本文探讨了大数据处理中的关键技术和流处理框架，包括Spark、Flink在实时数据处理中的应用，以及Kafka作为消息队列在数据流中的作用。深入分析了Scala在大数据生态中的地位，并讨论了Hadoop、Zookeeper等基础设施的重要性。
https://blog.fundebug.com/2018/08/27/code-interview-data-structure/
scala: https://www.cnblogs.com/fxjwind/p/3338829.html
java read and save json https://howtodoinjava.com/json/json-simple-read-write-json-examples/
scala: libraryDependencies += “com.typesafe.play” % “play-json_2.11” % “2.4.6”
- LinkedList
binlog: https://aws.amazon.com/cn/blogs/china/mysql-binlog-architecture/
kafaka: https://www.cnblogs.com/likehua/p/3999538.html
Spark踩坑记——Spark Streaming+Kafka: https://www.cnblogs.com/xlturing/p/6246538.html
Streaming与Flume的联调: https://www.cnblogs.com/kinghey-java-ljx/p/8544405.html
flume: https://www.zybuluo.com/sasaki/note/278653
zookeeper and hadoop http://blog.jobbole.com/110388/
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