Hive_UDF开发指南
最近在看 《Hive 编程指南》 其中提到了对Hive 自定义函数的几种扩展，
对于我们日常开发，这个功能还是非常有用的。
打算细致的研究一下，这里我们将研究结果整理成博客，方便大家理解 ：
参考文章：
- Hive UDF教程（一）https://blog.csdn.net/u010376788/article/details/50532166
- Hive开发UDFhttps://blog.csdn.net/qq_33792843/article/details/74945718#commentBox
- hive UDF 测试样例开发 https://blog.csdn.net/zwjzqqb/article/details/79042636
- Hive- UDF&GenericUDF https://www.jianshu.com/p/ca9dce6b5c37
- [一起学Hive]之十八-Hive UDF开 https://www.cnblogs.com/1130136248wlxk/articles/5519276.html
- Hive+GenericUDF示例二 https://blog.csdn.net/wisgood/article/details/26169383
- Hive+GenericUDF示例一 https://blog.csdn.net/wisgood/article/details/26169313
- 将Hive统计分析结果导入到MySQL数据库表中（三）——使用Hive UDF或GenericUDF http://www.bubuko.com/infodetail-763295.html
本篇主要讲解 UDF , 对于 UDAF (用户自定义聚合函数) ， UDTF ( 用户自定义表生成函数 )
对于 这两个请参考问的其他博文
UDAF (用户自定义聚合函数)
UDTF (用户自定义表生成函数)
本文大纲
1. UDF 实现的两种策略
2. UDF 中的注解
3. 简单的 UDF 实现
4. 更为复杂的 GenericUDF 实现
5. 打包,加入到集群中,进行测试。
1. UDF 实现的两种策略
Hive 的 UDF 主要分为2种类型的接口 UDF, GenericUDF
1) UDF 为一种比较简单的类，继承的基类为 org.apache.hadoop.hive.ql.exec.UDF;
2) GenericUDF 相对复杂一些，主要针对于类型检查等具有更好的控制，
继承的基类为 org.apache.hadoop.hive.ql.udf.generic.GenericUDF;
2. UDF 中的注解
在对这接口进行讲解之前，我们先对基本的注解进行一下讲解。注解非常有利于我们程序的开发。
对于UDF 注解主要使用 @Description 注解
@Description 注解
主要的3个属性： name ， value , extended
主要的宏 ：_FUNC_
---------------------------------------------------------------------------------------
还有一些其他的注解
public @interface UDFType {
boolean deterministic() default true;
boolean stateful() default false;
boolean distinctLike() default false;
}
=============================
下面先对 @Description 注解 进行详细的讲解。
@Description 是可选的。该注解主要注明了关于函数的文档说明。
主要的3个属性： name ， value , extended
name : 表明了该函数的名称。
value : 描述了该函数在 DESCRIBE FUNCTION ... 时 显示的提示。
extended : 主要用来编写示例，如 函数使用示例，DESCRIBE FUNCTION EXTENDED 显示的提示。
主要的宏 ：_FUNC_
_FUN_ 会被替换为 这个函数定义的“临时”函数名称
下面是一些DESCRIBE FUNCTION / DESCRIBE FUNCTION EXTENDED 的例子：
下面是一个 @Description 注解使用的示例：
/**
* Created by szh on 2018/7/16.
*
* @author szh
* @date 2018/7/16
*/
@Description(
name = "zodiac",
value = "_FUNC_ (date) - " +
" from the input date string " +
" or separate month and day arguments, \n" +
" returns the sign of the Zodiac.",
extended = "Example :\n" +
"> SELECT _FUNC_ (date_string) FROM src;\n" +
"> SELECT _FUNC_ (month, day) FROM src;")
public class HiveTestZodiacUDF extends UDF {===============================
public @interface UDFType {
boolean deterministic() default true;
boolean stateful() default false;
boolean distinctLike() default false;
}
deterministic 定数性标注：
大多数函数都是定数性的，rand() 函数是个例外。如果rand() 是定数性的，那么结果只会在计算阶段计算一次。
如果一个UDF 是非定数性的，那么就不会包含在分区裁剪中。
因为包含rand() 是非定数性的，因此对于每一行数据，rand() 的值都会重新计算一次。
stateful 状态性标注：
几乎所有的UDF 默认都是有状态性的，rand() 函数是无状态性的，每次调用都会返回不同的值。
stateful 适用以下场景：
1） 有状态性的UDF 只能使用在SELECT 语句后面， 而不能使用到其他如 WHERE, ON, ORDER, GROUP 语句后面。
2）当一个查询语句中存在有状态性的UDF时，其隐含信息是，SELECT 将会和 TRANSFORM (例如，DISTRIBUTE,
CLUSTER, SORT 语句 ) 进行类似的处理，然会会在对应的Reducer 内部进行执行，以保证结果是预期的结果。
3）如果状态性标记 statefule 设置为 true, 那么这个UDF 同样作为非定数性的。
（ 即使此时定数性标记 deterministic 的值是显式设置为 true 的 ）。
distinctLike 唯一性标注：
有些函数，即使其输入的列的值是非排重值，其结果也是类似于使用了DISTINCT 进行了排重操作，这类场景可以定义为
具有唯一性。
例子有min, max ，即使实际数据中有重复值，其最终结果也是唯一排重值。
最新版本的 UDFType
//
// Source code recreated from a .class file by IntelliJ IDEA
// (powered by Fernflower decompiler)
//
package org.apache.hadoop.hive.ql.udf;
import java.lang.annotation.ElementType;
import java.lang.annotation.Inherited;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;
import org.apache.hadoop.hive.common.classification.InterfaceAudience.Public;
import org.apache.hadoop.hive.common.classification.InterfaceStability.Evolving;
@Target({ElementType.TYPE})
@Retention(RetentionPolicy.RUNTIME)
@Inherited
@Public
@Evolving
public @interface UDFType {
boolean deterministic() default true;
boolean stateful() default false;
boolean distinctLike() default false;
boolean impliesOrder() default false;
}
对于 impliesOrder 属性的作用，目前我不是特别的明确，欢迎清楚的朋友在评论区补充。
3. 简单的 UDF 实现
UDF 主要需要实现evaluate() 函数。
并主要通过方法重载的方式实现对多种数据的支持。
需要注意的是：
在查询执行过程中，查询中对应的每个应用到该函数的地方都会对这个类进行实例化。
示例如下：
UDF 功能描述，该UDF 主要用于判断某一个日期属于哪一个星座。
package com.test.hive.udf;
import org.apache.hadoop.hive.ql.exec.Description;
import org.apache.hadoop.hive.ql.exec.UDF;
import org.apache.hadoop.hive.ql.udf.UDFType;
import org.joda.time.DateTime;
import java.util.Date;
/**
* Created by szh on 2018/7/16.
*
* @author szh
* @date 2018/7/16
*/
@UDFType
@Description(
name = "zodiac",
value = "_FUNC_ (date) - " +
" from the input date string " +
" or separate month and day arguments, \n" +
" returns the sign of the Zodiac.",
extended = "Example :\n" +
"> SELECT _FUNC_ (date_string) FROM src;\n" +
"> SELECT _FUNC_ (month, day) FROM src;")
public class HiveTestZodiacUDF extends UDF {
private static final String ERROR_DATE_OF_MONTH = "invalid date of specify month";
private static final String ERROR_MONTH_ARGS = "invalid argument of month";
private static final String ERROR_DATE_STRING = "invalid date format";
public String evaluate(Date bday) {
return this.evaluate(bday.getMonth(), bday.getDay());
}
public String evaluate(String dateString) {
DateTime dateTime = null;
try {
dateTime = new DateTime(dateString);
} catch (Exception e) {
return ERROR_DATE_STRING;
}
return this.evaluate(dateTime.getMonthOfYear(), dateTime.getDayOfMonth());
}
public String evaluate(Integer month, Integer day) {
switch (month) {
//判断是几月
case 1:
//判断是当前月的哪一段时间；然后就可以得到星座了；下面代码都一样的
if (day > 0 && day < 20) {
return "魔蝎座";
} else if (day < 32) {
return "水瓶座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 2:
if (day > 0 && day < 19) {
return "水瓶座";
} else if (day < 29) {
return "双鱼座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 3:
if (day > 0 && day < 21) {
return "双鱼座";
} else if (day < 32) {
return "白羊座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 4:
if (day > 0 && day < 20) {
return "白羊座";
} else if (day < 31) {
return "金牛座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 5:
if (day > 0 && day < 21) {
return "金牛座";
} else if (day < 32) {
return "双子座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 6:
if (day > 0 && day < 22) {
return "双子座";
} else if (day < 31) {
return "巨蟹座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 7:
if (day > 0 && day < 23) {
return "巨蟹座";
} else if (day < 32) {
return "狮子座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 8:
if (day > 0 && day < 23) {
return "狮子座";
} else if (day < 32) {
return "处女座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 9:
if (day > 0 && day < 23) {
return "处女座";
} else if (day < 31) {
return "天平座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 10:
if (day > 0 && day < 24) {
return "天平座";
} else if (day < 32) {
return "天蝎座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 11:
if (day > 0 && day < 23) {
return "天蝎座";
} else if (day < 31) {
return "射手座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 12:
if (day > 0 && day < 22) {
return "射手座";
} else if (day < 32) {
return "摩羯座";
} else {
return ERROR_DATE_OF_MONTH;
}
default:
return ERROR_MONTH_ARGS;
}
}
}
4. 更为复杂的 GenericUDF 实现
GenericUDF 是一个更为复杂的类，其主要对代码整理构建，使用了模板模式，规范了各个步奏应该完成的流程。
我们先来看下 GenricUDF 的源码：
//
// Source code recreated from a .class file by IntelliJ IDEA
// (powered by Fernflower decompiler)
//
package org.apache.hadoop.hive.ql.udf.generic;
import java.io.Closeable;
import java.io.IOException;
import java.sql.Timestamp;
import java.text.ParseException;
import java.util.Date;
import org.apache.hadoop.hive.ql.exec.FunctionRegistry;
import org.apache.hadoop.hive.ql.exec.MapredContext;
import org.apache.hadoop.hive.ql.exec.UDFArgumentException;
import org.apache.hadoop.hive.ql.exec.UDFArgumentLengthException;
import org.apache.hadoop.hive.ql.exec.UDFArgumentTypeException;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.udf.UDFType;
import org.apache.hadoop.hive.serde2.io.ByteWritable;
import org.apache.hadoop.hive.serde2.io.DateWritable;
import org.apache.hadoop.hive.serde2.io.DoubleWritable;
import org.apache.hadoop.hive.serde2.io.ShortWritable;
import org.apache.hadoop.hive.serde2.io.TimestampWritable;
import org.apache.hadoop.hive.serde2.objectinspector.ConstantObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorConverters;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorUtils;
import org.apache.hadoop.hive.serde2.objectinspector.PrimitiveObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector.Category;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorConverters.Converter;
import org.apache.hadoop.hive.serde2.objectinspector.PrimitiveObjectInspector.PrimitiveCategory;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorUtils;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorUtils.PrimitiveGrouping;
import org.apache.hadoop.io.BooleanWritable;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hive.common.util.DateUtils;
@UDFType(
deterministic = true
)
public abstract class GenericUDF implements Closeable {
private static final String[] ORDINAL_SUFFIXES = new String[]{"th", "st", "nd", "rd", "th", "th", "th", "th", "th", "th"};
public GenericUDF() {
}
public abstract ObjectInspector initialize(ObjectInspector[] var1) throws UDFArgumentException;
public void configure(MapredContext context) {
}
public ObjectInspector initializeAndFoldConstants(ObjectInspector[] arguments) throws UDFArgumentException {
ObjectInspector oi = this.initialize(arguments);
if(this.getRequiredFiles() == null && this.getRequiredJars() == null) {
boolean allConstant = true;
for(int ii = 0; ii < arguments.length; ++ii) {
if(!ObjectInspectorUtils.isConstantObjectInspector(arguments[ii])) {
allConstant = false;
break;
}
}
if(allConstant && !ObjectInspectorUtils.isConstantObjectInspector((ObjectInspector)oi) && FunctionRegistry.isDeterministic(this) && !FunctionRegistry.isStateful(this) && ObjectInspectorUtils.supportsConstantObjectInspector((ObjectInspector)oi)) {
GenericUDF.DeferredObject[] argumentValues = new GenericUDF.DeferredJavaObject[arguments.length];
for(int ii = 0; ii < arguments.length; ++ii) {
argumentValues[ii] = new GenericUDF.DeferredJavaObject(((ConstantObjectInspector)arguments[ii]).getWritableConstantValue());
}
try {
Object constantValue = this.evaluate(argumentValues);
oi = ObjectInspectorUtils.getConstantObjectInspector((ObjectInspector)oi, constantValue);
} catch (HiveException var6) {
throw new UDFArgumentException(var6);
}
}
return (ObjectInspector)oi;
} else {
return (ObjectInspector)oi;
}
}
public String[] getRequiredJars() {
return null;
}
public String[] getRequiredFiles() {
return null;
}
public abstract Object evaluate(GenericUDF.DeferredObject[] var1) throws HiveException;
public abstract String getDisplayString(String[] var1);
public void close() throws IOException {
}
public GenericUDF flip() {
return this;
}
public GenericUDF negative() {
throw new UnsupportedOperationException("Negative function doesn't exist for " + this.getFuncName());
}
public String getUdfName() {
return this.getClass().getName();
}
public void copyToNewInstance(Object newInstance) throws UDFArgumentException {
if(this.getClass() != newInstance.getClass()) {
throw new UDFArgumentException("Invalid copy between " + this.getClass().getName() + " and " + newInstance.getClass().getName());
}
}
protected String getStandardDisplayString(String name, String[] children) {
return this.getStandardDisplayString(name, children, ", ");
}
protected String getStandardDisplayString(String name, String[] children, String delim) {
StringBuilder sb = new StringBuilder();
sb.append(name);
sb.append("(");
if(children.length > 0) {
sb.append(children[0]);
for(int i = 1; i < children.length; ++i) {
sb.append(delim);
sb.append(children[i]);
}
}
sb.append(")");
return sb.toString();
}
protected String getFuncName() {
return this.getClass().getSimpleName().substring(10).toLowerCase();
}
protected void checkArgsSize(ObjectInspector[] arguments, int min, int max) throws UDFArgumentLengthException {
if(arguments.length < min || arguments.length > max) {
StringBuilder sb = new StringBuilder();
sb.append(this.getFuncName());
sb.append(" requires ");
if(min == max) {
sb.append(min);
} else {
sb.append(min).append("..").append(max);
}
sb.append(" argument(s), got ");
sb.append(arguments.length);
throw new UDFArgumentLengthException(sb.toString());
}
}
protected void checkArgPrimitive(ObjectInspector[] arguments, int i) throws UDFArgumentTypeException {
Category oiCat = arguments[i].getCategory();
if(oiCat != Category.PRIMITIVE) {
throw new UDFArgumentTypeException(i, this.getFuncName() + " only takes primitive types as " + this.getArgOrder(i) + " argument, got " + oiCat);
}
}
protected void checkArgGroups(ObjectInspector[] arguments, int i, PrimitiveCategory[] inputTypes, PrimitiveGrouping... grps) throws UDFArgumentTypeException {
PrimitiveCategory inputType = ((PrimitiveObjectInspector)arguments[i]).getPrimitiveCategory();
PrimitiveGrouping[] var6 = grps;
int j = grps.length;
for(int var8 = 0; var8 < j; ++var8) {
PrimitiveGrouping grp = var6[var8];
if(PrimitiveObjectInspectorUtils.getPrimitiveGrouping(inputType) == grp) {
inputTypes[i] = inputType;
return;
}
}
StringBuilder sb = new StringBuilder();
sb.append(this.getFuncName());
sb.append(" only takes ");
sb.append(grps[0]);
for(j = 1; j < grps.length; ++j) {
sb.append(", ");
sb.append(grps[j]);
}
sb.append(" types as ");
sb.append(this.getArgOrder(i));
sb.append(" argument, got ");
sb.append(inputType);
throw new UDFArgumentTypeException(i, sb.toString());
}
protected void obtainStringConverter(ObjectInspector[] arguments, int i, PrimitiveCategory[] inputTypes, Converter[] converters) throws UDFArgumentTypeException {
PrimitiveObjectInspector inOi = (PrimitiveObjectInspector)arguments[i];
PrimitiveCategory inputType = inOi.getPrimitiveCategory();
Converter converter = ObjectInspectorConverters.getConverter(arguments[i], PrimitiveObjectInspectorFactory.writableStringObjectInspector);
converters[i] = converter;
inputTypes[i] = inputType;
}
protected void obtainIntConverter(ObjectInspector[] arguments, int i, PrimitiveCategory[] inputTypes, Converter[] converters) throws UDFArgumentTypeException {
PrimitiveObjectInspector inOi = (PrimitiveObjectInspector)arguments[i];
PrimitiveCategory inputType = inOi.getPrimitiveCategory();
switch(null.$SwitchMap$org$apache$hadoop$hive$serde2$objectinspector$PrimitiveObjectInspector$PrimitiveCategory[inputType.ordinal()]) {
case 1:
case 2:
case 3:
case 4:
Converter converter = ObjectInspectorConverters.getConverter(arguments[i], PrimitiveObjectInspectorFactory.writableIntObjectInspector);
converters[i] = converter;
inputTypes[i] = inputType;
return;
default:
throw new UDFArgumentTypeException(i, this.getFuncName() + " only takes INT/SHORT/BYTE types as " + this.getArgOrder(i) + " argument, got " + inputType);
}
}
protected void obtainLongConverter(ObjectInspector[] arguments, int i, PrimitiveCategory[] inputTypes, Converter[] converters) throws UDFArgumentTypeException {
PrimitiveObjectInspector inOi = (PrimitiveObjectInspector)arguments[i];
PrimitiveCategory inputType = inOi.getPrimitiveCategory();
switch(null.$SwitchMap$org$apache$hadoop$hive$serde2$objectinspector$PrimitiveObjectInspector$PrimitiveCategory[inputType.ordinal()]) {
case 1:
case 2:
case 3:
case 5:
Converter converter = ObjectInspectorConverters.getConverter(arguments[i], PrimitiveObjectInspectorFactory.writableIntObjectInspector);
converters[i] = converter;
inputTypes[i] = inputType;
return;
case 4:
default:
throw new UDFArgumentTypeException(i, this.getFuncName() + " only takes LONG/INT/SHORT/BYTE types as " + this.getArgOrder(i) + " argument, got " + inputType);
}
}
protected void obtainDoubleConverter(ObjectInspector[] arguments, int i, PrimitiveCategory[] inputTypes, Converter[] converters) throws UDFArgumentTypeException {
PrimitiveObjectInspector inOi = (PrimitiveObjectInspector)arguments[i];
PrimitiveCategory inputType = inOi.getPrimitiveCategory();
Converter converter = ObjectInspectorConverters.getConverter(arguments[i], PrimitiveObjectInspectorFactory.writableDoubleObjectInspector);
converters[i] = converter;
inputTypes[i] = inputType;
}
protected void obtainDateConverter(ObjectInspector[] arguments, int i, PrimitiveCategory[] inputTypes, Converter[] converters) throws UDFArgumentTypeException {
PrimitiveObjectInspector inOi = (PrimitiveObjectInspector)arguments[i];
PrimitiveCategory inputType = inOi.getPrimitiveCategory();
Object outOi;
switch(null.$SwitchMap$org$apache$hadoop$hive$serde2$objectinspector$PrimitiveObjectInspector$PrimitiveCategory[inputType.ordinal()]) {
case 4:
case 9:
case 10:
outOi = PrimitiveObjectInspectorFactory.writableDateObjectInspector;
break;
case 5:
default:
throw new UDFArgumentTypeException(i, this.getFuncName() + " only takes STRING_GROUP or DATE_GROUP types as " + this.getArgOrder(i) + " argument, got " + inputType);
case 6:
case 7:
case 8:
outOi = PrimitiveObjectInspectorFactory.writableStringObjectInspector;
}
converters[i] = ObjectInspectorConverters.getConverter(inOi, (ObjectInspector)outOi);
inputTypes[i] = inputType;
}
protected void obtainTimestampConverter(ObjectInspector[] arguments, int i, PrimitiveCategory[] inputTypes, Converter[] converters) throws UDFArgumentTypeException {
PrimitiveObjectInspector inOi = (PrimitiveObjectInspector)arguments[i];
PrimitiveCategory inputType = inOi.getPrimitiveCategory();
switch(null.$SwitchMap$org$apache$hadoop$hive$serde2$objectinspector$PrimitiveObjectInspector$PrimitiveCategory[inputType.ordinal()]) {
case 6:
case 7:
case 8:
case 9:
case 10:
ObjectInspector outOi = PrimitiveObjectInspectorFactory.writableTimestampObjectInspector;
converters[i] = ObjectInspectorConverters.getConverter(inOi, outOi);
inputTypes[i] = inputType;
return;
default:
throw new UDFArgumentTypeException(i, this.getFuncName() + " only takes STRING_GROUP or DATE_GROUP types as " + this.getArgOrder(i) + " argument, got " + inputType);
}
}
protected String getStringValue(GenericUDF.DeferredObject[] arguments, int i, Converter[] converters) throws HiveException {
Object obj;
return (obj = arguments[i].get()) == null?null:converters[i].convert(obj).toString();
}
protected Integer getIntValue(GenericUDF.DeferredObject[] arguments, int i, Converter[] converters) throws HiveException {
Object obj;
if((obj = arguments[i].get()) == null) {
return null;
} else {
Object writableValue = converters[i].convert(obj);
int v = ((IntWritable)writableValue).get();
return Integer.valueOf(v);
}
}
protected Long getLongValue(GenericUDF.DeferredObject[] arguments, int i, Converter[] converters) throws HiveException {
Object obj;
if((obj = arguments[i].get()) == null) {
return null;
} else {
Object writableValue = converters[i].convert(obj);
long v = ((LongWritable)writableValue).get();
return Long.valueOf(v);
}
}
protected Double getDoubleValue(GenericUDF.DeferredObject[] arguments, int i, Converter[] converters) throws HiveException {
Object obj;
if((obj = arguments[i].get()) == null) {
return null;
} else {
Object writableValue = converters[i].convert(obj);
double v = ((DoubleWritable)writableValue).get();
return Double.valueOf(v);
}
}
protected Date getDateValue(GenericUDF.DeferredObject[] arguments, int i, PrimitiveCategory[] inputTypes, Converter[] converters) throws HiveException {
Object obj;
if((obj = arguments[i].get()) == null) {
return null;
} else {
Object date;
switch(null.$SwitchMap$org$apache$hadoop$hive$serde2$objectinspector$PrimitiveObjectInspector$PrimitiveCategory[inputTypes[i].ordinal()]) {
case 6:
case 7:
case 8:
String dateStr = converters[i].convert(obj).toString();
try {
date = DateUtils.getDateFormat().parse(dateStr);
break;
} catch (ParseException var9) {
return null;
}
case 9:
case 10:
Object writableValue = converters[i].convert(obj);
date = ((DateWritable)writableValue).get();
break;
default:
throw new UDFArgumentTypeException(0, this.getFuncName() + " only takes STRING_GROUP and DATE_GROUP types, got " + inputTypes[i]);
}
return (Date)date;
}
}
protected Timestamp getTimestampValue(GenericUDF.DeferredObject[] arguments, int i, Converter[] converters) throws HiveException {
Object obj;
if((obj = arguments[i].get()) == null) {
return null;
} else {
Object writableValue = converters[i].convert(obj);
if(writableValue == null) {
return null;
} else {
Timestamp ts = ((TimestampWritable)writableValue).getTimestamp();
return ts;
}
}
}
protected String getConstantStringValue(ObjectInspector[] arguments, int i) {
Object constValue = ((ConstantObjectInspector)arguments[i]).getWritableConstantValue();
String str = constValue == null?null:constValue.toString();
return str;
}
protected Boolean getConstantBooleanValue(ObjectInspector[] arguments, int i) throws UDFArgumentTypeException {
Object constValue = ((ConstantObjectInspector)arguments[i]).getWritableConstantValue();
if(constValue == null) {
return Boolean.valueOf(false);
} else if(constValue instanceof BooleanWritable) {
return Boolean.valueOf(((BooleanWritable)constValue).get());
} else {
throw new UDFArgumentTypeException(i, this.getFuncName() + " only takes BOOLEAN types as " + this.getArgOrder(i) + " argument, got " + constValue.getClass());
}
}
protected Integer getConstantIntValue(ObjectInspector[] arguments, int i) throws UDFArgumentTypeException {
Object constValue = ((ConstantObjectInspector)arguments[i]).getWritableConstantValue();
if(constValue == null) {
return null;
} else {
int v;
if(constValue instanceof IntWritable) {
v = ((IntWritable)constValue).get();
} else if(constValue instanceof ShortWritable) {
v = ((ShortWritable)constValue).get();
} else {
if(!(constValue instanceof ByteWritable)) {
throw new UDFArgumentTypeException(i, this.getFuncName() + " only takes INT/SHORT/BYTE types as " + this.getArgOrder(i) + " argument, got " + constValue.getClass());
}
v = ((ByteWritable)constValue).get();
}
return Integer.valueOf(v);
}
}
protected String getArgOrder(int i) {
++i;
switch(i % 100) {
case 11:
case 12:
case 13:
return i + "th";
default:
return i + ORDINAL_SUFFIXES[i % 10];
}
}
public static class DeferredJavaObject implements GenericUDF.DeferredObject {
private final Object value;
public DeferredJavaObject(Object value) {
this.value = value;
}
public void prepare(int version) throws HiveException {
}
public Object get() throws HiveException {
return this.value;
}
}
public interface DeferredObject {
void prepare(int var1) throws HiveException;
Object get() throws HiveException;
}
}可以看到对于GenericUDF 类，我们使用了 deterministic 定数性标注，
deterministic 定数性标注：
大多数函数都是定数性的，rand() 函数是个例外。如果rand() 是定数性的，那么结果只会在计算阶段计算一次。
如果一个UDF 是非定数性的，那么就不会包含在分区裁剪中。
因为包含rand() 是非定数性的，因此对于每一行数据，rand() 的值都会重新计算一次。
我们继承一下 GenricUDF 类，看需要实现那几个方法
/**
* Created by szh on 2018/7/17.
*
* @author szh
* @date 2018-07-17
*/
public class HiveTestGenericUDF extends GenericUDF {
@Override
public ObjectInspector initialize(ObjectInspector[] objectInspectors) throws UDFArgumentException {
return null;
}
@Override
public Object evaluate(DeferredObject[] deferredObjects) throws HiveException {
return null;
}
@Override
public String getDisplayString(String[] strings) {
return null;
}
}需要注意的几个方法：
public void configure(MapredContext context) { }
//可选，该方法中可以通过context.getJobConf()获取job执行时候的Configuration；
//可以通过Configuration传递参数值
public ObjectInspector initialize(ObjectInspector[] arguments) { }
//必选，该方法用于函数初始化操作，并定义函数的返回值类型；
//比如，在该方法中可以初始化对象实例，初始化数据库链接，初始化读取文件等；
public Object evaluate(DeferredObject[] args){ }
//必选，函数处理的核心方法，用途和UDF中的evaluate一样；
public String getDisplayString(String[] children) { }
//必选，显示函数的提示信息（当出现异常导致终止的时候）
public void close(){ }
//可选，map完成后，执行关闭操作
一些开发注意事项：
注意：在Hive-1.0.1估计之后的版本也是，evaluate()方法中从Object Inspectors取出的值，需要先保存为Lazy包中的数据类型（org.apache.hadoop.hive.serde2.lazy），然后才能转换成Java的数据类型进行处理。否则会报错，解决方案可以参考Hive报错集锦中的第5个。
该提议经实际测试并未发生，目前不知道具体的原因 ，请知道原因的小伙伴踊跃留言 ！！！！
private GenericUDFUtils.ReturnObjectInspectorResolver returnObjectInspectorResolver;
returnObjectInspectorResolver 是一个内置的类，其通过获取非null 的值的变量并使用这个数据类型来确定返回值类型。
示例：
该函数功能与上面的UDF 函数功能一致。即计算某一个日期的星座。
package com.test.hive.udf;
import org.apache.hadoop.hive.ql.exec.Description;
import org.apache.hadoop.hive.ql.exec.UDFArgumentException;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.udf.UDFType;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDF;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils;
import org.apache.hadoop.hive.serde2.lazy.LazyDate;
import org.apache.hadoop.hive.serde2.lazy.LazyInteger;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.*;
import org.joda.time.DateTime;
import java.util.Date;
/**
* Created by szh on 2018/7/17.
*
* @author szh
* @date 2018-07-17
*/
@UDFType
@Description(
name = "zodiac",
value = "_FUNC_ (date) - " +
" from the input date string " +
" or separate month and day arguments, \n" +
" returns the sign of the Zodiac.",
extended = "Example :\n" +
"> SELECT _FUNC_ (date_string) FROM src;\n" +
"> SELECT _FUNC_ (month, day) FROM src;")
public class HiveTestZodiacGenericUDF extends GenericUDF {
private static final Integer ONE_ARG = 1;
private static final Integer TWO_ARG = 2;
private StringObjectInspector dateString = null;
private DateObjectInspector dateObject = null;
private IntObjectInspector monthInt = null;
private IntObjectInspector dayInt = null;
private static final String ERROR_DATE_OF_MONTH = "invalid date of specify month";
private static final String ERROR_MONTH_ARGS = "invalid argument of month";
private static final String ERROR_DATE_STRING = "invalid date format";
private GenericUDFUtils.ReturnObjectInspectorResolver returnObjectInspectorResolver;
@Override
//必选，该方法用于函数初始化操作，并定义函数的返回值类型；
//比如，在该方法中可以初始化对象实例，初始化数据库链接，初始化读取文件等；
public ObjectInspector initialize(ObjectInspector[] objectInspectors) throws UDFArgumentException {
Integer len = objectInspectors.length;
if (!len.equals(ONE_ARG) && !len.equals(TWO_ARG)) {
throw new UDFArgumentException("Not Invalid num of arguments");
}
if (len.equals(ONE_ARG)) {
ObjectInspector tmpDate = objectInspectors[0];
if (tmpDate instanceof DateObjectInspector) {
this.dateObject = (DateObjectInspector) tmpDate;
} else if (tmpDate instanceof StringObjectInspector) {
this.dateString = (StringObjectInspector) tmpDate;
} else {
throw new UDFArgumentException("Not Invalid type of date (string or date)");
}
}
if (len.equals(TWO_ARG)) {
ObjectInspector tmpMonthInt = objectInspectors[0];
ObjectInspector tmpDayInt = objectInspectors[1];
if (!(tmpDayInt instanceof IntObjectInspector) || !(tmpMonthInt instanceof IntObjectInspector)) {
throw new UDFArgumentException("Not Invalid type of month or day , please use int type");
}
this.monthInt = (IntObjectInspector) tmpMonthInt;
this.dayInt = (IntObjectInspector) tmpDayInt;
}
//确定返回值类型
return PrimitiveObjectInspectorFactory.javaStringObjectInspector;
}
@Override
public Object evaluate(DeferredObject[] deferredObjects) throws HiveException {
Integer length = deferredObjects.length;
Integer month = null;
Integer day = null;
if (length.equals(ONE_ARG)) {
if (this.dateObject != null) {
// LazyDate dateObjTmp = (LazyDate) ((deferredObjects[0].get()));
// Date date = (this.dateObject).getPrimitiveJavaObject(dateObjTmp);
Date date = (this.dateObject).getPrimitiveJavaObject(deferredObjects[0].get());
DateTime dateTime = new DateTime(date);
month = dateTime.getMonthOfYear();
day = dateTime.getDayOfMonth();
} else if (this.dateString != null) {
// LazyDate dateStringTmp = (LazyDate) (deferredObjects[0].get());
// String dateString = (this.dateString).getPrimitiveJavaObject(dateStringTmp);
String dateString = (this.dateString).getPrimitiveJavaObject(deferredObjects[0].get());
DateTime dateTime = new DateTime(dateString);
month = dateTime.getMonthOfYear();
day = dateTime.getDayOfMonth();
}
}
if (length.equals(TWO_ARG)) {
// LazyInteger monthIntTmp = (LazyInteger) (deferredObjects[0].get());
// LazyInteger dayIntTmp = (LazyInteger) ((deferredObjects[1].get()));
// month = (this.monthInt).get(monthIntTmp);
// day = (this.dayInt).get(dayIntTmp);
month = this.monthInt.get(deferredObjects[0].get());
day = this.dayInt.get(deferredObjects[1].get());
}
switch (month) {
//判断是几月
case 1:
//判断是当前月的哪一段时间；然后就可以得到星座了；下面代码都一样的
if (day > 0 && day < 20) {
return "魔蝎座";
} else if (day < 32) {
return "水瓶座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 2:
if (day > 0 && day < 19) {
return "水瓶座";
} else if (day < 29) {
return "双鱼座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 3:
if (day > 0 && day < 21) {
return "双鱼座";
} else if (day < 32) {
return "白羊座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 4:
if (day > 0 && day < 20) {
return "白羊座";
} else if (day < 31) {
return "金牛座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 5:
if (day > 0 && day < 21) {
return "金牛座";
} else if (day < 32) {
return "双子座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 6:
if (day > 0 && day < 22) {
return "双子座";
} else if (day < 31) {
return "巨蟹座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 7:
if (day > 0 && day < 23) {
return "巨蟹座";
} else if (day < 32) {
return "狮子座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 8:
if (day > 0 && day < 23) {
return "狮子座";
} else if (day < 32) {
return "处女座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 9:
if (day > 0 && day < 23) {
return "处女座";
} else if (day < 31) {
return "天平座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 10:
if (day > 0 && day < 24) {
return "天平座";
} else if (day < 32) {
return "天蝎座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 11:
if (day > 0 && day < 23) {
return "天蝎座";
} else if (day < 31) {
return "射手座";
} else {
return ERROR_DATE_OF_MONTH;
}
case 12:
if (day > 0 && day < 22) {
return "射手座";
} else if (day < 32) {
return "摩羯座";
} else {
return ERROR_DATE_OF_MONTH;
}
default:
return ERROR_MONTH_ARGS;
}
}
@Override
public String getDisplayString(String[] strings) {
return "Please check your code, unknown Exception!!!";
}
}
5. 打包,加入到集群中,进行测试。
为了方便大家确保环境一致，这里我贴出我编程环境的pom.xml
4.0.0
hive
hive-udf-test
1.0-SNAPSHOT
3.0.0
2.3.2
org.apache.hive
hive-exec
${hive.version}
org.apache.hadoop
hadoop-common
3.0.0
junit
junit
4.10
test
org.apache.maven.plugins
maven-compiler-plugin
2.3.2
1.8
1.8
UTF-8
下面演示下如何打包，这里我使用的是IDEA , IDEA 中集成较好，
打完包如图所示：
我们将这个包拷贝到 hive 目录下，另创建一个 my-jar 目录
执行 hive 客户端进行测试，
beeline -u jdbc:hive2://master:10000/test -n root
将打好的jar 载入hive 客户端：
（注意，载入的jar 只在此连接生效，并不会跨客户端，也就是说另一个客户端需要重新 add jar）
Hive 不仅将这个JAR文件加入到classpath 下，同时还将其加入到了分布式缓存中。
add jar /usr/local/hive/my-jar/hive-udf-test-1.0-SNAPSHOT.jar;
查看已经载入的jar
list jars;
注册函数：
create temporary function zodiac as 'com.test.hive.udf.HiveTestZodiacUDF';
create temporary function zodiacx as 'com.test.hive.udf.HiveTestZodiacGenericUDF';
查看函数帮助文档：
describe function zodiac;
describe function zodiacx;
describe function extended zodiac;
describe function extended zodiacx;
构造测试用例：
先测试下函数功能：
创建表 :
create table date_one(day string);
构建正确的样例：
insert into date_one values ('1992-12-25'),('2018-01-20'),('2018-07-20');
查询：
select zodiac(day) from date_one;
select zodiacx(day) from date_one;
插入错误的数据：
insert into date_one values ('2222-32'),('2018-04-20'),('2018-17-20');
查询数据：
select zodiac(day) from date_one;
0: jdbc:hive2://master:10000/test> select zodiac(day) from date_one;
+----------------------+--+
| _c0 |
+----------------------+--+
| 摩羯座 |
| 水瓶座 |
| 巨蟹座 |
| invalid date format |
| 金牛座 |
| invalid date format |
+----------------------+--+
6 rows selected (0.185 seconds)
=========================================
select zodiacx(day) from date_one;
0: jdbc:hive2://master:10000/test> select zodiacx(day) from date_one;
Error: java.io.IOException: org.apache.hadoop.hive.ql.metadata.HiveException: Error evaluating Please check your code, unknown Exception!!! (state=,code=0)
0: jdbc:hive2://master:10000/test>
Please check your code, unknown Exception!!! 就是之前在 getDisplayString 中定义的返回值！！