Tachyon 概述

    Tachyon是一个以内存为中心的分布式存储系统，能够可靠的在跨集群框架之间以内存速度进行共享，比如 Spark 和 MapReduce。它通过利用 lineage 信息和使用内存实现了高性能，Tachyon 在内存中缓存工作文件集，从而避免频繁读取的数据从磁盘去加载数据，这使得不同的 jobs/queries 和框架 以内存的速度 去访问缓存的文件集。

    Tachyon与 Hadoop 是可以兼容的，现有的Spark 和 MapReduce 程序能够在它上面运行而不用修改任何代码。这个项目是开源的(Apache License 2.0) ，被部署在多个公司。已经有超过过来自30多个机构的80余贡献者，包括：Yahoo,Intel, Red Hat, 和 Tachyon Nexus. 该项目是Berkeley 数据分析栈（BDAS）的存储层，并还有部分Fedora发行版的（Fedora distribution.）。

GIt仓库（Github Repository） | 发布和下载（Releases and Downloads） | 用户文档（User Documentation） | （开发者文档）Developer Documentation | Meetup 组（Meetup Group） | JIRA | User Mailing List

现阶段特性

• 类似Java 文件API：Tachyon’s 本地化API类似于 java.io.File 类, 提供了 InputStream and OutputStream 接口， 高效的支持内存I/O映射. 我们推荐使用Tacyon这些API 获得最佳效能。 

• 兼容性: Tachyon 实现了Hadoop FileSystem 接口.因此，Hadoop MapReduce 和 Spark 能够不做修改进行运行。然后，紧密结合才能充分利用Tachyon的优势，我们正在努力实现这个目标。点到点延迟加速依赖于工作负载和所述框架，由于各种框架有不同的执行开销。

• Pluggable underlayer file system: To provide fault-tolerance, Tachyon checkpoints in-memory data to the underlayer file system. It has a generic interface to make plugging different underlayer file systems easy. We currently support HDFS, S3, GlusterFS, and single-node local file systems, and support for many other file systems is coming.

• Native support for raw tables: Table data with over hundreds of columns is common in data warehouses. Tachyon provides native support for multi-columned data, with the option to put only hot columns in memory to save space.

• Web UI: Users can browse the file system easily through the web UI. Under debug mode, administrators can view detailed information of each file, including locations, checkpoint path, etc.

• Command line interaction: Users can use ./bin/tachyon tfs to interact with Tachyon, e.g. copy data in and out of the file system.

User Documentation

Deployment Guide:

• Single Node

• Cluster

• Master Fault Tolerant Cluster

• Tachyon Deploy Module (Virtualbox and AWS EC2)

• Amazon AWS Through mesos/spark-ec2

Configuration:

• Configure Underlayer Storage System: Learn how to configure underlayer storage system or to create a new one.

• Configuration Settings: How to configure Tachyon.

Frameworks on Tachyon:

• Running Apache Spark on Tachyon: Get Apache Spark running on Tachyon

• Running Shark on Tachyon: Get Shark running on Tachyon

• Running Apache Hadoop MapReduce on Tachyon: Get Apache Hadoop MapReduce running on Tachyon

• Running Apache Flink on Tachyon: Get Apache Flink running on Tachyon

Others:

• Command-Line Interface: Interact with Tachyon through the command line.

• Syncing the Underlayer Storage System: Make Tachyon understand an existing underlayer storage system.

• FAQ

• Tachyon Java API (Javadoc)

• Tiered Storage (Beta)

Tachyon Presentations:

• Strata and Hadoop World 2014 (October, 2014) pdf pptx

• Spark Summit 2014 (July, 2014) pdf

• Strata and Hadoop World 2013 (October, 2013) pdf

Developer Documentation

Contributing to Tachyon

Building Tachyon Master Branch

External resources

Tachyon Mini Courses:

• AMPCamp 5

• Strata 2014

Hot Rod Hadoop With Tachyon on Fedora 21

Support or Contact

You are welcome to join our mailing list to discuss questions and make suggestions. We use JIRA to track development and issues. If you are interested in trying out Tachyon in your cluster, please contact Haoyuan.

Acknowledgement

Tachyon is an open source project started in the UC Berkeley AMP Lab. This research is supported in part by NSF CISE Expeditions Award CCF-1139158, LBNL Award 7076018, and DARPA XData Award FA8750-12-2-0331, and gifts from Amazon Web Services, Google, SAP, The Thomas and Stacey Siebel Foundation, Adatao, Adobe, Apple, Inc., Blue Goji, Bosch, C3Energy, Cisco, Cray, Cloudera, EMC, Ericsson, Facebook, Guavus, Huawei, Informatica, Intel, Microsoft, NetApp, Pivotal, Samsung, Splunk, Virdata, VMware, and Yahoo!.

We would also like to thank to our project contributors.

Related Projects

Berkeley Data Analysis Stack (BDAS) from AMPLab at Berkeley

Tachyon 概述

原文：http://my.oschina.net/Rayn/blog/517690