Hadoop MapReduce HDFS yarn: Hadoop: Hadoop concept, version, history, HDFS working principle, yarn introduction, component introduction.

Big data storage stage: hbase, hive, sqoop.

Big data architecture design stage: Flume distributed, Zookeeper, Kafka.

Real-time computing stage of big data: Mahout, Spark, storm.

Big data data collection stage: Python, Scala.

Big data business practice stage: practical operation of enterprise big data processing business scenarios, demand analysis, solution implementation, and practical application of comprehensive technologies.

Several aspects of big data analysis:

1, Visual analysis: Visual analysis can intuitively present the characteristics of big data, and it is also easy to be accepted by readers, just like looking at pictures and talking.

2. Data mining algorithm: The theoretical core of big data analysis is data mining algorithm.

3. Predictive analysis: Mining features from big data, scientifically establishing models and predicting future data.

4. Semantic engine: We need to design enough artificial intelligence to actively extract information from data.

5. Data quality and data management: the authenticity of the analysis results can be guaranteed.