Category Archives: Performance

YCSB, the Open Standard for NoSQL Benchmarking, Joins Cloudera Labs

Categories: Cloudera Labs HBase Performance

YCSB, the open standard for comparative performance evaluation of data stores, is now available to CDH users for their Apache HBase deployments via new packages from Cloudera Labs.

Many factors go into deciding which data store should be used for production applications, including basic features, data model, and the performance characteristics for a given type of workload. It’s critical to have the ability to compare multiple data stores intelligently and objectively so that you can make sound architectural decisions.

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Using Apache Parquet at AppNexus

Categories: Guest Impala Parquet Performance

Thanks to Chen Song, Data Team Lead at AppNexus, for allowing us to republish the following post about his company’s use case for Apache Parquet (incubating at this writing), the open standard for columnar storage across the Apache Hadoop ecosystem.

At AppNexus, over 2MM log events are ingested into our data pipeline every second. Log records are sent from upstream systems in the form of Protobuf messages. Raw logs are compressed in Snappy when stored on HDFS.

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Improving Sort Performance in Apache Spark: It’s a Double

Categories: Performance Spark

Cloudera and Intel engineers are collaborating to make Spark’s shuffle process more scalable and reliable. Here are the details about the approach’s design.

What separates computation engines like MapReduce and Apache Spark (the next-generation data processing engine for Apache Hadoop) from embarrassingly parallel systems is their support for “all-to-all” operations. As distributed engines, MapReduce and Spark operate on sub-slices of a dataset partitioned across the cluster. Many operations process single data-points at a time and can be carried out fully within each partition.

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5 Pitfalls of Benchmarking Big Data Systems

Categories: Hadoop Performance

Benchmarking Big Data systems is nontrivial. Avoid these traps!

Here at Cloudera, we know how hard it is to get reliable performance benchmarking results. Benchmarking matters because one of the defining characteristics of Big Data systems is the ability to process large datasets faster. “How large” and “how fast” drive technology choices, purchasing decisions, and cluster operations. Even with the best intentions, performance benchmarking is fraught with pitfalls—easy to get numbers,

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Tuning Java Garbage Collection for HBase

Categories: Guest HBase Performance

This guest post from Intel Java performance architect Eric Kaczmarek (originally published here) explores how to tune Java garbage collection (GC) for Apache HBase focusing on 100% YCSB reads.

Apache HBase is an Apache open source project offering NoSQL data storage. Often used together with HDFS, HBase is widely used across the world. Well-known users include Facebook, Twitter, Yahoo, and more. From the developer’s perspective, HBase is a “distributed,

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