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Hadoop 0.22.0 及其 RAID 部署

        使用0.20.X系列版本的Hadoop快有一年时间了,主要集中在HDFS上。期间自己参与了部署Hadoop集群(1 Server + 20 PC),也参与了分析HDFS的源码。

Authored by Last updated on 01/24/2019 - 16:00
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Intel Keynote and Intel technical presentations at Spark Summit West 2015

To find new trends and strong patterns from large complex data sets, a strong analytics foundation is needed. Intel is working closely with Databricks, AMPLab, Spark community and its ecosystem to advance these analytics capabilities…
Authored by Mike P. (Intel) Last updated on 06/07/2017 - 09:33
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Tuning Java* Garbage Collection for Spark* Applications

Spark is gaining wide industry adoption due to its superior performance, simple interfaces, and a rich library for analysis and calculation.

Authored by Mike P. (Intel) Last updated on 05/10/2019 - 08:30
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As the volume and velocity of enterprise data continue to grow, extracting high-value insight is becoming more challenging and more important. Businesses that can analyze fresh operational data instantly—without the delays of traditional data warehouses and data marts—can make the right decisions faster to deliver better outcomes.
Authored by Nguyen, Khang T (Intel) Last updated on 07/06/2019 - 16:40
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OpenStack App Developer Survey

As part of a long-term commitment to enhance ease-of-use, the OpenStack UX project, with support of the OpenStack Foundation and the Technical Committee, is now bu

Authored by Mike P. (Intel) Last updated on 06/07/2017 - 12:14
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BigDL – Scale-out Deep Learning on Apache Spark* Cluster

Learn how to install and use BigDL for training and testing some of the commonly used deep neural network models on Apache Spark.
Authored by Sunny G. (Intel) Last updated on 03/11/2019 - 13:17
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Authored by Sunny G. (Intel) Last updated on 03/11/2019 - 13:17
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Vector API Developer Program for Java* Software

This article introduces Vector API to Java* developers. It shows how to start using the API in Java programs, and provides examples of vector algorithms. It provides step-by-step details on how to build the Vector API and build Java applications using it. It provides the location for downloadable binaries for Project Panama binaries.
Authored by Neil V. (Intel) Last updated on 07/06/2019 - 16:30
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Intel® Accelerates Hardware and Software Performance for Server-Side Java* Applications

Intel® contributes significantly to both software and hardware optimizations for Java*.

Authored by Mike P. (Intel) Last updated on 07/06/2019 - 16:30
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Performance and Agility with Big Data in a Containerized Environment

Big data analytics solution developers no longer need to choose between performance and agility.
Authored by Michael G. (Intel) Last updated on 08/01/2019 - 10:32