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Benchmarking Cloud Serving Systems with YCSB Brian F. Cooper, Adam Silberstein, Erwin Tam, Raghu Ramakrishnan, Russell Sears Yahoo! Research Presenter.

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Presentation on theme: "Benchmarking Cloud Serving Systems with YCSB Brian F. Cooper, Adam Silberstein, Erwin Tam, Raghu Ramakrishnan, Russell Sears Yahoo! Research Presenter."— Presentation transcript:

1 Benchmarking Cloud Serving Systems with YCSB Brian F. Cooper, Adam Silberstein, Erwin Tam, Raghu Ramakrishnan, Russell Sears Yahoo! Research Presenter Duncan

2 Benchmarking Cloud Serving Systems with YCSB Benchmarking vs Testing Any difference? My opinion – Benchmarking: Performance – Testing: usability test, security test, performance etc…

3 Motivation A lot of new systems in Cloud for data storage and management – MongoDB, MySQL, Asterix, etc.. Tradeoff – E.g. Append update to a sequential disk-log Good for write, bad for read – Synchronous replication copies up to date, but high write latency How to choose? – Use benchmark to model your scenario!

4 Evaluate Performance =? Latency – Users don’t want to wait! Throughput – Want to serve more requests! Inherent tradeoff between latency and throughput – More requests => more resource contention=> higher latency

5 Which system is better? “ Typically application designers must decide on an acceptable latency, and provision enough servers to achieve the desired throughput ” achieve the desired latency and throughput with fewer servers. – Desired latency:0.1 sec, 100 request/sec – MongoDB, 10 server – Asterix DB, 15 server

6 What else to evaluate? Cloud platform Scalability – Good scalability=>performance proportional to # of servers Elasticity – Good elasticity=>performance improvement with small disruption

7 A Short Summary Evaluate performance = evaluate latency, throughput, scalability, elasticity A better system= less machine to achieve the performance goal

8 YCSB Data generator Workload generator YCSB client – Interface to communicate with DB

9 YCSB Data Generator A table with F fields and N records Each field => a random string E.g. 1,000 byte records, F=10, 100 bytes per field

10 Workload Generator Basic operations – Insert, update, read, scan – No join, aggregate etc. Able to control the distributions of: Which operation to perform – E.g. 0.95 read, 0.05 update, 0 scan => read-heavy workload Which record to read or write – Uniform – Zipfian: some records are extremely popular – Latest: recent records are more popular

11 YCSB Client A script – Use the script to run the benchmark Workload parameter files – You can change the parameter Java program DB interface layer – You can implement the interface for your DB system

12 Experiments Experiment Setup: – 6 servers – YCSB client on another server – Cassandra, HBase, MySQL, PNUTS Update heavy, read heavy, read only, read latest, short range scan workload.

13 Future Work Availability – Impact of failure on the system performance Replication – Impact to performance when increase replication

14 4 criteria Author’s 4 criteria for a good benchmark: – Relevance to application – Portability Not just for 1 system! – Scalability Not just for small system, small data! – simplicity

15 Reference Benchmarking Cloud Serving Systems with YCSB, Brian F. Cooper, Adam Silberstein, Erwin Tam, Raghu Ramakrishnan, Russell Sears, SOCC 10 BG: A Benchmark to Evaluate Interactive Social Networking Actions, Sumita Barahmand, Shahram Ghandeharizadeh, CIDR 13 http://en.wikipedia.org/wiki/Software_testing http://en.wikipedia.org/wiki/Benchmark_(computing)

16 Thank You! Questions?

17 Why a new benchmark? Most cloud systems do not have a SQL interface => hard to implement complex queries Benchmark only for specific applications – TPC-W for E-commerce – TPC-C for apps that mange, sell, distribute product/service


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