| /* ----------------------------------------------------------------------- *//** |
| * |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you under the Apache License, Version 2.0 (the |
| * "License"); you may not use this file except in compliance |
| * with the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, |
| * software distributed under the License is distributed on an |
| * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| * KIND, either express or implied. See the License for the |
| * specific language governing permissions and limitations |
| * under the License. |
| * |
| * |
| * @file balance_sample.sql_in |
| * |
| * @brief SQL functions for balanced data sets sampling. |
| * @date 12/14/2017 |
| * |
| * @sa Given a table, balanced sampling returns a sampled data set |
| * with specified proportions for each class (defaults to uniform sampling). |
| * |
| *//* ----------------------------------------------------------------------- */ |
| |
| m4_include(`SQLCommon.m4') |
| |
| |
| /** |
| @addtogroup grp_balance_sampling |
| |
| <div class="toc"><b>Contents</b> |
| <ul> |
| <li><a href="#strs">Balanced Sampling</a></li> |
| <li><a href="#examples">Examples</a></li> |
| <li><a href="#literature">Literature</a></li> |
| <li><a href="#related">Related Topics</a></li> |
| </ul> |
| </div> |
| |
| @brief A method to independently sample classes to produce a |
| balanced data set. |
| This is commonly used when classes are imbalanced, |
| to ensure that subclasses are adequately represented in the sample. |
| |
| 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. |
| |
| @anchor strs |
| @par Balanced Sampling |
| |
| <pre class="syntax"> |
| balance_sample( source_table, |
| output_table, |
| class_col, |
| class_sizes, |
| output_table_size, |
| grouping_cols, |
| with_replacement, |
| keep_null |
| ) |
| </pre> |
| |
| \b Arguments |
| <dl class="arglist"> |
| <dt>source_table</dt> |
| <dd>TEXT. Name of the table containing the input data.</dd> |
| |
| <dt>output_table</dt> |
| <dd>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. </dd> |
| |
| <dt>class_col</dt> |
| <dd>TEXT, Name of the column containing the class to be balanced. |
| </dd> |
| |
| <dt>class_sizes (optional)</dt> |
| <dd>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: |
| |
| <ul> |
| <li><b>‘uniform’</b>: |
| All class values will be resampled to have the same number of rows. |
| </li> |
| <li><b>'undersample'</b>: |
| Undersample such that all class values end up with the same number of |
| observations as the minority class. Done without replacement by default |
| unless the parameter ‘with_replacement’ is set to TRUE. |
| </li> |
| <li><b>'oversample'</b>: |
| Oversample with replacement such that all class values end up with the |
| same number of observations as the majority class. Not affected by the |
| parameter ‘with_replacement’ since oversampling is always done with |
| replacement. |
| </li> |
| Short forms of the above will work too, e.g., 'uni' works the same |
| as 'uniform'. |
| </ul> |
| |
| 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’. |
| </li> |
| </ul> |
| |
| @note |
| The allowed names for class values follows object naming rules in |
| PostgreSQL [1]. Quoted identifiers are allowed and should be enclosed |
| in double quotes in the usual way. If for some reason the class values |
| in the examples above were “ReD” and “BluE” then the comma delimited |
| list for ‘class_size’ would be: ‘“ReD”=3000, “BluE”=4000’. |
| </dd> |
| |
| <dt>output_table_size (optional)</dt> |
| <dd>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). |
| </dd> |
| |
| <dt>grouping_cols (optional)</dt> |
| <dd>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. |
| |
| @note |
| The 'output_table_size' and the 'class_sizes' are defined for the whole table. |
| When grouping is used, these parameters are split evenly for each group. |
| Further, if a specific class value is specified in the 'class_sizes' parameter, |
| that particular class value should be present in each group. If not, an error |
| will be thrown. |
| </dd> |
| |
| <dt>with_replacement (optional)</dt> |
| <dd>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.</dd> |
| |
| <dt>keep_null (optional)</dt> |
| <dd>BOOLEAN, default FALSE. Determines whether to |
| sample rows whose class values are NULL. By default, |
| all rows with NULL class values are ignored. If this |
| is set to TRUE, then NULL is treated as another class |
| value.</dd> |
| </dl> |
| |
| <b>How Output Table Size is Determined</b> |
| |
| 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.) | |
| |
| @anchor examples |
| @par Examples |
| |
| Note that due to the random nature of sampling, your |
| results may look different from those below. |
| |
| -# Create an input table using part of the flags |
| data set from https://archive.ics.uci.edu/ml/datasets/Flags : |
| <pre class="syntax"> |
| 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); |
| </pre> |
| |
| -# Uniform sampling. All class values will be resampled |
| so that they have the same number of rows. The output data |
| size will be the same as the input data size, ignoring |
| NULL values. Uniform sampling |
| is the default for the 'class_size' parameter so we do not |
| need to explicitly set it: |
| <pre class="syntax"> |
| 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; |
| </pre> |
| <pre class="result"> |
| __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) |
| </pre> |
| Next we do uniform sampling again, but this time we specify a |
| size for the output table: |
| <pre class="syntax"> |
| 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; |
| </pre> |
| <pre class="result"> |
| __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) |
| </pre> |
| |
| -# Oversampling. Oversample with replacement such that all |
| class values except NULLs end up with the same number of observations as |
| the majority class. Countries with red flags is the majority |
| class with 10 observations, so other class values will be |
| oversampled to 10 observations: |
| <pre class="syntax"> |
| 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; |
| </pre> |
| <pre class="result"> |
| __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) |
| </pre> |
| |
| -# Undersampling. Undersample such that all class values except NULLs end |
| up with the same number of observations as the minority class. |
| Countries with white flags is the minority class with 2 observations, |
| so other class values will be undersampled to 2 observations: |
| <pre class="syntax"> |
| 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; |
| </pre> |
| <pre class="result"> |
| __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) |
| </pre> |
| We may also want to undersample with replacement, so we set the 'with_replacement' parameter to TRUE: |
| <pre class="syntax"> |
| 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; |
| </pre> |
| <pre class="result"> |
| __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) |
| </pre> |
| Note above that some rows may appear multiple times above since we sampled with replacement. |
| |
| -# Setting class size by count. Here we set the number of rows for |
| red and blue flags, and leave green and white flags unchanged: |
| <pre class="syntax"> |
| 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; |
| </pre> |
| <pre class="result"> |
| __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) |
| </pre> |
| 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: |
| <pre class="syntax"> |
| 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; |
| </pre> |
| <pre class="result"> |
| __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) |
| </pre> |
| |
| -# To make NULL a valid class value, set the parameter to keep NULLs: |
| <pre class="syntax"> |
| 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; |
| </pre> |
| <pre class="result"> |
| __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) |
| </pre> |
| |
| -# To perform the balance sampling for independent groups, use the 'grouping_cols' |
| parameter. Note below that each group (zone) has a different count of the |
| classes (mainhue), with some groups not containing some class values. |
| <pre class="syntax"> |
| 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; |
| </pre> |
| <pre class="result"> |
| __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) |
| </pre> |
| |
| -# Grouping can be used with class size specification as well. Note below that |
| 'blue=<Integer>' is the only valid class value since 'blue' is the only class |
| value that is present in each group. Further, 'blue=8' will be split between the |
| four groups, resulting in two blue rows for each group. |
| <pre class="syntax"> |
| 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; |
| </pre> |
| <pre class="result"> |
| __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) |
| </pre> |
| |
| @anchor literature |
| @par Literature |
| |
| [1] Object naming in PostgreSQL |
| https://www.postgresql.org/docs/current/static/sql-syntax-lexical.html#SQL-SYNTAX-IDENTIFIERS |
| |
| @anchor related |
| @par Related Topics |
| |
| File balance_sample.sql_in for list of functions and usage. |
| |
| */ |
| |
| CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.balance_sample( |
| source_table TEXT, |
| output_table TEXT, |
| class_col TEXT, |
| class_sizes VARCHAR, |
| output_table_size INTEGER, |
| grouping_cols TEXT, |
| with_replacement BOOLEAN, |
| keep_null BOOLEAN |
| ) RETURNS VOID AS $$ |
| PythonFunction(sample, balance_sample, balance_sample) |
| $$ LANGUAGE plpythonu VOLATILE |
| m4_ifdef(`\_\_HAS_FUNCTION_PROPERTIES\_\_', `MODIFIES SQL DATA', `'); |
| |
| ------------------------------------------------------------------------------- |
| |
| CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.balance_sample( |
| source_table TEXT, |
| output_table TEXT, |
| class_col TEXT, |
| class_sizes VARCHAR, |
| output_table_size INTEGER, |
| grouping_cols TEXT, |
| with_replacement BOOLEAN |
| ) RETURNS VOID AS $$ |
| SELECT MADLIB_SCHEMA.balance_sample($1, $2, $3, $4, $5, $6, $7, NULL); |
| $$ LANGUAGE sql VOLATILE |
| m4_ifdef(`\_\_HAS_FUNCTION_PROPERTIES\_\_', `MODIFIES SQL DATA', `'); |
| |
| CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.balance_sample( |
| source_table TEXT, |
| output_table TEXT, |
| class_col TEXT, |
| class_sizes VARCHAR, |
| output_table_size INTEGER, |
| grouping_cols TEXT |
| ) RETURNS VOID AS $$ |
| SELECT MADLIB_SCHEMA.balance_sample($1, $2, $3, $4, $5, $6, NULL, NULL); |
| $$ LANGUAGE sql VOLATILE |
| m4_ifdef(`\_\_HAS_FUNCTION_PROPERTIES\_\_', `MODIFIES SQL DATA', `'); |
| |
| CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.balance_sample( |
| source_table TEXT, |
| output_table TEXT, |
| class_col TEXT, |
| class_sizes VARCHAR, |
| output_table_size INTEGER |
| ) RETURNS VOID AS $$ |
| SELECT MADLIB_SCHEMA.balance_sample($1, $2, $3, $4, $5, NULL, NULL, NULL); |
| $$ LANGUAGE sql VOLATILE |
| m4_ifdef(`\_\_HAS_FUNCTION_PROPERTIES\_\_', `MODIFIES SQL DATA', `'); |
| |
| CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.balance_sample( |
| source_table TEXT, |
| output_table TEXT, |
| class_col TEXT, |
| class_sizes VARCHAR |
| ) RETURNS VOID AS $$ |
| SELECT MADLIB_SCHEMA.balance_sample($1, $2, $3, $4, NULL, NULL, NULL, NULL); |
| $$ LANGUAGE sql VOLATILE |
| m4_ifdef(`\_\_HAS_FUNCTION_PROPERTIES\_\_', `MODIFIES SQL DATA', `'); |
| |
| CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.balance_sample( |
| source_table TEXT, |
| output_table TEXT, |
| class_col TEXT |
| ) RETURNS VOID AS $$ |
| SELECT MADLIB_SCHEMA.balance_sample($1, $2, $3, 'uniform', NULL, NULL, NULL, NULL); |
| $$ LANGUAGE sql VOLATILE |
| m4_ifdef(`\_\_HAS_FUNCTION_PROPERTIES\_\_', `MODIFIES SQL DATA', `'); |
| |
| ------------------------------------------------------------------------------- |
| |
| -- Online help |
| CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.balance_sample( |
| message VARCHAR |
| ) RETURNS VARCHAR AS $$ |
| PythonFunction(sample, balance_sample, balance_sample_help) |
| $$ LANGUAGE plpythonu IMMUTABLE |
| m4_ifdef(`\_\_HAS_FUNCTION_PROPERTIES\_\_', `CONTAINS SQL', `'); |
| |
| ------------------------------------------------------------------------------- |
| |
| CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.balance_sample() |
| RETURNS VARCHAR AS $$ |
| SELECT MADLIB_SCHEMA.balance_sample(''); |
| $$ LANGUAGE sql IMMUTABLE |
| m4_ifdef(`\_\_HAS_FUNCTION_PROPERTIES\_\_', `CONTAINS SQL', `'); |
| ------------------------------------------------------------------------------- |