Configuration space complexity makes the big-data software systems hard to configure well.
Consider Hadoop, with over nine hundred parameters, developers often just use the default …

The Apache Hadoop framework is an open source implementation of MapReduce for
processing and storing big data. However, to get the best performance from this is a big …

Apache Hadoop is a distributed platform for storing, processing and analyzing of big data on
commodity machines. Hadoop has tunable parameters and they affect the performance of …

There are more than 190 configuration parameters affecting the performance of MapReduce
jobs on Hadoop. It is time-consuming and tedious for general users who have no deep …

The Named Data Networking (NDN) architecture retrieves content by names rather than
connecting to specific hosts. It provides benefits such as highly efficient and resilient content …

MapReduce parameter tuning is time consuming, and existing tuning systems are difficult to
use. We present an open source project, Catla for Hadoop and Spark, to provide …

Many Hadoop configuration parameters have significant influence in the performance of
running MapReduce jobs on Hadoop. It is time-consuming and tedious for general users to …

Methods Architecture Figure 1 illustrates the Catla-HS architecture, which facilitates the
efficient tuning of configuration parameters in a flexible and automated manner, solving the …

Apache Hadoop is a widely used open-source distributed platform towards big data
processing and provides YARN based distributed parallel processing framework on low cost …

Similarity search is the principle operation not only in databases but also in disciplinary
majors such as information retrieval, machine learning, or data mining. In addition, it has …