UDTF(User-Defined Table-Generating Functions) 用来解决 输入一行输出多行(On-to-many maping) 的需求。
继承org.apache.hadoop.hive.ql.udf.generic.GenericUDTF,实现initialize, process, close三个方法。
UDTF首先会调用initialize方法,此方法返回UDTF的返回行的信息(返回个数,类型)。
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。
最后close()方法调用,对需要清理的方法进行清理。
下面是我写的一个用来切分”key:value;key:value;”这种字符串,返回结果为key, value两个字段。供参考:
import java.util.ArrayList; import org.apache.hadoop.hive.ql.udf.generic.GenericUDTF; import org.apache.hadoop.hive.ql.exec.UDFArgumentException; import org.apache.hadoop.hive.ql.exec.UDFArgumentLengthException; import org.apache.hadoop.hive.ql.metadata.HiveException; 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; public class ExplodeMap extends GenericUDTF{ @Override public void close() throws HiveException { // TODO Auto-generated method stub } @Override public StructObjectInspector initialize(ObjectInspector[] args) throws UDFArgumentException { if (args.length != 1) { throw new UDFArgumentLengthException("ExplodeMap takes only one argument"); } if (args[0].getCategory() != ObjectInspector.Category.PRIMITIVE) { throw new UDFArgumentException("ExplodeMap takes string as a parameter"); } 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; } } } }
UDTF有两种使用方法,一种直接放到select后面,一种和lateral view一起使用。
1:直接select中使用
select explode_map(properties) as (col1,col2) from src;
不可以添加其他字段使用
select a, explode_map(properties) as (col1,col2) from src
不可以嵌套调用
select explode_map(explode_map(properties)) from src
不可以和group by/cluster by/distribute by/sort by一起使用
select explode_map(properties) as (col1,col2) from src group by col1, col2
2:和lateral view一起使用
select src.id, mytable.col1, mytable.col2 from src lateral view explode_map(properties) mytable as col1, col2;
此方法更为方便日常使用。执行过程相当于单独执行了两次抽取,然后union到一个表里。
参考文档
http://wiki.apache.org/hadoop/Hive/LanguageManual/UDF
http://wiki.apache.org/hadoop/Hive/DeveloperGuide/UDTF
http://www.slideshare.net/pauly1/userdefined-table-generating-functions