How Java Objects Are Stored In Memory

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Stardog 2.1: Extensibility improvements resulting from concurrency, memory management, and GC mechanisms

The upcoming Stardog 2.1 query scalability improves by about 3 orders of magnitude and can handle 50 billion triple on a 10,000-dollar server. We have never focused too much on stardog scalability itself: we first consider its ease of use and then consider its speed. We just assumed it would make it extremely scalable. Stardog 2.1 makes querying, data loading, and scalability a huge leap forward. Run S on a 10,000 dollar server hardware (32 cores, 256 GB RAM).

Hadoop Serialization System

This article is my second time reading Hadoop 0.20.2 notes, encountered many problems in the reading process, and ultimately through a variety of ways to solve most of the.   Hadoop the whole system is well designed, the source code is worth learning distributed students read, will be all notes one by one post, hope to facilitate reading Hadoop source code, less detours. 1 serialization core Technology The objectwritable in 0.20.2 version Hadoop supports the following types of data format serialization: Data type examples say ...

Java thread pool management and distributed Hadoop scheduling framework

Multithreading is the problem that programmers often face in the interview, the level of mastery and understanding of multithreading concept is often used to measure a person's programming strength. Yes, ordinary multithreading is not easy, then when multithreading encounter "elephants" will produce what kind of sparks?   Here we share the Java thread Pool management and distributed Hadoop scheduling framework with 严澜, the Shanghai Creative Technology director. Usually the development of the thread is a thing, such as Tomcat in the servlet is the threads, no thread how we provide more ...

"Book pick" Big Data development deep HDFs

This paper is an excerpt from the book "The Authoritative Guide to Hadoop", published by Tsinghua University Press, which is the author of Tom White, the School of Data Science and engineering, East China Normal University. This book begins with the origins of Hadoop, and integrates theory and practice to introduce Hadoop as an ideal tool for high-performance processing of massive datasets. The book consists of 16 chapters, 3 appendices, covering topics including: Haddoop;mapreduce;hadoop Distributed file system; Hadoop I/O, MapReduce application Open ...

Manage Java thread pool and build distributed Hadoop scheduling framework

Usually the development of the thread is a thing, such as Tomcat is a servlet in the threads, there is no thread how do we provide multi-user access? But many developers who have just started to touch threads have suffered a lot.   How to do a set of simple threading Development Mode framework for everyone from the single thread development into multithreaded development, this is really a relatively difficult project. What is the specific thread? First look at what the process is, the process is a system executed a program, this program can use memory, processor, file system and other related resources ...

Spark: A framework for cluster computing on a workgroup

Translation: Esri Lucas The first paper on the Spark framework published by Matei, from the University of California, AMP Lab, is limited to my English proficiency, so there must be a lot of mistakes in translation, please find the wrong direct contact with me, thanks. (in parentheses, the italic part is my own interpretation) Summary: MapReduce and its various variants, conducted on a commercial cluster on a large scale ...

Recent advances in SQL on Hadoop and 7 related technology sharing

The greatest fascination with large data is the new business value that comes from technical analysis and excavation. SQL on Hadoop is a critical direction. CSDN Cloud specifically invited Liang to write this article, to the 7 of the latest technology to do in-depth elaboration. The article is longer, but I believe there must be a harvest. December 5, 2013-6th, "application-driven architecture and technology" as the theme of the seventh session of China Large Data technology conference (DA data Marvell Conference 2013,BDTC 2013) before the meeting, ...

A study of JVM virtualization characteristics in cloud computing environment

At present, what is cloud computing, what kind of platform belongs to the cloud computing platform, and so on cloud computing related issues, different hardware and software manufacturers have their own different understanding, have their own different definitions. The cloud computing platform they offer is also vastly different. When it comes to cloud computing, people always think of these things: high scalability (scalability), cost savings (saving), on-demand (use on Demand), and so on. Let's give it a few of the myriad things that cloud computing brings ...

The combination of Spark and Hadoop

Spark can read and write data directly to HDFS and also supports Spark on YARN. Spark runs in the same cluster as MapReduce, shares storage resources and calculations, borrows Hive from the data warehouse Shark implementation, and is almost completely compatible with Hive. Spark's core concepts 1, Resilient Distributed Dataset (RDD) flexible distribution data set RDD is ...

Object-oriented + distributed computing = direction of software architecture

"Cloud" is not only a metaphor for those networked computers, but also a computational process of data that is hidden from the server as you need it, carving out the one you need from the big cloud. It's a very romantic metaphor. Cloud computing is an emerging business computing model. Using high-speed Internet transmission capabilities, data processing is moved from personal computers or servers to computer clusters on the Internet. These computers are very common industrial standard servers, managed by a large data processing center, data centers in accordance with the needs of customers to allocate computing resources to achieve with supercomputing ...

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