2.1、spark shell中使用hive

显示所有数据库

scala> val df = spark.sql("show databases")
df: org.apache.spark.sql.DataFrame = [databaseName: string]

scala> df.show
+------------+
|databaseName|
+------------+
|     bigdata|
|     default|
|          lx|
+------------+

选择数据库并显示所有表

scala> spark.sql("use lx").show
++
||
++
++

scala> spark.sql("show tables").show
+--------+---------+-----------+
|database|tableName|isTemporary|
+--------+---------+-----------+
|      lx|   cource|      false|
|      lx|  student|      false|
|      lx|      tmp|      false|
|      lx|      www|      false|
+--------+---------+-----------+

查询表数据

scala> spark.sql("select * from sg").show(100,false)　　//100条记录全显示，不截断
+---+---+-----+
|sno|cno|grade|
+---+---+-----+
|1  |5  |50   |
|1  |3  |70   |
|2  |1  |40   |
|3  |6  |50   |
|4  |5  |80   |
|4  |5  |70   |
|6  |5  |60   |
|7  |2  |40   |
|8  |4  |50   |
+---+---+-----+

RDD -- DataFrame -- select API

　　　　　　　　  -- 创建临时表 -- 查询

//构造RDD
scala> val rdd1 = sc.parallelize(Array((1,"tom1",12),(2,"tom2",13),(3,"tom3",14)))
rdd1: org.apache.spark.rdd.RDD[(Int, String, Int)] = ParallelCollectionRDD[29] at parallelize at <console>:24
//转换RDD成DataFrame
scala> val df = rdd1.toDF("id","name","age")
df: org.apache.spark.sql.DataFrame = [id: int, name: string ... 1 more field]
//通过DataFrame select API实现sql中的select语句
scala> df.select("id","age").show()
+---+---+
| id|age|
+---+---+
|  1| 12|
|  2| 13|
|  3| 14|
+---+---+


scala> df.create
createGlobalTempView   createOrReplaceTempView   createTempView
//创建或替换临时表
scala> df.createOrReplaceTempView
   def createOrReplaceTempView(viewName: String): Unit

scala> df.createOrReplaceTempView("stuTable")
//通过临时表操作数据
scala> spark.sql("select * from stuTable").show(100,false)
+---+----+---+
|id |name|age|
+---+----+---+
|1  |tom1|12 |
|2  |tom2|13 |
|3  |tom3|14 |
+---+----+---+