json、数组、map相关的hive函数

邵浩大
2023-12-01

hive-third-functions

参考文献:https://github.com/aaronshan/hive-third-functions/blob/master/README-zh.md

简介

hive-third-functions 包含了一些很有用的hive udf函数,特别是数组和json函数.

注意:
hive-third-functions支持hive-0.11.0或更高版本.

编译

1. 安装依赖

目前, jdo2-api-2.3-ec.jar 在maven中央仓库中已经不可用, 因此我们不得不自己下载并安装到本地的maven库中. 命令如下:

wget http://www.datanucleus.org/downloads/maven2/javax/jdo/jdo2-api/2.3-ec/jdo2-api-2.3-ec.jar -O ~/jdo2-api-2.3-ec.jar
mvn install:install-file -DgroupId=javax.jdo -DartifactId=jdo2-api -Dversion=2.3-ec -Dpackaging=jar -Dfile=~/jdo2-api-2.3-ec.jar

2. 用mvn打包

cd ${project_home}
mvn clean package

如果你想跳过单元测试,可以这样运行:

cd ${project_home}
mvn clean package -DskipTests

命令执行完成后, 将会在target目录下生成hive-third-functions-${version}-shaded.jar文件.

你也可以直接在发布页下载打包好了最新版本 发布页.

当前最新的版本是 2.1.3

函数

1. 字符函数

函数描述
pinyin(string) -> string将汉字转换为拼音
md5(string) -> stringmd5 哈希
sha256(string) -> stringsha256 哈希

2. 数组函数

函数描述
array_contains(array<E>, E) -> boolean判断数组是否包含某个值.
array_equals(array<E>, array<E>) -> boolean判断两个数组是否相等.
array_intersect(array, array) -> array返回两个数组的交集.
array_max(array<E>) -> E返回数组中的最大值.
array_min(array<E>) -> E返回数组中的最小值.
array_join(array, delimiter, null_replacement) -> string使用给定的连接符来连接数组中的元素, null_replacement是一个可选项, 用来替代空值.
array_distinct(array) -> array移除数组中的重复元素.
array_position(array<E>, E) -> long返回给定元素在数组中第一次出现的位置 (如果没找到, 返回0).
array_remove(array<E>, E) -> array删除数组中的给定元素.
array_reverse(array) -> array反转一个数组.
array_sort(array) -> array对数组排序, 数组中的元素必需是可排序的.
array_concat(array, array) -> array连接两个数组.
array_value_count(array<E>, E) -> long统计数组中包含给定元素的个数.
array_slice(array, start, length) -> array对数组进行分片操作,start为正数从前开始分片, start为负数从后开始分片, 长度为指定的长度.
array_element_at(array<E>, index) -> E返回指定位置的数组元素. 如果索引位置 < 0, 则从尾部开始计数并返回.

3. map函数

函数描述
map_build(x<K>, y<V>) -> map<K, V>根据指定的键/值对数组创建map.
map_concat(x<K, V>, y<K, V>) -> map<K,V>返回两个map的并集. 如果一个键在 xy中同时出现, 那对应值来自y.
map_element_at(map<K, V>, key) -> V如果指定的key存在,返回对应的值, 否则返回 NULL .
map_equals(x<K, V>, y<K, V>) -> boolean判断map x 和 map y是否相等.

4. 日期函数

函数描述
day_of_week(date_string | date) -> int一周的第几天,周一返回 1, 周日返回 7, 出错返回null.
day_of_year(date_string | date) -> int一年的第几天. 值的范围从 1 到 366.
zodiac_en(date_string | date) -> string将日期转换为星座英文
zodiac_cn(date_string | date) -> string将日期转换为星座中文
type_of_day(date_string | date) -> string获取日期的类型(1: 法定节假日, 2: 正常周末, 3: 正常工作日 4:攒假的工作日),错误返回-1.

5. json函数

函数描述
json_array_get(json, jsonPath) -> array(varchar)returns the element at the specified index into the json_array. The index is zero-based.
json_array_length(json, jsonPath) -> array(varchar)returns the array length of json (a string containing a JSON array).
json_array_extract(json, jsonPath) -> array(varchar)extract json array by given jsonPath.
json_array_extract_scalar(json, jsonPath) -> array(varchar)like json_array_extract, but returns the result value as a string (as opposed to being encoded as JSON).
json_extract(json, jsonPath) -> array(varchar)extract json by given jsonPath.
json_extract_scalar(json, jsonPath) -> array(varchar)like json_extract, but returns the result value as a string (as opposed to being encoded as JSON).
json_size(json, jsonPath) -> array(varchar)like json_extract, but returns the size of the value. For objects or arrays, the size is the number of members, and the size of a scalar value is zero.

6. 位函数

函数描述
bit_count(x, bits) -> bigintcount the number of bits set in x (treated as bits-bit signed integer) in 2’s complement representation
bitwise_and(x, y) -> bigintreturns the bitwise AND of x and y in 2’s complement arithmetic.
bitwise_not(x) -> bigintreturns the bitwise NOT of x in 2’s complement arithmetic.
bitwise_or(x, y) -> bigintreturns the bitwise OR of x and y in 2’s complement arithmetic.
bitwise_xor(x, y) -> bigintreturns the bitwise XOR of x and y in 2’s complement arithmetic.

7. 中国身份证函数

函数描述
id_card_province(string) -> string从身份证号获取省份
id_card_city(string) -> string从身份证号获取城市
id_card_area(string) -> string从身份证号获取区/县
id_card_birthday(string) -> string从身份证号获取生日
id_card_gender(string) -> string从身份证号获取性别
is_valid_id_card(string) -> boolean鉴定身份证号是否有效.
id_card_info(string) -> json获取身份证号信息. 包活省份、城市、区县等.

8. 坐标系函数

函数描述
wgs_distance(double lat1, double lng1, double lat2, double lng2) -> double计算 WGS84坐标距离, 单位米.
gcj_to_bd(double,double) -> jsonGCJ-02(火星坐标系) 转为 BD-09(百度坐标系), 谷歌、高德——>百度
bd_to_gcj(double,double) -> jsonBD-09(百度坐标系) 转为 GCJ-02(火星坐标系), 百度——>谷歌、高德
wgs_to_gcj(double,double) -> jsonWGS84(地球坐标系) 转为 GCJ02(火星坐标系)
gcj_to_wgs(double,double) -> jsonGCJ02(火星坐标系) 转为 GPS84(地球坐标系), 输出的坐标精度在1到2米.
gcj_extract_wgs(double,double) -> jsonGCJ02(火星坐标系) 转为 GPS84, 输出的坐标精度在0.5米. 但是计算比gcj_to_wgs耗时长.

关于互联网地图坐标系的说明见: 当前互联网地图的坐标系现状

9. url函数

函数描述
url_encode(value) -> stringescapes value by encoding it so that it can be safely included in URL query parameter names and values
url_decode(value) -> stringunescape the URL encoded value. This function is the inverse of url_encode.

用法

将下面这些内容写入 ${HOME}/.hiverc 文件, 或者也可以按需在hive命令行环境中执行.

add jar ${jar_location_dir}/hive-third-functions-${version}-shaded.jar
create temporary function array_contains as 'cc.shanruifeng.functions.array.UDFArrayContains';
create temporary function array_equals as 'cc.shanruifeng.functions.array.UDFArrayEquals';
create temporary function array_intersect as 'cc.shanruifeng.functions.array.UDFArrayIntersect';
create temporary function array_max as 'cc.shanruifeng.functions.array.UDFArrayMax';
create temporary function array_min as 'cc.shanruifeng.functions.array.UDFArrayMin';
create temporary function array_join as 'cc.shanruifeng.functions.array.UDFArrayJoin';
create temporary function array_distinct as 'cc.shanruifeng.functions.array.UDFArrayDistinct';
create temporary function array_position as 'cc.shanruifeng.functions.array.UDFArrayPosition';
create temporary function array_remove as 'cc.shanruifeng.functions.array.UDFArrayRemove';
create temporary function array_reverse as 'cc.shanruifeng.functions.array.UDFArrayReverse';
create temporary function array_sort as 'cc.shanruifeng.functions.array.UDFArraySort';
create temporary function array_concat as 'cc.shanruifeng.functions.array.UDFArrayConcat';
create temporary function array_value_count as 'cc.shanruifeng.functions.array.UDFArrayValueCount';
create temporary function array_slice as 'cc.shanruifeng.functions.array.UDFArraySlice';
create temporary function array_element_at as 'cc.shanruifeng.functions.array.UDFArrayElementAt';
create temporary function bit_count as 'cc.shanruifeng.functions.bitwise.UDFBitCount';
create temporary function bitwise_and as 'cc.shanruifeng.functions.bitwise.UDFBitwiseAnd';
create temporary function bitwise_not as 'cc.shanruifeng.functions.bitwise.UDFBitwiseNot';
create temporary function bitwise_or as 'cc.shanruifeng.functions.bitwise.UDFBitwiseOr';
create temporary function bitwise_xor as 'cc.shanruifeng.functions.bitwise.UDFBitwiseXor';
create temporary function map_build as 'cc.shanruifeng.functions.map.UDFMapBuild';
create temporary function map_concat as 'cc.shanruifeng.functions.map.UDFMapConcat';
create temporary function map_element_at as 'cc.shanruifeng.functions.map.UDFMapElementAt';
create temporary function map_equals as 'cc.shanruifeng.functions.map.UDFMapEquals';
create temporary function day_of_week as 'cc.shanruifeng.functions.date.UDFDayOfWeek';
create temporary function day_of_year as 'cc.shanruifeng.functions.date.UDFDayOfYear';
create temporary function type_of_day as 'cc.shanruifeng.functions.date.UDFTypeOfDay'; 
create temporary function zodiac_cn as 'cc.shanruifeng.functions.date.UDFZodiacSignCn';
create temporary function zodiac_en as 'cc.shanruifeng.functions.date.UDFZodiacSignEn';
create temporary function pinyin as 'cc.shanruifeng.functions.string.UDFChineseToPinYin';
create temporary function md5 as 'cc.shanruifeng.functions.string.UDFMd5';
create temporary function sha256 as 'cc.shanruifeng.functions.string.UDFSha256';
create temporary function json_array_get as 'cc.shanruifeng.functions.json.UDFJsonArrayGet';
create temporary function json_array_length as 'cc.shanruifeng.functions.json.UDFJsonArrayLength';
create temporary function json_array_extract as 'cc.shanruifeng.functions.json.UDFJsonArrayExtract';
create temporary function json_array_extract_scalar as 'cc.shanruifeng.functions.json.UDFJsonArrayExtractScalar';
create temporary function json_extract as 'cc.shanruifeng.functions.json.UDFJsonExtract';
create temporary function json_extract_scalar as 'cc.shanruifeng.functions.json.UDFJsonExtractScalar';
create temporary function json_size as 'cc.shanruifeng.functions.json.UDFJsonSize';
create temporary function id_card_province as 'cc.shanruifeng.functions.card.UDFChinaIdCardProvince';
create temporary function id_card_city as 'cc.shanruifeng.functions.card.UDFChinaIdCardCity';
create temporary function id_card_area as 'cc.shanruifeng.functions.card.UDFChinaIdCardArea';
create temporary function id_card_birthday as 'cc.shanruifeng.functions.card.UDFChinaIdCardBirthday';
create temporary function id_card_gender as 'cc.shanruifeng.functions.card.UDFChinaIdCardGender';
create temporary function is_valid_id_card as 'cc.shanruifeng.functions.card.UDFChinaIdCardValid';
create temporary function id_card_info as 'cc.shanruifeng.functions.card.UDFChinaIdCardInfo';
create temporary function wgs_distance as 'cc.shanruifeng.functions.geo.UDFGeoWgsDistance';
create temporary function gcj_to_bd as 'cc.shanruifeng.functions.geo.UDFGeoGcjToBd';
create temporary function bd_to_gcj as 'cc.shanruifeng.functions.geo.UDFGeoBdToGcj';
create temporary function wgs_to_gcj as 'cc.shanruifeng.functions.geo.UDFGeoWgsToGcj';
create temporary function gcj_to_wgs as 'cc.shanruifeng.functions.geo.UDFGeoGcjToWgs';
create temporary function gcj_extract_wgs as 'cc.shanruifeng.functions.geo.UDFGeoGcjExtractWgs';
create temporary function url_encode as 'cc.shanruifeng.functions.url.UDFUrlEncode';
create temporary function url_decode as 'cc.shanruifeng.functions.url.UDFUrlDecode';

你可以在hive的命令杭中使用下面的语句来查看函数的细节.

hive> describe function zodiac_cn;
zodiac_cn(date) - from the input date string or separate month and day arguments, returns the sing of the Zodiac.

或者

hive> describe function extended zodiac_cn;
zodiac_cn(date) - from the input date string or separate month and day arguments, returns the sing of the Zodiac.
Example:
 > select zodiac_cn(date_string) from src;
 > select zodiac_cn(month, day) from src;

示例

 select pinyin('中国') => zhongguo
 select md5('aaronshan') => 95686bc0483262afe170b550dd4544d1
 select sha256('aaronshan') => d16bb375433ad383169f911afdf45e209eabfcf047ba1faebdd8f6a0b39e0a32
select day_of_week('2016-07-12') => 2
select day_of_year('2016-01-01') => 1
select type_of_day('2016-10-01') => 1
select type_of_day('2016-07-16') => 2
select type_of_day('2016-07-15') => 3
select type_of_day('2016-09-18') => 4
select zodiac_cn('1989-01-08') => 魔羯座
select zodiac_en('1989-01-08') => Capricorn
select array_contains(array(16,12,18,9), 12) => true
select array_equals(array(16,12,18,9), array(16,12,18,9)) => true
select array_intersect(array(16,12,18,9,null), array(14,9,6,18,null)) => [null,9,18]
select array_max(array(16,13,12,13,18,16,9,18)) => 18
select array_min(array(16,12,18,9)) => 9
select array_join(array(16,12,18,9,null), '#','=') => 16#12#18#9#=
select array_distinct(array(16,13,12,13,18,16,9,18)) => [9,12,13,16,18]
select array_position(array(16,13,12,13,18,16,9,18), 13) => 2
select array_remove(array(16,13,12,13,18,16,9,18), 13) => [16,12,18,16,9,18]
select array_reverse(array(16,12,18,9)) => [9,18,12,16]
select array_sort(array(16,13,12,13,18,16,9,18)) => [9,12,13,13,16,16,18,18]
select array_concat(array(16,12,18,9,null), array(14,9,6,18,null)) => [16,12,18,9,null,14,9,6,18,null]
select array_value_count(array(16,13,12,13,18,16,9,18), 13) => 2
select array_slice(array(16,13,12,13,18,16,9,18), -2, 3) => [9,18]
select array_element_at(array(16,13,12,13,18,16,9,18), -1) => 18
select map_build(array('key1','key2'), array(16,12)) => {"key1":16,"key2":12}
select map_concat(map_build(array('key1','key2'), array(16,12)), map_build(array('key1','key3'), array(17,18))) => {"key1":17,"key2":12,"key3":18}
select map_element_at(map_build(array('key1','key2'), array(16,12)), 'key1') => 16
select map_equals(map_build(array('key1','key2'), array(16,12)), map_build(array('key1','key2'), array(16,12))) => true
select id_card_info('110101198901084517') => {"valid":true,"area":"东城区","province":"北京市","gender":"男","city":"北京市"}
select json_array_get("[{\"a\":{\"b\":\"13\"}}, {\"a\":{\"b\":\"18\"}}, {\"a\":{\"b\":\"12\"}}]", 1); => {"a":{"b":"18"}}
select json_array_get('["a", "b", "c"]', 0); => a
select json_array_get('["a", "b", "c"]', 1); => b
select json_array_get('["c", "b", "a"]', -1); => a
select json_array_get('["c", "b", "a"]', -2); => b
select json_array_get('[]', 0); => null
select json_array_get('["a", "b", "c"]', 10); => null
select json_array_get('["c", "b", "a"]', -10); => null
select json_array_length("[{\"a\":{\"b\":\"13\"}}, {\"a\":{\"b\":\"18\"}}, {\"a\":{\"b\":\"12\"}}]"); => 3
select json_array_extract("[{\"a\":{\"b\":\"13\"}}, {\"a\":{\"b\":\"18\"}}, {\"a\":{\"b\":\"12\"}}]", "$.a.b"); => ["\"13\"","\"18\"","\"12\""]
select json_array_extract_scalar("[{\"a\":{\"b\":\"13\"}}, {\"a\":{\"b\":\"18\"}}, {\"a\":{\"b\":\"12\"}}]", "$.a.b") => ["13","18","12"]
select json_extract("{\"a\":{\"b\":\"12\"}}", "$.a.b"); => "12"
select json_extract_scalar("{\"a\":{\"b\":\"12\"}}", "$.a.b") => 12
select json_extract_scalar('[1, 2, 3]', '$[2]');
select json_extract_scalar(json, '$.store.book[0].author');
select json_size('{"x": {"a": 1, "b": 2}}', '$.x'); => 2
select json_size('{"x": [1, 2, 3]}', '$.x'); => 3
select json_size('{"x": {"a": 1, "b": 2}}', '$.x.a'); => 0
select gcj_to_bd(39.915, 116.404) => {"lng":116.41036949371029,"lat":39.92133699351022}
select bd_to_gcj(39.915, 116.404) => {"lng":116.39762729119315,"lat":39.90865673957631}
select wgs_to_gcj(39.915, 116.404) => {"lng":116.41024449916938,"lat":39.91640428150164}
select gcj_to_wgs(39.915, 116.404) => {"lng":116.39775550083061,"lat":39.91359571849836}
select gcj_extract_wgs(39.915, 116.404) => {"lng":116.39775549316407,"lat":39.913596801757805}
select url_encode('http://shanruifeng.cc/') => http%3A%2F%2Fshanruifeng.cc%2F
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