Category Archives: Hardware

New Study: Evaluating Apache HBase Performance on Modern Storage Media

Categories: Guest Hardware HBase Performance

For the first time, this new study by Intel software engineers analyzes the performance impact of using Apache HBase on various modern storage technologies.

As more “fast” storage technologies (such as SSD and NVMe SSD) emerge, organizations with big data use cases want to make better use of them to achieve better throughput and latency. But to this point, there have been no detailed analyses published about the true significance of that performance boost, nor about how to best mix fast and “slow”

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How-to: Deploy Apache Hadoop Clusters Like a Boss

Categories: Hadoop Hardware How-to

Learn how to set up a Hadoop cluster in a way that maximizes successful production-ization of Hadoop and minimizes ongoing, long-term adjustments.

Previously, we published some recommendations on selecting new hardware for Apache Hadoop deployments. That post covered some important ideas regarding cluster planning and deployment such as workload profiling and general recommendations for CPU, disk, and memory allocations. In this post, we’ll provide some best practices and guidelines for the next part of the implementation process: configuring the machines once they arrive.

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BigBench: Toward An Industry-Standard Benchmark for Big Data Analytics

Categories: General Hardware Performance

Learn about BigBench, the new industrywide effort to create a sorely needed Big Data benchmark.

Benchmarking Big Data systems is an open problem. To address this concern, numerous hardware and software vendors are working together to create a comprehensive end-to-end big data benchmark suite called BigBench. BigBench builds upon and borrows elements from existing benchmarking efforts in the Big Data space (such as YCSB, TPC-xHS,

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Using Apache Hadoop and Impala with MySQL for Data Analysis

Categories: Guest Hardware Impala Parquet

Thanks to Alexander Rubin of Percona for allowing us to re-publish the post below!

Apache Hadoop is commonly used for data analysis. It is fast for data loads and scalable. In a previous post I showed how to integrate MySQL with Hadoop. In this post I will show how to export a table from  MySQL to Hadoop, load the data to Cloudera Impala (columnar format),

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The Truth About MapReduce Performance on SSDs

Categories: Hadoop Hardware MapReduce Performance

Cost-per-performance, not cost-per-capacity, turns out to be the better metric for evaluating the true value of SSDs.

In the Big Data ecosystem, solid-state drives (SSDs) are increasingly considered a viable, higher-performance alternative to rotational hard-disk drives (HDDs). However, few results from actual testing are available to the public.

Recently, Cloudera engineers did such a study based on a combination of SSDs and HDDs, with the goal of determining to what extent SSDs accelerate different MapReduce workloads,

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