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2.1.0
User Documentation for Apache MADlib
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2.1.0
User Documentation for Apache MADlib
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Some classification algorithms only perform optimally when the number of samples in each class is roughly the same. Highly skewed datasets are common in many domains (e.g., fraud detection), so resampling to offset this imbalance can produce a better decision boundary.
This module offers a number of resampling techniques including undersampling majority classes, oversampling minority classes, and combinations of the two.
balance_sample( source_table,
output_table,
class_col,
class_sizes,
output_table_size,
grouping_cols,
with_replacement,
keep_null
)
Arguments
TEXT. Name of the table containing the input data.
TEXT. Name of output table that contains the sampled data. The output table contains all columns present in the source table, plus a new generated id called "__madlib_id__" added as the first column.
TEXT, Name of the column containing the class to be balanced.
VARCHAR, default ‘uniform’. Parameter to define the size of the different class values. (Class values are sometimes also called levels). Can be set to the following:
Alternatively, you can also explicitly set class size in a string containing a comma-delimited list. Order does not matter and all class values do not need to be specified. Use the format “class_value_1=x, class_value_2=y, …” where 'class_value' in the list must exist in the column 'class_col'. Set to an integer representing the desired number of observations. E.g., ‘red=3000, blue=4000’ means you want to resample the dataset to result in exactly 3000 red and 4000 blue rows in the ‘output_table’.
INTEGER, default NULL. Desired size of the output data set. This parameter is ignored if ‘class_size’ parameter is set to either ‘oversample’ or ‘undersample’ since output table size is already determined. If NULL, the resulting output table size will depend on the settings for the ‘class_size’ parameter (see table below for more details).
TEXT, default: NULL. A single column or a list of comma-separated columns that defines the strata. When this parameter is NULL, no grouping is used so the sampling is non-stratified, that is, the whole table is treated as a single group.
BOOLEAN, default FALSE. Determines whether to sample with replacement or without replacement (default). With replacement means that it is possible that the same row may appear in the sample set more than once. Without replacement means a given row can be selected only once. This parameter affects undersampling only since oversampling is always done with replacement.
How Output Table Size is Determined
The rule of thumb is that if you specify a value for 'output_table_size', then you will generally get an output table of that size, with some minor rounding variations. If you set 'output_table_size' to NULL, then the size of the output table will be calculated depending on what you put for the 'class_size' parameter. The following table shows how the parameters 'class_size' and 'output_table_size' work together:
| Case | 'class_size' | 'output_table_size' | Result |
|---|---|---|---|
| 1 | 'uniform' | NULL | Resample for uniform class size with output size = input size (i.e., balanced). |
| 2 | 'uniform' | 10000 | Resample for uniform class size with output size = 10K (i.e., balanced). |
| 3 | NULL | NULL | Resample for uniform class size with output size = input size (i.e., balanced). Class_size=NULL has same behavior as ‘uniform’. |
| 4 | NULL | 10000 | Resample for uniform class size with output size = 10K (i.e., balanced). Class_size=NULL has same behavior as ‘uniform’. |
| 5 | 'undersample' | n/a | Undersample such that all class values end up with the same number of observations as the minority. |
| 6 | 'oversample' | n/a | Oversample with replacement (always) such that all class values end up with the same number of observations as the majority. |
| 7 | 'red=3000' | NULL | Resample red to 3K, leave rest of the class values (blue, green, etc.) as is. |
| 8 | 'red=3000, blue=4000' | 10000 | Resample red to 3K and blue to 4K, divide remaining class values evenly 3K/(n-2) each, where n=number of class values. Note that if red and blue are the only class values, then output table size will be 7K not 10K. (This is the only case where specifying a value for 'output_table_size' may not actually result in an output table of that size.) |
Note that due to the random nature of sampling, your results may look different from those below.
DROP TABLE IF EXISTS flags;
CREATE TABLE flags (
id INTEGER,
name TEXT,
landmass INTEGER,
zone INTEGER,
area INTEGER,
population INTEGER,
language INTEGER,
colours INTEGER,
mainhue TEXT
);
INSERT INTO flags VALUES
(1, 'Argentina', 2, 3, 2777, 28, 2, 2, 'blue'),
(2, 'Australia', 6, 2, 7690, 15, 1, 3, 'blue'),
(3, 'Austria', 3, 1, 84, 8, 4, 2, 'red'),
(4, 'Brazil', 2, 3, 8512, 119, 6, 4, 'green'),
(5, 'Canada', 1, 4, 9976, 24, 1, 2, 'red'),
(6, 'China', 5, 1, 9561, 1008, 7, 2, 'red'),
(7, 'Denmark', 3, 1, 43, 5, 6, 2, 'red'),
(8, 'Greece', 3, 1, 132, 10, 6, 2, 'blue'),
(9, 'Guatemala', 1, 4, 109, 8, 2, 2, 'blue'),
(10, 'Ireland', 3, 4, 70, 3, 1, 3, 'white'),
(11, 'Jamaica', 1, 4, 11, 2, 1, 3, 'green'),
(12, 'Luxembourg', 3, 1, 3, 0, 4, 3, 'red'),
(13, 'Mexico', 1, 4, 1973, 77, 2, 4, 'green'),
(14, 'Norway', 3, 1, 324, 4, 6, 3, 'red'),
(15, 'Portugal', 3, 4, 92, 10, 6, 5, 'red'),
(16, 'Spain', 3, 4, 505, 38, 2, 2, 'red'),
(17, 'Sweden', 3, 1, 450, 8, 6, 2, 'blue'),
(18, 'Switzerland', 3, 1, 41, 6, 4, 2, 'red'),
(19, 'UK', 3, 4, 245, 56, 1, 3, 'red'),
(20, 'USA', 1, 4, 9363, 231, 1, 3, 'white'),
(21, 'xElba', 3, 1, 1, 1, 6, NULL, NULL),
(22, 'xPrussia', 3, 1, 249, 61, 4, NULL, NULL);
DROP TABLE IF EXISTS output_table;
SELECT madlib.balance_sample(
'flags', -- Source table
'output_table', -- Output table
'mainhue'); -- Class column
SELECT * FROM output_table ORDER BY mainhue, name;
__madlib_id__ | id | name | landmass | zone | area | population | language | colours | mainhue
---------------+----+-------------+----------+------+------+------------+----------+---------+---------
5 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
2 | 2 | Australia | 6 | 2 | 7690 | 15 | 1 | 3 | blue
3 | 8 | Greece | 3 | 1 | 132 | 10 | 6 | 2 | blue
4 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
1 | 17 | Sweden | 3 | 1 | 450 | 8 | 6 | 2 | blue
11 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
12 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
14 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
15 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
13 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
8 | 3 | Austria | 3 | 1 | 84 | 8 | 4 | 2 | red
10 | 5 | Canada | 1 | 4 | 9976 | 24 | 1 | 2 | red
9 | 7 | Denmark | 3 | 1 | 43 | 5 | 6 | 2 | red
6 | 15 | Portugal | 3 | 4 | 92 | 10 | 6 | 5 | red
7 | 18 | Switzerland | 3 | 1 | 41 | 6 | 4 | 2 | red
19 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
20 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
18 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
16 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
17 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
(20 rows)
Next we do uniform sampling again, but this time we specify a size for the output table:
DROP TABLE IF EXISTS output_table;
SELECT madlib.balance_sample(
'flags', -- Source table
'output_table', -- Output table
'mainhue', -- Class column
'uniform', -- Uniform sample
12); -- Desired output table size
SELECT * FROM output_table ORDER BY mainhue, name;
__madlib_id__ | id | name | landmass | zone | area | population | language | colours | mainhue
---------------+----+-----------+----------+------+------+------------+----------+---------+---------
10 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
12 | 2 | Australia | 6 | 2 | 7690 | 15 | 1 | 3 | blue
11 | 8 | Greece | 3 | 1 | 132 | 10 | 6 | 2 | blue
2 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
3 | 11 | Jamaica | 1 | 4 | 11 | 2 | 1 | 3 | green
1 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
5 | 7 | Denmark | 3 | 1 | 43 | 5 | 6 | 2 | red
6 | 14 | Norway | 3 | 1 | 324 | 4 | 6 | 3 | red
4 | 15 | Portugal | 3 | 4 | 92 | 10 | 6 | 5 | red
9 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
7 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
8 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
(12 rows)
DROP TABLE IF EXISTS output_table;
SELECT madlib.balance_sample(
'flags', -- Source table
'output_table', -- Output table
'mainhue', -- Class column
'oversample'); -- Oversample
SELECT * FROM output_table ORDER BY mainhue, name;
__madlib_id__ | id | name | landmass | zone | area | population | language | colours | mainhue
---------------+----+-------------+----------+------+------+------------+----------+---------+---------
35 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
33 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
37 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
34 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
36 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
32 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
31 | 2 | Australia | 6 | 2 | 7690 | 15 | 1 | 3 | blue
39 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
38 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
40 | 17 | Sweden | 3 | 1 | 450 | 8 | 6 | 2 | blue
19 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
20 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
12 | 11 | Jamaica | 1 | 4 | 11 | 2 | 1 | 3 | green
11 | 11 | Jamaica | 1 | 4 | 11 | 2 | 1 | 3 | green
13 | 11 | Jamaica | 1 | 4 | 11 | 2 | 1 | 3 | green
17 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
15 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
16 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
18 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
14 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
9 | 3 | Austria | 3 | 1 | 84 | 8 | 4 | 2 | red
8 | 5 | Canada | 1 | 4 | 9976 | 24 | 1 | 2 | red
1 | 6 | China | 5 | 1 | 9561 | 1008 | 7 | 2 | red
10 | 7 | Denmark | 3 | 1 | 43 | 5 | 6 | 2 | red
2 | 12 | Luxembourg | 3 | 1 | 3 | 0 | 4 | 3 | red
4 | 14 | Norway | 3 | 1 | 324 | 4 | 6 | 3 | red
6 | 15 | Portugal | 3 | 4 | 92 | 10 | 6 | 5 | red
3 | 16 | Spain | 3 | 4 | 505 | 38 | 2 | 2 | red
5 | 18 | Switzerland | 3 | 1 | 41 | 6 | 4 | 2 | red
7 | 19 | UK | 3 | 4 | 245 | 56 | 1 | 3 | red
22 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
26 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
24 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
21 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
27 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
25 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
23 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
29 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
30 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
28 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
(40 rows)
DROP TABLE IF EXISTS output_table;
SELECT madlib.balance_sample(
'flags', -- Source table
'output_table', -- Output table
'mainhue', -- Class column
'undersample'); -- Undersample
SELECT * FROM output_table ORDER BY mainhue, name;
__madlib_id__ | id | name | landmass | zone | area | population | language | colours | mainhue
---------------+----+-------------+----------+------+------+------------+----------+---------+---------
1 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
2 | 2 | Australia | 6 | 2 | 7690 | 15 | 1 | 3 | blue
4 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
3 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
5 | 16 | Spain | 3 | 4 | 505 | 38 | 2 | 2 | red
6 | 18 | Switzerland | 3 | 1 | 41 | 6 | 4 | 2 | red
8 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
7 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
(8 rows)
We may also want to undersample with replacement, so we set the 'with_replacement' parameter to TRUE:
DROP TABLE IF EXISTS output_table;
SELECT madlib.balance_sample(
'flags', -- Source table
'output_table', -- Output table
'mainhue', -- Class column
'undersample', -- Undersample
NULL, -- Output table size will be calculated
NULL, -- No grouping
'TRUE'); -- Sample with replacement
SELECT * FROM output_table ORDER BY mainhue, name;
__madlib_id__ | id | name | landmass | zone | area | population | language | colours | mainhue
---------------+----+-----------+----------+------+------+------------+----------+---------+---------
2 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
1 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
3 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
4 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
6 | 5 | Canada | 1 | 4 | 9976 | 24 | 1 | 2 | red
5 | 19 | UK | 3 | 4 | 245 | 56 | 1 | 3 | red
7 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
8 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
(8 rows)
Note above that some rows may appear multiple times above since we sampled with replacement.
DROP TABLE IF EXISTS output_table;
SELECT madlib.balance_sample(
'flags', -- Source table
'output_table', -- Output table
'mainhue', -- Class column
'red=7, blue=7'); -- Want 7 reds and 7 blues
SELECT * FROM output_table ORDER BY mainhue, name;
__madlib_id__ | id | name | landmass | zone | area | population | language | colours | mainhue
---------------+----+------------+----------+------+------+------------+----------+---------+---------
5 | 2 | Australia | 6 | 2 | 7690 | 15 | 1 | 3 | blue
7 | 8 | Greece | 3 | 1 | 132 | 10 | 6 | 2 | blue
6 | 8 | Greece | 3 | 1 | 132 | 10 | 6 | 2 | blue
1 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
3 | 17 | Sweden | 3 | 1 | 450 | 8 | 6 | 2 | blue
2 | 17 | Sweden | 3 | 1 | 450 | 8 | 6 | 2 | blue
4 | 17 | Sweden | 3 | 1 | 450 | 8 | 6 | 2 | blue
8 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
18 | 11 | Jamaica | 1 | 4 | 11 | 2 | 1 | 3 | green
19 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
13 | 3 | Austria | 3 | 1 | 84 | 8 | 4 | 2 | red
14 | 5 | Canada | 1 | 4 | 9976 | 24 | 1 | 2 | red
17 | 6 | China | 5 | 1 | 9561 | 1008 | 7 | 2 | red
15 | 12 | Luxembourg | 3 | 1 | 3 | 0 | 4 | 3 | red
16 | 14 | Norway | 3 | 1 | 324 | 4 | 6 | 3 | red
11 | 15 | Portugal | 3 | 4 | 92 | 10 | 6 | 5 | red
12 | 16 | Spain | 3 | 4 | 505 | 38 | 2 | 2 | red
9 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
10 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
(19 rows)
Next we set the number of rows for red and blue flags, and also set an output table size. This means that green and white flags will be uniformly sampled to get to the desired output table size:
DROP TABLE IF EXISTS output_table;
SELECT madlib.balance_sample(
'flags', -- Source table
'output_table', -- Output table
'mainhue', -- Class column
'red=7, blue=7', -- Want 7 reds and 7 blues
22); -- Desired output table size
SELECT * FROM output_table ORDER BY mainhue, name;
__madlib_id__ | id | name | landmass | zone | area | population | language | colours | mainhue
---------------+----+-------------+----------+------+------+------------+----------+---------+---------
16 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
20 | 2 | Australia | 6 | 2 | 7690 | 15 | 1 | 3 | blue
21 | 2 | Australia | 6 | 2 | 7690 | 15 | 1 | 3 | blue
22 | 8 | Greece | 3 | 1 | 132 | 10 | 6 | 2 | blue
18 | 17 | Sweden | 3 | 1 | 450 | 8 | 6 | 2 | blue
19 | 17 | Sweden | 3 | 1 | 450 | 8 | 6 | 2 | blue
17 | 17 | Sweden | 3 | 1 | 450 | 8 | 6 | 2 | blue
9 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
10 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
8 | 11 | Jamaica | 1 | 4 | 11 | 2 | 1 | 3 | green
11 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
6 | 3 | Austria | 3 | 1 | 84 | 8 | 4 | 2 | red
7 | 5 | Canada | 1 | 4 | 9976 | 24 | 1 | 2 | red
2 | 7 | Denmark | 3 | 1 | 43 | 5 | 6 | 2 | red
1 | 12 | Luxembourg | 3 | 1 | 3 | 0 | 4 | 3 | red
3 | 15 | Portugal | 3 | 4 | 92 | 10 | 6 | 5 | red
5 | 16 | Spain | 3 | 4 | 505 | 38 | 2 | 2 | red
4 | 18 | Switzerland | 3 | 1 | 41 | 6 | 4 | 2 | red
14 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
13 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
15 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
12 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
(22 rows)
DROP TABLE IF EXISTS output_table;
SELECT madlib.balance_sample(
'flags', -- Source table
'output_table', -- Output table
'mainhue', -- Class column
NULL, -- Uniform
NULL, -- Output table size
NULL, -- No grouping
NULL, -- Sample without replacement
'TRUE'); -- Make NULLs a valid class value
SELECT * FROM output_table ORDER BY mainhue, name;
__madlib_id__ | id | name | landmass | zone | area | population | language | colours | mainhue
---------------+----+-------------+----------+------+------+------------+----------+---------+---------
25 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
22 | 2 | Australia | 6 | 2 | 7690 | 15 | 1 | 3 | blue
24 | 8 | Greece | 3 | 1 | 132 | 10 | 6 | 2 | blue
21 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
23 | 17 | Sweden | 3 | 1 | 450 | 8 | 6 | 2 | blue
7 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
6 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
10 | 11 | Jamaica | 1 | 4 | 11 | 2 | 1 | 3 | green
8 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
9 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
3 | 3 | Austria | 3 | 1 | 84 | 8 | 4 | 2 | red
1 | 5 | Canada | 1 | 4 | 9976 | 24 | 1 | 2 | red
2 | 16 | Spain | 3 | 4 | 505 | 38 | 2 | 2 | red
4 | 18 | Switzerland | 3 | 1 | 41 | 6 | 4 | 2 | red
5 | 19 | UK | 3 | 4 | 245 | 56 | 1 | 3 | red
13 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
11 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
14 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
12 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
15 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
17 | 21 | xElba | 3 | 1 | 1 | 1 | 6 | |
18 | 21 | xElba | 3 | 1 | 1 | 1 | 6 | |
16 | 21 | xElba | 3 | 1 | 1 | 1 | 6 | |
20 | 22 | xPrussia | 3 | 1 | 249 | 61 | 4 | |
19 | 22 | xPrussia | 3 | 1 | 249 | 61 | 4 | |
(25 rows)
DROP TABLE IF EXISTS output_table;
SELECT madlib.balance_sample(
'flags', -- Source table
'output_table', -- Output table
'mainhue', -- Class column
NULL, -- Uniform
NULL, -- Output table size
'zone' -- Grouping by zone
);
SELECT * FROM output_table ORDER BY zone, mainhue;
__madlib_id__ | id | name | landmass | zone | area | population | language | colours | mainhue
---------------+----+-------------+----------+------+------+------------+----------+---------+---------
6 | 8 | Greece | 3 | 1 | 132 | 10 | 6 | 2 | blue
5 | 8 | Greece | 3 | 1 | 132 | 10 | 6 | 2 | blue
8 | 17 | Sweden | 3 | 1 | 450 | 8 | 6 | 2 | blue
7 | 8 | Greece | 3 | 1 | 132 | 10 | 6 | 2 | blue
2 | 7 | Denmark | 3 | 1 | 43 | 5 | 6 | 2 | red
1 | 6 | China | 5 | 1 | 9561 | 1008 | 7 | 2 | red
4 | 12 | Luxembourg | 3 | 1 | 3 | 0 | 4 | 3 | red
3 | 18 | Switzerland | 3 | 1 | 41 | 6 | 4 | 2 | red
1 | 2 | Australia | 6 | 2 | 7690 | 15 | 1 | 3 | blue
1 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
2 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
6 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
5 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
4 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
12 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
10 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
11 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
1 | 19 | UK | 3 | 4 | 245 | 56 | 1 | 3 | red
3 | 5 | Canada | 1 | 4 | 9976 | 24 | 1 | 2 | red
2 | 15 | Portugal | 3 | 4 | 92 | 10 | 6 | 5 | red
8 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
7 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
9 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
(23 rows)
DROP TABLE IF EXISTS output_table;
SELECT madlib.balance_sample(
'flags', -- Source table
'output_table', -- Output table
'mainhue', -- Class column
'blue=8', -- Specified class value size. Rest of the values are outputed as is.
NULL, -- Output table size
'zone' -- Group by zone
);
SELECT * FROM output_table ORDER BY zone, mainhue;
__madlib_id__ | id | name | landmass | zone | area | population | language | colours | mainhue
---------------+----+-------------+----------+------+------+------------+----------+---------+---------
2 | 17 | Sweden | 3 | 1 | 450 | 8 | 6 | 2 | blue
1 | 8 | Greece | 3 | 1 | 132 | 10 | 6 | 2 | blue
3 | 3 | Austria | 3 | 1 | 84 | 8 | 4 | 2 | red
5 | 7 | Denmark | 3 | 1 | 43 | 5 | 6 | 2 | red
4 | 6 | China | 5 | 1 | 9561 | 1008 | 7 | 2 | red
8 | 18 | Switzerland | 3 | 1 | 41 | 6 | 4 | 2 | red
7 | 14 | Norway | 3 | 1 | 324 | 4 | 6 | 3 | red
6 | 12 | Luxembourg | 3 | 1 | 3 | 0 | 4 | 3 | red
1 | 2 | Australia | 6 | 2 | 7690 | 15 | 1 | 3 | blue
2 | 2 | Australia | 6 | 2 | 7690 | 15 | 1 | 3 | blue
1 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
2 | 1 | Argentina | 2 | 3 | 2777 | 28 | 2 | 2 | blue
3 | 4 | Brazil | 2 | 3 | 8512 | 119 | 6 | 4 | green
2 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
1 | 9 | Guatemala | 1 | 4 | 109 | 8 | 2 | 2 | blue
5 | 11 | Jamaica | 1 | 4 | 11 | 2 | 1 | 3 | green
6 | 13 | Mexico | 1 | 4 | 1973 | 77 | 2 | 4 | green
3 | 5 | Canada | 1 | 4 | 9976 | 24 | 1 | 2 | red
7 | 15 | Portugal | 3 | 4 | 92 | 10 | 6 | 5 | red
8 | 16 | Spain | 3 | 4 | 505 | 38 | 2 | 2 | red
9 | 19 | UK | 3 | 4 | 245 | 56 | 1 | 3 | red
10 | 20 | USA | 1 | 4 | 9363 | 231 | 1 | 3 | white
4 | 10 | Ireland | 3 | 4 | 70 | 3 | 1 | 3 | white
(23 rows)
[1] Object naming in PostgreSQL https://www.postgresql.org/docs/current/static/sql-syntax-lexical.html#SQL-SYNTAX-IDENTIFIERS
File balance_sample.sql_in for list of functions and usage.
1.8.13