Thursday Nov 08, 2012

SPARC T4-4 Delivers World Record Performance on Oracle OLAP Perf Version 2 Benchmark

Oracle's SPARC T4-4 server delivered world record performance with subsecond response time on the Oracle OLAP Perf Version 2 benchmark using Oracle Database 11g Release 2 running on Oracle Solaris 11.

  • The SPARC T4-4 server achieved throughput of 430,000 cube-queries/hour with an average response time of 0.85 seconds and the median response time of 0.43 seconds. This was achieved by using only 60% of the available CPU resources leaving plenty of headroom for future growth.

Performance Landscape

Oracle OLAP Perf Version 2 Benchmark
4 Billion Fact Table Rows
System Queries/
hour
Users* Response Time (sec)
Average Median
SPARC T4-4 430,000 7,300 0.85 0.43

* Users - the supported number of users with a given think time of 60 seconds

Configuration Summary and Results

Hardware Configuration:

SPARC T4-4 server with
4 x SPARC T4 processors, 3.0 GHz
1 TB memory
Data Storage
1 x Sun Fire X4275 (using COMSTAR)
2 x Sun Storage F5100 Flash Array (each with 80 FMODs)
Redo Storage
1 x Sun Fire X4275 (using COMSTAR with 8 HDD)

Software Configuration:

Oracle Solaris 11 11/11
Oracle Database 11g Release 2 (11.2.0.3) with Oracle OLAP option

Benchmark Description

The Oracle OLAP Perf Version 2 benchmark is a workload designed to demonstrate and stress the Oracle OLAP product's core features of fast query, fast update, and rich calculations on a multi-dimensional model to support enhanced Data Warehousing.

The bulk of the benchmark entails running a number of concurrent users, each issuing typical multidimensional queries against an Oracle OLAP cube. The cube has four dimensions: time, product, customer, and channel. Each query user issues approximately 150 different queries. One query chain may ask for total sales in a particular region (e.g South America) for a particular time period (e.g. Q4 of 2010) followed by additional queries which drill down into sales for individual countries (e.g. Chile, Peru, etc.) with further queries drilling down into individual stores, etc. Another query chain may ask for yearly comparisons of total sales for some product category (e.g. major household appliances) and then issue further queries drilling down into particular products (e.g. refrigerators, stoves. etc.), particular regions, particular customers, etc.

Results from version 2 of the benchmark are not comparable with version 1. The primary difference is the type of queries along with the query mix.

Key Points and Best Practices

  • Since typical BI users are often likely to issue similar queries, with different constants in the where clauses, setting the init.ora prameter "cursor_sharing" to "force" will provide for additional query throughput and a larger number of potential users. Except for this setting, together with making full use of available memory, out of the box performance for the OLAP Perf workload should provide results similar to what is reported here.

  • For a given number of query users with zero think time, the main measured metrics are the average query response time, the median query response time, and the query throughput. A derived metric is the maximum number of users the system can support achieving the measured response time assuming some non-zero think time. The calculation of the maximum number of users follows from the well-known response-time law

      N = (rt + tt) * tp

    where rt is the average response time, tt is the think time and tp is the measured throughput.

    Setting tt to 60 seconds, rt to 0.85 seconds and tp to 119.44 queries/sec (430,000 queries/hour), the above formula shows that the T4-4 server will support 7,300 concurrent users with a think time of 60 seconds and an average response time of 0.85 seconds.

    For more information see chapter 3 from the book "Quantitative System Performance" cited below.

See Also

Disclosure Statement

Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 11/2/2012.

Improved Performance on PeopleSoft Combined Benchmark using SPARC T4-4

Oracle's SPARC T4-4 server running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved a world record 18,000 concurrent users experiencing subsecond response time while executing a PeopleSoft Payroll batch job of 500,000 employees in 32.4 minutes.

  • This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier.

  • The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment.

  • The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 47% (online and batch) leaving significant headroom for additional processing across the three tiers.

  • The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices.

Performance Landscape

Results are presented for the PeopleSoft HRMS Self-Service and Payroll combined benchmark. The new result with 128 streams shows significant improvement in the payroll batch processing time with little impact on the self-service component response time.

PeopleSoft HRMS Self-Service and Payroll Benchmark
Systems Users Ave Response
Search (sec)
Ave Response
Save (sec)
Batch
Time (min)
Streams
SPARC T4-2 (web)
SPARC T4-4 (app)
SPARC T4-4 (db)
18,000 0.988 0.539 32.4 128
SPARC T4-2 (web)
SPARC T4-4 (app)
SPARC T4-4 (db)
18,000 0.944 0.503 43.3 64

The following results are for the PeopleSoft HRMS Self-Service benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the payroll component.

PeopleSoft HRMS Self-Service 9.1 Benchmark
Systems Users Ave Response
Search (sec)
Ave Response
Save (sec)
Batch
Time (min)
Streams
SPARC T4-2 (web)
SPARC T4-4 (app)
2x SPARC T4-2 (db)
18,000 1.048 0.742 N/A N/A

The following results are for the PeopleSoft Payroll benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the self-service component.

PeopleSoft Payroll (N.A.) 9.1 - 500K Employees (7 Million SQL PayCalc, Unicode)
Systems Users Ave Response
Search (sec)
Ave Response
Save (sec)
Batch
Time (min)
Streams
SPARC T4-4 (db)
N/A N/A N/A 30.84 96

Configuration Summary

Application Configuration:

1 x SPARC T4-4 server with
4 x SPARC T4 processors, 3.0 GHz
512 GB memory
Oracle Solaris 11 11/11
PeopleTools 8.52
PeopleSoft HCM 9.1
Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031
Java Platform, Standard Edition Development Kit 6 Update 32

Database Configuration:

1 x SPARC T4-4 server with
4 x SPARC T4 processors, 3.0 GHz
256 GB memory
Oracle Solaris 11 11/11
Oracle Database 11g Release 2
PeopleTools 8.52
Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031
Micro Focus Server Express (COBOL v 5.1.00)

Web Tier Configuration:

1 x SPARC T4-2 server with
2 x SPARC T4 processors, 2.85 GHz
256 GB memory
Oracle Solaris 11 11/11
PeopleTools 8.52
Oracle WebLogic Server 10.3.4
Java Platform, Standard Edition Development Kit 6 Update 32

Storage Configuration:

1 x Sun Server X2-4 as a COMSTAR head for data
4 x Intel Xeon X7550, 2.0 GHz
128 GB memory
1 x Sun Storage F5100 Flash Array (80 flash modules)
1 x Sun Storage F5100 Flash Array (40 flash modules)

1 x Sun Fire X4275 as a COMSTAR head for redo logs
12 x 2 TB SAS disks with Niwot Raid controller

Benchmark Description

This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2.

The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published.

PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions.

All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions.

The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes.

The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state.

Key Points and Best Practices

  • Two PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning.

  • Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads.

  • A total of 128 PeopleSoft streams server processes where used on the database node to complete payroll batch job of 500,000 employees in 32.4 minutes.

See Also

Disclosure Statement

Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 8 November 2012.

About

BestPerf is the source of Oracle performance expertise. In this blog, Oracle's Strategic Applications Engineering group explores Oracle's performance results and shares best practices learned from working on Enterprise-wide Applications.

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