THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
Hive User Defined Functions
In the CLI, use the commands below to show the latest documentation:
SHOW FUNCTIONS; DESCRIBE FUNCTION <function_name>; DESCRIBE FUNCTION EXTENDED <function_name>;
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 |
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 |
||
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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 |
https://issues.apache.org/jira/browse/HIVE-2005])]]></ac:plain-text-body></ac:structured-macro> |
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 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) e.g. 'foobar' like 'foo' evaluates to FALSE where as '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 string A matches the Java regular expression B(See Java regular expressions syntax), otherwise FALSE e.g. 'foobar' rlike 'foo' evaluates to FALSE where as 'foobar' rlike '^f.*r$' evaluates to TRUE |
||
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. e.g. 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 |
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. |
array |
(val1, val2, ...) |
Creates an array with the given elements |
Operators on Complex Types
The following operators provide mechanisms to access elements in Complex Types
Operator |
Operand types |
Description |
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|---|---|---|---|---|
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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 e.g. if A is an array comprising of ['foo', 'bar'] then A[0] returns 'foo' and A[1] returns 'bar' |
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M[key] |
M is a Map<K, V> and key has type K |
Returns the value corresponding to the key in the map e.g. if M is a map comprising of {'f' -> 'foo', 'b' -> 'bar', 'all' -> 'foobar'} then M['all'] returns 'foobar' |
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S.x |
S is a struct |
Returns the x field of S. e.g for 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 |
||
|---|---|---|---|---|
BIGINT |
round(double a) |
Returns the rounded BIGINT value of the double |
||
DOUBLE |
round(double a, int d) |
Returns the double rounded to d decimal places |
||
BIGINT |
floor(double a) |
Returns the maximum BIGINT value that is equal or less than the double |
||
BIGINT |
ceil(double a), ceiling(double a) |
Returns the minimum BIGINT value that is equal or greater than the double |
||
double |
rand(), rand(int seed) |
Returns a random number (that changes from row to row) that is distributed uniformly from 0 to 1. Specifiying the seed will make sure the generated random number sequence is deterministic. |
||
double |
exp(double a) |
Returns ea where e is the base of the natural logarithm |
||
double |
ln(double a) |
Returns the natural logarithm of the argument |
||
double |
log10(double a) |
Returns the base-10 logarithm of the argument |
||
double |
log2(double a) |
Returns the base-2 logarithm of the argument |
||
double |
log(double base, double a) |
Return the base "base" logarithm of the argument |
||
double |
pow(double a, double p) power(double a, double p) |
Return ap |
||
double |
sqrt(double a) |
Returns the square root of a |
||
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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]]) |
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string |
hex(BIGINT a) hex(string a) |
If the argument is an int, hex returns the number as a string in hex format. Otherwise if the number is a string, it converts each character into its hex representation and returns the resulting string. (see [[http://dev.mysql.com/doc/refman/5.0/en/string-functions.html#function_hex]]) |
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string |
unhex(string a) |
Inverse of hex. Interprets each pair of characters as a hexidecimal number and converts to the character represented by the number. |
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string |
conv(BIGINT 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]]) |
]]></ac:plain-text-body></ac:structured-macro> |
double |
abs(double a) |
Returns the absolute value |
||
int double |
pmod(int a, int b) pmod(double a, double b) |
Returns the positive value of a mod b |
||
double |
sin(double a) |
Returns the sine of a (a is in radians) |
||
double |
asin(double a) |
Returns the arc sin of x if -1<=a<=1 or null otherwise |
||
double |
cos(double a) |
Returns the cosine of a (a is in radians) |
||
double |
acos(double a) |
Returns the arc cosine of x if -1<=a<=1 or null otherwise |
||
double |
tan(double a) |
Returns the tangent of a (a is in radians) |
||
double |
atan(double a) |
Returns the arctangent of a |
||
double |
degrees(double a) |
Converts value of a from radians to degrees |
||
double |
radians(double a) |
Converts value of a from degrees to radians |
||
int double |
positive(int a) positive(double a) |
Returns a |
||
int double |
negative(int a) negative(double a) |
Returns -a |
||
float |
sign(double a) |
Returns the sign of a as '1.0' or '-1.0' |
||
double |
e() |
Returns the value of e |
||
double |
pi() |
Returns the value of pi |
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 |
|---|---|---|
Expected "=" to follow "type" |
cast(expr as <type>) |
Converts the results of the expression expr to <type> e.g. cast('1' as BIGINT) will convert the string '1' to it 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 |
||
|---|---|---|---|---|
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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" |
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bigint |
unix_timestamp() |
Gets current time stamp using the default time zone. |
||
bigint |
unix_timestamp(string date) |
Converts time string in format |
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bigint |
unix_timestamp(string date, string pattern) |
Convert time string with given pattern (see [[http://java.sun.com/j2se/1.4.2/docs/api/java/text/SimpleDateFormat.html]]) to Unix time stamp, return 0 if fail: unix_timestamp('2009-03-20', 'yyyy-MM-dd') = 1237532400 |
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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) |
Return 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) |
Return 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) |
Return the number of days from startdate to enddate: datediff('2009-03-01', '2009-02-27') = 2 |
||
int |
date_add(string startdate, int days) |
Add a number of days to startdate: date_add('2008-12-31', 1) = '2009-01-01' |
||
int |
date_sub(string startdate, int days) |
Subtract a number of days to startdate: date_sub('2008-12-31', 1) = '2008-12-30' |
Conditional Functions
Return Type |
Name(Signature) |
Description |
||
|---|---|---|---|---|
T |
if(boolean testCondition, T valueTrue, T valueFalseOrNull) |
Return valueTrue when testCondition is true, returns valueFalseOrNull otherwise |
||
T |
COALESCE(T v1, T v2, ...) |
Return the first v that is not NULL, or NULL if all v's are NULL |
||
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T |
CASE a WHEN b THEN c [WHEN d THEN e]* [ELSE f] END |
When a = b, returns c; when a = d, return e; else return f |
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T |
CASE WHEN a THEN b [WHEN c THEN d]* [ELSE e] END |
When a = true, returns b; when c = true, return d; else return e |
]]></ac:plain-text-body></ac:structured-macro> |
String Functions
The following are built-in String functions are supported in hive:
Return Type |
Name(Signature) |
Description |
||
|---|---|---|---|---|
int |
length(string A) |
Returns the length of the string |
||
string |
reverse(string A) |
Returns the reversed string |
||
string |
concat(string A, string B...) |
Returns the string resulting from concatenating the strings passed in as parameters in order. e.g. concat('foo', 'bar') results in 'foobar'. Note that this function can take any number of input strings. |
||
string |
concat_ws(string SEP, string A, string B...) |
Like concat() above, but with custom separator SEP. |
||
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string |
substr(string A, int start) substring(string A, int start) |
Returns the substring of A starting from start position till the end of string A e.g. substr('foobar', 4) results in 'bar' (see [[http://dev.mysql.com/doc/refman/5.0/en/string-functions.html#function_substr]]) |
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string |
substr(string A, int start, int len) substring(string A, int start, int len) |
Returns the substring of A starting from start position with length len e.g. substr('foobar', 4, 1) results in 'b' (see [[http://dev.mysql.com/doc/refman/5.0/en/string-functions.html#function_substr]]) |
]]></ac:plain-text-body></ac:structured-macro> |
string |
upper(string A) ucase(string A) |
Returns the string resulting from converting all characters of A to upper case e.g. upper('fOoBaR') results in 'FOOBAR' |
||
string |
lower(string A) lcase(string A) |
Returns the string resulting from converting all characters of B to lower case e.g. lower('fOoBaR') results in 'foobar' |
||
string |
trim(string A) |
Returns the string resulting from trimming spaces from both ends of A e.g. trim(' foobar ') results in 'foobar' |
||
string |
ltrim(string A) |
Returns the string resulting from trimming spaces from the beginning(left hand side) of A e.g. ltrim(' foobar ') results in 'foobar ' |
||
string |
rtrim(string A) |
Returns the string resulting from trimming spaces from the end(right hand side) of A e.g. rtrim(' foobar ') results in ' foobar' |
||
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, e.g. 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; ' |
||
string |
regexp_extract(string subject, string pattern, int index) |
Returns the string extracted using the pattern. e.g. 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; ' |
||
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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. e.g. 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, e.g. parse_url('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'QUERY', 'k1') returns 'v1'. |
]]></ac:plain-text-body></ac:structured-macro> |
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string |
get_json_object(string json_string, string path) |
Extract json object from a json string based on json path specified, and return 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. |
]]></ac:plain-text-body></ac:structured-macro> |
string |
space(int n) |
Return a string of n spaces |
||
string |
repeat(string str, int n) |
Repeat str n times |
||
int |
ascii(string str) |
Returns the numeric value of the first character of str |
||
string |
lpad(string str, int len, string pad) |
Returns str, left-padded with pad to a length of len |
||
string |
rpad(string str, int len, string pad) |
Returns str, right-padded with pad to a length of len |
||
array |
split(string str, string pat) |
Split str around pat (pat is a regular expression) |
||
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. e.g. find_in_set('ab', 'abc,b,ab,c,def') returns 3 |
||
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int |
locate(string substr, string str[, int pos]) |
Returns the position of the first occurrence of substr in str after position pos |
]]></ac:plain-text-body></ac:structured-macro> |
int |
instr(string str, string substr) |
Returns the position of the first occurence of substr in str |
||
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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. |
]]></ac:plain-text-body></ac:structured-macro> |
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. e.g. sentences('Hello there! How are you?') returns ( ("Hello", "there"), ("How", "are", "you") ) |
||
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. |
||
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. |
||
boolean |
in_file(string str, string filename) |
Returns true if the string str appears as an entire line in filename. |
||
string |
printf(String format, Obj... args) |
Returns the input formatted according do printf-style format strings (as of Hive 0.9.0) |
Misc. Functions
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 |
||
|---|---|---|---|---|
<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="b53a2132-5ecf-41fe-87e5-d248eb8b6ff9"><ac:plain-text-body><![CDATA[ |
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. |
]]></ac:plain-text-body></ac:structured-macro> |
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 pth 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. |
||
<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="b091e811-b4a4-4554-823e-6f1e3a690066"><ac:plain-text-body><![CDATA[ |
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). pi 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. |
]]></ac:plain-text-body></ac:structured-macro> |
<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="a0d0d7d5-90ec-4309-9a62-c679e41b58ab"><ac:plain-text-body><![CDATA[ |
double |
percentile_approx(DOUBLE col, p [, B]) |
Returns an approximate pth 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. |
]]></ac:plain-text-body></ac:structured-macro> |
<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="9a557a61-5477-41eb-acac-a89910afcd8f"><ac:plain-text-body><![CDATA[ |
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. |
]]></ac:plain-text-body></ac:structured-macro> |
array<struct { |
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 |
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.
explode
explode() takes in an array as an input and outputs the elements of the array 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 |
||
|---|---|---|
<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="4201a21e-f8a8-49d8-b3a3-afcae60627c8"><ac:plain-text-body><![CDATA[ |
[1,2,3] |
]]></ac:plain-text-body></ac:structured-macro> |
<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="7e479ecb-b070-4cdb-b701-02fb6c8288d3"><ac:plain-text-body><![CDATA[ |
[4,5,6] |
]]></ac:plain-text-body></ac:structured-macro> |
Then running the query:
SELECT explode(myCol) AS myNewCol FROM myTable;
Will produce:
(int) myNewCol |
|---|
1 |
2 |
3 |
4 |
5 |
6 |
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.
The following are built-in table-generating functions are supported in Hive:
Return Type |
Name(Signature) |
Description |
|---|---|---|
Array Type |
explode(array<TYPE> a) |
For each element in a, explode() generates a row containing that element |
|
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. |
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, e.g. 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 (e.g. 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.