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Scalability Evaluation of the Replication Support of JOnAS,
an Industrial J2EEApplication Server
A. Paz, F. Pérez-Sorrosal, M. Patiño-Martínez, R. Jiménez-PerisR. Jiménez-Peris
Distributed Systems LaboratoryLsd
Universidad Politécnica de Madrid (UPM)
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EDCC 2010 - Valencia, Apr. 2010
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FocusReporting on the implementation of
replication protocol in an industrial application server, JOnAS, for J2EE-based multi-tier architectures
and its evaluation using the industrial benchmark for J2EE, SPEC AppServ.
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Replication Model
(App)
App. Data
(App) (App)
ReplicationProtocol
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Replication Protocol: Features
Multi-master/Update everywhereBased on eager replicationPreserves state/data consistency
Exactly-once semanticsTransparent replication via specialized
replication proxies.Suitable for J2EE environments, which
include:Transactional Service (JTA/JTS)Component Model: Enterprise Java Beans (EJBs)
Stateless (SLSB) and Stateful (SFSB) Session Beans, Entity Beans (EB) & Message-Driven (MDB)
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Replication Protocol
Each client session/request is encompassed in a TX (container managed transactions)
An invocation performs changes on client-related state (SFSFs) and persistent state (EBs)
At commit time...The client session state (SFSBs) is multicast to
the replicas acting as backups (FIFO Order)EBs are written to the shared DB
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Replication Protocol (II)To preserve exactly-once semantics...
As part of an update request, a marker (e.g. TX Id) is written in the shared DB with the returned response
When SFSBs are replicated, the marker and the response are attached to the message
In case of failover...The client connects to a new replicaIf client has not received a response from the
old primary...Resubmits the request to the new primaryThe new primary checks if the marker is present in
the DBIf present, it returns the stored result. Otherwise, it re-
executes the request
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Example
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Evaluation: SPECjAppServer 2004
Benchmark to compare J2EE AS implementations
Car Dealer Application DomainWorkload Generator injects load (IR) in the App.Clients = IR x 103 TX Types:
Browse Vehicle Catalog (50%) Read-onlyPurchase Vehicles (25%) Read-writeManage Dealer Inventory (25%) Read-write
Max. Response Time for requests (2 secs.)Throughput measured as TX/Sec.3 Phases: Ramp-up (4 Min) + Measure (10 Min) +
Cool-down (4 Min)
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Evaluation: EnvironmentHW Environment
Up to 10 nodesConnected through 100 MBps EthernetNode: 2xAMD Athlon 2GHz CPU, 1GB RAM, 2x320 GB
HDSW Environment
Fedora Core 3 OSApache 2.2.0 + MOD_JK (Load Balancing)Tomcat 5.5.17 Servlet ContainerJOnAS AS 4.8.1 (Baseline) and 4.8.5 (Rep. Service)Two DBMSs: PostgreSQL 8.2 and Oracle 10JGroups GCS
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Evaluation: Configuration
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Results: PostgreSQL Throughput
1 replica
no replication
2 replicas
3-6 replicas
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Results: Postgres Resp. Time(Browse)
1 replica
no replication
2-5 replicas
6 replicas
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Results: Oracle Throughput
1 replica
2 replicas
3 replicas
4 replicas
5-9 replicas
no replication
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Results: Oracle Resp. Time(Browse)
1 replicano
replication
2 replicas
3 replicas
4 replicas
5-9 replicas
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Results: Postgres Resp. Time(Purchase)
1 replica
no replication
2-5 replicas
6 replicas
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Results: Oracle Resp. Time(Purchase)
1 replicano
replication2 replicas
3 replicas
4-9 replicas
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Results: Postgres CPU Usage (No Replication IR=3 and 4)
ASDB
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Results: Postgres CPU Usage (1 Replica IR=3 and 4)
ASDB
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Results: Postgres CPU Usage (6 Replicas IR=3 and 4)
ASDB
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Results: Oracle CPU Usage (1 Replica With and WO Rep.
IR=8)
DBAS
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Results: Oracle CPU Usage (2 Replicas IR=13)
DB
AS
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ConclusionsWe have presented an experience
in implementing replication for an industrial J2EE application server, JOnAS,
evaluating the protocol with an industrial benchmark
Provides exactly-once semanticsThe evaluation has shown...
Scalability can be achieved in addition to HAThe database is the limiting factor for
scalability