udf

I'm trying to create a spark UDF to extract a Map of (key, value) pairs from a User defined case class. The scala function seems to work fine, but when I try to convert that to a UDF in spark2.0, I'm running into the " Schema for type Any is not supported" error. case class myType(c1: String, c2: Int) def getCaseClassParams(cc: Product): Map[String, Any] = { cc .getClass .getDeclaredFields // all field names .map(_.getName) .zip(cc.productIterator.to) // zipped with all values .toMap } But when I try to instantiate a function value as a UDF it results in the following error - val ccUDF = udf{

1、pom.xml引入依赖及打包 <dependencies> <dependency> <groupId>org.apache.hive</groupId> <artifactId>hive-exec</artifactId> <version>1.1.0</version> </dependency> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-common</artifactId> <version>2.6.0</version> </dependency> </dependencies> <build> <plugins> <!-- 配置java插件，指定版本 --> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-compiler-plugin</artifactId> <configuration> <encoding>UTF-8</encoding> <source>1.8</source> <target>1.8</target> <showWarnings>true</showWarnings> </configuration> </plugin> </plugins> <

一、redis简介 Redis是一个key-value存储系统。和Memcached类似，为了保证效率，数据都是缓存在内存中。区别的是redis会周期性的把更新的数据写入磁盘或者把修改操作写入追加的记录文件，并且在此基础上实现了master-slave(主从)同步。在部分场合可以对关系数据库起到很好的补充作用。它提供了Java，C/C++( hiredis )，C#，PHP，JavaScript，Perl，Object-C，Python，Ruby等客户端，使用很方便。 二、架构图 大致结构就是读写分离，将mysql中的数据通过触发器同步到redis中 三、安装LNMP环境 (这里为了省事，就是用yum来安装) 1、修改yum源 [root@redis ~]# vim /etc/yum.repos.d/epel.repo #添加这个文件 [epel] name=Extra Packages for Enterprise Linux 6 - $basearch baseurl=http://download.fedoraproject.org/pub/epel/6/$basearch failovermethod=priority enabled=1 gpgcheck=0 [nginx] name=nginx repo baseurl=http://nginx.org/packages

In my Project, I want to achieve ADD( + ) function, but my parameter maybe LongType , DoubleType , IntType . I use sqlContext.udf.register("add",XXX) , but I don't know how to write XXX , which is to make generic functions. You can create a generic UDF by creating a StructType with struct($"col1", $"col2") that holds your values and have your UDF work off of this. It gets passed into your UDF as a Row object, so you can do something like this: val multiAdd = udf[Double,Row](r => { var n = 0.0 r.toSeq.foreach(n1 => n = n + (n1 match { case l: Long => l.toDouble case i: Int => i.toDouble case d:

I know I can define a User Defined Function in order to perform some custom calculation. I also know I can use the 'out-of-the-box' aggregation functions to reduce a collection of values to a single value when using a GROUP BY clause. Is it possible to define a custom user-defined, Aggregation Function to use with a GROUP BY clause? Turns out that this IS possible (as long as the groups we seek to aggregate are of a reasonable size in memory) with a little bit of 'glue' - namely the ARRAY_AGG function The steps are as follows: Create a UDF with an input parameter of type ARRAY<T> where T is