Hive 自定义 UDTF 函数

本是古典何须时尚 2021-12-03 05:34 432阅读 0赞

1.  **继承org.apache.hadoop.hive.ql.udf.generic.GenericUDTF**
2.  **重写 initialize，process 和 close方法**
    
    1.  Hive 调用 initialize 方法来确定传入参数的类型并确定 UDTF 生成表的每个字段的数据类型（即输入类型和输出类型。initialize 方法必须返回一个生成表的字段的相应的 StructObjectInspector。
    2.  初始化完成后，会调用process方法,真正的处理过程在process函数中，在process中，每一次forward()调用产生一行；如果产生多列可以将多个列的值放在一个数组中，然后将该数组传入到forward()函数。
    3.  调用close()方法，对需要清理的方法进行清理。
        
            package com.cloudera.udtf;
            import org.apache.hadoop.hive.ql.exec.UDFArgumentException;
            import org.apache.hadoop.hive.ql.metadata.HiveException;
            import org.apache.hadoop.hive.ql.udf.generic.GenericUDTF;
            import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
            import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory;
            import org.apache.hadoop.hive.serde2.objectinspector.StructObjectInspector;
            import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;	
            import java.util.ArrayList;	
            
            public class UDTFExplode extends GenericUDTF { 
            
                @Override
                public void close() throws HiveException { 
            
                }
            
                @Override
                public StructObjectInspector initialize(StructObjectInspector argOIs) throws UDFArgumentException { 
                    ArrayList<String> fieldNames = new ArrayList<String>();
                    ArrayList<ObjectInspector> fieldOIs = new ArrayList<ObjectInspector>();
                    fieldNames.add("col1");
                    fieldOIs.add(PrimitiveObjectInspectorFactory.javaStringObjectInspector);
                    fieldNames.add("col2");
                    fieldOIs.add(PrimitiveObjectInspectorFactory.javaStringObjectInspector);
                    return ObjectInspectorFactory.getStandardStructObjectInspector(fieldNames, fieldOIs);
                }
            
                @Override
                public void process(Object[] args) throws HiveException { 
                    String input = args[0].toString();
                    String[] test = input.split(";");
                    for (int i = 0; i < test.length; i++) { 
                        try { 
                            String[] result = test[i].split(":");
                            forward(result);
                        } catch (Exception e) { 
                            continue;
                        }
                    }
                }
            }
3.  **打成Jar包，并上传到服务器**
4.  **注册UDF函数**
    
        hive > add jar /root/hive-demo-0.0.1-SNAPSHOT.jar;
        hive > create temporary function split_test as 'com.cloudera.UDTFExplode';
5.  **使用自定义UDTF函数**
    
    1.  直接select中使用
        
            select split_test('asd:123\;rtrt:3445\;vbvx:6787') as (col1,col2) ;
        
            [root@cdh02 ~]# beeline 
            WARNING: Use "yarn jar" to launch YARN applications.
            ...
            Beeline version 2.1.1-cdh6.1.1 by Apache Hive
            beeline> !connect jdbc:hive2://192.168.1.101:10000
            Connecting to jdbc:hive2://192.168.1.101:10000
            Enter username for jdbc:hive2://192.168.1.101:10000: hive
            Enter password for jdbc:hive2://192.168.1.101:10000: 
            Connected to: Apache Hive (version 2.1.1-cdh6.1.1)
            Driver: Hive JDBC (version 2.1.1-cdh6.1.1)
            Transaction isolation: TRANSACTION_REPEATABLE_READ
            0: jdbc:hive2://192.168.1.101:10000> create temporary function split_test as 'com.cloudera.udtf.UDTFExplode';
            ...
            INFO  : OK
            No rows affected (0.248 seconds)
            0: jdbc:hive2://192.168.1.101:10000> select split_test('asd:123\;rtrt:3445\;vbvx:6787') as (col1,col2);
            ...
            INFO  : OK
            +-------+-------+
            | col1  | col2  |
            +-------+-------+
            | asd   | 123   |
            | rtrt  | 3445  |
            | vbvx  | 6787  |
            +-------+-------+
            3 rows selected (18.492 seconds)
        
        **注意:**  
        UDTF不可以添加其他字段使用，不可以嵌套调用，不可以和group by,cluster by,distribute by,sort by一起使用。
    2.  和lateral view一起使用
        
            select '1', mytable.col1, mytable.col2 from dual lateral view split_test('asd:123\;rtrt:3445\;vbvx:6787') mytable as col1, col2;
        
            0: jdbc:hive2://192.168.1.101:10000> select '1', 
            . . . . . . . . . . . . . . . . . .> mytable.col1, 
            . . . . . . . . . . . . . . . . . .> mytable.col2 
            . . . . . . . . . . . . . . . . . .> from test 
            . . . . . . . . . . . . . . . . . .> lateral view split_test('asd:123\;rtrt:3445\;vbvx:6787') 
            . . . . . . . . . . . . . . . . . .> mytable 
            . . . . . . . . . . . . . . . . . .> as col1, col2;
            I...
            INFO  : OK
            +------+---------------+---------------+
            | _c0  | mytable.col1  | mytable.col2  |
            +------+---------------+---------------+
            | 1    | asd           | 123           |
            | 1    | rtrt          | 3445          |
            | 1    | vbvx          | 6787          |
            +------+---------------+---------------+
            9 rows selected (21.693 seconds)