7)BIT类型的转换把非零值转换为1,并仍以BIT类型存储。 8)试图转换到不同长度的数据类型,会截短转换值并在转换值后显示“+”,以标识发生了这种截断。 9)用CONVERT()函数的style 选项能以不同的格式显示日期和时间。style 是将DATATIME 和SMALLDATETIME 数据转换为字符串时所选用的由SQL Server 系统提供的转换样...
{DataType, DataTypes, StructField, StructType} import util.BitMapUtil object S11_SPARKQL的UDF自定义函数应用实战1 { def main(args: Array[String]): Unit = { val spark: SparkSession = SparkSession.builder() .appName("自定义UDAF") .master("local") .config("spark.sql.shuffle.partitions", 2...
getCatalystType(sqlType: Int, typeName: String, size: Int, md: MetadataBuilder):输入数据库中的SQLType,得到对应的Spark DataType的mapping关系; getJDBCType(dt: DataType):输入Spark 的DataType,得到对应的数据库的SQLType; quoteIdentifier(colName: String):引用标识符,用来放置某些字段名用了数据库的保留...
getCatalystType(sqlType: Int, typeName: String, size: Int, md: MetadataBuilder):输入数据库中的SQLType,得到对应的Spark DataType的mapping关系; getJDBCType(dt: DataType):输入Spark 的DataType,得到对应的数据库的SQLType; quoteIdentifier(colName: String):引用标识符,用来放置某些字段名用了数据库的保留...
scala>import org.apache.spark.sql.types.DataTypes; import org.apache.spark.sql.types.DataTypes scala>df.select(col("*"),|udf{| (e:Int) => |if(e =="23") {|1| }else{|2|}| }.apply(df("rsrp")).cast(DataTypes.DoubleType).as("rsrp_udf")|).show+---+---+---+---+ |id|...
Spark SQL示例用法所有函数权威详解 SparkSession: Spark入口 1.创建DataFrames 2.未命名的Dataset操作(也称为DataFrame操作) 3.以编程方式运行SQL查询 4.全局临时视图 5.创建Datasets 6.如何将RDD转换为Datasets 6.1使用反射推断模式 6.2以编程方式指定模式 7.标量函数 数组函数 映射函数 日期和时间函数 JSON函数 数...
名称函数参数说明格式与返回值FDL的SparkSQL算子内用法 MD5MD5(expr) - 示例:SELECT MD5('FineDataLink') SHASHA(expr)-- 示例:SELECT SHA('FineDataLink') SHA1SHA1(expr)-- 示例:SELECT SHA1('FineDataLink') SHA2 SHA2(expr, bitLength)
Tables and views are basically the same thing as DataFrames. We just execute SQL against them instead of DataFrame code. We cover all of this inChapter 10, which focuses specifically on Spark SQL. To add a bit more specificity to these definitions, we need to talk about schemas, which are...
In contrast, the Spark framework applies intelligence to data analytics tasks at hand. It constructs a Directed Acyclic Graph (DAG) of execution before scheduling tasks, very similar to how SQL Server constructs a query execution plan before executing a data retrieval or manipulation...
Spark SQL provides a programming abstraction for its users in the form of DataFrames, which is a distributed collection of data organized into columns. DataFrames also allows the integration of SQL commands into applications that use the MLlib library. This is explained a bit more in the ML...