is great in that it provides a simple text console for easy access to the distributed collections.

To fire this up, we need to run this class using the Hazelcast JAR file as the classpath. Alternatively, we can also use the console scripts that were provided in the demo/ directory.

$ java -cp hazelcast-3.5.jar com.hazelcast.console.ConsoleApp

This should bring up a fair amount of verbose logging, but a reassuring section to look for so that we can see that a cluster has been formed, is the following output:

Members [1] {
    Member [127.0.0.1]:5701 this
}

The output lets us know that a new cluster comprising a node has been created. The current node is indicated by this. The configuration, which is the default built-in JAR, was used to start up the instance...

Mapping back to the real world

Having briefly explored Hazelcast's distributed capabilities via a test console, let's have a look at how we are more likely to interact with a cluster in the real world. Let's create a new SimpleMapExample class with a main method to spin up and manipulate a named distributed map called capitals. Hazelcast refers to these named collections as a namespace. These collections must be uniquely named across the cluster, as follows:

import com.hazelcast.core.Hazelcast;
import com.hazelcast.core.HazelcastInstance;
import java.util.Map;

public class SimpleMapExample {
  public static void main(String[] args) {
    HazelcastInstance hz = Hazelcast.newHazelcastInstance();

    Map<String, String> capitals = hz.getMap("capitals");
    capitals.put("GB", "London");
    capitals.put("FR", "Paris");
    capitals.put("US", "Washington DC");
    capitals.put("AU", "Canberra...

Sets, lists, and queues

In the previous examples, we looked at key-value storage provided by Hazelcast maps. However, there are a number of other collections that provide keyless groups of objects. Two of these additional types are distributed versions of collections that you may be already familiar with—sets and lists.

The primary difference between these two collections is that lists allow for multiple entries and a set does not. So, if we add them to the previous map example, we will get the following code:

Set<String> cities = hz.getSet("cities");
cities.addAll(captials.values());
cities.add("London");
cities.add("Rome");
cities.add("New York");

List<String> countries = hz.getList("countries");
countries.addAll(captials.keySet());
countries.add("CA");
countries.add("DE");
countries.add("GB"); // duplicate entry

When using the test console again to interact with these new collections, we...

Many things at a time

We have previously seen that Hazelcast provides us with a generic key-value map. However, this capability is popularly used to create a key/list-of-values map. While there is nothing stopping us from defining these ourselves using the standard Java generics, we will have to manually handle the initialization of each key entry. Hazelcast has luckily gone out of its way to make our lives easier by handling this case for us by using the specialized MultiMap collection.

Let's have a look at the following example:

public class MultiMapExample {
  public static void main(String[] args) {
    HazelcastInstance hz = Hazelcast.newHazelcastInstance();

    Map<String, List<String>> manualCities =
      hz.getMap("manualCities");

    List<String> gbCities = new ArrayList<String>();
    manualCities.put("GB", gbCities);

    gbCities = manualCities.get("GB");
    gbCities.add("London");
    manualCities.put(&quot...

Searching and indexing

When creating a clean storage that is based on key-values, we may find that we have lost some of the extra searching capabilities that traditional databases offer. Mainly, we now can't find records within a dataset without knowing the primary key to the entry. However, fear not. Hazelcast provides similar capabilities that allow you to search its maps using predefined indexes. These can be either ordered (ascending) or unordered, depending on our particular data needs. However, keep in mind that indexing doesn't come for free. The internal lookup table that is used to quickly search the reads is maintained as we make changes to the map. This will add latency to every write operation in the namespace.

So firstly, let's create a new plain old Java object (POJO) to represent a city, as follows:

import java.io.Serializable;

public class City implements Serializable, Comparable<City> {
  private String name;
  private String country;
  private int population...

Let's get started

First things first, let's create a working directory for our project.

Navigate to Hazelcast's download page. To download Hazelcast, visit www.hazelcast.org/download/.

The following image shows what the download page looks like:

We will use the latest version, in this case, Version 3.5.

Note

While there is nothing stopping you from working with Hazelcast Enterprise, there is nothing within this book that requires it. For our purposes, the community version will do just fine.

When you unzip the archive, you will find a lib/ directory. This contains the various library JAR files that we can use within our application. For now, let's copy lib/hazelcast-3.5.jar to the working directory.

Showing off straightaway

Within the Hazelcast JAR file, there is a very useful ConsoleApp utility class (this class was previously known as TestApp, but the name was a little deceptive as it can be used for operations beyond just testing). It is great in that it provides a simple text console for easy access to the distributed collections.

To fire this up, we need to run this class using the Hazelcast JAR file as the classpath. Alternatively, we can also use the console scripts that were provided in the demo/ directory.

$ java -cp hazelcast-3.5.jar com.hazelcast.console.ConsoleApp

This should bring up a fair amount of verbose logging, but a reassuring section to look for so that we can see that a cluster has been formed, is the following output:

Members [1] {
    Member [127.0.0.1]:5701 this
}

The output lets us know that a new cluster comprising a node has been created. The current node is indicated by this. The configuration, which is the default built-in JAR, was used to start up the instance...

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Description

This book is a great introduction for Java developers, software architects, or DevOps looking to enable scalable and agile data within their applications. Providing in-memory object storage, cluster-wide state and messaging, or even scalable task execution, Hazelcast helps solve a number of issues that have troubled technologists for years.

Who is this book for?

This book is a great introduction for Java developers, software architects, or DevOps looking to enable scalable and agile data within their applications. Providing in-memory object storage, cluster-wide state and messaging, or even scalable task execution, Hazelcast helps solve a number of issues that have troubled technologists for years.

What you will learn

  • Learn and store numerous data types in different distributed collections
  • Set up a cluster from the ground up
  • Work with truly distributed queues and topics for clusterwide messaging
  • Make your application more resilient by listening into cluster internals
  • Run tasks within and alongside our stored data
  • Filter and search our data using MapReduce jobs
  • Discover the new JCache standard and one of its first implementations

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 30, 2015
Length: 162 pages
Edition : 1st
Language : English
ISBN-13 : 9781783554058
Category :
Programming
Languages :
Java
Concepts :
Programming Language
Tools :
Hazelcast

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Publication date : Jul 30, 2015
Length: 162 pages
Edition : 1st
Language : English
ISBN-13 : 9781783554058
Category :
Programming
Languages :
Java
Concepts :
Programming Language
Tools :
Hazelcast

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Table of Contents

13 Chapters
1. What is Hazelcast? Chevron down icon Chevron up icon
1. What is Hazelcast?
Starting out as usual
Data deciding to hang around
Therein lies the problem
Breaking the mould
Moving to new ground
Summary
2. Getting off the Ground Chevron down icon Chevron up icon
2. Getting off the Ground
Let's get started
Showing off straightaway
Mapping back to the real world
Sets, lists, and queues
Many things at a time
Searching and indexing
What happens when we reach our limits?
Summary
3. Going Concurrent Chevron down icon Chevron up icon
3. Going Concurrent
Atomic control
Distributed locking
Transactionally rolling on
Spreading the word
Summary
4. Divide and Conquer Chevron down icon Chevron up icon
4. Divide and Conquer
Divvying up the data
Backups everywhere and nowhere
Scaling up the cluster
Having some of our data everywhere
Grouping and separating nodes
Network partitioning
Maintaining quorum
Summary
5. Listening Out Chevron down icon Chevron up icon
5. Listening Out
Listening to the goings-on
The sound of our own data
Programmatic configuration ahead of time
Events unfolding in the wider world
Moving data around the place
Extending quorum
Summary
6. Spreading the Load Chevron down icon Chevron up icon
6. Spreading the Load
All power to the compute
Running once, running everywhere
Placing tasks next to the data
Summary
7. Gathering Results Chevron down icon Chevron up icon
7. Gathering Results
What is this big data hype all about?
Putting theory into practice
Simplifying just aggregating up
Summary
8. Typical Deployments Chevron down icon Chevron up icon
8. Typical Deployments
All heap and nowhere to go
Stepping back from the cluster
Serialization and classes
Getting straight to the point
Architectural overview
Summary
9. From the Outside Looking In Chevron down icon Chevron up icon
9. From the Outside Looking In
What about the rest of us?
Memcache
Going RESTful
Summary
10. Going Global Chevron down icon Chevron up icon
10. Going Global
Getting set up in the cloud
Spreading out around the globe
Summary
11. Playing Well with Others Chevron down icon Chevron up icon
11. Playing Well with Others
Don't pass what you need, depend on it
Transparently caching others' data
Cacheable methods with the Spring cache
Caching by standard
Collection persistence
Web session storage
Cluster management
Summary
A. Configuration Summary Chevron down icon Chevron up icon
A. Configuration Summary
Cluster name
Management center
General properties
WAN replication configuration
Local network/interface binding
Cluster discovery (multicast-, unicast-, or EC2-based)
Map configuration
Listeners notified on map events
Listeners notified on topic broadcast
Cluster-wide listener registration
Index Chevron down icon Chevron up icon
Index

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Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.3
(3 Ratings)
5 star 33.3%
4 star 33.3%
3 star 0%
2 star 0%
1 star 33.3%
Chris Everett Sep 08, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is a great introduction for Java developers, software architects, or DevOps looking to enable scalable and agile data within their applications. Hands-on examples to progressively walk you through all the powerful features and capabilities on offer. Book also covers distributed task execution, in-place data manipulations and big data analytical processing using MapReduce.
Amazon Verified review Amazon
Dustin Marx Aug 22, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
The second edition of "Getting Started with Hazelcast" (2015) adds three new chapters that cover trendy topics such as Big Data; Cloud; use of Hazelcast with popular frameworks such as Spring and Hibernate, and JMX, and how to use Hazelcast as an implementation of JCache (JSR 107). The book's title is apropos as the book is focused on "getting started with Hazelcast." The book serves as a nice complement for the Hazelcast Documentation (Reference Manual) and "Mastering Hazelcast" (a download available from Hazelcast for those who provide their name and email address)."Getting Started with Hazelcast" provides a narrative of what makes a technology like Hazelcast desirable and how Hazelcast meets different needs. In this way, the book helps familiarize the reader with concepts and vernacular of Hazelcast. Greater details on Hazelcast can be found online in forums and blogs and in "Mastering Hazelcast." "Getting Started with Hazelcast" does not cover the differences between standard Hazelcast and Hazelcast Enterprise.
Amazon Verified review Amazon
kalyan Nov 17, 2017
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
This book does not cover all topics , neither any topic in detail.
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About the author

Profile icon Matthew Johns
Matthew Johns
contacted on 6 may '16 ________ Matthew Johns is an agile software engineer and hands-on technical/solution architect; specialising in designing and delivering highly scaled and available distributed systems, with broad experience across the whole stack. He is the solution architect and lead engineer at Sky.
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