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HiveSwarm: User Defined Functions for Hive

Hive provides a number of useful user defined functions, but there is certainly room for more. HiveSwarm provides a collection of additional useful functions.
HiveSwarm requires Hive >= 0.7.0.


Assuming you have Hadoop and Hive set up (along with your HADOOP_HOME and HIVE_HOME environment variables set correctly), run the following:

git clone git://
cd HiveSwarm

You should now have a jar file in your dist folder named HiveSwarm.jar.


Each of the following methods assumes you have first run the following in your hive session:

add jar /path/to/HiveSwarm.jar;

After you do that, you can create temporary functions as needed.

max_date(date string, ...)


create temporary function max_date as 'com.livingsocial.hive.udf.MaxDate'

max_date takes any number of date ('2011-01-10') or date time ('2011-01-10 10:01:00') or null arguments. The max date among non-null arguments is returned.

min_date(date string, ...)

Same as max_date, but returns min.

intervals(group column, interval column)


create temporary function intervals as 'com.livingsocial.hive.udtf.Intervals';

intervals takes a group column argument and an interval argument and returns a two column table with the intervals between the rows per group. The interval column can be a numerical or date/datetime (string) column.

smax(column) / smin(column)


create temporary function smin as 'com.livingsocial.hive.udf.SMin';

smin and smax act just like min and max but treat string columns like timestamps.

ilike(colname, pattern)

Same as regular Hive like but is case irrespective (just like MySQL's like). Use is like:

create temporary function ilike as 'com.livingsocial.hive.udf.ILike';
select city_name, count from city_counts where ilike(city_name, "%baltimore%");

first_n(group column, value column, count)

Table generating function that returns up to count rows per group column of the group and value columns.

create temporary function first_n as 'com.livingsocial.hive.udtf.FirstN';
select first_n(person_id, value, 20) as (one, two) from person_values;

This will output the first 20 rows (by person_id) of (person_id, value).


Same as regular Hive unix_timestamp but can handle "yyyy-MM-dd HH:mm:ss" as well as "yyyy-MM-dd". Use is like:

create temporary function unix_liberal_timestamp as 'com.livingsocial.hive.udf.UnixLiberalTimestamp';
select city_name, unix_liberal_timestsamp(created_at) from cities;

index_of(needle, haystack[, startIndex])

Get first index of string needle in string haystack (optionally, starting search from startIndex). Returns -1 if not found.

create temporary function index_of as 'com.livingsocial.hive.udf.IndexOf';
select email from users where index_of('@', email) > -1;

in_array(needle, haystack)

Returns true if needle (primitive) is in haystack (array of primitives) and if needle is not null. Returns false otherwise.

create temporary function in_array as 'com.livingsocial.hive.udf.InArray';
select in_array(user_id, array(1,2,3,4)) from users;


Get day of week (as integer) from date (of format "yyyy-mm-dd"). Sunday is 1, Monday 2, etc.

create temporary function dayofweek as 'com.livingsocial.hive.udf.DayOfWeek';
select dayofweek(to_date(created_at)) from src;

bin_case(long, array(names))

Get representations of bits in a bitfield (it's like the bin UDF and a long case statement - hence, bin_case). If long represents a (big endian) bit field, bin_case will generate a single column table with a row for each positive bit containing the corresponding value in names. For instance, here are some examples:

create temporary function bin_case as 'com.livingsocial.hive.udtf.BinCase';
select bin_case(1, array("foo", "bar", "baz")) as c from source;
> foo
select bin_case(2, array("foo", "bar", "baz")) as c from source;
> bar
select bin_case(3, array("foo", "bar", "baz")) as c from source;
> foo
> bar
select bin_case(4, array("foo", "bar", "baz")) as c from source;
> baz
select bin_case(5, array("foo", "bar", "baz")) as c from source;
> foo
> baz
select bin_case(7, array("foo", "bar", "baz")) as c from source;
> foo
> bar
> baz

aes_decrypt(encrypted_string, key)

AES decrypt the given string (which should be Base32 hex encoded) with the given key.

create temporary function aes_decrypt as 'com.livingsocial.hive.udf.AESDecrypt';
select aes_decrypt(credit_card_number, "textkey") from credit_cards;

This will require downloading this file from Sun and installing to /usr/java/jdk1.6.0_22/jre/lib/security (due to cryptographic export controls).

gpsDistanceFrom(latitude1 double, longitude1 double, latitude2 double, longitude2 double)

Calculate the distance between two gps coordinates, return result in miles.

hive -e "select gpsDistanceFrom(38, -97, 37.33181, -122.02955) from test_coordinates"

Coordinates are entered as doubles, and a double is returned.


Return the index of an element greater than or equal to all of the other elements. In case of equality earlier elements will be preferred.

create temporary function index_of_max_elem as 'com.livingsocial.hive.udf.IndexOfMaxElem';
select index_of_max_elem(array(3,5,9,2)) from some_table;
> 2

Bugs / Contact

Any bugs / request can be submited via tickets on Github.

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