大数据（Big Data）

[itang]

• [ ] 从Apache Kafka 重温文件高效读写 http://calvin1978.blogcn.com/articles/kafkaio.html [ ] http://thenewstack.io/apache-samza-linkedins-framework-for-stream-processing/
• [ ] http://allthingshadoop.com/2014/12/29/multi-datacenter-replication-with-apache-kafka/
• [ ] http://www.infoq.com/presentations/spark-scala-mapreduce-java
• [ ] http://www.infoworld.com/article/2854894/application-development/spark-and-storm-for-real-time-computation.html
• [ ] http://sysadvent.blogspot.com/2014/12/day-4-introduction-to-kafka.html
• [ ] http://blog.cloudera.com/blog/2014/11/apache-hive-on-apache-spark-the-first-demo/
• [ ] https://stripe.com/blog/four-new-hadoop-projects
• [ ] Kafka and Samza: Distributed stream processing in practice

http://nosql.mypopescu.com/post/102868229019/kafka-and-samza-distributed-stream-processing-in

• [ ] http://www.slideshare.net/ptgoetz/apache-storm-vs-spark-streaming
• [ ] Three Reasons a Data Engineer Should Learn Scala http://www.hakkalabs.co/articles/three-reasons-data-eng-learn-scala
• [ ] http://www.eweek.com/database/big-data-giants-flex-at-strata-hadoop-world.html
• [ ] http://siliconangle.com/blog/2014/10/17/hortonworks-adds-object-storage-and-spiffier-query-language-to-hadoop/
• [ ] Building a Forex trading platform using Kafka, Storm and Cassandra http://insightdataengineering.com/blog/Building_a_Forex_trading_platform_using_Kafka_Storm_Cassandra.html
• [ ] http://www.hakkalabs.co/articles/kafka-hadoop-2
• [ ] http://blog.cloudera.com/blog/2014/11/nosql-in-a-hadoop-world-2/

  MapReduce

• [ ] Using Nosql and Spark (How to Start) https://blogs.oracle.com/NoSQL/entry/using_nosql_and_spark_how

  云存储

  Cassandra

• [ ] http://www.datastax.com/dev/blog/cassandra-error-handling-done-right

  机器学习

• [ ] http://cxwangyi.github.io/2014/01/20/distributed-machine-learning/
• [ ] http://www.datasciencecentral.com/profiles/blogs/implementing-a-distributed-deep-learning-network-over-spark

  已完成

• [x] http://vitalflux.com/big-data-functional-technology-architecture-beginners/

通俗易懂的一篇文章， 对BigData有个全貌的介绍。 把bigdata处理划分为两个层次： 数据工程和数据科学， 并列出每个层次下对应的数据处理阶段及其涉及到的技术（工具）