首先要获取Spark SQL编程"入口":SparkSession(当然在早期版本中大家可能更熟悉的是SQLContext,如果是操作hive则为HiveContext)。这里以读取parquet为例: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 val spark=SparkSession.builder().appName("example").master("local[*]").getOrCreate();val df=sparkS...
*/defcol(colName:String):Column= colNamematch{case"*"=>Column(ResolvedStar(queryExecution.analyzed.output))case_ =>if(sqlContext.conf.supportQuotedRegexColumnName) { colRegex(colName) }else{valexpr = resolve(colName)Column(expr) } } 2、使用org.apache.spark.sql.functions中定义的col或者column...
在Spark SQL中SparkSession是创建DataFrame和执行SQL的入口,创建DataFrame有三种方式:通过Spark的数据源进行创建;从一个存在的RDD进行转换;还可以从Hive Table进行查询返回。 2.2 SQL风格语法 SQL语法风格是指我们查询数据的时候使用SQL语句来查询,这种风格的查询必须要有临时视图或者全局视图来辅助 1)创建一个DataFrame ...
SparkSQLDemo.scalaimport org.apache.spark.sql.{Row, SparkSession} import org.apache.spark.sql.types.{StringType, StructField, StructType} object SparkSQLDemo { // $example on:create_ds$ case class Person(name: String, age: Long) // $example on:create_ds$ def main(args: Array[String])...
importorg.apache.spark.SparkConfimportorg.apache.spark.sql.SparkSession object Test{defmain(args:Array[String]):Unit={val conf=newSparkConf()conf.setMaster("local")conf.set("spark.driver.host","127.0.0.1")val spark=SparkSession.builder().appName("HandleExample").config(conf).getOrCreate()...
3) If trash is enabled, it leads to an execution error when encrypted databases are dropped in a cascade. Spark SQL was incepted to overcome these inefficiencies. Architecture of Spark SQL It consists of three main layers: Language API: Spark is compatible with and even supported by the langu...
完整示例代码可在Spark存储库的“examples/src/main/scala/org/apache/spark/examples/sql/SparkSQLExample.scala”中找到。 4.全局临时视图 Spark SQL中的临时视图是会话范围的,如果创建它的会话终止,临时视图将消失。如果您想要一个在所有会话中共享且在Spark应用程序终止之前保持活动的临时视图,可以创建一个全局临时...
case...when...then 就像在sql 中写脚本! case when (age<50) then 'young' when (age>50) then 'old' else 'other' end 就相当于一个字段! select name,case when (age<50) then 'young' when (age>50) then 'old' else 'other' end from people; ...
Like SQL "case when" statement and Swith statement from popular programming languages, Spark SQL Dataframe also supports similar syntax using "when otherwise" or we can also use "case when" statement.
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