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Essbase and Exalytics Subtitle Kumar Ramiayer Sr. Director Essbase Development Steve Liebermensch Director, Product Management – Essbase October 2, 2014 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. |

Introducing X4-4 Subject to Change New Intel Processor – Designed for Oracle – Intel Xeon E v2 – 60 Cores (4*15) – Up to 1.8X throughput increase with the same software configuration Clock Speed range between GHz – Manually controlled or automated Memory and disk resources identical to X3-4 – 2 TB Memory, 2.4 TB Flash storage 4

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Exalytics X4-4 Uses “Designed for Oracle” Intel Processor – E v2 – An “All-In-One” CPU - Another major step for Exalytics as an Engineered Systems Has as much capacity as the largest E7 Processor (15C) – Larger scalability and consolidation Runs Faster than any other Intel 4 Socket Processor (3.6 GHz) – Faster single threaded performance for Essbase Addresses key Exalytics use cases – When high scalability is required, opt for more cores with reduced clock speed – When running batch processes with limited parallelism, opt for less cores with higher clock speed 5 15C 155W 2.8GHz 37.5M E v2 10C 155W 3.2GHz 37.5M 6C 155W 3.4GHz 37.5M E v2 E v2 15C 10C 6C 155W 2.8GHz 3.2GHz 3.4GHz max Turbo Freq 3.6GHz 37.5M E v2

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Exalytics Hardware Updates Exalytics X3-4 2TB RAM, 2.4TB Flash Exalytics X2-4 1TB RAM, 40 cores Q1FY14Q2FY14Q3FY14Q4FY14Q1FY15 Exalytics T5-8, Sparc 4TB RAM, 128 cores Exalytics X4-4 2TB RAM, 60 cores Q1FY15 PS5PS3PS4 6

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Software Updates 7

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Oracle 12c DBIM on Exalytics 8

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Oracle Database In-Memory and Exalytics 9 + = Awesome In-Memory Hardware Awesome In-Memory Database Analytics Nirvana Exalytics is the Fast Path to trying out DB 12c In-Memory Option

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | 12c DB In-Memory Option Certification on Exalytics Oracle Database and In-memory Option – Installation on Exalytics – OBIEE certification for 12c Summary Advisor Aggregate Persistence As a regular data source “In-memory Data Mart” TimesTen in offered parallel to 12c IMDB 10

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | HFM Certification HFM on Linux is coming with EPM PS4 Certified to run on Exalytics – Both bare metal and OVM configurations 11

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Essbase Enhancements Essbase becomes “Pure” in-memory engine as calculation will no longer wait for I/O (background write) In-Memory Aggregate Views for ASO Improved Resource management and CPU utilization – Thread management and thread based memory allocation – Fundamental improvement to Essbase infrastructure, will impact resource consumption, stability and performance. Leverage X4-4 capabilities by improving scalability 12

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Essbase Performance TPS Scalability Testing Identical version of Essbase – Based on an Hyperion Planning customer use case (BSO) 13 Exalytics X4 vs. X3 X3 X4 X3 X4 X3 X4 Exalytics X4 vs. X3

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Exalytics T5-8 Performance Software/Hardware Optimizations 14

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Exalytics T5-8 Performance Software/Hardware Optimizations 15

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Customer Results 16

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Why Exalytics Pure performance – Improve the uptime of my system – Increase the volume of data I can process during my update window – Allow users to iterate more times – Allow users to iterate over more data Total Cost of Ownership – Server consolidation – Reduced deployment time 17

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Hyperion Performance with Exalytics Examples of high performance gains with X improvement factor Operation Artifact DB Current timeExalyticsDesiredX Factor Calc ScriptTFCCalc1Fin RestructureFin ExportFin RestructureFin Calc ScriptAggFocusFin Calc ScriptTCalcFCCap Calc ScriptTFCAggWrkF Calc ScriptISAGGAllFin Calc ScriptCvAggallCap Calc ScriptWfAggAllWrkF

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Hyperion Performance with Exalytics Selected examples of high performance gains CurrentExalyticsX improvement Total Process AggLMAct AggLM Clear Upper Blocks Calc Restructure MyAggAll Note: Total Process is in hours; all other times are minutes.

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Exalytics POC Results Scenario # 6 – Query Testing Single QueryCurrentExalyticsX factor% Improve France Unit % North America Cons % Global Cons % Mexico Cons % Avg 25CurrentExalyticsX factor% Improve France Unit % North America Cons % Global Cons % Mexico Cons % Longest 25CurrentExalyticsX factor% Improve France Unit % North America Cons % Global Cons % Mexico Cons %

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Exalytics POC Results Scenario #Load / ConcurrencyOperation Type Notes on settings/fix statements/special cases, etc… Current time (hh:mm:ss) Exalytics (hh:mm)x Faster% Improve 11 CubeAggregation Aggregation process based on query tracking (based on 8 queries) 0:0:350:0: % 211 cube RebuildBuild/DataLoad Launch 11 Rebuilds from the LaunchPad 0:41:190:24: % 320 cube RebuildBuild/DataLoad Launch 20 Rebuilds from the LaunchPad 2:20:331:29: % 430 cube RebuildBuild/DataLoad Launch 30 Rebuilds from the LaunchPad 2:46:371:34: % 55 CubeAggregation Aggregation based on size (200% growth factor) 1:41:571:14: % 5a20 cubeAggregation Aggregation based on size (200% growth factor) 1:53:541:12: %

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Exalytics vs. Exalytics SPARC vs. Linux or T vs. X 22 X seriesT series LinuxSolaris 60 core Intel128 core SPARC 2TB RAM4TB RAM 3.6GHz max speed3.6GHz 2 IB, 4 10GBE, 2 16GB FC4 IB, 4 10GBE, 4 8GB FC 2.4 TB Flash6.4 TB Flash Platform specific optimizations

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Design Ethos Oracle Confidential – Highly Restricted23

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Developing Software for Exalytics Exalytics first – In place block writes Exalytics restricted – FixParallel Exalytics only – Chip/OS based optimizations Oracle Confidential – Highly Restricted24

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Engineering for Exalytics – Large Memory Challenge Platform and processor Number of Sockets Memory Speed (MHz) Local Memory (ns) 1-HOP remote (ns) 2-HOP remote (ns) 2S WSM-EP 3.3GHz NA 4S WSM-EX 2.4GHz NA 8S WSM-EX 2.4GHz S SNB-EP 2.9GHz NA 4S SNB-EP 2.7GHz Socket S1 10 cores with L1 and L2 cache 250 GB Memory Socket S1 10 cores with L1 and L2 cache 250 GB Memory Socket S1 10 cores with L1 and L2 cache 250 GB Memory Socket S1 10 cores with L1 and L2 cache 250 GB Memory Memory CPU SMP systems Multi-Socket Large Memory NUMA system Symmetric Multi-processing (SMP) System guarantees uniform memory latency for all CPU, but total memory is limited Multi-socket systems are needed for supporting large memory, but the memory latency is not uniform Complexity shifts from hardware to software In-memory analytics require all data in memory for processing How does the software utilize all the memory but all work faster?

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Engineering for Exalytics – NUMA Challenges Two engineering solutions – Use local socket memory in “critical parts of the software” by using thread affinity – Use padding to avoid false sharing – align important memory structures to cache lines Example -- use thread-affinity below to pin thread to a socket // Suppose thread is scheduled initially in Socket S1. Now memory gets allocated in Socket S1 int * p = (int*)malloc(1024*sizeof(int)); // Compute p[i] and store value in memory – latency 117 ns p[i] = a * b + 43 // perform I/O – thread yields Read_From_Disk_Storage(24); // Now do computation. Thread wakes up – but in a CPU that belongs to different socket – S2 // Accessing memory p[i] is now “remote” and it costs 176 ns T = p[i] * 32; // Insert the following code before I/O to // pin the thread to current CPU pthread_setaffinity_np(…)

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Engineering for Exalytics – High CPU CORE count Challenge Exalytics Software Use Cases – Large number of users performing fast and small workloads – Small number of users or single user performing a large highly parallelizable workload – Large and Legacy code and scripts that run sequentially but require faster CPU Engineering Solutions Adopted – Basic principles of semaphores, mutual exclusion and synchronization don’t help – Any locking is bad and leads to poor utilization of CPU cores – Lockless algorithms based on Intel hardware instructions (compare and swap) were designed and implemented – We need shared data structures for doing any useful applications, but sharing cannot be done using typical semaphores  use lockless algorithms to reduce contention

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | Q&A Oracle Confidential – Highly Restricted 28

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. |Oracle Confidential – Highly Restricted29