###算法描述与应用文档：

####聚类

DBSCAN

####推荐

MF-ALS

###开发相关：

稀疏数据结构

git相关

###TODO：

• 1. 监控：

• 方便的查看web ui

• For instance, a Ganglia dashboard can quickly reveal whether a particular workload is disk bound, network bound, or CPU bound.

• OS profiling tools such as dstat, iostat, and iotop can provide fine-grained profiling on individual nodes.

• JVM utilities such as jstack for providing stack traces, jmap for creating heap-dumps, jstat for reporting time-series statistics and jconsole for visually exploring various JVM properties are useful for those comfortable with JVM internals.

• 2. 性能：

• 按照参数，对开发的算法做性能调优。

• https://spark.apache.org/docs/latest/configuration.html

• https://spark.apache.org/docs/latest/tuning.html

• 3. DBSCAN利弊与参数选择调研

• https://en.wikipedia.org/wiki/DBSCAN

• 4. dbscan spark与单机对比：

• spark集群配置，计算时间，计算资源

• 与单机效果对比

• 与单机性能对比