我用Java编写了一个sparksql UDF,但似乎有些地方出了问题

Question

我的项目的整个依赖关系如下代码所示：

<dependencies>

    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.11</artifactId>
        <version>2.1.2</version>
    </dependency>

    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-sql_2.11</artifactId>
        <version>2.1.2</version>
    </dependency>

    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-hive_2.11</artifactId>
        <version>2.1.2</version>
    </dependency>

</dependencies>

我想用udf来计算两个格式为'yyyy-mm-ss hh:mm:ss.ss'的输入日期字符串之间的时间间隔（例如'2017-12-26 00:00:02.044')，结果将加倍，精度达到毫秒，例如，当我传递“2017-12-26 00:00:02.044”、“2017-12-26 00:00:03.045”给udf时，结果将是1.001秒，然后附带Java代码段：

import org.apache.commons.lang.StringUtils;
import org.apache.spark.sql.api.java.UDF2;

import java.text.SimpleDateFormat;
import java.util.Date;

public class DateDistance implements UDF2<String,String,Double> {

    public Double call(String s, String s2) throws Exception {
        Double result=0D;
        if(StringUtils.isNotBlank(s)&&StringUtils.isNotBlank(s2)){
            SimpleDateFormat sdf = new SimpleDateFormat("yyyy-mm-ss HH:mm:ss.SSS");
            Date parse = sdf.parse(s);
            Date parse2=sdf.parse(s2);
            Long milisecond1= parse.getTime();
            Long milisecond2= parse2.getTime();
            Long abs = Math.abs(milisecond1 - milisecond2);
            result = (abs.doubleValue()) / 1000D;
        }
        return result;
    }
}

使用UDF的步骤如下：

1. 添加jar/home/hulk/learning/datedistance-1.0-snapshot.jar
2. 将临时函数tmp_date_distance创建为“com.test.datedistance.datedistance”
3. 使用SQL测试UDF:

Select tmp_date_distance('2017-12-26 00:00:02.044','2017-12-26
00:00:03.045') from stg.car_fact_order where dt='2018-01-09' limit 1;

之后，我得到了以下提示：

Error in query: No handler for Hive UDF 'com.sqyc.datedistance.DateDistance'; line 1 pos 7

你能给我一些建议吗？

Answer 1

第二步不正确：

将临时函数tmp_date_distance创建为“com.test.datedistance.datedistance”

Spark UDF与配置单元不兼容，应使用

sqlContext.udf().register(name, object, type);

或（2.0或更高版本）：

spark.udf().register(name, object, type);

但您不需要UDF：

SELECT ABS(
       CAST(CAST('2017-12-26 00:00:02.044' AS TIMESTAMP) AS DOUBLE) - 
       CAST(CAST('2017-12-26 00:00:03.045' AS TIMESTAMP) AS DOUBLE) ) AS diff

+-----------------+
|             diff|
+-----------------+
|1.001000165939331|
+-----------------+

或四舍五入：

SELECT ROUND(ABS(
       CAST(CAST('2017-12-26 00:00:02.044' AS TIMESTAMP) AS DOUBLE) - 
       CAST(CAST('2017-12-26 00:00:03.045' AS TIMESTAMP) AS DOUBLE)), 3) AS diff

+-----+
| diff|
+-----+
|1.001|
+-----+