This document introduces the syntax of conditional functions in Spark SQL. IF You are advised to use theIFfunction inNew Calculation Columnof FineDatalink. For details about the example, seeAdding a Column Using the IF Function. NVL Syntax: NVL(Expression,Default value) ...
除了SQL 介面之外,Spark 還可讓您使用 Scala、Python 和 Java API 來建立自定義使用者定義純量和聚合函數。 如需詳細資訊,請參閱外部使用者定義純量函數 (UDF) 和使用者定義聚合函數 (UDAFs)。 語法 複製 CREATE [ OR REPLACE ] [ TEMPORARY ] FUNCTION [ IF NOT EXISTS ] function_name AS clas...
今天我们来聊聊flink sql中另外一种自定义函数-TableFuntion. TableFuntion 可以有0个、一个、多个输入参数,他的返回值可以是任意行,每行可以有多列数据. 实现自定义TableFunction需要继承TableFunction类,然后定义一个public类型的eval方法。结合官网的例子具体来讲解一下。 自定义函数 单个eval方法 代码语言:javascript...
...//这里registry 是通过 外部类 Analyzer的构造方法传入的,在 spark 1.6 实例化如下://SQLContext : val functionRegistry: FunctionRegistry = FunctionRegistry.builtin.copy()//HiveContext : val functionRegistry: FunctionRegistry = new HiveFunctionRegistry(FunctionRegistry.builtin.copy(), this.executionHi...
(See the SQL_DRIVER_HDESC or SQL_DRIVER_HSTMT descriptors later in this function description for more information.)If InfoValuePtr is NULL, StringLengthPtr will still return the total number of bytes (excluding the null-termination character for character data) available to return in the buffer...
Learn the syntax of the rtrim function of the SQL language in Databricks SQL and Databricks Runtime.
import org.apache.spark.sql.SparkSessionobject SparkUdfInSqlBasicUsageStudy {def main(args: Array[String]): Unit = {val spark = SparkSession.builder().master("local[*]").appName("SparkUdfStudy").getOrCreate() import spark.implicits._ // 注册可以在sql语句中使用的UDF...
(See the SQL_DRIVER_HDESC or SQL_DRIVER_HSTMT descriptors later in this function description for more information.)If InfoValuePtr is NULL, StringLengthPtr will still return the total number of bytes (excluding the null-termination character for character data) available to return in the buffer...
添加至缓存override def processElement(input: InputData, context: ProcessFunction[InputData, String]#Context, collector: Collector[String]): Unit = {if (cache.sismember(setKey, input.num.toString)) {collector.collect(input + " is in Cache")} else {collector.collect(input + " is not in ...
> SELECT substring('Spark SQL', 5);k SQL unbase64(str) Decode the Base64 encoded string into a Byte[] byte array - upper(str) Return the str in the form of full uppercase letter. > SELECT upper('SparkSql'); SPARKSQL ascii(str) Return the ASCII code value of the first character...