Apache Spark is a fast and general-purpose cluster computing system that claims 10x to 100x performance improvements over Hadoop. It runs “everywhere” from standalone to EC2 and runs on Hadoop, Mesos, standalone, or in the cloud.
Apache Spark (click to learn more)
Spark runs provides high-level APIs in Java, Scala and Python, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming. It can access diverse data sources including HDFS, Cassandra, HBase, S3.
Spark was initially developed as a UC Berkeley research project, and much of the design is documented in papers. The Wiki lists the following papers about Spark and related projects.
- Shark: SQL and Rich Analytics at Scale. Reynold Xin, Joshua Rosen, Matei Zaharia, Michael J. Franklin, Scott Shenker, Ion Stoica. Technical Report UCB/EECS-2012-214. November 2012.
- Discretized Streams: An Efficient and Fault-Tolerant Model for Stream Processing on Large Clusters. Matei Zaharia, Tathagata Das, Haoyuan Li, Scott Shenker, Ion Stoica. HotCloud 2012. June 2012.
- Shark: Fast Data Analysis Using Coarse-grained Distributed Memory (demo). Cliff Engle, Antonio Lupher, Reynold Xin, Matei Zaharia, Haoyuan Li, Scott Shenker, Ion Stoica. SIGMOD 2012. May 2012. Best Demo Award.
- Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing. Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, Ion Stoica. NSDI 2012. April 2012. Best Paper Award and Honorable Mention for Community Award.
- Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing. Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, Ion Stoica. Technical Report UCB/EECS-2011-82. July 2011.
- Spark: Cluster Computing with Working Sets. Matei Zaharia, Mosharaf Chowdhury, Michael J. Franklin, Scott Shenker, Ion Stoica.HotCloud 2010. June 2010.
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