importorg.apache.spark.sql.SparkSessionimportorg.apache.spark.sql.functions._valspark=SparkSession.builder().appName("String to Double").getOrCreate()valdata=spark.read.text("input.txt")defstringToDouble(str:String):Double={try{str.toDouble}catch{case_:NumberFormatException=>0.0}}valdfWithDoubl...
在上面的代码中,首先将String转换为Java的BigDecimal类型,然后使用setScale方法设置要保留的小数位数(15位),并选择舍入模式(这里使用四舍五入)。最后,使用doubleValue方法将结果转换为Double类型。 总结 在使用SparkSQL进行String到Double的转换时,由于浮点数的精度限制,可能会导致精度丢失。为了解决这个问题,可以使用Spark...
背景:A表的关联字段是bigint,B表的关联字段是string.关联之后出来的结果多了. 1.查看SQL的解析计划 explain select 13 as scenario_no -- 此处注释掉多余干扰部分,使解析计划看的比较清晰 from ( select purchase_item_id ,premium_before_discount ,account_id ,from_unixtime(unix_timestamp(gmt_modified)+36...
importorg.apache.spark.sql.SparkSessionvalspark=SparkSession.builder.appName("Create DataFrame").getOrCreate()importspark.implicits._caseclassPerson(name: String, age: Int)valrdd=spark.sparkContext.parallelize(Seq(Person("Alice",25), Person("Bob",30)))valdf=rdd.toDF() df.show() 从外部数据...
val tupleSum: RDD[(String, Double)] = linesRdd.map(line => (line.split(" ")(4),line.split(" ")(5).toDouble)).filter(line => line._1.equals("chinese")).reduceByKey((x, y)=> x+y).map(line => (line._1,line._2 / peopleSum)) ...
toInt)}).toDS res0: org.apache.spark.sql.Dataset[Person] = [name: string, age: Long] 3.3DataSet转换为RDD 调用rdd方法即可。 1)创建一个DataSet scala> val DS = Seq(Person("zhangcuishan", 32)).toDS() DS: org.apache.spark.sql.Dataset[Person] = [name: string, age: Long] 2)将Dat...
string, boolean, byte, short, int, long, float, double, decimal, date, timestamp. // Casts colA to integer.df.select(df("colA").cast("int"))Since1.3.0 第二种 def cast(to: DataType): Column Casts the column to a different data type. ...
_2.getString("policy_status") if(null != policyStatus && "1".equals(policyStatus) && null!= t._1.getString("mor_rate")){ true }else{ false } }).map(t => { val p_num = t._2.getString("p_num") val nowMorRate = t._2.getString("mor_rate").toDouble val chMorRate =...
问在spark sql中将Double数组转换为StringEN版权声明：本文内容由互联网用户自发贡献，该文观点仅代表作者...
The data in parentheses needs to be a Base64-encoded string Returns the decoded base64 string in binary form. Example One You can use the following statement in theSpark SQLoperator. select unbase64('YWJjZA==') Example Two 1. Use thebase64function to encode strings. ...