Hive Operators and User-Defined Functions (UDFs) hive 日期函数

When hive.cache.expr.evaluation is set to true (which is the default) a UDF can give incorrect results if it is nested in another UDF or a Hive function. This bug affects releases 0.12.0, 0.13.0, and 0.13.1. Release 0.14.0 will fix the bug (HIVE-7314).

The problem relates to the UDF's implementation of the getDisplayString method, as discussed in the Hive user mailing list.

Built-in Operators

Relational Operators

The following operators compare the passed operands and generate a TRUE or FALSE value depending on whether the comparison between the operands holds.

Operator	Operand types	Description
A = B	All primitive types	TRUE if expression A is equal to expression B otherwise FALSE.
A <=> B	All primitive types	Returns same result with EQUAL(=) operator for non-null operands, but returns TRUE if both are NULL, FALSE if one of the them is NULL. (As of version 0.9.0.)
A == B	None!	Fails because of invalid syntax. SQL uses =, not ==.
A <> B	All primitive types	NULL if A or B is NULL, TRUE if expression A is NOT equal to expression B, otherwise FALSE.
A != B	All primitive types	Synonym for the <> operator.
A < B	All primitive types	NULL if A or B is NULL, TRUE if expression A is less than expression B, otherwise FALSE.
A <= B	All primitive types	NULL if A or B is NULL, TRUE if expression A is less than or equal to expression B, otherwise FALSE.
A > B	All primitive types	NULL if A or B is NULL, TRUE if expression A is greater than expression B, otherwise FALSE.
A >= B	All primitive types	NULL if A or B is NULL, TRUE if expression A is greater than or equal to expression B, otherwise FALSE.
A [NOT] BETWEEN B AND C	All primitive types	NULL if A, B or C is NULL, TRUE if A is greater than or equal to B AND A less than or equal to C, otherwise FALSE. This can be inverted by using the NOT keyword. (As of version 0.9.0.)
A IS NULL	All types	TRUE if expression A evaluates to NULL, otherwise FALSE.
A IS NOT NULL	All types	FALSE if expression A evaluates to NULL, otherwise TRUE.
A [NOT] LIKE B	strings	NULL if A or B is NULL, TRUE if string A matches the SQL simple regular expression B, otherwise FALSE. The comparison is done character by character. The _ character in B matches any character in A (similar to . in posix regular expressions) while the % character in B matches an arbitrary number of characters in A (similar to .* in posix regular expressions). For example, 'foobar' like 'foo' evaluates to FALSE whereas 'foobar' like 'foo_ _ _' evaluates to TRUE and so does 'foobar' like 'foo%'.
A RLIKE B	strings	NULL if A or B is NULL, TRUE if any (possibly empty) substring of A matches the Java regular expression B, otherwise FALSE. For example, 'foobar' RLIKE 'foo' evaluates to TRUE and so does 'foobar' RLIKE '^f.*r$'.
A REGEXP B	strings	Same as RLIKE.

Arithmetic Operators

The following operators support various common arithmetic operations on the operands. All return number types; if any of the operands are NULL, then the result is also NULL.

Operator	Operand types	Description
A + B	All number types	Gives the result of adding A and B. The type of the result is the same as the common parent(in the type hierarchy) of the types of the operands. For example since every integer is a float, therefore float is a containing type of integer so the + operator on a float and an int will result in a float.
A - B	All number types	Gives the result of subtracting B from A. The type of the result is the same as the common parent(in the type hierarchy) of the types of the operands.
A * B	All number types	Gives the result of multiplying A and B. The type of the result is the same as the common parent(in the type hierarchy) of the types of the operands. Note that if the multiplication causing overflow, you will have to cast one of the operators to a type higher in the type hierarchy.
A / B	All number types	Gives the result of dividing B from A. The result is a double type.
A % B	All number types	Gives the reminder resulting from dividing A by B. The type of the result is the same as the common parent(in the type hierarchy) of the types of the operands.
A & B	All number types	Gives the result of bitwise AND of A and B. The type of the result is the same as the common parent(in the type hierarchy) of the types of the operands.
A \| B	All number types	Gives the result of bitwise OR of A and B. The type of the result is the same as the common parent(in the type hierarchy) of the types of the operands.
A ^ B	All number types	Gives the result of bitwise XOR of A and B. The type of the result is the same as the common parent(in the type hierarchy) of the types of the operands.
~A	All number types	Gives the result of bitwise NOT of A. The type of the result is the same as the type of A.

Logical Operators

The following operators provide support for creating logical expressions. All of them return boolean TRUE, FALSE, or NULL depending upon the boolean values of the operands. NULL behaves as an "unknown" flag, so if the result depends on the state of an unknown, the result itself is unknown.

Operator	Operand types	Description
A AND B	boolean	TRUE if both A and B are TRUE, otherwise FALSE. NULL if A or B is NULL.
A && B	boolean	Same as A AND B.
A OR B	boolean	TRUE if either A or B or both are TRUE, FALSE OR NULL is NULL, otherwise FALSE.
A \|\| B	boolean	Same as A OR B.
NOT A	boolean	TRUE if A is FALSE or NULL if A is NULL. Otherwise FALSE.
! A	boolean	Same as NOT A.
A IN (val1, val2, ...)	boolean	TRUE if A is equal to any of the values. As of Hive 0.13 subqueries are supported in IN statements.
A NOT IN (val1, val2, ...)	boolean	TRUE if A is not equal to any of the values. As of Hive 0.13 subqueries are supported in NOT IN statements.
[NOT] EXISTS (subquery)		TRUE if the the subquery returns at least one row. Supported as of Hive 0.13.

Complex Type Constructors

The following functions construct instances of complex types.

Constructor Function	Operands	Description
map	(key1, value1, key2, value2, ...)	Creates a map with the given key/value pairs.
struct	(val1, val2, val3, ...)	Creates a struct with the given field values. Struct field names will be col1, col2, ....
named_struct	(name1, val1, name2, val2, ...)	Creates a struct with the given field names and values. (As of Hive 0.8.0.)
array	(val1, val2, ...)	Creates an array with the given elements.
create_union	(tag, val1, val2, ...)	Creates a union type with the value that is being pointed to by the tag parameter.

Operators on Complex Types

The following operators provide mechanisms to access elements in Complex Types

Operator	Operand types	Description
A[n]	A is an Array and n is an int	Returns the nth element in the array A. The first element has index 0. For example, if A is an array comprising of ['foo', 'bar'] then A[0] returns 'foo' and A[1] returns 'bar'.
M[key]	M is a Map<K, V> and key has type K	Returns the value corresponding to the key in the map. For example, if M is a map comprising of {'f' -> 'foo', 'b' -> 'bar', 'all' -> 'foobar'} then M['all'] returns 'foobar'.
S.x	S is a struct	Returns the x field of S. For example for the struct foobar {int foo, int bar}, foobar.foo returns the integer stored in the foo field of the struct.

Built-in Functions

Mathematical Functions

The following built-in mathematical functions are supported in hive; most return NULL when the argument(s) are NULL:

Return Type	Name (Signature)	Description
DOUBLE	round(DOUBLE a)	Returns the rounded `BIGINT` value of `a`.
DOUBLE	round(DOUBLE a, INT d)	Returns `a` rounded to `d` decimal places.
BIGINT	floor(DOUBLE a)	Returns the maximum `BIGINT` value that is equal to or less than `a`.
BIGINT	ceil(DOUBLE a), ceiling(DOUBLE a)	Returns the minimum BIGINT value that is equal to or greater than `a`.
DOUBLE	rand(), rand(INT seed)	Returns a random number (that changes from row to row) that is distributed uniformly from 0 to 1. Specifying the seed will make sure the generated random number sequence is deterministic.
DOUBLE	exp(DOUBLE a), exp(DECIMAL a)	Returns `e^a` where `e` is the base of the natural logarithm. Decimal version added in Hive 0.13.0.
DOUBLE	ln(DOUBLE a), ln(DECIMAL a)	Returns the natural logarithm of the argument `a`. Decimal version added in Hive 0.13.0.
DOUBLE	log10(DOUBLE a), log10(DECIMAL a)	Returns the base-10 logarithm of the argument `a`. Decimal version added in Hive 0.13.0.
DOUBLE	log2(DOUBLE a), log2(DECIMAL a)	Returns the base-2 logarithm of the argument `a`. Decimal version added in Hive 0.13.0.
DOUBLE	log(DOUBLE base, DOUBLE a) log(DECIMAL base, DECIMAL a)	Returns the base-`base` logarithm of the argument `a`. Decimal versions added in Hive 0.13.0.
DOUBLE	pow(DOUBLE a, DOUBLE p), power(DOUBLE a, DOUBLE p)	Returns `a^p`.
DOUBLE	sqrt(DOUBLE a), sqrt(DECIMAL a)	Returns the square root of `a`. Decimal version added in Hive 0.13.0.
STRING	bin(BIGINT a)	Returns the number in binary format (see http://dev.mysql.com/doc/refman/5.0/en/string-functions.html#function_bin).
STRING	hex(BIGINT a) hex(STRING a) hex(BINARY a)	If the argument is an `INT` or `binary`, `hex` returns the number as a `STRING` in hexadecimal format. Otherwise if the number is a `STRING`, it converts each character into its hexadecimal representation and returns the resulting `STRING`. (See http://dev.mysql.com/doc/refman/5.0/en/string-functions.html#function_hex, `BINARY` version as of Hive 0.12.0.)
BINARY	unhex(STRING a)	Inverse of hex. Interprets each pair of characters as a hexadecimal number and converts to the byte representation of the number. (`BINARY` version as of Hive 0.12.0, used to return a string.)
STRING	conv(BIGINT num, INT from_base, INT to_base), conv(STRING num, INT from_base, INT to_base)	Converts a number from a given base to another (see http://dev.mysql.com/doc/refman/5.0/en/mathematical-functions.html#function_conv).
DOUBLE	abs(DOUBLE a)	Returns the absolute value.
INT or DOUBLE	pmod(INT a, INT b), pmod(DOUBLE a, DOUBLE b)	Returns the positive value of `a mod b`.
DOUBLE	sin(DOUBLE a), sin(DECIMAL a)	Returns the sine of `a` (`a` is in radians). Decimal version added in Hive 0.13.0.
DOUBLE	asin(DOUBLE a), asin(DECIMAL a)	Returns the arc sin of `a` if -1<=a<=1 or NULL otherwise. Decimal version added in Hive 0.13.0.
DOUBLE	cos(DOUBLE a), cos(DECIMAL a)	Returns the cosine of `a` (`a` is in radians). Decimal version added in Hive 0.13.0.
DOUBLE	acos(DOUBLE a), acos(DECIMAL a)	Returns the arccosine of `a` if -1<=a<=1 or NULL otherwise. Decimal version added in Hive 0.13.0.
DOUBLE	tan(DOUBLE a), tan(DECIMAL a)	Returns the tangent of `a` (`a` is in radians). Decimal version added in Hive 0.13.0.
DOUBLE	atan(DOUBLE a), atan(DECIMAL a)	Returns the arctangent of `a`. Decimal version added in Hive 0.13.0.
DOUBLE	degrees(DOUBLE a), degrees(DECIMAL a)	Converts value of `a` from radians to degrees. Decimal version added in Hive 0.13.0.
DOUBLE	radians(DOUBLE a), radians(DOUBLE a)	Converts value of `a` from degrees to radians. Decimal version added in Hive 0.13.0.
INT or DOUBLE	positive(INT a), positive(DOUBLE a)	Returns `a`.
INT or DOUBLE	negative(INT a), negative(DOUBLE a)	Returns `-a`.
DOUBLE or INT	sign(DOUBLE a), sign(DECIMAL a)	Returns the sign of `a` as '1.0' (if `a` is positive) or '-1.0' (if `a` is negative), '0.0' otherwise. The decimal version returns INT instead of DOUBLE. Decimal version added in Hive 0.13.0.
DOUBLE	e()	Returns the value of e.
DOUBLE	pi()	Returns the value of pi.

Mathematical Functions and Operators for Decimal Datatypes

Version

Icon

The decimal datatype was introduced in Hive 0.11.0 (HIVE-2693).

All regular arithmetic operators (such as +, -, *, /) and relevant mathematical UDFs (Floor, Ceil, Round, and many more) have been updated to handle decimal types. For a list of supported UDFs, see Mathematical UDFs in Hive Data Types.

Collection Functions

The following built-in collection functions are supported in hive:

Return Type	Name(Signature)	Description
int	size(Map<K.V>)	Returns the number of elements in the map type.
int	size(Array<T>)	Returns the number of elements in the array type.
array<K>	map_keys(Map<K.V>)	Returns an unordered array containing the keys of the input map.
array<V>	map_values(Map<K.V>)	Returns an unordered array containing the values of the input map.
boolean	array_contains(Array<T>, value)	Returns TRUE if the array contains value.
array<t>	sort_array(Array<T>)	Sorts the input array in ascending order according to the natural ordering of the array elements and returns it (as of version 0.9.0).

Type Conversion Functions

The following type conversion functions are supported in hive:

Return Type	Name(Signature)	Description
binary	binary(string\|binary)	Casts the parameter into a binary.
Expected "=" to follow "type"	cast(expr as <type>)	Converts the results of the expression expr to <type>. For example, cast('1' as BIGINT) will convert the string '1' to its integral representation. A null is returned if the conversion does not succeed.

Date Functions

The following built-in date functions are supported in hive:

Return Type	Name(Signature)	Description
string	from_unixtime(bigint unixtime[, string format])	Converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a string representing the timestamp of that moment in the current system time zone in the format of "1970-01-01 00:00:00".
bigint	unix_timestamp()	Gets current Unix timestamp in seconds.
bigint	unix_timestamp(string date)	Converts time string in format `yyyy-MM-dd HH:mm:ss` to Unix timestamp (in seconds), using the default timezone and the default locale, return 0 if fail: unix_timestamp('2009-03-20 11:30:01') = 1237573801
bigint	unix_timestamp(string date, string pattern)	Convert time string with given pattern (see [http://docs.oracle.com/javase/tutorial/i18n/format/simpleDateFormat.html]) to Unix time stamp (in seconds), return 0 if fail: unix_timestamp('2009-03-20', 'yyyy-MM-dd') = 1237532400.
string	to_date(string timestamp)	Returns the date part of a timestamp string: to_date("1970-01-01 00:00:00") = "1970-01-01".
int	year(string date)	Returns the year part of a date or a timestamp string: year("1970-01-01 00:00:00") = 1970, year("1970-01-01") = 1970.
int	month(string date)	Returns the month part of a date or a timestamp string: month("1970-11-01 00:00:00") = 11, month("1970-11-01") = 11.
int	day(string date) dayofmonth(date)	Returns the day part of a date or a timestamp string: day("1970-11-01 00:00:00") = 1, day("1970-11-01") = 1.
int	hour(string date)	Returns the hour of the timestamp: hour('2009-07-30 12:58:59') = 12, hour('12:58:59') = 12.
int	minute(string date)	Returns the minute of the timestamp.
int	second(string date)	Returns the second of the timestamp.
int	weekofyear(string date)	Returns the week number of a timestamp string: weekofyear("1970-11-01 00:00:00") = 44, weekofyear("1970-11-01") = 44.
int	datediff(string enddate, string startdate)	Returns the number of days from startdate to enddate: datediff('2009-03-01', '2009-02-27') = 2.
string	date_add(string startdate, int days)	Adds a number of days to startdate: date_add('2008-12-31', 1) = '2009-01-01'.
string	date_sub(string startdate, int days)	Subtracts a number of days to startdate: date_sub('2008-12-31', 1) = '2008-12-30'.
timestamp	from_utc_timestamp(timestamp, string timezone)	Assumes given timestamp is UTC and converts to given timezone (as of Hive 0.8.0).
timestamp	to_utc_timestamp(timestamp, string timezone)	Assumes given timestamp is in given timezone and converts to UTC (as of Hive 0.8.0).

Conditional Functions

Return Type	Name(Signature)	Description
T	if(boolean testCondition, T valueTrue, T valueFalseOrNull)	Returns valueTrue when testCondition is true, returns valueFalseOrNull otherwise.
T	COALESCE(T v1, T v2, ...)	Returns the first v that is not NULL, or NULL if all v's are NULL.
T	CASE a WHEN b THEN c [WHEN d THEN e]* [ELSE f] END	When a = b, returns c; when a = d, returns e; else returns f.
T	CASE WHEN a THEN b [WHEN c THEN d]* [ELSE e] END	When a = true, returns b; when c = true, returns d; else returns e.

String Functions

The following built-in String functions are supported in hive:

Return Type	Name(Signature)	Description
int	ascii(string str)	Returns the numeric value of the first character of str.
string	base64(binary bin)	Converts the argument from binary to a base 64 string (as of Hive 0.12.0).
string	concat(string\|binary A, string\|binary B...)	Returns the string or bytes resulting from concatenating the strings or bytes passed in as parameters in order. For example, concat('foo', 'bar') results in 'foobar'. Note that this function can take any number of input strings.
array<struct<string,double>>	context_ngrams(array<array<string>>, array<string>, int K, int pf)	Returns the top-k contextual N-grams from a set of tokenized sentences, given a string of "context". See StatisticsAndDataMining for more information.
string	concat_ws(string SEP, string A, string B...)	Like concat() above, but with custom separator SEP.
string	concat_ws(string SEP, array<string>)	Like concat_ws() above, but taking an array of strings. (as of Hive 0.9.0)
string	decode(binary bin, string charset)	Decodes the first argument into a String using the provided character set (one of 'US_ASCII', 'ISO-8859-1', 'UTF-8', 'UTF-16BE', 'UTF-16LE', 'UTF-16'). If either argument is null, the result will also be null. (As of Hive 0.12.0.)
binary	encode(string src, string charset)	Encodes the first argument into a BINARY using the provided character set (one of 'US_ASCII', 'ISO-8859-1', 'UTF-8', 'UTF-16BE', 'UTF-16LE', 'UTF-16'). If either argument is null, the result will also be null. (As of Hive 0.12.0.)
int	find_in_set(string str, string strList)	Returns the first occurance of str in strList where strList is a comma-delimited string. Returns null if either argument is null. Returns 0 if the first argument contains any commas. For example, find_in_set('ab', 'abc,b,ab,c,def') returns 3.
string	format_number(number x, int d)	Formats the number X to a format like '#,###,###.##', rounded to D decimal places, and returns the result as a string. If D is 0, the result has no decimal point or fractional part. (As of Hive0.10.0; bug with float types fixed in Hive 0.14.0.)
string	get_json_object(string json_string, string path)	Extracts json object from a json string based on json path specified, and returns json string of the extracted json object. It will return null if the input json string is invalid. *NOTE: The json path can only have the characters [0-9a-z_], i.e., no upper-case or special characters. Also, the keys cannot start with numbers.*** This is due to restrictions on Hive column names.
boolean	in_file(string str, string filename)	Returns true if the string str appears as an entire line in filename.
int	instr(string str, string substr)	Returns the position of the first occurrence of `substr` in `str`. Returns `null` if either of the arguments are `null` and returns `0` if `substr` could not be found in `str`. Be aware that this is not zero based. The first character in `str` has index 1.
int	length(string A)	Returns the length of the string.
int	locate(string substr, string str[, int pos])	Returns the position of the first occurrence of substr in str after position pos.
string	lower(string A) lcase(string A)	Returns the string resulting from converting all characters of B to lower case. For example, lower('fOoBaR') results in 'foobar'.
string	lpad(string str, int len, string pad)	Returns str, left-padded with pad to a length of len.
string	ltrim(string A)	Returns the string resulting from trimming spaces from the beginning(left hand side) of A. For example, ltrim(' foobar ') results in 'foobar '.
array<struct<string,double>>	ngrams(array<array<string>>, int N, int K, int pf)	Returns the top-k N-grams from a set of tokenized sentences, such as those returned by the sentences() UDAF. See StatisticsAndDataMining for more information.
string	parse_url(string urlString, string partToExtract [, string keyToExtract])	Returns the specified part from the URL. Valid values for partToExtract include HOST, PATH, QUERY, REF, PROTOCOL, AUTHORITY, FILE, and USERINFO. For example, parse_url('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'HOST') returns 'facebook.com'. Also a value of a particular key in QUERY can be extracted by providing the key as the third argument, for example, parse_url('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'QUERY', 'k1') returns 'v1'.
string	printf(String format, Obj... args)	Returns the input formatted according do printf-style format strings (as of Hive 0.9.0).
string	regexp_extract(string subject, string pattern, int index)	Returns the string extracted using the pattern. For example, regexp_extract('foothebar', 'foo(.*?)(bar)', 2) returns 'bar.' Note that some care is necessary in using predefined character classes: using '\s' as the second argument will match the letter s; '\\s' is necessary to match whitespace, etc. The 'index' parameter is the Java regex Matcher group() method index. See docs/api/java/util/regex/Matcher.html for more information on the 'index' or Java regex group() method.
string	regexp_replace(string INITIAL_STRING, string PATTERN, string REPLACEMENT)	Returns the string resulting from replacing all substrings in INITIAL_STRING that match the java regular expression syntax defined in PATTERN with instances of REPLACEMENT. For example, regexp_replace("foobar", "oo\|ar", "") returns 'fb.' Note that some care is necessary in using predefined character classes: using '\s' as the second argument will match the letter s; '\\s' is necessary to match whitespace, etc.
string	repeat(string str, int n)	Repeats str n times.
string	reverse(string A)	Returns the reversed string.
string	rpad(string str, int len, string pad)	Returns str, right-padded with pad to a length of len.
string	rtrim(string A)	Returns the string resulting from trimming spaces from the end(right hand side) of A. For example, rtrim(' foobar ') results in ' foobar'.
array<array<string>>	sentences(string str, string lang, string locale)	Tokenizes a string of natural language text into words and sentences, where each sentence is broken at the appropriate sentence boundary and returned as an array of words. The 'lang' and 'locale' are optional arguments. For example, sentences('Hello there! How are you?') returns ( ("Hello", "there"), ("How", "are", "you") ).
string	space(int n)	Returns a string of n spaces.
array	split(string str, string pat)	Splits str around pat (pat is a regular expression).
map<string,string>	str_to_map(text[, delimiter1, delimiter2])	Splits text into key-value pairs using two delimiters. Delimiter1 separates text into K-V pairs, and Delimiter2 splits each K-V pair. Default delimiters are ',' for delimiter1 and '=' for delimiter2.
string	substr(string\|binary A, int start) substring(string\|binary A, int start)	Returns the substring or slice of the byte array of A starting from start position till the end of string A. For example, substr('foobar', 4) results in 'bar' (see [http://dev.mysql.com/doc/refman/5.0/en/string-functions.html#function_substr]).
string	substr(string\|binary A, int start, int len) substring(string\|binary A, int start, int len)	Returns the substring or slice of the byte array of A starting from start position with length len. For example, substr('foobar', 4, 1) results in 'b' (see [http://dev.mysql.com/doc/refman/5.0/en/string-functions.html#function_substr]).
string	translate(string input, string from, string to)	Translates the input string by replacing the characters present in the `from` string with the corresponding characters in the `to` string. This is similar to the `translate` function inPostgreSQL. If any of the parameters to this UDF are NULL, the result is NULL as well. (Available as of Hive 0.10.0.)
string	trim(string A)	Returns the string resulting from trimming spaces from both ends of A. For example, trim(' foobar ') results in 'foobar'
binary	unbase64(string str)	Converts the argument from a base 64 string to BINARY. (As of Hive 0.12.0.)
string	upper(string A) ucase(string A)	Returns the string resulting from converting all characters of A to upper case. For example, upper('fOoBaR') results in 'FOOBAR'.

Misc. Functions

Return Type	Name(Signature)	Description
varies	java_method(class, method[, arg1[, arg2..]])	Synonym for `reflect`. (As of Hive 0.9.0.)
varies	reflect(class, method[, arg1[, arg2..]])	Calls a Java method by matching the argument signature, using reflection. (As of Hive 0.7.0.) See Reflect (Generic) UDF for examples.
int	hash(a1[, a2...])	Returns a hash value of the arguments. (As of Hive 0.4.)

xpath

The following functions are described in LanguageManual XPathUDF:

xpath, xpath_short, xpath_int, xpath_long, xpath_float, xpath_double, xpath_number, xpath_string

get_json_object

A limited version of JSONPath is supported:

$ : Root object
. : Child operator
[] : Subscript operator for array
* : Wildcard for []

Syntax not supported that's worth noticing:

: Zero length string as key
.. : Recursive descent
@ : Current object/element
() : Script expression
?() : Filter (script) expression.
[,] : Union operator
[start:end.step] : array slice operator

Example: src_json table is a single column (json), single row table:

`+----+` `json` `+----+` `{` `"store"` `:` `{` `"fruit"` `:\[{` `"weight"` `:` `8` `,` `"type"` `:` `"apple"` `},{` `"weight"` `:` `9` `,` `"type"` `:` `"pear"` `}],` `"bicycle"` `:{` `"price"` `:` `19.95` `,` `"color"` `:` `"red"` `}` `},` `"email"` `:` `"amy@only_for_json_udf_test.net"` `,` `"owner"` `:` `"amy"` `}` `+----+`

The fields of the json object can be extracted using these queries:

`hive> SELECT get_json_object(src_json.json,` `'$.owner'` `) FROM src_json;` `amy` `hive> SELECT get_json_object(src_json.json,` `'$.store.fruit\[0]'` `) FROM src_json;` `{` `"weight"` `:` `8` `,` `"type"` `:` `"apple"` `}` `hive> SELECT get_json_object(src_json.json,` `'$.non_exist_key'` `) FROM src_json;` `NULL`

Built-in Aggregate Functions (UDAF)

The following are built-in aggregate functions are supported in Hive:

Return Type	Name(Signature)	Description
BIGINT	count(*), count(expr), count(DISTINCT expr[, expr_.])	count(*) - Returns the total number of retrieved rows, including rows containing NULL values; count(expr) - Returns the number of rows for which the supplied expression is non-NULL; count(DISTINCT expr[, expr]) - Returns the number of rows for which the supplied expression(s) are unique and non-NULL.
DOUBLE	sum(col), sum(DISTINCT col)	Returns the sum of the elements in the group or the sum of the distinct values of the column in the group.
DOUBLE	avg(col), avg(DISTINCT col)	Returns the average of the elements in the group or the average of the distinct values of the column in the group.
DOUBLE	min(col)	Returns the minimum of the column in the group.
DOUBLE	max(col)	Returns the maximum value of the column in the group.
DOUBLE	variance(col), var_pop(col)	Returns the variance of a numeric column in the group.
DOUBLE	var_samp(col)	Returns the unbiased sample variance of a numeric column in the group.
DOUBLE	stddev_pop(col)	Returns the standard deviation of a numeric column in the group.
DOUBLE	stddev_samp(col)	Returns the unbiased sample standard deviation of a numeric column in the group.
DOUBLE	covar_pop(col1, col2)	Returns the population covariance of a pair of numeric columns in the group.
DOUBLE	covar_samp(col1, col2)	Returns the sample covariance of a pair of a numeric columns in the group.
DOUBLE	corr(col1, col2)	Returns the Pearson coefficient of correlation of a pair of a numeric columns in the group.
DOUBLE	percentile(BIGINT col, p)	Returns the exact p^th percentile of a column in the group (does not work with floating point types). p must be between 0 and 1. NOTE: A true percentile can only be computed for integer values. Use PERCENTILE_APPROX if your input is non-integral.
array<double>	percentile(BIGINT col, array(p₁ [, p₂]...))	Returns the exact percentiles p₁, p₂, ... of a column in the group (does not work with floating point types). p_i must be between 0 and 1. NOTE: A true percentile can only be computed for integer values. Use PERCENTILE_APPROX if your input is non-integral.
DOUBLE	percentile_approx(DOUBLE col, p [, B])	Returns an approximate p^th percentile of a numeric column (including floating point types) in the group. The B parameter controls approximation accuracy at the cost of memory. Higher values yield better approximations, and the default is 10,000. When the number of distinct values in col is smaller than B, this gives an exact percentile value.
array<double>	percentile_approx(DOUBLE col, array(p₁ [, p₂]...) [, B])	Same as above, but accepts and returns an array of percentile values instead of a single one.
array<struct {`'x','y'`}>	histogram_numeric(col, b)	Computes a histogram of a numeric column in the group using b non-uniformly spaced bins. The output is an array of size b of double-valued (x,y) coordinates that represent the bin centers and heights
array	collect_set(col)	Returns a set of objects with duplicate elements eliminated.
array	collect_list(col)	Returns a list of objects with duplicates. (As of Hive 0.13.0.)
INTEGER	ntile(INTEGER x)	Divides an ordered partition into `x` groups called buckets and assigns a bucket number to each row in the partition. Thisallows easy calculation of tertiles, quartiles, deciles, percentiles and other common summary statistics. (As of Hive0.11.0.)

Built-in Table-Generating Functions (UDTF)

Normal user-defined functions, such as concat(), take in a single input row and output a single output row. In contrast, table-generating functions transform a single input row to multiple output rows.

Return Type	Name(Signature)	Description
N rows	explode(ARRAY)	Returns one row for each element from the array.
N rows	explode(MAP)	Returns one row for each key-value pair from the input map with two columns in each row: one for the key and another for the value. (As of Hive 0.8.0.)
	inline(ARRAY<STRUCT[,STRUCT]>)	Explodes an array of structs into a table. (As of Hive 0.10.)
Array Type	explode(array<TYPE> a)	For each element in a, generates a row containing that element.
tuple	json_tuple(jsonStr, k1, k2, ...)	Takes a set of names (keys) and a JSON string, and returns a tuple of values. This is a more efficient version of the`get_json_object` UDF because it can get multiple keys with just one call.
tuple	parse_url_tuple(url, p1, p2, ...)	This is similar to the `parse_url()` UDF but can extract multiple parts at once out of a URL. Valid part names are: HOST, PATH, QUERY, REF, PROTOCOL, AUTHORITY, FILE, USERINFO, QUERY:<KEY>.
N rows	posexplode(ARRAY)	Behaves like `explode` for arrays, but includes the position of items in the original array by returning a tuple of `(pos, value)`. (As of Hive 0.13.0.)
	stack(INT n, v_1, v_2, ..., v_k)	Breaks up v_1, ..., v_k into n rows. Each row will have k/n columns. n must be constant.

Using the syntax "SELECT udtf(col) AS colAlias..." has a few limitations:

No other expressions are allowed in SELECT

SELECT pageid, explode(adid_list) AS myCol... is not supported

UDTF's can't be nested

SELECT explode(explode(adid_list)) AS myCol... is not supported

GROUP BY / CLUSTER BY / DISTRIBUTE BY / SORT BY is not supported

SELECT explode(adid_list) AS myCol ... GROUP BY myCol is not supported

Please see LanguageManual LateralView for an alternative syntax that does not have these limitations.

Also see Writing UDTFs if you want to create a custom UDTF.

explode

explode() takes in an array (or a map) as an input and outputs the elements of the array (map) as separate rows. UDTF's can be used in the SELECT expression list and as a part of LATERAL VIEW.

An example use of explode() in the SELECT expression list is as follows:

Consider a table named myTable that has a single column (myCol) and two rows:

Array<int> myCol
[100,200,300]
[400,500,600]

Then running the query:

`SELECT` `explode(myCol)` `AS` `myNewCol` `FROM` `myTable;`

Will produce:

(int) myNewCol
100
200
300
400
500
600

The usage with Maps is similar:

`SELECT` `explode(myMap)` `AS` `myMapKey, myMapValue` `FROM` `myMapTable;`

posexplode

Version

Icon

Available as of Hive 0.13.0. See HIVE-4943.

posexplode() is similar to explode but instead of just returning the elements of the array it returns the element as well as its position in the original array.

An example use of posexplode() in the SELECT expression list is as follows:

Consider a table named myTable that has a single column (myCol) and two rows:

Array<int> myCol
[100,200,300]
[400,500,600]

Then running the query:

`SELECT` `posexplode(myCol)` `AS` `pos, myNewCol` `FROM` `myTable;`

Will produce:

(int) pos	(int) myNewCol
1	100
2	200
3	300
1	400
2	500
3	600

json_tuple

A new json_tuple() UDTF is introduced in hive 0.7. It takes a set of names (keys) and a JSON string, and returns a tuple of values using one function. This is much more efficient than calling GET_JSON_OBJECT to retrieve more than one key from a single JSON string. In any case where a single JSON string would be parsed more than once, your query will be more efficient if you parse it once, which is what JSON_TUPLE is for. As JSON_TUPLE is a UDTF, you will need to use the LATERAL VIEW syntax in order to achieve the same goal.

For example,

`select a.timestamp, get_json_object(a.appevents,` `'$.eventid'` `), get_json_object(a.appenvets,` `'$.eventname'` `) from log a;`

should be changed to

`select a.timestamp, b.*` `from log a lateral view json_tuple(a.appevent,` `'eventid'` `,` `'eventname'` `) b as f1, f2;`

parse_url_tuple

The parse_url_tuple() UDTF is similar to parse_url(), but can extract multiple parts of a given URL, returning the data in a tuple. Values for a particular key in QUERY can be extracted by appending a colon and the key to the partToExtract argument, for example, parse_url_tuple('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'QUERY:k1', 'QUERY:k2') returns a tuple with values of 'v1','v2'. This is more efficient than calling parse_url() multiple times. All the input parameters and output column types are string.

`SELECT b.*` `FROM src LATERAL VIEW parse_url_tuple(fullurl,` `'HOST'` `,` `'PATH'` `,` `'QUERY'` `,` `'QUERY:id'` `) b as host, path, query, query_id LIMIT` `1` `;`

GROUPing and SORTing on f(column)

A typical OLAP pattern is that you have a timestamp column and you want to group by daily or other less granular date windows than by second. So you might want to select concat(year(dt),month(dt)) and then group on that concat(). But if you attempt to GROUP BY or SORT BY a column on which you've applied a function and alias, like this:

`select f(col) as fc, count(*) from table_name group by fc;`

You will get an error:

`FAILED: Error in semantic analysis: line` `1` `:` `69` `Invalid Table Alias or Column Reference fc`

Because you are not able to GROUP BY or SORT BY a column alias on which a function has been applied. There are two workarounds. First, you can reformulate this query with subqueries, which is somewhat complicated:

`select sq.fc,col1,col2,...,colN,count(*) from` `(select f(col) as fc,col1,col2,...,colN from table_name) sq` `group by sq.fc,col1,col2,...,colN;`

Or you can make sure not to use a column alias, which is simpler:

`select f(col) as fc, count(*) from table_name group by f(col);`

Contact Tim Ellis (tellis) at RiotGames dot com if you would like to discuss this in further detail.

UDF internals

The context of a UDF's evaluate method is one row at a time. A simple invocation of a UDF like

`SELECT length(string_col) FROM table_name;`

would evaluate the length of each of the string_col's values in the map portion of the job. The side effect of the UDF being evaluated on the map-side is that you can't control the order of rows which get sent to the mapper. It is the same order in which the file split sent to the mapper gets deserialized. Any reduce side operation (such as SORT BY, ORDER BY, regular JOIN, etc.) would apply to the UDFs output as if it is just another column of the table. This is fine since the context of the UDF's evaluate method is meant to be one row at a time.

If you would like to control which rows get sent to the same UDF (and possibly in what order), you will have the urge to make the UDF evaluate during the reduce phase. This is achievable by making use of DISTRIBUTE BY, DISTRIBUTE BY + SORT BY, CLUSTER BY. An example query would be:

`SELECT reducer_udf(my_col, distribute_col, sort_col) FROM` `(SELECT my_col, distribute_col, sort_col FROM table_name DISTRIBUTE BY distribute_col SORT BY distribute_col, sort_col) t`

However, one could argue that the very premise of your requirement to control the set of rows sent to the same UDF is to do aggregation in that UDF. In such a case, using a User Defined Aggregate Function (UDAF) is a better choice. You can read more about writing a UDAF here. Alternatively, you can user a custom reduce script to accomplish the same using Hive's Transform functionality. Both of these options would do aggregations on the reduce side.