docs/v1.9.1/group__grp__profile.html - madlib-site - Git at Google

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 <div class="header">
   <div class="headertitle">
 <div class="title">Profile<div class="ingroups"><a class="el" href="group__grp__deprecated.html">Deprecated Modules</a></div></div>  </div>
 </div><!--header-->
 <div class="contents">
 <dl class="section warning"><dt>Warning</dt><dd><em> This is an old implementation of summary function. Replacement of this function is available as the Summary module <a class="el" href="group__grp__summary.html">Summary</a></em></dd></dl>
 <div class="toc"><b>Contents</b> </p><ul>
 <li>
 <a href="#syntax">Function Syntax</a> </li>
 <li>
 <a href="#examples">Examples</a> </li>
 <li>
 <a href="#notes">Implementation Notes</a> </li>
 <li>
 <a href="#related">Related Topics</a> </li>
 </ul>
 </div><p>This module computes a "profile" of a table or view: a predefined set of aggregates to be run on each column of a table.</p>
 <p>The following aggregates are called on every integer column:</p><ul>
 <li>min(), max(), <a class="el" href="linalg_8sql__in.html#a1aa37f73fb1cd8d7d106aa518dd8c0b4" title="Compute the average of vectors. ">avg()</a></li>
 <li>madlib.cmsketch_median()</li>
 <li>madlib.cmsketch_depth_histogram()</li>
 <li>madlib.cmsketch_width_histogram()</li>
 </ul>
 <p>The following aggregates are called on non-integer columns:</p><ul>
 <li>madlib.fmsketch_dcount()</li>
 <li>madlib.mfvsketch_quick_histogram()</li>
 <li>madlib.mfvsketch_top_histogram()</li>
 </ul>
 <p>Because the input schema of the table or view is unknown, SQL is synthesized to suit the input. This is done either via the <code>profile</code> or <code>profile_full</code> user defined function.</p>
 <p><a class="anchor" id="syntax"></a></p><dl class="section user"><dt>Function Syntax</dt><dd></dd></dl>
 <p>Generate basic profile information (subset of predefined aggregate functions) for all columns of the input table. </p><pre class="syntax">
 profile( input_table )
 </pre><p>Generate full profile information (all predefined aggregate functions) for all columns of the input table. </p><pre class="syntax">
 profile_full( input_table,
               buckets
             )
 </pre><p><a class="anchor" id="examples"></a></p><dl class="section user"><dt>Examples</dt><dd></dd></dl>
 <ol type="1">
 <li>Generate basic profile information. <pre class="example">
 SELECT * FROM profile( 'pg_catalog.pg_tables');
 </pre> Result: <pre class="result">
  schema_name | table_name | column_name |       function    | value
 &#160;------------+------------+-------------+-------------------+-------
  pg_catalog  | pg_tables  | *           | COUNT()           | 105
  pg_catalog  | pg_tables  | schemaname  | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a> | 6
  pg_catalog  | pg_tables  | tablename   | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a> | 104
  pg_catalog  | pg_tables  | tableowner  | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a> | 2
  pg_catalog  | pg_tables  | tablespace  | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a> | 1
  pg_catalog  | pg_tables  | hasindexes  | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a> | 2
  pg_catalog  | pg_tables  | hasrules    | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a> | 1
  pg_catalog  | pg_tables  | hastriggers | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a> | 2
 (8 rows)
 </pre></li>
 <li>Generate full profile information. <pre class="example">
 SELECT * FROM profile_full( 'pg_catalog.pg_tables',
                              5
                           );
 </pre> Result: <pre class="result">
  schema_name | table_name | column_name |                        function                 |                                               value
 &#160;------------+------------+-------------+-------------------------------------------------+----------------------------------------------------------------------------------------------------
  pg_catalog  | pg_tables  | *           | COUNT()                                         | 105
  pg_catalog  | pg_tables  | schemaname  | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a>                               | 6
  pg_catalog  | pg_tables  | schemaname  | array_collapse(mfvsketch_quick_histogram((),5)) | [0:4]={pg_catalog:68,public:19,information_schema:7,gp_toolkit:5,maddy:5}
  pg_catalog  | pg_tables  | schemaname  | array_collapse(mfvsketch_top_histogram((),5))   | [0:4]={pg_catalog:68,public:19,information_schema:7,gp_toolkit:5,maddy:5}
  pg_catalog  | pg_tables  | tablename   | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a>                               | 104
  pg_catalog  | pg_tables  | tablename   | array_collapse(mfvsketch_quick_histogram((),5)) | [0:4]={migrationhistory:2,pg_statistic:1,sql_features:1,sql_implementation_info:1,sql_languages:1}
  pg_catalog  | pg_tables  | tablename   | array_collapse(mfvsketch_top_histogram((),5))   | [0:4]={migrationhistory:2,pg_statistic:1,sql_features:1,sql_implementation_info:1,sql_languages:1}
  pg_catalog  | pg_tables  | tableowner  | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a>                               | 2
  pg_catalog  | pg_tables  | tableowner  | array_collapse(mfvsketch_quick_histogram((),5)) | [0:1]={agorajek:104,alex:1}
  pg_catalog  | pg_tables  | tableowner  | array_collapse(mfvsketch_top_histogram((),5))   | [0:1]={agorajek:104,alex:1}
  pg_catalog  | pg_tables  | tablespace  | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a>                               | 1
  pg_catalog  | pg_tables  | tablespace  | array_collapse(mfvsketch_quick_histogram((),5)) | [0:0]={pg_global:28}
  pg_catalog  | pg_tables  | tablespace  | array_collapse(mfvsketch_top_histogram((),5))   | [0:0]={pg_global:28}
  pg_catalog  | pg_tables  | hasindexes  | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a>                               | 2
  pg_catalog  | pg_tables  | hasindexes  | array_collapse(mfvsketch_quick_histogram((),5)) | [0:1]={t:59,f:46}
  pg_catalog  | pg_tables  | hasindexes  | array_collapse(mfvsketch_top_histogram((),5))   | [0:1]={t:59,f:46}
  pg_catalog  | pg_tables  | hasrules    | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a>                               | 1
  pg_catalog  | pg_tables  | hasrules    | array_collapse(mfvsketch_quick_histogram((),5)) | [0:0]={f:105}
  pg_catalog  | pg_tables  | hasrules    | array_collapse(mfvsketch_top_histogram((),5))   | [0:0]={f:105}
  pg_catalog  | pg_tables  | hastriggers | <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin&#39;s distinct count estimation. ">fmsketch_dcount()</a>                               | 2
  pg_catalog  | pg_tables  | hastriggers | array_collapse(mfvsketch_quick_histogram((),5)) | [0:1]={f:102,t:3}
  pg_catalog  | pg_tables  | hastriggers | array_collapse(mfvsketch_top_histogram((),5))   | [0:1]={f:102,t:3}
 (22 rows)
 </pre></li>
 </ol>
 <p><a class="anchor" id="notes"></a></p><dl class="section user"><dt>Implementation Notes</dt><dd></dd></dl>
 <p>Because some of the aggregate functions used in profile return multi-dimensional arrays, which are not easily handled in pl/python, we are using <code>array_collapse</code> function to collaps the n-dim arrays to 1-dim arrays. All values of 2 and upper dimensions are separated with ':' character.</p>
 <p>Note that this module is not available in HAWQ. Instead, we suggest the Summary module in Descriptive Statistics as a replacement of this module.</p>
 <p><a class="anchor" id="related"></a></p><dl class="section user"><dt>Related Topics</dt><dd>File <a class="el" href="profile_8sql__in.html" title="SQL function for single-pass table profiles. ">profile.sql_in</a> documenting SQL functions. </dd></dl>
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	<div class="header">
	<div class="headertitle">
	<div class="title">Profile<div class="ingroups"><a class="el" href="group__grp__deprecated.html">Deprecated Modules</a></div></div> </div>
	</div><!--header-->
	<div class="contents">
	<dl class="section warning"><dt>Warning</dt><dd><em> This is an old implementation of summary function. Replacement of this function is available as the Summary module <a class="el" href="group__grp__summary.html">Summary</a></em></dd></dl>
	<div class="toc"><b>Contents</b> </p><ul>
	<li>
	<a href="#syntax">Function Syntax</a> </li>
	<li>
	<a href="#examples">Examples</a> </li>
	<li>
	<a href="#notes">Implementation Notes</a> </li>
	<li>
	<a href="#related">Related Topics</a> </li>
	</ul>
	</div><p>This module computes a "profile" of a table or view: a predefined set of aggregates to be run on each column of a table.</p>
	<p>The following aggregates are called on every integer column:</p><ul>
	<li>min(), max(), <a class="el" href="linalg_8sql__in.html#a1aa37f73fb1cd8d7d106aa518dd8c0b4" title="Compute the average of vectors. ">avg()</a></li>
	<li>madlib.cmsketch_median()</li>
	<li>madlib.cmsketch_depth_histogram()</li>
	<li>madlib.cmsketch_width_histogram()</li>
	</ul>
	<p>The following aggregates are called on non-integer columns:</p><ul>
	<li>madlib.fmsketch_dcount()</li>
	<li>madlib.mfvsketch_quick_histogram()</li>
	<li>madlib.mfvsketch_top_histogram()</li>
	</ul>
	<p>Because the input schema of the table or view is unknown, SQL is synthesized to suit the input. This is done either via the <code>profile</code> or <code>profile_full</code> user defined function.</p>
	<p><a class="anchor" id="syntax"></a></p><dl class="section user"><dt>Function Syntax</dt><dd></dd></dl>
	<p>Generate basic profile information (subset of predefined aggregate functions) for all columns of the input table. </p><pre class="syntax">
	profile( input_table )
	</pre><p>Generate full profile information (all predefined aggregate functions) for all columns of the input table. </p><pre class="syntax">
	profile_full( input_table,
	buckets
	)
	</pre><p><a class="anchor" id="examples"></a></p><dl class="section user"><dt>Examples</dt><dd></dd></dl>
	<ol type="1">
	<li>Generate basic profile information. <pre class="example">
	SELECT * FROM profile( 'pg_catalog.pg_tables');
	</pre> Result: <pre class="result">
	schema_name \| table_name \| column_name \| function \| value
	------------+------------+-------------+-------------------+-------
	pg_catalog \| pg_tables \| * \| COUNT() \| 105
	pg_catalog \| pg_tables \| schemaname \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 6
	pg_catalog \| pg_tables \| tablename \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 104
	pg_catalog \| pg_tables \| tableowner \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 2
	pg_catalog \| pg_tables \| tablespace \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 1
	pg_catalog \| pg_tables \| hasindexes \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 2
	pg_catalog \| pg_tables \| hasrules \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 1
	pg_catalog \| pg_tables \| hastriggers \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 2
	(8 rows)
	</pre></li>
	<li>Generate full profile information. <pre class="example">
	SELECT * FROM profile_full( 'pg_catalog.pg_tables',
	5
	);
	</pre> Result: <pre class="result">
	schema_name \| table_name \| column_name \| function \| value
	------------+------------+-------------+-------------------------------------------------+----------------------------------------------------------------------------------------------------
	pg_catalog \| pg_tables \| * \| COUNT() \| 105
	pg_catalog \| pg_tables \| schemaname \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 6
	pg_catalog \| pg_tables \| schemaname \| array_collapse(mfvsketch_quick_histogram((),5)) \| [0:4]={pg_catalog:68,public:19,information_schema:7,gp_toolkit:5,maddy:5}
	pg_catalog \| pg_tables \| schemaname \| array_collapse(mfvsketch_top_histogram((),5)) \| [0:4]={pg_catalog:68,public:19,information_schema:7,gp_toolkit:5,maddy:5}
	pg_catalog \| pg_tables \| tablename \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 104
	pg_catalog \| pg_tables \| tablename \| array_collapse(mfvsketch_quick_histogram((),5)) \| [0:4]={migrationhistory:2,pg_statistic:1,sql_features:1,sql_implementation_info:1,sql_languages:1}
	pg_catalog \| pg_tables \| tablename \| array_collapse(mfvsketch_top_histogram((),5)) \| [0:4]={migrationhistory:2,pg_statistic:1,sql_features:1,sql_implementation_info:1,sql_languages:1}
	pg_catalog \| pg_tables \| tableowner \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 2
	pg_catalog \| pg_tables \| tableowner \| array_collapse(mfvsketch_quick_histogram((),5)) \| [0:1]={agorajek:104,alex:1}
	pg_catalog \| pg_tables \| tableowner \| array_collapse(mfvsketch_top_histogram((),5)) \| [0:1]={agorajek:104,alex:1}
	pg_catalog \| pg_tables \| tablespace \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 1
	pg_catalog \| pg_tables \| tablespace \| array_collapse(mfvsketch_quick_histogram((),5)) \| [0:0]={pg_global:28}
	pg_catalog \| pg_tables \| tablespace \| array_collapse(mfvsketch_top_histogram((),5)) \| [0:0]={pg_global:28}
	pg_catalog \| pg_tables \| hasindexes \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 2
	pg_catalog \| pg_tables \| hasindexes \| array_collapse(mfvsketch_quick_histogram((),5)) \| [0:1]={t:59,f:46}
	pg_catalog \| pg_tables \| hasindexes \| array_collapse(mfvsketch_top_histogram((),5)) \| [0:1]={t:59,f:46}
	pg_catalog \| pg_tables \| hasrules \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 1
	pg_catalog \| pg_tables \| hasrules \| array_collapse(mfvsketch_quick_histogram((),5)) \| [0:0]={f:105}
	pg_catalog \| pg_tables \| hasrules \| array_collapse(mfvsketch_top_histogram((),5)) \| [0:0]={f:105}
	pg_catalog \| pg_tables \| hastriggers \| <a class="el" href="sketch_8sql__in.html#ae27d5aaa5e4b426bcfe55e05a89c8e0b" title="Flajolet-Martin's distinct count estimation. ">fmsketch_dcount()</a> \| 2
	pg_catalog \| pg_tables \| hastriggers \| array_collapse(mfvsketch_quick_histogram((),5)) \| [0:1]={f:102,t:3}
	pg_catalog \| pg_tables \| hastriggers \| array_collapse(mfvsketch_top_histogram((),5)) \| [0:1]={f:102,t:3}
	(22 rows)
	</pre></li>
	</ol>
	<p><a class="anchor" id="notes"></a></p><dl class="section user"><dt>Implementation Notes</dt><dd></dd></dl>
	<p>Because some of the aggregate functions used in profile return multi-dimensional arrays, which are not easily handled in pl/python, we are using <code>array_collapse</code> function to collaps the n-dim arrays to 1-dim arrays. All values of 2 and upper dimensions are separated with ':' character.</p>
	<p>Note that this module is not available in HAWQ. Instead, we suggest the Summary module in Descriptive Statistics as a replacement of this module.</p>
	<p><a class="anchor" id="related"></a></p><dl class="section user"><dt>Related Topics</dt><dd>File <a class="el" href="profile_8sql__in.html" title="SQL function for single-pass table profiles. ">profile.sql_in</a> documenting SQL functions. </dd></dl>
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