資料內(nèi)容：
Spark Architecture
When you have small data, it is possible to analyze it with a single
computer in a reasonable amount of time. When you have large volumes ofdata,using a single computer to analyze and process that data (and store it)might be prohibitively slow, or even impossible. This is why we want to useSpark.
Spark has a core library and a set of built-in libraries (SQL, GraphX，Stream ing, MLlib), as shown in Figure 1-3.As you can see, through itsDataSource API,Spark can interact with many data sources, such as
Hadoop,HBase,Amazon S3, Elasticsearch, and MySQL, to mention a few.
