Big Data Benchmarks
Srinivasa Rao Aravilli
N Venkata Naga Ravi

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Why ..
 Evaluating the effect of a hardware/software
upgrade:
 OS, Java VM,. . .
 Hadoop, Cloudera CDH, Pig, Hive, Impala,.
. .
 Debugging:
 Compare with other clusters or published
results.
 Performance tuning

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Industry Standard benchmarking organizations
• TPC - Transaction Processing Performance Council (http://www.tpc.org/ )
• SPEC - The Standard Performance Evaluation Corporation
(https://www.spec.org/ )
• CLDS – Centre for Large- scale Data System Research
(http://clds.sdsc.edu/bdbc)
• Top Outcomes
• BigData Top100 - an end-to-end application-layer benchmark for big data
applications
• Terasort - Functional benchmark focusing on Sort function ( quicksort using
MapReduce)
• Hibench
• Sort, Machine learning ( K-means clustering, Classification)

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Types of Benchmark
• Micro-benchmarks. To evaluate specific lower-level, system operations
• E.g., A Micro-benchmark Suite for Evaluating HDFS Operations on
Modern Clusters, Panda et al, OSU
• Functional / component benchmarks. Specific high-level function.
• E.g. Sorting: Terasort
• E.g. Basic SQL: Individual SQL operations, e.g. Select, Project, Join,
Order-By, ...
• Application-level benchmarks.
• Measure system performance (hardware and software) for a given
application scenario—with given data and workload

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Terasort using Hadoop
Terasort includes 3 MapReduce Applications
• Teragen – generates the data
• Terasort – samples the input data and uses them with MapReduce to
sort the data
• Teravalidate – validates the output data is sorted

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MapReduce for Teragen

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Map Reduce Modelloser look at MapReduce’s implementation model
source: http:/ / developer.yahoo.com/ hadoop/ tutorial/ module4.html”

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Benchmarking Suite
• HiBench, Yan Li, Intel (https://github.com/intel-hadoop/HiBench)
• YCSB -Yahoo Cloud Serving Benchmark, Brian Cooper, Yahoo!
(https://github.com/brianfrankcooper/YCSB/)
• Berkeley Big Data Benchmark, Pavlo et al., AMPLab
(https://amplab.cs.berkeley.edu/benchmark/)
• BigDataBench, Jianfeng Zhan, Chinese Academy of Sciences
(http://prof.ict.ac.cn/BigDataBench/)
• Grid Mix (http://hadoop.apache.org/docs/r1.2.1/gridmix.html)
• Big Bench (https://github.com/intel-hadoop/Big-Bench)
• TPCx-HS (http://www.tpc.org/tpcx-hs/ )

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TPCx-HS benchmarks
X: Express H: Hadoop S: Sort
• TPCx-HS was developed to provide an
objective measure of hardware,
operating system and commercial
Apache Hadoop File System API
compatible software distributions, and
to provide the industry with verifiable
performance, price-performance and
availability metrics.
• http://www.tpc.org/tpcx-hs/

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TPCx HS Demo

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TPCx-HS benchmarks
Scale Factor
The TPCx-HS follows a stepped size model. Scale factor (SF) used for the test
dataset must be chosen from the set of fixed Scale Factors defined as :
• 1TB, 3TB, 10TB, 30TB, 100TB, 300TB, 1000TB, 3000TB, 10000TB.
• The corresponding number of records are
• 10B, 30B, 100B, 300B, 1000B, 3000B, 10000B, 30000B, 100000B,
where each record is 100 bytes generated by HSGen.
• http://www.tpc.org/tpcx-hs/

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TPCx-HS benchmarks - Metrics

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TPCx-HS Results on Cisco UCS
Cisco Published Results

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Comparison of various Benchmarks Suites.

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Spark Performance

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Spark sorted the same data 3X faster using 10X fewer machines. All the sorting
took place on disk (HDFS), without using Spark’s in-memory cache.

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Sort Bench Mark http://sortbenchmark.org/
• GraySort
• MinuteSort
• CloudSort
• JouleSort
• PennySort
• TeraByteSort
• DatamationSort