Building Highly Scalable Spring Applications using In-Memory Data Grids

SPRINGONE2GX
WASHINGTON, DC
Unless otherwise indicated, these slides are © 2013 -2015 Pivotal Software, Inc. and licensed under a Creative Commons Attributio n-NonCommercial license: http://creativecommons.org/licenses/by-nc/3.0/
Building Highly Scalable Spring
Applications using In-Memory Data Grids
By John Blum & Luke Shannon
@john_blum

Unless otherwise indicated, these slides are © 2013 -2015 Pivotal Software, Inc. and licensed under a
Creative Commons Attribution-NonCommercial license: http://creativecommons.org/licenses/by-nc/3.0/
Presenters
2
John Blum - @john_blum
Spring Data GemFire Project Lead
Apache Geode Committer
GemFire Engineer/Technical Lead
Pivotal Software, Inc
Luke Shannon
Field/Community Engineer
Apache Geode Committer
Pivotal Software, Inc.

Agenda
3
• Introduction to Apache Geode
• Distributed System & In-Memory Database Concepts
• Overview of Spring Data GemFire
• How to build highly scalable applications
• Spring Data GemFire in Action
• Fast Foot Shoes Demo
• Caching Demo (?)
• What’s New
• QA

Why Apache Geode?
4
Motivation…
1. Volume of Data (Big Data)
2. Velocity of Data (Fast Data)
3. Verity of Data (Data Accuracy)
Enables new and existing Spring applications to operate at cloud-scale in a
consistent, highly-available and predictable manner in order to transact and
analyze big, fast data in real-time thereby achieving meaningful and impactful
business results.

What is Apache Geode?
5
In a nutshell…
• Open Source core of Pivotal GemFire
• https://pivotal.io/big-data/pivotal-gemfire
• Apache Incubator project
• https://wiki.apache.org/incubator/GeodeProposal
• http://geode.incubator.apache.org/

What is Apache Geode?
6
“A distributed, in-memory compute and
data management platform that
elastically scales to achieve high-
throughput, low-latency access to big,
fast data powering business critical,
analytical applications in real-time.”
– John Blum, 
Elastic capacity +/-
Nodes
Ops /
SecLinear scalability
Latency optimized
data distribution

Apache Geode Use Cases
7
• Persistent, OLTP/OLAP Database (System of Record)
• JSR-107 Cache Provider (Key/Value Store)
• HTTP Session State Management
• Distributed L2 Caching for Hibernate
• Memcached Server (Gemcached)
• Message Bus with guaranteed message delivery
• Glorified version of ConcurrentHashMap

China Railway Corporation
GemFire runs on ten primary x86 servers with over two
terabytes of memory and there are ten backup servers –
this has replaced the 72 UNIX boxes and traditional
RDBMS with a more efficient, cost-effective approach.
With so many people relying on the website for travel, it must be
continuously available. Demand has far exceeded expectations
and the future shows as much as 50% growth per year as
mobile phone access is added.
https://pivotal.io/big-data/case-study/scaling-online-sales-for-the-largest-
railway-in-the-world-china-railway-corporation
8
China Railway
Corporation
• 20 million users per day; 40,000
visits per second
• 4.5 million ticket purchases &.
• Spikes of 15,000 tickets sold per
minute
“The system is operating with solid
performance and uptime. Now, we have a
reliable, economically sound production
system that supports record volumes and
has room to grow”
Dr. Jiansheng Zhu, Vice Director of China
Academy of Railway Sciences

How Apache Geode Works
9
• Stores data In-Memory
• JVM Heap + Off-Heap
• Functions as a Distributed System, In-Memory Data Grid (IMDG)
• Pools system resources across multiple nodes in a cluster to manage both
application state and behavior
• Includes: Memory, CPU, Network & (optionally) Disk
• (optional) Stores data to Disk
• In OPLOGS | HDFS for Overflow & Persistence

Memory Management
Apache Geode manages memory using…
• Eviction: LRU
• Expiration: Time-To-Live (TTL), Idle Timeout (TTI)
• Auto resource management: critical/eviction HEAP % thresholds
• (Region) Data Compression: Snappy
• JVM/GC Tuning
10

Where to begin?
11
Data NodeData Node
Application
What about load?

Where to begin?
12
Data Node

Where to begin?
13
Locator
High read throughput What about writes?

Where to begin?
14
Locator
Partition
X
Y
Z
Partition
X
Y
Z
Partition
A
B
C
Partition
A
B
C
High read/write throughput What about
consistency?
Partition
X
Y
Z

Partition Region
15

Where to begin?
16
Locator
Partition
X
Y
Z
Partition
X
Y
Z
Partition
A
B
C
Partition
A
B
C
Partition
X
Y
Z
Partition
A
B
C
Partition
X
Y
Z

Network Partition Resolution
17

Apache Geode Topologies
18

Summary of Apache Geode
• Open Source
• In-Memory
• Distributed
• Scalable (scale-out)
• High Throughput & Low/Predictable Latency
• Highly Available
• Consistent
• Durable
• Fault Tolerant (resilient)
• Data-Aware / Parallel Compute
19

Other Features of Apache Geode
• Data Serialization (PDX, Java Serialization)
• Delta Propagation
• Transactions (Local & Global JTA-based TX)
• Querying (OQL) + Continuous Queries
• Functions (Stored Procedures)
• Native Client Support (C#/C++)
• REST API
• Management & Monitoring (JMX with Gfsh & Pulse)
• Security (Auth, Secure Transport with SSL, No Encryption)
• Statistics & Logging (Log4j)
20

Spring Data GemFire
21

“Simple things should be simple;
complex things should be possible”
– Alan Kay
22

Spring Data GemFire (SDG)
23
Applies Spring's powerful, non-invasive programming model to simplify
configuration and development of Apache Geode applications.
Spring Ecosystem Integration
– Spring Cache Abstraction / Transaction Management
– Spring Data Commons + REST
– Spring Integration (Inbound/Outbound Channel Adapters)
– Spring Session (coming soon)
– Spring XD (Sources & Sinks)

Apache Geode with Spring Data GemFire and Spring’s Cache
Abstraction is a JSR-107 (JCache) caching provider
24
+ +

Spring Data GemFire Use Cases
25
• Configure & Bootstrap Apache Geode
– Replacement for cache.xml; Can be used with Cluster Configuration
• Build an Application Peer Cache (Cache)
– Embedded Cache
• Build an Application Cache Client (ClientCache)
– Client/Server

Spring Data GemFire Features
• Pivotal GemFire / Apache Geode Configuration & Bootstrapping
• Spring Data Repositories
• CRUD + Querying (OQL) + (basic) POJO Mapping
• Annotated-based Function Implementation / Execution
• Transaction Management with Spring Transaction Infrastructure
• Exception Translation into Spring DAO Exception Hierarchy
• Register Interests & Continuous Querying Support
• JSON Region Proxies
• Data Snapshots Imports/Exports
• Client/Server Applications
• WAN Architecture Support
• GemFire / Geode caching provider support in Spring’s Cache Abstraction
26

Spring Data GemFire / Apache Geode Coordinates
27
<repository>
<id>spring-libs-snapshot</id>
<name>Spring Maven libs-snapshot Repository</name>
<url>https://repo.spring.io/libs-snapshot</url>
</repository>
<dependency>
<groupId>org.springframework.data</groupId>
<artifactId>spring-data-gemfire</artifactId>
<version>1.7.0.APACHE-GEODE-EA-SNAPSHOT</version>
</dependency>

Configuration & Bootstrapping
28

Configuring Apache Geode with Spring
29
XML Java-based Configuration

Bootstrapping Apache Geode with Spring
30
@SpringBootApplication
@ImportResource("/spring-gemfire-context.xml")
public class SpringGemFireApplication {
public static void main(String[] args) {
SpringApplication.run(SpringGemFireApplication.class, args);
}
}
gfsh>start server -–name=Example --spring-xml-location=
<classpath-to-spring-application-context.xml>

EXAMPLE
31

Spring Data GemFire in Action
Fast Foot Shoes Demo
32

Caching
41

Spring Cache Abstraction
Caching is useful in cases when an “expensive” operation (i.e. CPU, IO bound)
produces the same output given identical input; results can be reused.
Spring enables Declarative, Annotation-based Caching…
 @Cacheable – triggers cache population
 @CacheEvict – triggers cache eviction
 @CachePut – updates cache without interfering with method execution
 @Caching – groups multiple cache operations per method
 @CacheConfig – class-level cache-related settings

Spring Supports JSR-107 (JCache)
Spring JCache
@Cacheable @CacheResult
@CachePut @CachePut
@CacheEvict @CacheRemove
@CacheEvict(allEntries=true) @CacheRemoveAll
@CacheConfig @CacheDefaults
http://docs.spring.io/spring/docs/current/spring-framework-reference/htmlsingle/#cache-jsr-107

Apache Geode Caching Provider
@Configuration
@EnableCaching
@Import(GemFireConfiguration.class)
class ApplicationConfiguration {
@Bean
public CacheManager cacheManager(
Cache gemfireCache) {
GemfireCacheManager cacheManager =
new GemfireCacheManager();
cacheManager.setCache(gemfireCache);
return cacheManager;
}
}
<beans …
xmlns:cache=“http://www.springframework.org/schema/cach
e”…>
<gfe:cache properties-
ref="gemfireProperties"/>
<cache:annotation-driven/>
<bean id="cacheManager" class=
”o.s.data.gemfire.support.GemfireCacheManager"
p:cache-ref="gemfireCache"/>

EXAMPLE
45

What’s New – Annotation-based Expiration
46
@TimeToLiveExpiration(timeout=“@expirationSettings[‘spel-defined-timeout’]”, action=“DESTROY”)
@IdleTimeout(timeout=“300”, action=“${property.placeholder.defined.action}”)
class ApplicationDomainObject { .. }
<gfe:partitioned-region id="Example" persistent="false">
<gfe:custom-entry-ttl>
<bean class=“org.springframework.data.gemfire.support.AnnotationBasedExpiration”
factoryMethod=“forTimeToLive”/>
</gfe:custom-etnry-ttl>
<gfe:custom-entry-tti ref="ttiExpiration"/>
</gfe:partitioned-region>
<bean id="ttiExpiration" class=”….AnnotationBasedExpiration” factory-method="forIdleTimeout">
<constructor-arg ref="defaultExpirationAttributes"/>
</bean>
<bean id="defaultExpirationAttributes" class="com.gemstone.gemfire.cache.ExpirationAttributes">
<constructor-arg value="600"/>
<constructor-arg value="#{T(com.gemstone.gemfire.cache.ExpirationAction).DESTROY}"/>
</bean>
http://docs.spring.io/spring-data-gemfire/docs/current/reference/html/#bootstrap:region:expiration:annotation

What’s New – Annotation-based OQL
extensions
interface CustomerRepository extends GemfireRepository<Customer, Long> {
@Trace
@Limit(25)
@Import(“org.example.app.domain.Customer”)
@Hint({ “CustomerIdIdx”, “CustomerLastNameIdx” })
List<Customer> findByLastName(String lastName);
}
47
http://docs.spring.io/spring-data-gemfire/docs/current/reference/html/#gemfire-repositories.oql-extension

What’s New – Data Snapshot Imports/Exports
<gfe:cache/>
<gfe:partitioned-region id=“Users” persistent=“true” … />
<gfe:partitioned-region id=“GuestUsers” persistent=“false” … />
<gfe-data:snapshot-service id=“cacheSnapshotService”>
<gfe-data:snapshot-import location=“/path/to/users.zip”/>
<gfe-data:snapshot-export location=“/path/to/snapshot/directory”/>
</gfe-data:snapshot-service/>
<gfe-data:snapshot-service id=“guestUsersSnapshotService” region-ref=“GuestUsers”>
<gfe-data:snapshot-import location=“/path/to/users.snapshot”>
<bean class=“example.GuestUsersSnapshotFilter”/>
</gfe-data:snapshot-import>
<gfe-data:snapshot-export location=“/path/to/activeUsers.snapshot”
filter-ref=“activeUsersFilter”/>
</gfe-data:snapshot-service>
48
http://docs.spring.io/spring-data-gemfire/docs/current/reference/html/#bootstrap:snapshot

Presentation References
 Presentation Slides - http://www.slideshare.net/john_blum
 Configuration / Bootstrapping & Caching Example Source Code -
https://github.com/jxblum/scalable-spring-gemfire
 Fast Foot Shoes Example Source Code - https://github.com/Pivotal-Open-Source-
Hub/geode-demo-application

Apache Geode References
 Project Page - http://geode.incubator.apache.org/contribute/
 Community Events - http://geode.incubator.apache.org/community/
 Contribute - http://geode.incubator.apache.org/contribute/
– Ideas - https://cwiki.apache.org/confluence/display/GEODE/How+to+Contribute
 Documentation - http://geode.incubator.apache.org/docs/
– Docs Project - https://github.com/project-geode/docs
 Source Code - https://github.com/apache/incubator-geode
 JIRA - https://issues.apache.org/jira/browse/GEODE
 StackOverflow - http://stackoverflow.com/questions/tagged/gemfire+and+geode

Spring Data GemFire References
 Project Page - http://projects.spring.io/spring-data/
 Documentation –
– Reference Guide - http://docs.spring.io/spring-data-gemfire/docs/current/reference/html/
– API - http://docs.spring.io/spring-data-gemfire/docs/current/api/
– Spring IO Guides - http://spring.io/guides
– Spring GemFire Examples –
 Source Code - https://github.com/spring-projects/spring-data-gemfire
 Examples - https://github.com/spring-projects/spring-gemfire-examples
 JIRA – https://jira.spring.io/browse/SGF
 StackOverflow - http://stackoverflow.com/questions/tagged/spring-data-gemfire

Creative Commons Attribution-NonCommercial license: http://creativecommons.org/licenses/by-nc/3.0/ 52
Boot Your Search with Spring
12:45 – 14:15 - Salon M - Christoph Strobl
Learn More. Stay Connected.
@springcentral Spring.io/video

Creative Commons Attribution-NonCommercial license: http://creativecommons.org/licenses/by-nc/3.0/ 53
Spring Data REST – Data Meets Hypermedia + Security
14:30 – 16:00 – Salon M – Roy Clarkson & Greg Turnquist
Learn More. Stay Connected.
@springcentral Spring.io/video

Questions
54

Thank You
55

Building Highly Scalable Spring Applications using In-Memory Data Grids

Building Highly Scalable Spring Applications using In-Memory Data Grids

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