- Scala
- Spark
- Session
- Dataset DataFrame
- Data Source API
- Row
- Column
- Schema
- Typed Transformations
- Untyped Transformations
- Actions
- DataFrameNaFunctions
- DataFrameStatFunctions
- Basic Aggregate
- transform 高阶函数
- Window Aggregate
- Collection Functions
- Date and Time Functions
- Regular Functions
- UDF
- UDAF,Aggregator
- Pivot
- cube/rollup/groupings_set
- CheckPoint Cache Persist
- Configure
- Execute Plan
- Spark Structured Streaming
- Practice
- Program Language Part A
- Emacs
- ML
- spark na.fill 当接收Map作为参数时，Map的value类型只能为Int, Long, Float, Double, String, Boolean.
- Unable to find encoder for type stored in a Dataset. Primitive types (Int, String, etc) and Product types (case classes) are supported by importing spark.implicits._ Support for serializing other types will be added in future releases.
- case class 使用时遇到的问题，放在main方法作用域外面，否则容易出现奇奇怪怪的错
- What does setMaster
local[*]mean in spark?
- 极客学院
- Scala Doc
- Some Scala Blog Geeksforgeeks
- Some Scala Blog alvinalexander
- allaboutscala.com
- Play Framework
- 过往记忆的大数据
- Scala 一些特殊符号
- transfrom
- Kudu：一个融合低延迟写入和高性能分析的存储系统
- Kafka 简明教程
- 技术分享丨HDFS 入门
- 深入浅出 Hadoop YARN
- 列存储格式Parquet浅析
- 美图离线ETL实践
- Avro
- SQL优化器原理——查询优化器综述
- 深入理解spark之架构与原理
- 你真的了解Join吗？
- Scala 隐式转换implicit详解
- 扩展Spark Catalyst，打造自定义的Spark SQL引擎
- scala 下划线解析报错： missing parameter type for expanded function
- 深入浅出Spark的Checkpoint机制
- Spark
- 简单了解
- Spark SQL
- The Internals of Spark SQL
- FILE-BASED DATA SOURCES, KAFKA DATA SOURCE, AVRO DATA SOURCE, HIVE DATA SOURCE
- DEVELOPING SPARK SQL APPLICATIONS
- Spark UI
- Spark Structured Streaming