Performance and scalability of Informix ultimate warehouse edtion on Intel Xeon 7500 and E7 processors
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Performance and scalability of Informix ultimate warehouse edtion on Intel Xeon 7500 and E7 processors

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Talk at Information on Demand Conference 2011. As part of the Informix Ultimate Warehouse Edition, Informix ...

Talk at Information on Demand Conference 2011. As part of the Informix Ultimate Warehouse Edition, Informix
Warehouse Accelerator (IWA) transparently provides up to several
orders of a magnitude speed up in query performance for
Informix Dynamic Server (IDS), as well as enormous administrative
cost savings. Combined with the Intel Xeon E7 processor series,
Informix and the Accelerator brings the performance and
scalability of IDS solutions to new levels. This presentation will
give best practices and benefits of IWA and the Intel Xeon E7
processors, and highlight the implications and performance
benefits of running IDS and IWA on these processors, compared
to previous releases of IDS and prior Intel server platforms.

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Performance and scalability of Informix ultimate warehouse edtion on Intel Xeon 7500 and E7 processors Performance and scalability of Informix ultimate warehouse edtion on Intel Xeon 7500 and E7 processors Presentation Transcript

  • Performance and Scalability ofInformix® Ultimate Warehouse Editionon Intel Xeon® 7500 and E7 processorsSession Number 2864 Keshava Murthy, IBM® Jantz Tran, Intel®
  • Agenda• Intel Inside• IWA Overview• Key performance features in Intel• How IWA is exploiting the Intel features.• Performance results1
  • Tick-Tock Development Model Sustained Xeon® Microprocessor Leadership Tick Tock Tick Tock Tick Tock Tick Tock 65nm 45nm 32nm 22nm 00 y ridge ® 53 7400 7500 ® E7 Sand /EN Ivy B N Xeon 5100 X eon ® X eon ® X eon ® Xeon e-EP EP/E Bridg Intel® Core™ Nehalem/Westmere Sandy Bridge/Ivy Bridge Microarchitecture Microarchitecture Microarchitecture First high-volume server Quad- Up to 10 cores Up to 8 cores Core CPUs and 20MB Cache and 30MB Cache Integrated memory controller Dedicated high- Integrated PCI Express with DDR3 support speed bus per CPU Turbo Boost 2.0 Turbo Boost, Intel HT, AES- 1 HW-assisted NI Intel Advanced Vector virtualization (VT-x) Extensions (AVX) End-to-end HW-assisted virtualization (VT-x, -d, -c)2
  • Intel Xeon Processor ® ® Family for Business Scalable Intel® Xeon® processor E7 platforms Enterprise Scalable (up to 256-way), reliable, powerful 64-bit multi-core servers offering industry- leading performance, expanded memory & I/O capacity, and advanced reliability ideal for Mainstream Top-of-the-line performance, the most demanding enterprise and mission critical workloads, large scale virtualization and Enterprise large-node HPC applications. scalability, and reliability Best combination of performance, power efficiency, Intel® Xeon® processor 5000 sequence platforms (E5 in 2012) and costSmall Mission Critical Versatile (up to 2-way) servers for all your infrastructure, high-density, workstationthe most and HPCBusiness Enterprise Server optimal performancePerformance and reliability forfor the applications with features that enable business critical efficiency outstanding and power workloads with data center. Versatility for infrastructure apps (up to 4S) economicsEconomical and more Cloud Computing Cloud Computingdependable vs. desktop Efficient, secure, and open platforms for Highest virtualization density and advanced Intel® Xeon® processor 3000 and IAAS Internet datacenters sequence platforms (E3 in 2012) reliability for private cloudEntry Servers andEconomical (1-way) dependable general purpose 64-bit servers well-suited for small High Performance Computing & High Performance ComputingWorkstations businesses and education with features that optimize performance, uptime, and security WorkstationsMore features and performance than Bandwidth-optimized for high Greater scaling and memory capacitytraditional desktop systems performance analytics & visualization Increasing capability
  • Intel® Xeon® ProcessorE7-8800/4800/2800 Product FamiliesBuilding on Xeon® 7500 Leadership Capabilities More Performance More Expandable • 10 cores / 20 threads • Supports 32GB DDR3 DIMMs (2TB per 4-socket system)1 • 30MB of last level cache More Security & RAS E7-4800 E7-4800 More Efficient SECURITY • More performance within same max CPU TDP as Xeon • Intel® Advanced Encryption 7500 Standard-New Instructions E7-4800 E7-4800 • Lower partial active & idle • Intel® Trusted Execution power via Intel Intelligent Technology (TXT) Power Technology2 • Support for Low Voltage- RELIABILITY, AVAILABILITY, SERVICEABILITY DIMMs3• Enhanced DRAM Double Device Data Correction • Reduced power memory • Fine Grained Memory Mirroring buffers4 Delivers more Performance, Expandability and RAS while improving Energy Efficiency 1. Up to 64 slots per standard 4 socket system x 32GB/DIMM = 2TB 2. Uses similar core and package C6 power states enabled on Intel Xeon 5500/5600 series processors. Requires OS support. 3. Savings dependent on workload and configuration. 4. Memory buffer power savings of up to 1.3W active and 3W idle per buffer per Intel estimates. Slightly more savings when used with LV DIMMs
  • Advantages of the Xeon® E7 Platform 4-socket systems can… …process the biggest workloads…maximize consolidation …increase system uptime…handle highly variable workloads Intel ® Xeon® Processor E7-4800 Product Family vs. Xeon® Processor 5600 Series Large Workloads Mission Critical Class System Highly Variable Workloads & Max. Consolidation Availability Over 2X the compute performance Protects your data by preventing across a range of benchmarks1 More performance headroom to handle peak, errors unexpected, or underestimated workloadsUp to 7X memory capacity for greater Increased availability via healing,performance, headroom and memory Compute, memory and I/O scalability extends redundancy and failover DIMM savings2 useful server life in high-growth workloads technologies Up to 2X higher consolidation3 Denser compute resources per server Minimized downtime via failure maximizes performance in constrained sites prediction and proactive replacement of failing components Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark andMobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products.1. Results have been estimated based on internal Intel analysis and are provided for informational purposes only. Any difference in system hardware or software design or configuration may affect actual performance. For more information on performance tests and on the performance of Intel products, visit http://www.intel.com/performance/resources/limits.htm2. 64 DIMM slots vs. 18 slots for the Xeon 5600 processor series platform3. 2X higher consolidation refresh ratio based on ROI tool comparing Xeon 7500 and Xeon 5600 vs.. older generations.
  • Advanced Reliability Starts With Silicon Intel® Xeon® processor E7 family RAS Capabilities Memory I/O Hub CPU/Socket • Inter-socket Memory Mirroring • Physical IOH Hot Add • Machine Check Architecture Machine Check Architecture (MCA) ® • Intel® Scalable Memory • OS IOH On-lining* recovery (MCA-R) (MCA) recovery (MCA-R) Interconnect (Intel® SMI) Lane • PCI-E Hot Plug • Corrected Machine Check Interrupt Failover (CMCI) ® • Intel® SMI Clock Fail Over • Corrupt Data Containment Mode • Intel® SMI Packet Retry ® • Viral Mode • Memory Address Parity • OS Assisted Processor Socket • Failed DIMM Isolation Migration* • Memory Board Hot Add/Remove • OS CPU on-lining * • Dynamic Memory Migration* • CPU Board Hot Add at QPI • OS Memory On-lining * • Electronically Isolated (Static) • Recovery from Single DRAM Partitioning Device Failure (SDDC) plus • Single Core Disable for Fault random bit error Resilient Boot • Memory Thermal Throttling • Demand and Patrol scrubbing • Fail Over from Single DRAM Intel® QuickPath Interconnect Device Failure (SDDC) • Enhanced DRAM Double Device • Intel QPI Packet Retry Data Correction • Intel QPI Protocol Protection via • Fine Grained Memory Mirroring CRC (8bit or 16bit rolling) • Memory DIMM and Rank Sparing • QPI Clock Fail Over • Intra-socket Memory Mirroring • QPI Self-Healing • Mirrored Memory Board Hot Add/Remove Advanced reliability features work to maintain data integrity6
  • ® ®Intel Xeon processor E5-2600 product family (Sandy Bridge-EP)New micro-architecture on the 32nm process technology Higher performance Platform Features More Efficient Lower platform power1 Up to 8 cores, 20 MB cache New Intel® Advanced Vector Extensions Optimized Turbo Boost Technology Optimized Turbo Boost More Intelligent Intel Node Manager Sandy Bridge-EP enhancements QPI Up to Intel AES-NI improvements 2 QPI Up to More Secure More robust Intel TXT solutions links 4 channels between DDR3 1600 Up to 8 Cores CPUs memory Optimized platforms for: Integrated PCI Express* 3.0 Up to 40 lanes per socket More Options Performance Smaller Form Factors Best value 1 Lower platform power claim based on a Xeon® 5600 CPU and Sandy Bridge-EP CPU with the same TDP specification and comparable platform configurations. Platform power reduction is primarily attributed to TDP reduction from a two-chip solution based on the Intel 5520 chip set and ICH-10R, down to a one-chip south bridge solution(Patsburg chip) on the Sandy Bridge platform.
  • INTEL: Breakthrough technologies for performance 7. Multi-core, multi-node environment 1. Large memory support Nehalem has 8 cores and Westmere 10 cores. This 64-bit computing; System X with MAX5 supports up trend is expected to continue. to 6TB on a single SMP box; Up to 640GB on each node of blade center. 6. Single Instruction Multiple Data 2. Large on-chip Cache Specialized instructions for manipulating L1 cache 64KB per core, L2 cache is 256KB per 128-bit data simultaneously. 7 7 1 1 core and L3 cache is about 24-30 MB. Additional Translation lookaside buffer (TLB). 6 6 2 2 5 5 3 3 5. Hyperthreading 4 4 3. Frequency Partitioning 2x logical processors; increases Enabler for the effective parallel access of processor throughput and overall the compressed data for scanning. performance of threaded software. Horizontal and Vertical Partition Elimination. 4. Virtualization Performance Lower overhead: Core micro-architecture enhancements, EPT, VPID, and End-to-End HW assist8
  • Intel® Xeon® E7 Processor Architecture Core 0 L1 L2 L2 L1 Core 5 Core 1 L1 L2 L2 L1 Core 6 Cache Architecture Core 2 L1 L2 Shared L3 L2 L1 Core 7 •64K L1 Cache Core 3 L1 L2 L2 L1 Core 8 •256K L2 Cache Core 4 L1 L2 L2 L1 Core 9 •30MB 10 slice shared Last Level cache (L3) (compared to 24MB 8 slice L3 on Xeon® 7500) IMC IMC QPI (4 Links) • 2 integrated memory controllers • Scalable Memory Interconnect (SMI) with support for up to 8 DDR channels • 4 Quick Path Interconnect (QPI) system interconnect links9
  • Intel QuickPath Architecture•Connectivity – Fully-connected by 4 Intel® QuickPath – interconnects per socket MB MB – 6.4, 5.86, or 4.8 GT/s on all links MB MB 7500/E7 CPU 7500/E7 CPU MB MB MB MB – With 2 IOHs: 82 PCIe lanes (72 Gen2 Boxboro lanes + 4 Gen1 lanes on unused ESI port + 6 Gen1 ICH10 lanes) MB MB MB MB 7500/E7 CPU 7500/E7 CPU MB MB – PCE-E Gen 2.0 MB MB Intel® QuickPath interconnects•Memory Boxboro Boxboro – Registered DDR3 800/1066 MHz via on- board memory buffer – 64 DIMM support (4:1 DIMM to buffer ratio)
  • Intel® Xeon® 7500/E7 8 Socket Configuration 4+4 (8S) IBM® System x3850 X5 Up to 10 cores and 2.4 Ghz per CPU Support 8 socket mode by combining 2 systems via external QPI links Memory Configuration 4TB in 8 socket server 6TB in 8 socket + MAX5 Continued 1066MHz support11
  • Intel®: SIMD – Single Instruction Multiple Datatechnology• The Intel Xeon® E7 processor supports up to SSE 4.2 • SIMD capabilities will be expanded to 256-bit registers with the new AVX instruction set in the upcoming Intel® Xeon® E5 series processors• Informix leverages SSE in the Warehouse Accelerator
  • Intel® Xeon® Processors: Virtualization Performance Greater Virtualization Virtualization Performance2 Efficiency: VMmark* Performance Intel QPI DDR3 Memory bandwidth and capacity Intel® VT VT-x VT-d VT-c 1 Best published VMmark results as of 20 October 2010. See legal information slide, speaker notes and backup foils (if needed) for notes and disclaimers. Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products.
  • Third Generation of Database Technology According to IDC’s Article (Carl Olofson) – Feb. 2010 1st Generation: - Vendor proprietary databases of IMS, IDMS, Datacom 2nd Generation: - RDBMS for Open Systems, dependent on disk layout, limitations in scalability and disk I/O - Database tuning by adding updating stats, creating/dropping indexes, data partitioning, summary tables & cubes, force query plans, resource governing 3rd Generation: IDC Predicts that within 5 years: • Most data warehouses will be stored in a columnar fashion • Most OLTP database will either be augmented by an in-memory database (IMDB) or reside entirely in memory • Most large-scale database servers will achieve horizontal scalability through clustering14
  • Informix Warehouse Accelerator IBM Smart AnalyticsStep 1. Install, configure, Studiostart InformixStep 2. Install, configure, Step 3start Accelerator Step 1Step 3. Connect Studio toInformix & add accelerator Step 4 Informix Database ServerStep 4. Design, validate,Deploy Data mart Step 5Step 5. Load data toacceleratorReady for Queries BI Applications Step 2 Ready Informix warehouse Accelerator15
  • Informix Warehouse Accelerator 3rd Generation Database Technology is Here How is it different? What is it? • Performance: Unprecedented response The Informix Warehouse Accelerator (IWA) is a times to enable train of thought analysis workload optimized, appliance-like, add-on, that enables frequently blocked by poor query the integration of business insights into operational performance. processes to drive winning strategies. It accelerates • Integration: Connects to IDS through deep select queries, with unprecedented response times. integration providing transparency to all applications. • Self-managed workloads: queries are executed in the most efficient way • Transparency: applications connected to IDS, are entirely unaware of IWA • Simplified administration: appliance-like hands-free operations, eliminating many database tuning tasks Breakthrough Technology Enabling New Opportunities16
  • 17
  • IWA Software Components • Linux on Intel x86_64 (RHEL 5 or SUSE SLES 11) • IDS 11.70 + IWA code modules including IDS Stored Procedures – Linux on Intel (64 bit) – AIX on Power (64 bit) – HPUX on Itanium (64 bit) – Solaris on Sparc (64bit) • ISAO Studio Plug-in – GUI for Mart definition • OnIWA – On Utilities for Monitoring IWA18
  • INTEL/IWA: Breakthrough technologies for performance 7. Multi-core, multi-node environment 1. Large memory support Nehalem has 8 cores and Westmere 10 cores. This trend is 64-bit computing; System X with MAX5 supports up expected to continue. IWA: Parallelize the scan, join, group to 6TB on a single SMP box; Up to 640GB on each operations. Keep copies of dimensions to avoid cross-node node of blade center. IWA: Compress large dataset synchronization. and keep it in memory; totally avoid IO.6. Single Instruction Multiple DataSpecialized instructions for manipulating 2. Large on-chip Cache128-bit data simultaneously. IWA: L1 cache 64KB per core, L2 cache is 256KB perCompresses the data into deep columnar 7 7 1 1 core and L3 cache is about 4-12 MB.fashion optimized to exploit SIMD. Used in Additional Translation lookaside buffer (TLB).parallel predicate evaluation in scans. 6 6 2 2 IWA: New algorithms to avoid pipeline flushing and cache hash tables in L2/L3 cache 5 5 3 35. Hyperthreading 4 4 3. Frequency Partitioning2x logical processors; increases processor IWA: Enabler for the effective parallel accessthroughput and overall performance of threaded of the compressed data for scanning.software. IWA: Does not exploit this since the Horizontal and Vertical Partition Elimination.software is written to avoid pipeline flushing. 4. Virtualization Performance Lower overhead: Core micro-architecture enhancements, EPT, VPID, and End-to-End HW assist IWA: Helps informix and IWA to seemlessly run and perform in virtualized environment.19
  • IWA: Multi-core and Multi-node environment Step 1. Submit SQL DB protocol: SQLI or DRDA Informix Network : TCP/IP,SHM Applications 2. Query matching and BI Tools redirection technology Local Step 5. Return results/describe/error Execution Database protocol: SQLI or DRDA Network : TCP/IP, SHM Step 3 Step 4 offload SQL. Results: DRDA over TCP/IP DRDA over TCP/IP Coordinator Worker Worker Worker Worker Compressed Compressed Compressed Compressed data data data data In memory In memory In memory In memory Memory Memory Memory image image on disk Memory image on disk on disk image on disk20
  • IWA: Multi-core and Multi-node environment Step1 SQL from Informix Step5: Send the results back to Infomrix server Step2 Send the queries to all the Step4: merge intermediate workers Coordinator results, ORDER BY, FIRSTN Worker Worker Worker Worker Compressed data Compressed data Compressed data Compressed data In memory In memory In memory In memory Step3: Scan, Filter, Step3: Scan, Filter, Step3: Scan, Filter, Step3: Scan, Filter, join, group join, group join, group join, group21
  • IWA: Multi-core and Multi-node environment Dictionaries Dictionaries Query Executor Cell 3 core + $ (HT) core + $ (HT) Compressed and Cell 1 core + $ (HT) core + $ (HT) Partitioned Data Cell core + $ (HT) core + $ (HT) 2 • Cell is also the unit of processing, each cell… – Assigned to one core – Has its own hash table in cache (so no shared object that needs latching!) • Main operator: SCAN over compressed, main-memory table – Do selections, GROUP BY, and aggregation as part of this SCAN – Only need de-compress for aggregation • Response time ∝ (database size) / (# cores x # nodes) – Embarrassing Parallelism – little data exchange across nodes
  • Expoloiting Larger Memory: Row Oriented Data StoreEach row stored sequentially • Optimized for record I/O • Fetch and decompress entire row, every time • Result – • Very efficient for transactional workloads • Not always efficient for analytical workloads If only few columns are required the complete row is still fetched and uncompressed23
  • Expoloiting Larger Memory: Data is Processed in Compressed Format • Within a Register – Store, several columns are grouped together. • The sum of the width of the compressed columns doesn‘t exceed a register compatible width. This utilizes the full capabilities of a 64 bit system. It doesn‘t matter how many columns are placed within the register – wide data element. • It is beneficial to place commonly used columns within the same register – wide data element. But this requires dynamic knowledge about the executed workload (runtime statistics). • Having multiple columns within the same register – wide data element prevents ANDing of different results. Predicate evaluation is done against compressed data! The Register – Store is an optimization of the Column – Store approach where we try to make the best use of existing hardware. Reshuffeling small data elements at runtime into a register is time consuming and can be avoided. The Register – Store also delivers good vectorization capabilities.24
  • Exploiting Large memory: Compression: Frequency Partitioning Trade Info (volume, product, Column Partitions origin country) Histogram Occurrences Number of Vol Prod Origin on Origin China GER, USA FRA, … Rest Common Rare Values values Origin Top 64 traded goods Cell Cell 3 Cell 4 – 6 bit code 1 Product Cell 2 Cell 5 Cell 6 Rest Histogram on Product Table partitioned into Cells • Field lengths vary between cells • Higher Frequencies  Shorter Codes (Approximate Huffman) • Field lengths fixed within cells25
  • IWA: SIMD: Register Stores Facilitate SIMD Parallelism• Access only the banks referenced in the query (like a column store): –SELECT SUM (T.G) –FROM T –WHERE T.A > 5 –GROUP BY T.D• Pack multiple rows from the same bank into the 128-bit register• Enables yet another layer of parallelism: SIMD (Single-Instruction, Multiple-Data)! A1 D1 G1 B1 E1 F1 C1 H1 Cell Block A2 D2 G2 B2 E2 F2 C2 H2 Operand 32 bits Operand 32 bits Operand 32 bits Operand 32 bits A3 D3 G3 B3 E3 F3 C3 H3 Vector Operation A4 D4 G4 B4 E4 F4 C4 H4 Result1128 bits Result2 Result3 Result Bank β3 4 Bank β1 (32 bits) Bank β2 (32 bits) (16 bits)26
  • IWA:SIMD: Simultaneous Evaluation of Equality Predicates • CPU operates on 128-bit units State==‘CA’ && Quarter == ‘Q4’ • Lots of fields fit in 128 bits Translate value query • These fields are at fixed offsets to Code query • Apply predicates to all columns State==01001 && Quarter==1110 simultaneously! State Quarter … … … … Row & 11111 0 1111 0 Mask == Selection 01001 0 1110 0 result27
  • Exploiting Large on-chip Cache•Encoding makes grouping simple! –Coded values assigned densely (by construction) –Hence, in principle, grouping is simple: aggTable[group] += aggValue•Challenges: –Fitting hash table in L2 cache –Avoiding all branches in hash table lookup•IWA adaptively uses one of 2 techniques, depending on # of distinct groups 1.Use dictionary code as a perfect hash (i.e. collision-free), OR •aggTable[groupCode] += aggValue •No branches, no hash function computation •Works great if groupCode is dense – i.e., single column, or multiple column with little correlation 2.Use usual linear probing •Involves branches, random access, …
  • Case Study #1: U.S. Government Agency29
  • Case Study #2: Datamart at a Government Agency • Microstrategy report was run, which generates • 667 SQL statements of which 537 were Select statements • Datamart for this report has 250 Tables and 30 GB Data size • Original report on XPS and Sun Sparc M9000 took 90 mins • With IDS 11.7 on Linux Intel box, it took 40 mins • With IWA, it took 67 seconds.30
  • Case Study #3: Skechers, USA. Shoe Retailer • Top 7 time-consuming queries in Retail BI and Warehouse: (Against 1 Billion rows Fact Tables) Query IDS 11.5 IDS 11.7 IWA 1 22 mins 4 secs 2 1 min 3 secs 2 secs 3 3 mins 40 secs 2 secs 4 30 mins & up 4 secs 5 2 mins 2 secs 6 30 mins 2 secs 7 45 mins & up 2 secs Query acceleration 30x to 1400x – average acceleration 450x31
  • Systems Tested • 4S Intel® Xeon® 7560 (whitebox) – 2.26 GHz 8C CPU • 4S Intel® Xeon® E7 4870 (whitebox) – 2.40 GHz 10C CPU – 256GB 1066GHz DDR3 memory • 8S Intel® Xeon® E7 7560 (IBM® System x3850 X5) – 2.26 GHz 8C CPU – 2TB 1066GHz DDR3 memory32
  • POPS schema daily_sales Customer Product 350 million rows Store Promotion daily_forecast Period 1 billion rows33
  • Systems Tested • 8S Intel® Xeon® E7 7560 (IBM® System x3850 X5) – 2.26 GHz 8C CPU – 2TB 1066GHz DDR3 memory37
  • 500 GB SSEDStore Sales ER-Diagram 73,049 402 204,000 4,594,771,672 86,400 1000 1,920,800 1,000,000 7200 20 2,000,000
  • IWA2 IWA3 IWA4 IWA AVG IDS1 IDS2 IDS3 IDS AVG Improvement 109046 104246 92653 97666 100902.75 3294554 3338352 3341873 3324926.333 3295.179104 31190 27175 26927 27417 28177.25 1538219 1538364 1538959 1538514 5460.128295 93377 97192 95638 92691 94724.5 1910772 1884782 1899916 1898490 2004.222772 119587 117053 117513 117902 118013.75 1765145 1722746 1690400 1726097 1462.623635 37587 33551 35579 31651 34592 3167302 3173656 3150876 3163944.667 9146.463537 28228 29301 24602 29846 27994.25 1525738 1526089 1528724 1526850.333 5454.156955 27644 28075 30083 29362 28791 2201956 2211549 2517291 2310265.333 8024.262212 119871 123030 123593 117572 121016.5 5963515 6044626 5947525 5985222 4945.790037 38346 46412 44463 44918 43534.75 1578035 1557525 1544912 1560157.333 3583.705737 48450 46470 50032 43668 47155 1526529 1547404 1563874 1545935.667 3278.413035 43823 42441 45837 43215 43829 21990513 22354449 21903105 22082689 50383.73908 47400 46582 46573 47031 46896.5 2251672 2278167 2281946 2270595 4841.715267 56961 58315 56437 60119 57958 5295930 5310507 5325095 5310510.667 9162.687923 9037 9132 8724 9083 8994 2523942 2529234 2522585 2525253.667 28077.09214 47062 52354 51374 49932 50180.5 1546319 1570163 1568083 1561521.667 3111.8097 47643 50415 55660 52788 51626.5 2274649 2264463 2269677 2269596.333 4396.184776 85154 85711 83824 91692 86595.25 1620173 1656098 1606029 1627433.333 1879.356354 59766 59341 55436 58522 58266.25 5311906 5307202 5266918 5295342 9088.18055 8230 8207 8054 8115 8151.5 2159777 2179435 2181312 2173508 26663.90235 152764 152408 149153 151100 151356.25 2050590 2065049 2060862 2058833.667 1360.256789 30991 29582 27391 24197 28040.25 2025557 2037336 2040515 2034469.333 7255.532077 141504 145702 142908 139664 142444.5 5363204 5165693 5393336 5307411 3725.9501071383661 1392695 1372454 1368151 1379240.25 79262889 ArithMean 8936.42511
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