For Big dataMaster the various components of Hadoop architecture, familiar with HDFS system architecture and file access principle, familiar with MapReduce computing principles and core source code, familiar with Hadoop Yarn architectureMaster Hadoop HA cluster setup, quickly install, deploy and develop MapReduce programsFamiliar with Hive principle and construction method, can use Hive to carry out statistical analysis and efficient query of massive data, familiar with Hive tuningFamiliar with the principles of Spark, including resource scheduling and task scheduling processes, mastering the submission of the spark task, running mode, and execution flow.Familiar with Spark stacking services, you can use SparkStreaming and SparkSQL components to develop real-time/offline systems.Understand Spark source code, good at tuning Spark services (such as: resource tuning, shuffle tuning, parallelism tuning, code tuning, memory management, etc.)Familiar with Sqoop and Flume technologies. Ability to use Flume for efficient data collection and Sqoop to transfer data between Hadoop and relational databasesUnderstand the Storm cluster architecture and how it works, use Flume+Kafka+Storm to collect data and perform clean and real-time statistical analysisFamiliar with Scala and Python programming languagesFor JavaExperienced Senior Java Engineer with a demonstrated history of working in the computer software industry. Skilled in Oracle Database, iBatis, Spring Framework, Spring MVC, and Java Enterprise Edition.