TPC Benchmarks Charles Levine Microsoft [email protected] Western Institute of Computer Science Stanford, CA August 6, 1999 Outline Introduction History of TPC TPC-A/B Legacy TPC-C TPC-H/R TPC Futures Benchmarks: What and Why What is a benchmark?
Domain specific No single metric possible The more general the benchmark, the less useful it is for anything in particular. A benchmark is a distillation of the essential attributes of a workload Desirable attributes Relevant meaningful within the target domain Understandable Good metric(s) linear, orthogonal, monotonic Scaleable applicable to a broad spectrum of hardware/architecture Coverage does not oversimplify the typical environment Acceptance Vendors and Users embrace it Benefits and Liabilities
Good benchmarks Define the playing field Accelerate progress Engineers do a great job once objective is measureable and repeatable Set the performance agenda Measure release-to-release progress Set goals (e.g., 100,000 tpmC, < 10 $/tpmC) Something managers can understand (!) Benchmark abuse Benchmarketing Benchmark wars more $ on ads than development Benchmarks have a Lifetime
Good benchmarks drive industry and technology forward. At some point, all reasonable advances have been made. Benchmarks can become counter productive by encouraging artificial optimizations. So, even good benchmarks become obsolete over time. Outline Introduction History of TPC TPC-A Legacy TPC-C TPC-H/R TPC Futures What is the TPC?
TPC = Transaction Processing Performance Council Founded in Aug/88 by Omri Serlin and 8 vendors. Membership of 40-45 for last several years Everybody whos anybody in software & hardware De facto industry standards body for OLTP performance Administered by: Shanley Public Relations 650 N. Winchester Blvd, Suite 1 San Jose, CA 95128 ph: (408) 295-8894 fax: (408) 271-6648 email: [email protected] Most TPC specs, info, results are on the web page: http: www.tpc.org Two Seminal Events Leading to TPC
Anon, et al, A Measure of Transaction Processing Power, Datamation, April fools day, 1985. Anon = Jim Gray (Dr. E. A. Anon) Sort: 1M 100 byte records Mini-batch: copy 1000 records DebitCredit: simple ATM style transaction Tandem TopGun Benchmark DebitCredit 212 tps on NonStop SQL in 1987 (!) Audited by Tom Sawyer of Codd and Date (A first) Full Disclosure of all aspects of tests (A first) Started the ET1/TP1 Benchmark wars of 87-89 TPC Milestones
1989: TPC-A ~ industry standard for Debit Credit 1990: TPC-B ~ database only version of TPC-A 1992: TPC-C ~ more representative, balanced OLTP 1994: TPC requires all results must be audited 1995: TPC-D ~ complex decision support (query) 1995: TPC-A/B declared obsolete by TPC Non-starters: TPC-E ~ Enterprise for the mainframers TPC-S ~ Server component of TPC-C Both failed during final approval in 1996 1999: TPC-D replaced by TPC-H and TPC-R TPC vs. SPEC
SPEC (System Performance Evaluation Cooperative) SPEC ships code Unix centric CPU centric TPC ships specifications SPECMarks Ecumenical Database/System/TP centric Price/Performance The TPC and SPEC happily coexist
There is plenty of room for both Outline Introduction History of TPC TPC-A/B Legacy TPC-C TPC-H/R TPC Futures TPC-A Legacy First results in 1990: 38.2 tpsA, 29.2K$/tpsA (HP) Last results in 1994: 3700 tpsA, 4.8 K$/tpsA (DEC)
WOW! 100x on performance and 6x on price in five years!!! TPC cut its teeth on TPC-A/B; became functioning, representative body Learned a lot of lessons: If benchmark is not meaningful, it doesnt matter how many numbers or how easy to run (TPC-B). How to resolve ambiguities in spec How to police compliance Rules of engagement TPC-A Established OLTP Playing Field TPC-A criticized for being irrelevant, unrepresentative, misleading But, truth is that TPC-A drove performance, drove price/performance, and forced everyone to clean up their
products to be competitive. Trend forced industry toward one price/performance, regardless of size. Became means to achieve legitimacy in OLTP for some. Outline Introduction History of TPC TPC-A/B Legacy TPC-C TPC-D TPC Futures TPC-C Overview
Moderately complex OLTP The result of 2+ years of development by the TPC Application models a wholesale supplier managing orders. Order-entry provides a conceptual model for the benchmark; underlying components are typical of any OLTP system. Workload consists of five transaction types. Users and database scale linearly with throughput. Spec defines full-screen end-user interface. Metrics are new-order txn rate (tpmC) and price/performance ($/tpmC) Specification was approved July 23, 1992. TPC-Cs Five Transactions OLTP transactions:
New-order: enter a new order from a customer Payment: update customer balance to reflect a payment Delivery: deliver orders (done as a batch transaction) Order-status: retrieve status of customers most recent order Stock-level: monitor warehouse inventory Transactions operate against a database of nine tables. Transactions do update, insert, delete, and abort; primary and secondary key access. Response time requirement: 90% of each type of transaction must have a response time 5 seconds, except stock-level which is 20 seconds. TPC-C Database Schema Warehouse W Stock 100K W*100K W 100K (fixed) Legend
10 Table Name District one-to-many relationship W*10 secondary index 3K Customer W*30K Item Order 1+ W*30K+ 1+
2 Input screen 3 Output screen Cycle Time Decomposition (typical values, in seconds, for weighted average txn) Measure menu Response Time Menu = 0.3 Keying time Keying = 9.6 Measure txn Response Time Think time Txn RT = 2.1 Think = 11.4 Average cycle time = 23.4 Go back to 1
Data Skew NURand - Non Uniform Random NURand(A,x,y) = (((random(0,A) | random(x,y)) + C) % (y-x+1)) + x Customer Last Name: NURand(255, 0, 999) Customer ID: NURand(1023, 1, 3000) Item ID: NURand(8191, 1, 100000) bitwise OR of two random values skews distribution toward values with more bits on 75% chance that a given bit is one (1 - * ) skewed data pattern repeats with period of smaller random number NURand Distribution TPC-C NURand function: frequency vs 0...255 0.1 0.08 0.07 0.06 0.05
cumulative distribution 0.04 0.03 0.02 0.01 Record Identitiy [0..255] 250 240 230 220 210 200 190 180 170
10 0 0 Relative Frequency of Access to This Record 0.09 ACID Tests TPC-C requires transactions be ACID. Tests included to demonstrate ACID properties met. Atomicity Consistency Isolation
Verify that all changes within a transaction commit or abort. ANSI Repeatable reads for all but Stock-Level transactions. Committed reads for Stock-Level. Durability Must demonstrate recovery from Loss of power Loss of memory Loss of media (e.g., disk crash) Transparency TPC-C requires that all data partitioning be fully transparent to the application code. (See TPC-C Clause 1.6) Both horizontal and vertical partitioning is allowed All partitioning must be hidden from the application Most DBMSs do this today for single-node horizontal partitioning. Much harder: multiple-node transparency.
For example, in a two-node cluster: Any DML operation must be able to operate against the entire database, regardless of physical location. Warehouses: Node A Node B select * from warehouse where W_ID = 150 select * from warehouse where W_ID = 77 1-100 100-200 Transparency (cont.) How does transparency affect TPC-C?
Payment txn: 15% of Customer table records are non-local to the home warehouse. New-order txn: 1% of Stock table records are non-local to the home warehouse. In a distributed cluster, the cross warehouse traffic causes cross node traffic and either 2 phase commit, distributed lock management, or both. For example, with distributed txns: Number of nodes 1 2 3 n10.9 % Network Txns 0 5.5 7.3 TPC-C Rules of Thumb
1.2 tpmC per User/terminal (maximum) 10 terminals per warehouse (fixed) 65-70 MB/tpmC priced disk capacity (minimum) ~ 0.5 physical IOs/sec/tpmC (typical) 100-700 KB main memory/tpmC (how much $ do you have?) So use rules of thumb to size 5000 tpmC system: How many terminals? How many warehouses? How much memory? How much disk capacity? How many spindles? 4170 = 5000 / 1.2 417 = 4170 / 10 1.5 - 3.5 GB 325 GB = 5000 * 65 Depends on MB capacity vs. physical IO.
Capacity: 325 / 18 = 18 or 325 / 9 = 36 spindles IO: 5000*.5 / 18 = 138 IO/sec IO: 5000*.5 / 36 = 69 IO/sec TOO HOT! OK Typical TPC-C Configuration (Conceptual) Hardware Emulated User Load Driver System Presentation Services Term. LAN Client Database Functions C/S LAN Software Response Time measured here
Competitive TPC-C Configuration Today 40,013 tpmC; $18.86/tpmC; 5-yr COO= 754.7 K$ 4 GB memory, 252 9-GB disks & 225 4-GB disks (5.1 TB total) 8xPentium III Xeon 550MHz 32,400 users The Complete Guide to TPC-C In the spirit of The Compleat Works of Wllm Shkspr (Abridged) The Complete Guide to TPC-C:
First, do several years of prep work. Next, Install OS Install and configure database Build TPC-C database Install and configure TPC-C application Install and configure RTE Run benchmark Analyze results Publish Typical elapsed time: 2 6 months The Challenge: Do it all in the next 30 minutes! TPC-C Demo Configuration Emulated User Load Browser LAN Driver System Legend: Products Application Code Database Functions
Client DB Server Web Server UI APP COM+ Response Time measured here Remote Terminal Emulator (RTE) Presentation Services COMPONENT ODBC APP ODBC C/S LAN SQL Server New-Order Payment
Delivery Stock-Level Order-Status ... TPC-C Current Results - 1996 Best Performance is 30,390 tpmC @ $305/tpmC (Digital) Best Price/Perf. is 6,185 tpmC @ $111/tpmC (Compaq) $400 IBM $350 HP Digital $300 $250 $200 Sun $150
Compaq $100 $100/tpmC not yet. Soon! $50 $0 0 5000 10000 15000 20000 25000 30000 35000 TPC-C Current Results Best Performance is 115,395 tpmC @ $105/tpmC (Sun)
Best Price/Perf. is 20,195 tpmC @ $15/tpmC (Compaq) $160 C ompaq Sequent $140 IBM $120 Sun $100 HP $80 $60 $40 U nisys $20 $10/tpmC not yet. Soon! $0 0
Complex data: data attributes, size, skew Requires Transparency and ACID Full screen presentation services De facto standard for OLTP performance Preview of TPC-C rev 4.0 Rev 4.0 is major revision. Previous results will not be comparable; dropped from result list after six months. Make txns heavier, so fewer users compared to rev 3. Add referential integrity. Adjust R/W mix to have more read, less write. Reduce response time limits (e.g., 2 sec 90th %-tile vs 5 sec) TVRand Time Varying Random causes workload activity to vary across database Outline
Introduction History of TPC TPC-A/B Legacy TPC-C TPC-H/R TPC Futures TPC-H/R Overview Complex Decision Support workload Originally released as TPC-D Benchmark models ad hoc queries (TPC-H) or reporting (TPC-R)
extract database with concurrent updates multi-user environment Workload consists of 22 queries and 2 update streams the result of 5 years of development by the TPC SQL as written in spec Database is quantized into fixed sizes (e.g., 1, 10, 30, GB) Metrics are Composite Queries-per-Hour (QphH or QphR), and Price/Performance ($/QphH or $/QphR) TPC-D specification was approved April 5, 1995 TPC-H/R specifications were approved April, 1999 TPC-H/R Schema Customer Nation Region SF*150K 25
5 Order Supplier Part SF*1500K SF*10K SF*200K LineItem PartSupp SF*6000K SF*800K Legend: Arrows point in the direction of one-to-many relationships. The value below each table name is its cardinality. SF is the Scale Factor. TPC-H/R Database Scaling and Load
Database size is determined from fixed Scale Factors (SF): Database is generated by DBGEN 1, 10, 30, 100, 300, 1000, 3000, 10000 (note that 3 is missing, not a typo) These correspond to the nominal database size in GB. (i.e., SF 10 is approx. 10 GB, not including indexes and temp tables.) Indices and temporary tables can significantly increase the total disk capacity. (3-5x is typical) DBGEN is a C program which is part of the TPC-H/R specs Use of DBGEN is strongly recommended. TPC-H/R database contents must be exact. Database Load time must be reported
Includes time to create indexes and update statistics. Not included in primary metrics. How are TPC-H and TPC-R Different? Partitioning Indexes TPC-H: only on primary keys, foreign keys, and date columns; only using simple key breaks TPC-R: unrestricted for horizontal partitioning Vertical partitioning is not allowed TPC-H: only on primary keys, foreign keys, and date columns; cannot span multiple tables TPC-R: unrestricted
Auxiliary Structures What? materialized views, summary tables, join indexes TPC-H: not allowed TPC-R: allowed TPC-H/R Query Set 22 queries written in SQL92 to implement business questions. Queries are pseudo ad hoc: Substitution parameters are replaced with constants by QGEN QGEN replaces substitution parameters with random values No host variables No static SQL Queries cannot be modified -- SQL as written
There are some minor exceptions. All variants must be approved in advance by the TPC TPC-H/R Update Streams Update 0.1% of data per query stream Implementation of updates is left to sponsor, except: ACID properties must be maintained Update Function 1 (RF1) About as long as a medium sized TPC-H/R query Insert new rows into ORDER and LINEITEM tables equal to 0.1% of table size Update Function 2 (RF2)
Delete rows from ORDER and LINEITEM tables equal to 0.1% of table size TPC-H/R Execution Database Build Timed and reported, but not a primary metric Create DB Load Data Build Indexes Proceed directly to Power Test Build Database (timed) Power Test
Queries submitted in a single stream (i.e., no concurrency) Sequence: RF1 Query Set 0 Timed Sequence RF2 Proceed directly to Throughput Test TPC-H/R Execution (cont.) Throughput Test Multiple concurrent query streams Number of Streams (S) is determined by Scale Factor (SF) e.g.: SF=1 S=2; SF=100 S=5; SF=1000 S=7 Single update stream Sequence: Query Set 1
Query Set 2 .. . Query Set N Updates: RF1 RF2 RF1 RF2 RF1 RF2 1 2 N TPC-H/R Secondary Metrics Power Metric Geometric queries per hour times SF 3600 SF Power @ Size i 22 24 j 2
QI ( i , 0 ) RI ( j , 0 ) i 1 j 1 w h e re Q I(i,0 ) T im in g In te rv a l fo r Q u e ry i, s tre a m 0 R I(j,0 ) T im in g In te rv a l fo r re fre s h fu n c tio n R F j S F S c a le F a c to r Throughput Metric Linear queries per hour times SF TPC-R/H Primary Metrics Composite Query-Per-Hour Rating (QphH or QphR) The Power and Throughput metrics are combined to get the composite queries per hour. QphH @ Size Power @ Size Throughput @ Size
Reported metrics are: Composite: [email protected] Price/Performance: $/[email protected] Availability Date Comparability: Results within a size category (SF) are comparable. Comparisons among different size databases are strongly discouraged. TPC-H/R Results No TPC-R results yet. One TPC-H result: Sun Enterprise 4500 (Informix), 1280 [email protected],
816 $/[email protected], available 11/15/99 Too early to know how TPC-H and TPC-R will fare In general, hardware vendors seem to be more interested in TPC-H Outline Introduction History of TPC TPC-A/B TPC-C TPC-H/R TPC Futures Next TPC Benchmark: TPC-W
TPC-W (Web) is a transactional web benchmark. TPC-W models a controlled Internet Commerce environment that simulates the activities of a business oriented web server. The application portrayed by the benchmark is a Retail Store on the Internet with a customer browse-and-order scenario. TPC-W measures how fast an E-commerce system completes various E-commerce-type transactions TPC-W Characteristics TPC-W features: The simultaneous execution of multiple transaction types that span a breadth of complexity. On-line transaction execution modes. Databases consisting of many tables with a wide variety of sizes, attributes, and relationship.
Multiple on-line browser sessions. Secure browser interaction for confidential data. On-line secure payment authorization to an external server. Consistent web object update. Transaction integrity (ACID properties). Contention on data access and update. 24x7 operations requirement. Three year total cost of ownership pricing model. TPC-W Metrics There are three workloads in the benchmark, representing different customer environments. Primarily shopping (WIPS). Representing typical browsing, searching and ordering activities of on-line shopping. Browsing (WIPSB). Representing browsing activities with dynamic web page generation and searching activities. Web-based Ordering (WIPSO). Representing intranet and business to business secure web activities.
Primary metrics are: WIPS rate (WIPS), price/performance ($/WIPS), and the availability date of the priced configuration. TPC-W Public Review TPC-W specification is currently available for public review on TPC web site. Approved standard likely in Q1/2000 Reference Material Jim Gray, The Benchmark Handbook for Database and Transaction Processing Systems, Morgan Kaufmann, San Mateo, CA, 1991. Raj Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling, John Wiley & Sons, New York, 1991. William Highleyman, Performance Analysis of Transaction
Processing Systems, Prentice Hall, Englewood Cliffs, NJ, 1988. TPC Web site: www.tpc.org IDEAS web site: www.ideasinternational.com The End Background Material on TPC-A/B TPC-A Overview Transaction is simple bank account debit/credit Database scales with throughput Transaction submitted from terminal TPC-A Transaction Read 100 bytes including Aid, Tid, Bid, Delta from terminal (see Clause 1.3) BEGIN TRANSACTION Update Account where Account_ID = Aid: Read Account_Balance from Account Set Account_Balance = Account_Balance + Delta Write Account_Balance to Account Write to History: Aid, Tid, Bid, Delta, Time_stamp Update Teller where Teller_ID = Tid: Set Teller_Balance = Teller_Balance + Delta Write Teller_Balance to Teller Update Branch where Branch_ID = Bid:
Set Branch_Balance = Branch_Balance + Delta Write Branch_Balance to Branch COMMIT TRANSACTION Write 200 bytes including Aid, Tid, Bid, Delta, Account_Balance to terminal TPC-A Database Schema Branch B Teller B*10 10 100K Account History B*100K B*2.6M 10 Terminals per Branch row 10 second cycle time per terminal 1 transaction/second per Branch row Legend
Table Name one-to-many relationship TPC-A Transaction Workload is vertically aligned with Branch 15% of accounts non-local Produces cross database activity Whats good about TPC-A?
Makes scaling easy But not very realistic Easy to understand Easy to measured Stresses high transaction rate, lots of physical IO Whats bad about TPC-A? Too simplistic! Lends itself to unrealistic optimizations TPC-A Design Rationale Branch & Teller Account in cache, hotspot on branch too big to cache requires disk access History
sequential insert hotspot at end 90-day capacity ensures reasonable ratio of disk to cpu RTE SUT RTE - Remote Terminal Emulator SUT - System Under Test Emulates real user behavior Submits txns to SUT, measures RT Transaction rate includes think time Many, many users (10 x tpsA) All components except for terminal Model of system: SUT
RTE Host System(s) T T-C Network* T C L C-S Network* I E N T Response Time Measured Here S E R V
E R S-S Network* TPC-A Metric tpsA = transactions per second, average rate over 15+ minute interval, at which 90% of txns get <= 2 second RT Average Response Time 90th Percentile Response Time Number of Transactions 0 1 2 3 4 5
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Response time (seconds) TPC-A Price Price 5 year Cost of Ownership: hardware, software, maintenance Does not include development, comm lines, operators, power, cooling,
etc. Strict pricing model one of TPCs big contributions List prices System must be orderable & commercially available Committed ship date Differences between TPC-A and TPC-B TPC-B is database only portion of TPC-A TPC-B reduces history capacity to 30 days No terminals No think times Less disk in priced configuration TPC-B was easier to configure and run, BUT Even though TPC-B was more popular with vendors, it did not have much credibility with customers.
TPC Loopholes Pricing Client/Server Package pricing Price does not include cost of five star wizards needed to get optimal performance, so performance is not what a customer could get. Offload presentation services to cheap clients, but report performance of server Benchmark specials Discrete transactions Custom transaction monitors Hand coded presentation services
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