Dell EMC is focused on providing information that helps customers make the most of their big data technology investment. The failure rate for Hadoop big data projects is still too high given the maturity of the technology. Customers can’t afford to guess when designing and sizing a solution; they need to deliver optimal performance for their business use cases and to scale as needed. Dell EMC recently completed and published a new TPCx-BigBench (TPCx-BB) result that will help customers make the right choices for Hadoop performance and scalability. Today we are happy to announce that
- The Dell EMC Ready Bundle for Cloudera Hadoop and Dell EMC PowerEdge R730XD provides the #1 price/performance in TPCx-BigBench for Scale Factor 10000. (*Based on published results as of May 13, 2017)
Dell EMC is the industry leading supplier of hyper-converged, converged and “Ready” Solutions by many standards. Dell EMC’s tested and validated Ready Bundle for Cloudera Hadoop, together with the right performance benchmark results, takes the guess work out of Hadoop implementations.
The Transaction Processing Council (TPC) is a non-profit corporation founded to define transaction processing and database benchmarks and to disseminate objective, verifiable TPC performance data to the industry. Benchmarking has long been a standard practice of the computer industry and is used to discover, measure and assess the relative performance of alternative systems and configurations. This information can then be customized or extrapolated as an input to system design for systems that will provide similar services for real world applications.
Similar to the years of development and maturation of Relational Database Management Systems (RDBMSs), there is a rapidly expanding ecosystem of both complimentary and competing Big Data Analytics Systems (BDAS). As the big data analytics ecosystem matures, the pressure to evaluate and compare performance and price performance of these systems becomes more useful. To address this need in the industry, the TPC has developed a big data benchmarking specification called TPCx-BB. The TPCx-BB Benchmark was developed to cover essential functional and business aspects of big data use cases. The benchmark allows for an objective measurement of a BDAS and provides verifiable performance, price/performance, and availability metrics for those considering new investments.
Dell is the first to cross the significant milestone of publishing a result using SF10000 which is the largest data set executed thus far for TPCx-BB. SF10000 maps to a roughly 10TB data set which typically takes longer to execute than the smaller Scale Factors (1000 & 3000).
How realistic is the benchmark?
The TPCx-BB benchmark is designed to stress the CPU and IO systems of a BDAS using one or more concurrent streams. The test includes 30 unique queries in a simulated workload that is typical of real-world analytic applications. For a test to run and successfully pass an audit, 2 sequential performance runs must be executed. Each run is performed under 3 phases: Load, Power and Throughput.
The chart below shows the breadth of the query types and the average elapsed time in seconds to process the Power test.
The overall TPCx-BB performance data for the Dell R730/R730xd configuration is summarized in the table below:
|Performance Metric||495.283 BBQpm@SF10000|
|Total System Cost||$439,187|
|Availability Date||May 12, 2017|
The high failure rate of big data projects has left many organizations wary of adopting Hadoop despite the overwhelming evidence of the business benefits of big data technologies. Dell EMC helps customers through the Data Analytics journey by providing a robust portfolio of solutions that can match their needs from early sandbox development through support of large deployments for multiple use cases.
We simplify implementing and/or expanding your Hadoop capabilities with certified architectures, custom solution design, hardware and software deployment, coupled with ongoing support and training.Please visit our site and take us on the journey with you!