Question

我试图编写一个Hive UDF，它检查Hive表中的列并将字符串与它连接起来。我的Hive table-cityTab架构和数据：

Schema:
id         int
name       char(30)
rank       int

Data:
1   NewYork  10
2   Amsterdam  30

我写了以下Hive UDF：

public class MyHiveUdf extends UDF {
    private Text result = new Text();
    public Text evaluate(Text text) {
        if(text == null) {
            return null;
        } else {
            String str = text.toString();
            if(str.contains("NewYork")) {
                result.set(text.toString().concat(" America"));
            }
            return result;
        }
    }
}

我添加了jar，创建了一个临时函数并按如下所示执行：

ADD jar /home/cloudera/Desktop/HiveStrCon.jar;
create temporary function strcon as 'com.hiveudf.strmnp.MyHiveUdf';
select strcon(name) from cityTab;

但我看到输出数据没有新字符串的任何串联：

OK
NewYork
Amsterdam
Time taken: 0.191 seconds, Fetched: 3 row(s)

谁能告诉我我在这里犯的错误。

Answer 1

我已经尝试了你的例子，它在我的最后工作得很好，只是在代码中做了一个小的改动

public class MyHiveUdf extends UDF {
    private Text result = new Text();
    public Text evaluate(Text text) {
        if(text == null) {
            return null;
        } else {
            String str = text.toString();
            if(str.contains("NewYork")) {
                result.set(text.toString().concat(" America"));
                return result;
            }
            return text;
        }
    }

hive> ADD jar /root/HiveStrCon.jar;
Added [/root/HiveStrCon.jar] to class path
Added resources: [/root/HiveStrCon.jar]
hive> create temporary function strcon as 'com.hiveudf.strmnp.MyHiveUdf';
OK
Time taken: 0.005 seconds
hive> select strcon(name) from cityTab;
Query ID = root_20170331132222_690e8d43-381c-4e40-a90b-368397c1df5b
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1490796950103_0007, Tracking URL = http://mac127:8088/proxy/application_1490796950103_0007/
Kill Command = /opt/cloudera/parcels/CDH-5.9.0-1.cdh5.9.0.p0.23/lib/hadoop/bin/hadoop job  -kill job_1490796950103_0007
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
2017-03-31 13:22:42,264 Stage-1 map = 0%,  reduce = 0%
2017-03-31 13:22:50,720 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 2.14 sec
MapReduce Total cumulative CPU time: 2 seconds 140 msec
Ended Job = job_1490796950103_0007
MapReduce Jobs Launched:
Stage-Stage-1: Map: 1   Cumulative CPU: 2.14 sec   HDFS Read: 3166 HDFS Write: 26 SUCCESS
Total MapReduce CPU Time Spent: 2 seconds 140 msec
OK
NewYork America
Amsterdam
Time taken: 19.788 seconds, Fetched: 2 row(s)

我的HiveUDF中的错误

1 个答案: