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<title>MADlib: Summary</title>
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&#160;<span id="projectnumber">1.4.1</span>
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<div class="title">Summary<div class="ingroups"><a class="el" href="group__grp__desc__stats.html">Descriptive Statistics</a></div></div> </div>
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<div class="toc"><b>Contents</b> </p>
<ul>
<li>
<a href="#usage">Summary Function Syntax</a> </li>
<li>
<a href="#examples">Examples</a> </li>
<li>
<a href="#notes">Notes</a> </li>
<li>
<a href="#related">Related Topics</a> </li>
</ul>
</div><p>The MADlib <b><a class="el" href="summary_8sql__in.html#a14ff66aaa0248c5e2741dfaf2e360881">summary()</a></b> function is a generic function that produces summary statistics from any data table. The function invokes various methods from the MADlib library to provide an overview of the data.</p>
<p><a class="anchor" id="usage"></a></p>
<dl class="section user"><dt>Summary Function Syntax</dt><dd>The <b><a class="el" href="summary_8sql__in.html#a14ff66aaa0248c5e2741dfaf2e360881">summary()</a></b> function has the following syntax:</dd></dl>
<pre class="syntax">
summary ( source_table,
output_table,
target_cols,
grouping_cols,
get_distinct,
get_quartiles,
ntile_array,
how_many_mfv,
get_estimates
)
</pre><p> <b>Arguments</b> </p>
<dl class="arglist">
<dt>source_table </dt>
<dd>TEXT. The name of the table containing the input data. </dd>
<dt>output_table </dt>
<dd><p class="startdd">TEXT. The name of the table to contain the output summary data.</p>
<p>The <b><a class="el" href="summary_8sql__in.html#a14ff66aaa0248c5e2741dfaf2e360881">summary()</a></b> function returns a composite type containing three fields: </p>
<table class="output">
<tr>
<th>output_table </th><td>TEXT. The name of the output table. </td></tr>
<tr>
<th>row_count </th><td>INTEGER. The number of rows in the output table. </td></tr>
<tr>
<th>duration </th><td>FLOAT8. The time taken (in seconds) to compute the summary. </td></tr>
</table>
<p class="enddd">Summary statistics are saved in a table with the name specifed in the <em>output_table</em> argument. The table can contain the following columns: </p>
<table class="output">
<tr>
<th>group_by </th><td>Group-by column name. NULL if none provided. </td></tr>
<tr>
<th>group_by_value </th><td>Value of the Group-by column. NULL if there is no grouping. </td></tr>
<tr>
<th>target_column </th><td>Targeted column values for which summary is requested. </td></tr>
<tr>
<th>column_number </th><td>Physical column number for the target column, as described in <em>pg_attribute</em>. </td></tr>
<tr>
<th>data_type </th><td>Data type of the target column. Standard GPDB type descriptors are displayed. </td></tr>
<tr>
<th>row_count </th><td>Number of rows for the target column. </td></tr>
<tr>
<th>distinct_values </th><td>Number of distinct values in the target column. </td></tr>
<tr>
<th>missing_values </th><td>Number of missing values in the target column. </td></tr>
<tr>
<th>blank_values </th><td>Number of blank values. Blanks are defined by this regular expression:<pre class="fragment">'^\w*$'</pre> </td></tr>
<tr>
<th>fraction_missing </th><td>Percentage of total rows that are missing, as a decimal value, e.g. 0.3. </td></tr>
<tr>
<th>fraction_blank </th><td>Percentage of total rows that are blank, as a decimal value, e.g. 0.3. </td></tr>
<tr>
<th>mean </th><td>Mean value of target column if target is numeric, otherwise NULL. </td></tr>
<tr>
<th>variance </th><td>Variance of target column if target is numeric, otherwise NULL. </td></tr>
<tr>
<th>min </th><td>Minimum value of target column. For strings this is the length of the shortest string. </td></tr>
<tr>
<th>max </th><td>Maximum value of target column. For strings this is the length of the longest string. </td></tr>
<tr>
<th>first_quartile </th><td>First quartile (25th percentile), only for numeric columns. </td></tr>
<tr>
<th>median </th><td>Median value of target column, if target is numeric, otherwise NULL. </td></tr>
<tr>
<th>third_quartile </th><td>Third quartile (25th percentile), only for numeric columns. </td></tr>
<tr>
<th>quantile_array </th><td>Percentile values corresponding to <em>ntile_array</em>. </td></tr>
<tr>
<th>most_frequent_values </th><td>An array containing the most frequently occurring values. The <em>how_many_mfv</em> argument determines the length of the array, 10 by default. </td></tr>
<tr>
<th>mfv_frequencies </th><td>Array containing the frequency count for each of the most frequent values. </td></tr>
</table>
</dd>
<dt>target_columns (optional) </dt>
<dd>TEXT, default NULL. A comma-separated list of columns to summarize. If NULL, summaries are produced for all columns. </dd>
<dt>grouping_cols (optional) </dt>
<dd>TEXT, default: null. A comma-separated list of columns on which to group results. If NULL, summaries are produced on the complete table. </dd>
<dt>get_distinct (optional) </dt>
<dd>BOOLEAN, default TRUE. If true, distinct values are counted. </dd>
<dt>get_quartiles (optional) </dt>
<dd>BOOLEAN, default TRUE. If TRUE, qartiles are computed. </dd>
<dt>ntile_array (optional) </dt>
<dd>FLOAT8[], default NULL. An array of quantile values to compute. If NULL, quantile values are not computed. </dd>
<dt>how_many_mfv (optional) </dt>
<dd>INTEGER, default: 10. The number of most-frequent-values to compute. </dd>
<dt>get_estimates (optional) </dt>
<dd>BOOLEAN, default TRUE. If TRUE, estimated values are produced. If FALSE, exact values are calculated. </dd>
</dl>
<p><a class="anchor" id="examples"></a></p>
<dl class="section user"><dt>Examples</dt><dd><ol type="1">
<li>View online help for the <a class="el" href="summary_8sql__in.html#a14ff66aaa0248c5e2741dfaf2e360881">summary()</a> function. <pre class="example">
SELECT * FROM madlib.summary();
</pre></li>
<li>Create an input data set. <pre class="example">
CREATE TABLE houses (id INT, tax INT, bedroom INT, bath FLOAT, price INT,
size INT, lot INT);
COPY houses FROM STDIN WITH DELIMITER '|';
1 | 590 | 2 | 1 | 50000 | 770 | 22100
2 | 1050 | 3 | 2 | 85000 | 1410 | 12000
3 | 20 | 3 | 1 | 22500 | 1060 | 3500
4 | 870 | 2 | 2 | 90000 | 1300 | 17500
5 | 1320 | 3 | 2 | 133000 | 1500 | 30000
6 | 1350 | 2 | 1 | 90500 | 820 | 25700
7 | 2790 | 3 | 2.5 | 260000 | 2130 | 25000
8 | 680 | 2 | 1 | 142500 | 1170 | 22000
9 | 1840 | 3 | 2 | 160000 | 1500 | 19000
10 | 3680 | 4 | 2 | 240000 | 2790 | 20000
11 | 1660 | 3 | 1 | 87000 | 1030 | 17500
12 | 1620 | 3 | 2 | 118600 | 1250 | 20000
13 | 3100 | 3 | 2 | 140000 | 1760 | 38000
14 | 2070 | 2 | 3 | 148000 | 1550 | 14000
15 | 650 | 3 | 1.5 | 65000 | 1450 | 12000
\.
</pre></li>
<li>Run the <b><a class="el" href="summary_8sql__in.html#a14ff66aaa0248c5e2741dfaf2e360881">summary()</a></b> function. <pre class="example">
SELECT * FROM madlib.summary( 'houses',
'houses_summary',
'tax,bedroom,lot,bath,price,size,lot',
'bedroom',
TRUE,
TRUE,
NULL,
5,
FALSE
);
</pre> Result: <pre class="result">
output_table | row_count | duration
----------------+-----------+----------------
houses_summary | 21 | 0.207587003708
(1 row)
</pre></li>
<li>View the summary data. <pre class="example">
-- Turn on expanded display for readability.
\x on
SELECT * FROM houses_summary;
</pre> Result: <pre class="result">
&#160;-[ RECORD 1 ]--------+-----------------------------------
group_by | bedroom
group_by_value | 3
target_column | tax
column_number | 2
data_type | int4
row_count | 9
distinct_values | 9
missing_values | 0
blank_values |
fraction_missing | 0
fraction_blank |
mean | 1561.11111111111
variance | 936736.111111111
min | 20
max | 3100
most_frequent_values | {20,1320,2790,1840,1660}
mfv_frequencies | {1,1,1,1,1}
&#160;-[ RECORD 2 ]--------+-----------------------------------
group_by | bedroom
group_by_value | 3
target_column | bath
column_number | 4
...
</pre></li>
</ol>
</dd></dl>
<p><a class="anchor" id="notes"></a></p>
<dl class="section user"><dt>Notes</dt><dd><ul>
<li>Table names can be optionally schema qualified (current_schemas() would be searched if a schema name is not provided) and table and column names should follow case-sensitivity and quoting rules per the database. (For instance, 'mytable' and 'MyTable' both resolve to the same entity, i.e. 'mytable'. If mixed-case or multi-byte characters are desired for entity names then the string should be double-quoted; in this case the input would be '"MyTable"').</li>
<li>Estimated values are only implemented for the distinct values computation.</li>
<li>The <em>get_estimates</em> parameter controls computation for two statistics:<ul>
<li>If <em>get_estimates</em> is TRUE then the distinct value computation is estimated. Further, the most frequent values computation is computed using a "quick and dirty" method that does parallel aggregation in GPDB at the expense of missing some of the most frequent values.</li>
<li>If <em>get_estimates</em> is FALSE then the distinct values are computed in a slow but exact method. The most frequent values are computed using a faithful implementation that preserves the approximation guarantees of the Cormode/Muthukrishnan method (more information in <a class="el" href="group__grp__mfvsketch.html">MFV (Most Frequent Values)</a>).</li>
</ul>
</li>
</ul>
</dd></dl>
<p><a class="anchor" id="related"></a></p>
<dl class="section user"><dt>Related Topics</dt><dd>File <a class="el" href="summary_8sql__in.html" title="Summary function for descriptive statistics. ">summary.sql_in</a> documenting the <b><a class="el" href="summary_8sql__in.html#a14ff66aaa0248c5e2741dfaf2e360881">summary()</a></b> function</dd></dl>
<p><a class="el" href="group__grp__mfvsketch.html">MFV (Most Frequent Values)</a> </p>
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