1 <?xml version="1.0" encoding="UTF-8"?>
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2 <chapter xml:id="intro_to_sql" xmlns="http://docbook.org/ns/docbook" version="5.0" xml:lang="EN"
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3 xmlns:xi="http://www.w3.org/2001/XInclude" xmlns:xlink="http://www.w3.org/1999/xlink">
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5 <title>Introduction to SQL for Evergreen Administrators</title>
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7 <abstract id="itnroSQL_abstract">
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8 <simpara>This chapter was taken from Dan Scott's <emphasis>Introduction to SQL for Evergreen Administrators</emphasis>, February 2010.</simpara>
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10 <section id="intro_to_databases">
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11 <title>Introduction to SQL Databases</title>
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13 <title>Introduction</title>
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14 <simpara>Over time, the SQL database has become the standard method of storing,
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15 retrieving, and processing raw data for applications. Ranging from embedded
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16 databases such as SQLite and Apache Derby, to enterprise databases such as
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17 Oracle and IBM DB2, any SQL database offers basic advantages to application
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18 developers such as standard interfaces (Structured Query Language (SQL), Java
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19 Database Connectivity (JDBC), Open Database Connectivity (ODBC), Perl Database
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20 Independent Interface (DBI)), a standard conceptual model of data (tables,
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21 fields, relationships, constraints, etc), performance in storing and retrieving
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22 data, concurrent access, etc.</simpara>
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23 <simpara>Evergreen is built on PostgreSQL, an open source SQL database that began as
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24 <literal>POSTGRES</literal> at the University of California at Berkeley in 1986 as a research
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25 project led by Professor Michael Stonebraker. A SQL interface was added to a
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26 fork of the original POSTGRES Berkelely code in 1994, and in 1996 the project
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27 was renamed PostgreSQL.</simpara>
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29 <simplesect id="_tables">
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30 <title>Tables</title>
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31 <simpara>The table is the cornerstone of a SQL database. Conceptually, a database table
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32 is similar to a single sheet in a spreadsheet: every table has one or more
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33 columns, with each row in the table containing values for each column. Each
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34 column in a table defines an attribute corresponding to a particular data type.</simpara>
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35 <simpara>We’ll insert a row into a table, then display the resulting contents. Don’t
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36 worry if the INSERT statement is completely unfamiliar, we’ll talk more about
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37 the syntax of the insert statement later.</simpara>
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38 <formalpara><title><literal>actor.usr_note</literal> database table</title><para>
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39 <programlisting language="sql" linenumbering="unnumbered">
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40 evergreen=# INSERT INTO actor.usr_note (usr, creator, pub, title, value)
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41 VALUES (1, 1, TRUE, 'Who is this guy?', 'He''s the administrator!');
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43 evergreen=# select id, usr, creator, pub, title, value from actor.usr_note;
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44 id | usr | creator | pub | title | value
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45 ----+-----+---------+-----+------------------+-------------------------
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46 1 | 1 | 1 | t | Who is this guy? | He's the administrator!
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49 </para></formalpara>
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50 <simpara>PostgreSQL supports table inheritance, which lets you define tables that
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51 inherit the column definitions of a given parent table. A search of the data in
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52 the parent table includes the data in the child tables. Evergreen uses table
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53 inheritance: for example, the <literal>action.circulation</literal> table is a child of the
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54 <literal>money.billable_xact</literal> table, and the <literal>money.*_payment</literal> tables all inherit from
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55 the <literal>money.payment</literal> parent table.</simpara>
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57 <simplesect id="_schemas">
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58 <title>Schemas</title>
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59 <simpara>PostgreSQL, like most SQL databases, supports the use of schema names to group
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60 collections of tables and other database objects together. You might think of
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61 schemas as namespaces if you’re a programmer; or you might think of the schema
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62 / table / column relationship like the area code / exchange / local number
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63 structure of a telephone number.</simpara>
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66 rowsep="1" colsep="1"
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68 <title>Examples: database object names</title>
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69 <?dbhtml table-width="80%"?>
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70 <?dbfo table-width="80%"?>
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72 <colspec colname="col_1" colwidth="1.0*"/>
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73 <colspec colname="col_2" colwidth="1.0*"/>
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74 <colspec colname="col_3" colwidth="1.0*"/>
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75 <colspec colname="col_4" colwidth="1.0*"/>
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78 <entry align="left" valign="top">Full name </entry>
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79 <entry align="left" valign="top">Schema name </entry>
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80 <entry align="left" valign="top">Table name </entry>
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81 <entry align="left" valign="top">Field name</entry>
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86 <entry align="left" valign="top"><simpara>actor.usr_note.title</simpara></entry>
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87 <entry align="left" valign="top"><simpara>actor</simpara></entry>
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88 <entry align="left" valign="top"><simpara>usr_note</simpara></entry>
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89 <entry align="left" valign="top"><simpara>title</simpara></entry>
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92 <entry align="left" valign="top"><simpara>biblio.record_entry.marc</simpara></entry>
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93 <entry align="left" valign="top"><simpara>biblio</simpara></entry>
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94 <entry align="left" valign="top"><simpara>record_entry</simpara></entry>
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95 <entry align="left" valign="top"><simpara>marc</simpara></entry>
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100 <simpara>The default schema name in PostgreSQL is <literal>public</literal>, so if you do not specify a
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101 schema name when creating or accessing a database object, PostgreSQL will use
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102 the <literal>public</literal> schema. As a result, you might not find the object that you’re
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103 looking for if you don’t use the appropriate schema.</simpara>
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104 <formalpara><title>Example: Creating a table without a specific schema</title><para>
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105 <programlisting language="sql" linenumbering="unnumbered">
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106 evergreen=# CREATE TABLE foobar (foo TEXT, bar TEXT);
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108 evergreen=# \d foobar
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109 Table "public.foobar"
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110 Column | Type | Modifiers
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111 --------+------+-----------
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115 </para></formalpara>
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116 <formalpara><title>Example: Trying to access a unqualified table outside of the public schema</title><para>
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117 <programlisting language="sql" linenumbering="unnumbered">evergreen=# SELECT * FROM usr_note;
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118 ERROR: relation "usr_note" does not exist
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119 LINE 1: SELECT * FROM usr_note;
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121 </para></formalpara>
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122 <simpara>Evergreen uses schemas to organize all of its tables with mostly intuitive,
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123 if short, schema names. Here’s the current (as of 2010-01-03) list of schemas
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124 used by Evergreen:</simpara>
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127 rowsep="1" colsep="1"
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129 <title>Evergreen schema names</title>
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130 <?dbhtml table-width="80%"?>
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131 <?dbfo table-width="80%"?>
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133 <colspec colname="col_1" colwidth="1.0*"/>
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134 <colspec colname="col_2" colwidth="1.0*"/>
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137 <entry align="left" valign="top">Schema name </entry>
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138 <entry align="left" valign="top">Description</entry>
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143 <entry align="left" valign="top"><simpara><literal>acq</literal></simpara></entry>
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144 <entry align="left" valign="top"><simpara>Acquisitions</simpara></entry>
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147 <entry align="left" valign="top"><simpara><literal>action</literal></simpara></entry>
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148 <entry align="left" valign="top"><simpara>Circulation actions</simpara></entry>
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151 <entry align="left" valign="top"><simpara><literal>action_trigger</literal></simpara></entry>
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152 <entry align="left" valign="top"><simpara>Event mechanisms</simpara></entry>
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155 <entry align="left" valign="top"><simpara><literal>actor</literal></simpara></entry>
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156 <entry align="left" valign="top"><simpara>Evergreen users and organization units</simpara></entry>
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159 <entry align="left" valign="top"><simpara><literal>asset</literal></simpara></entry>
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160 <entry align="left" valign="top"><simpara>Call numbers and copies</simpara></entry>
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163 <entry align="left" valign="top"><simpara><literal>auditor</literal></simpara></entry>
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164 <entry align="left" valign="top"><simpara>Track history of changes to selected tables</simpara></entry>
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167 <entry align="left" valign="top"><simpara><literal>authority</literal></simpara></entry>
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168 <entry align="left" valign="top"><simpara>Authority records</simpara></entry>
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171 <entry align="left" valign="top"><simpara><literal>biblio</literal></simpara></entry>
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172 <entry align="left" valign="top"><simpara>Bibliographic records</simpara></entry>
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175 <entry align="left" valign="top"><simpara><literal>booking</literal></simpara></entry>
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176 <entry align="left" valign="top"><simpara>Resource bookings</simpara></entry>
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179 <entry align="left" valign="top"><simpara><literal>config</literal></simpara></entry>
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180 <entry align="left" valign="top"><simpara>Evergreen configurable options</simpara></entry>
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183 <entry align="left" valign="top"><simpara><literal>container</literal></simpara></entry>
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184 <entry align="left" valign="top"><simpara>Buckets for records, call numbers, copies, and users</simpara></entry>
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187 <entry align="left" valign="top"><simpara><literal>extend_reporter</literal></simpara></entry>
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188 <entry align="left" valign="top"><simpara>Extra views for report definitions</simpara></entry>
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191 <entry align="left" valign="top"><simpara><literal>metabib</literal></simpara></entry>
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192 <entry align="left" valign="top"><simpara>Metadata about bibliographic records</simpara></entry>
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195 <entry align="left" valign="top"><simpara><literal>money</literal></simpara></entry>
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196 <entry align="left" valign="top"><simpara>Fines and bills</simpara></entry>
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199 <entry align="left" valign="top"><simpara><literal>offline</literal></simpara></entry>
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200 <entry align="left" valign="top"><simpara>Offline transactions</simpara></entry>
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203 <entry align="left" valign="top"><simpara><literal>permission</literal></simpara></entry>
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204 <entry align="left" valign="top"><simpara>User permissions</simpara></entry>
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207 <entry align="left" valign="top"><simpara><literal>query</literal></simpara></entry>
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208 <entry align="left" valign="top"><simpara>Stored SQL statements</simpara></entry>
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211 <entry align="left" valign="top"><simpara><literal>reporter</literal></simpara></entry>
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212 <entry align="left" valign="top"><simpara>Report definitions</simpara></entry>
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215 <entry align="left" valign="top"><simpara><literal>search</literal></simpara></entry>
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216 <entry align="left" valign="top"><simpara>Search functions</simpara></entry>
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219 <entry align="left" valign="top"><simpara><literal>serial</literal></simpara></entry>
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220 <entry align="left" valign="top"><simpara>Serial MFHD records</simpara></entry>
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223 <entry align="left" valign="top"><simpara><literal>stats</literal></simpara></entry>
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224 <entry align="left" valign="top"><simpara>Convenient views of circulation and asset statistics</simpara></entry>
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227 <entry align="left" valign="top"><simpara><literal>vandelay</literal></simpara></entry>
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228 <entry align="left" valign="top"><simpara>MARC batch importer and exporter</simpara></entry>
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233 <note><simpara>The term <emphasis>schema</emphasis> has two meanings in the world of SQL databases. We have
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234 discussed the schema as a conceptual grouping of tables and other database
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235 objects within a given namespace; for example, "the <emphasis role="strong">actor</emphasis> schema contains the
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236 tables and functions related to users and organizational units". Another common
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237 usage of <emphasis>schema</emphasis> is to refer to the entire data model for a given database;
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238 for example, "the Evergreen database schema".</simpara></note>
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240 <simplesect id="_columns">
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241 <title>Columns</title>
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242 <simpara>Each column definition consists of:</simpara>
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251 (optionally) a default value to be used whenever a row is inserted that
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252 does not contain a specific value
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257 (optionally) one or more constraints on the values beyond data type
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261 <simpara>Although PostgreSQL supports dozens of data types, Evergreen makes our life
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262 easier by only using a handful.</simpara>
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265 rowsep="1" colsep="1"
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267 <title>PostgreSQL data types used by Evergreen</title>
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268 <?dbhtml table-width="90%"?>
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269 <?dbfo table-width="90%"?>
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271 <colspec colname="col_1" colwidth="1.0*"/>
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272 <colspec colname="col_2" colwidth="1.0*"/>
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273 <colspec colname="col_3" colwidth="2.5*"/>
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276 <entry align="left" valign="top">Type name </entry>
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277 <entry align="left" valign="top">Description </entry>
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278 <entry align="left" valign="top">Limits</entry>
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283 <entry align="left" valign="top"><simpara><literal>INTEGER</literal></simpara></entry>
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284 <entry align="left" valign="top"><simpara>Medium integer</simpara></entry>
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285 <entry align="left" valign="top"><simpara>-2147483648 to +2147483647</simpara></entry>
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288 <entry align="left" valign="top"><simpara><literal>BIGINT</literal></simpara></entry>
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289 <entry align="left" valign="top"><simpara>Large integer</simpara></entry>
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290 <entry align="left" valign="top"><simpara>-9223372036854775808 to 9223372036854775807</simpara></entry>
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293 <entry align="left" valign="top"><simpara><literal>SERIAL</literal></simpara></entry>
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294 <entry align="left" valign="top"><simpara>Sequential integer</simpara></entry>
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295 <entry align="left" valign="top"><simpara>1 to 2147483647</simpara></entry>
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298 <entry align="left" valign="top"><simpara><literal>BIGSERIAL</literal></simpara></entry>
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299 <entry align="left" valign="top"><simpara>Large sequential integer</simpara></entry>
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300 <entry align="left" valign="top"><simpara>1 to 9223372036854775807</simpara></entry>
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303 <entry align="left" valign="top"><simpara><literal>TEXT</literal></simpara></entry>
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304 <entry align="left" valign="top"><simpara>Variable length character data</simpara></entry>
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305 <entry align="left" valign="top"><simpara>Unlimited length</simpara></entry>
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308 <entry align="left" valign="top"><simpara><literal>BOOL</literal></simpara></entry>
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309 <entry align="left" valign="top"><simpara>Boolean</simpara></entry>
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310 <entry align="left" valign="top"><simpara>TRUE or FALSE</simpara></entry>
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313 <entry align="left" valign="top"><simpara><literal>TIMESTAMP WITH TIME ZONE</literal></simpara></entry>
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314 <entry align="left" valign="top"><simpara>Timestamp</simpara></entry>
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315 <entry align="left" valign="top"><simpara>4713 BC to 294276 AD</simpara></entry>
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318 <entry align="left" valign="top"><simpara><literal>TIME</literal></simpara></entry>
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319 <entry align="left" valign="top"><simpara>Time</simpara></entry>
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320 <entry align="left" valign="top"><simpara>Expressed in HH:MM:SS</simpara></entry>
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323 <entry align="left" valign="top"><simpara><literal>NUMERIC</literal>(precision, scale)</simpara></entry>
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324 <entry align="left" valign="top"><simpara>Decimal</simpara></entry>
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325 <entry align="left" valign="top"><simpara>Up to 1000 digits of precision. In Evergreen mostly used for money
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326 values, with a precision of 6 and a scale of 2 (<literal>####.##</literal>).</simpara></entry>
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331 <simpara>Full details about these data types are available from the
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332 <ulink url="http://www.postgresql.org/docs/8.4/static/datatype.html">data types section of
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333 the PostgreSQL manual</ulink>.</simpara>
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335 <simplesect id="_constraints">
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336 <title>Constraints</title>
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337 <simplesect id="_prevent_null_values">
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338 <title>Prevent NULL values</title>
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339 <simpara>A column definition may include the constraint <literal>NOT NULL</literal> to prevent NULL
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340 values. In PostgreSQL, a NULL value is not the equivalent of zero or false or
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341 an empty string; it is an explicit non-value with special properties. We’ll
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342 talk more about how to work with NULL values when we get to queries.</simpara>
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344 <simplesect id="_primary_key">
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345 <title>Primary key</title>
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346 <simpara>Every table can have at most one primary key. A primary key consists of one or
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347 more columns which together uniquely identify each row in a table. If you
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348 attempt to insert a row into a table that would create a duplicate or NULL
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349 primary key entry, the database rejects the row and returns an error.</simpara>
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350 <simpara>Natural primary keys are drawn from the intrinsic properties of the data being
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351 modelled. For example, some potential natural primary keys for a table that
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352 contains people would be:</simpara>
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355 rowsep="1" colsep="1"
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357 <title>Example: Some potential natural primary keys for a table of people</title>
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358 <?dbhtml table-width="90%"?>
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359 <?dbfo table-width="90%"?>
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361 <colspec colname="col_1" colwidth="1.0*"/>
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362 <colspec colname="col_2" colwidth="2.0*"/>
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363 <colspec colname="col_3" colwidth="2.0*"/>
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366 <entry align="left" valign="top">Natural key </entry>
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367 <entry align="left" valign="top">Pros </entry>
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368 <entry align="left" valign="top">Cons</entry>
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373 <entry align="left" valign="top"><simpara>First name, last name, address</simpara></entry>
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374 <entry align="left" valign="top"><simpara>No two people with the same name would ever live at the same address, right?</simpara></entry>
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375 <entry align="left" valign="top"><simpara>Lots of columns force data duplication in referencing tables</simpara></entry>
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378 <entry align="left" valign="top"><simpara>SSN or driver’s license</simpara></entry>
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379 <entry align="left" valign="top"><simpara>These are guaranteed to be unique</simpara></entry>
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380 <entry align="left" valign="top"><simpara>Lots of people don’t have an SSN or a driver’s license</simpara></entry>
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385 <simpara>To avoid problems with natural keys, many applications instead define surrogate
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386 primary keys. A surrogate primary keys is a column with an autoincrementing
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387 integer value added to a table definition that ensures uniqueness.</simpara>
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388 <simpara>Evergreen uses surrogate keys (a column named <literal>id</literal> with a <literal>SERIAL</literal> data type)
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389 for most of its tables.</simpara>
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391 <simplesect id="_foreign_keys">
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392 <title>Foreign keys</title>
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393 <simpara>Every table can contain zero or more foreign keys: one or more columns that
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394 refer to the primary key of another table.</simpara>
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395 <simpara>For example, let’s consider Evergreen’s modelling of the basic relationship
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396 between copies, call numbers, and bibliographic records. Bibliographic records
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397 contained in the <literal>biblio.record_entry</literal> table can have call numbers attached to
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398 them. Call numbers are contained in the <literal>asset.call_number</literal> table, and they can
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399 have copies attached to them. Copies are contained in the <literal>asset.copy</literal> table.</simpara>
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402 rowsep="1" colsep="1"
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404 <title>Example: Evergreen’s copy / call number / bibliographic record relationships</title>
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405 <?dbhtml table-width="100%"?>
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406 <?dbfo table-width="100%"?>
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408 <colspec colname="col_1" colwidth="1.0*"/>
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409 <colspec colname="col_2" colwidth="1.0*"/>
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410 <colspec colname="col_3" colwidth="1.0*"/>
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411 <colspec colname="col_4" colwidth="1.0*"/>
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414 <entry align="left" valign="top">Table </entry>
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415 <entry align="left" valign="top">Primary key </entry>
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416 <entry align="left" valign="top">Column with a foreign key </entry>
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417 <entry align="left" valign="top">Points to</entry>
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422 <entry align="left" valign="top"><simpara>asset.copy</simpara></entry>
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423 <entry align="left" valign="top"><simpara>asset.copy.id</simpara></entry>
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424 <entry align="left" valign="top"><simpara>asset.copy.call_number</simpara></entry>
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425 <entry align="left" valign="top"><simpara>asset.call_number.id</simpara></entry>
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428 <entry align="left" valign="top"><simpara>asset.call_number</simpara></entry>
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429 <entry align="left" valign="top"><simpara>asset.call_number.id</simpara></entry>
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430 <entry align="left" valign="top"><simpara>asset.call_number.record</simpara></entry>
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431 <entry align="left" valign="top"><simpara>biblio.record_entry.id</simpara></entry>
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434 <entry align="left" valign="top"><simpara>biblio.record_entry</simpara></entry>
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435 <entry align="left" valign="top"><simpara>biblio.record_entry.id</simpara></entry>
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436 <entry align="left" valign="top"><simpara></simpara></entry>
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437 <entry align="left" valign="top"><simpara></simpara></entry>
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443 <simplesect id="_check_constraints">
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444 <title>Check constraints</title>
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445 <simpara>PostgreSQL enables you to define rules to ensure that the value to be inserted
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446 or updated meets certain conditions. For example, you can ensure that an
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447 incoming integer value is within a specific range, or that a ZIP code matches a
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448 particular pattern.</simpara>
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451 <simplesect id="_deconstructing_a_table_definition_statement">
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452 <title>Deconstructing a table definition statement</title>
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453 <simpara>The <literal>actor.org_address</literal> table is a simple table in the Evergreen schema that
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454 we can use as a concrete example of many of the properties of databases that
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455 we have discussed so far.</simpara>
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456 <programlisting language="sql" linenumbering="unnumbered">
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457 CREATE TABLE actor.org_address (
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458 id SERIAL PRIMARY KEY, <co id="sqlCO1-1"/>
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459 valid BOOL NOT NULL DEFAULT TRUE, <co id="sqlCO1-2"/>
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460 address_type TEXT NOT NULL DEFAULT 'MAILING', <co id="sqlCO1-3"/>
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461 org_unit INT NOT NULL REFERENCES actor.org_unit (id) <co id="sqlCO1-4"/>
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462 DEFERRABLE INITIALLY DEFERRED,
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463 street1 TEXT NOT NULL,
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464 street2 TEXT, <co id="sqlCO1-5"/>
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465 city TEXT NOT NULL,
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467 state TEXT NOT NULL,
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468 country TEXT NOT NULL,
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469 post_code TEXT NOT NULL
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473 <callout arearefs="sqlCO1-1">
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475 The column named <literal>id</literal> is defined with a special data type of <literal>SERIAL</literal>; if
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476 given no value when a row is inserted into a table, the database automatically
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477 generates the next sequential integer value for the column. <literal>SERIAL</literal> is a
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478 popular data type for a primary key because it is guaranteed to be unique - and
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479 indeed, the constraint for this column identifies it as the <literal>PRIMARY KEY</literal>.
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482 <callout arearefs="sqlCO1-2">
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484 The data type <literal>BOOL</literal> defines a boolean value: <literal>TRUE</literal> or <literal>FALSE</literal> are the only
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485 acceptable values for the column. The constraint <literal>NOT NULL</literal> instructs the
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486 database to prevent the column from ever containing a NULL value. The column
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487 property <literal>DEFAULT TRUE</literal> instructs the database to automatically set the value
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488 of the column to <literal>TRUE</literal> if no value is provided.
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491 <callout arearefs="sqlCO1-3">
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493 The data type <literal>TEXT</literal> defines a text column of practically unlimited length.
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494 As with the previous column, there is a <literal>NOT NULL</literal> constraint, and a default
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495 value of <literal>'MAILING'</literal> will result if no other value is supplied.
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498 <callout arearefs="sqlCO1-4">
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500 The <literal>REFERENCES actor.org_unit (id)</literal> clause indicates that this column has a
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501 foreign key relationship to the <literal>actor.org_unit</literal> table, and that the value of
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502 this column in every row in this table must have a corresponding value in the
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503 <literal>id</literal> column in the referenced table (<literal>actor.org_unit</literal>).
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506 <callout arearefs="sqlCO1-5">
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508 The column named <literal>street2</literal> demonstrates that not all columns have constraints
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509 beyond data type. In this case, the column is allowed to be NULL or to contain a
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510 <literal>TEXT</literal> value.
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515 <simplesect id="_displaying_a_table_definition_using_literal_psql_literal">
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516 <title>Displaying a table definition using <literal>psql</literal></title>
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517 <simpara>The <literal>psql</literal> command-line interface is the preferred method for accessing
\r
518 PostgreSQL databases. It offers features like tab-completion, readline support
\r
519 for recalling previous commands, flexible input and output formats, and
\r
520 is accessible via a standard SSH session.</simpara>
\r
521 <simpara>If you press the <literal>Tab</literal> key once after typing one or more characters of the
\r
522 database object name, <literal>psql</literal> automatically completes the name if there are no
\r
523 other matches. If there are other matches for your current input, nothing
\r
524 happens until you press the <literal>Tab</literal> key a second time, at which point <literal>psql</literal>
\r
525 displays all of the matches for your current input.</simpara>
\r
526 <simpara>To display the definition of a database object such as a table, issue the
\r
527 command <literal>\d _object-name_</literal>. For example, to display the definition of the
\r
528 actor.usr_note table:</simpara>
\r
529 <programlisting language="sh" linenumbering="unnumbered">
\r
530 $ psql evergreen <co id="sqlCO2-1"/>
\r
532 Type "help" for help.
\r
534 evergreen=# \d actor.usr_note <co id="sqlCO2-2"/>
\r
535 Table "actor.usr_note"
\r
536 Column | Type | Modifiers
\r
537 -------------+--------------------------+-------------------------------------------------------------
\r
538 id | bigint | not null default nextval('actor.usr_note_id_seq'::regclass)
\r
539 usr | bigint | not null
\r
540 creator | bigint | not null
\r
541 create_date | timestamp with time zone | default now()
\r
542 pub | boolean | not null default false
\r
543 title | text | not null
\r
544 value | text | not null
\r
546 "usr_note_pkey" PRIMARY KEY, btree (id)
\r
547 "actor_usr_note_creator_idx" btree (creator)
\r
548 "actor_usr_note_usr_idx" btree (usr)
\r
549 Foreign-key constraints:
\r
550 "usr_note_creator_fkey" FOREIGN KEY (creator) REFERENCES actor.usr(id) ON DELETE CASCADE DEFERRABLE INITIALLY DEFERRED
\r
551 "usr_note_usr_fkey" FOREIGN KEY (usr) REFERENCES actor.usr(id) ON DELETE CASCADE DEFERRABLE INITIALLY DEFERRED
\r
553 evergreen=# \q <co id="sqlCO2-3"/>
\r
557 <callout arearefs="sqlCO2-1">
\r
559 This is the most basic connection to a PostgreSQL database. You can use a
\r
560 number of other flags to specify user name, hostname, port, and other options.
\r
563 <callout arearefs="sqlCO2-2">
\r
565 The <literal>\d</literal> command displays the definition of a database object.
\r
568 <callout arearefs="sqlCO2-3">
\r
570 The <literal>\q</literal> command quits the <literal>psql</literal> session and returns you to the shell prompt.
\r
576 <section id="basic_sql_queries">
\r
577 <title>Basic SQL queries</title>
\r
578 <simplesect id="_the_select_statement">
\r
579 <title>The SELECT statement</title>
\r
580 <simpara>The SELECT statement is the basic tool for retrieving information from a
\r
581 database. The syntax for most SELECT statements is:</simpara>
\r
583 <literallayout><literal>SELECT</literal> [<emphasis>columns(s)</emphasis>]
\r
584 <literal>FROM</literal> [<emphasis>table(s)</emphasis>]
\r
585 [<literal>WHERE</literal> <emphasis>condition(s)</emphasis>]
\r
586 [<literal>GROUP BY</literal> <emphasis>columns(s)</emphasis>]
\r
587 [<literal>HAVING</literal> <emphasis>grouping-condition(s)</emphasis>]
\r
588 [<literal>ORDER BY</literal> <emphasis>column(s)</emphasis>]
\r
589 [<literal>LIMIT</literal> <emphasis>maximum-results</emphasis>]
\r
590 [<literal>OFFSET</literal> <emphasis>start-at-result-#</emphasis>]
\r
593 <simpara>For example, to select all of the columns for each row in the
\r
594 <literal>actor.usr_address</literal> table, issue the following query:</simpara>
\r
595 <programlisting language="sql" linenumbering="unnumbered">SELECT *
\r
596 FROM actor.usr_address
\r
599 <simplesect id="_selecting_particular_columns_from_a_table">
\r
600 <title>Selecting particular columns from a table</title>
\r
601 <simpara><literal>SELECT *</literal> returns all columns from all of the tables included in your query.
\r
602 However, quite often you will want to return only a subset of the possible
\r
603 columns. You can retrieve specific columns by listing the names of the columns
\r
604 you want after the <literal>SELECT</literal> keyword. Separate each column name with a comma.</simpara>
\r
605 <simpara>For example, to select just the city, county, and state from the
\r
606 actor.usr_address table, issue the following query:</simpara>
\r
607 <programlisting language="sql" linenumbering="unnumbered">SELECT city, county, state
\r
608 FROM actor.usr_address
\r
611 <simplesect id="_sorting_results_with_the_order_by_clause">
\r
612 <title>Sorting results with the ORDER BY clause</title>
\r
613 <simpara>By default, a SELECT statement returns rows matching your query with no
\r
614 guarantee of any particular order in which they are returned. To force
\r
615 the rows to be returned in a particular order, use the ORDER BY clause
\r
616 to specify one or more columns to determine the sorting priority of the
\r
618 <simpara>For example, to sort the rows returned from your <literal>actor.usr_address</literal> query by
\r
619 city, with county and then zip code as the tie breakers, issue the
\r
620 following query:</simpara>
\r
621 <programlisting language="sql" linenumbering="unnumbered">
\r
622 SELECT city, county, state
\r
623 FROM actor.usr_address
\r
624 ORDER BY city, county, post_code
\r
628 <simplesect id="_filtering_results_with_the_where_clause">
\r
629 <title>Filtering results with the WHERE clause</title>
\r
630 <simpara>Thus far, your results have been returning all of the rows in the table.
\r
631 Normally, however, you would want to restrict the rows that are returned to the
\r
632 subset of rows that match one or more conditions of your search. The <literal>WHERE</literal>
\r
633 clause enables you to specify a set of conditions that filter your query
\r
634 results. Each condition in the <literal>WHERE</literal> clause is an SQL expression that returns
\r
635 a boolean (true or false) value.</simpara>
\r
636 <simpara>For example, to restrict the results returned from your <literal>actor.usr_address</literal>
\r
637 query to only those rows containing a state value of <emphasis>Connecticut</emphasis>, issue the
\r
638 following query:</simpara>
\r
639 <programlisting language="sql" linenumbering="unnumbered">
\r
640 SELECT city, county, state
\r
641 FROM actor.usr_address
\r
642 WHERE state = 'Connecticut'
\r
643 ORDER BY city, county, post_code
\r
646 <simpara>You can include more conditions in the <literal>WHERE</literal> clause with the <literal>OR</literal> and <literal>AND</literal>
\r
647 operators. For example, to further restrict the results returned from your
\r
648 <literal>actor.usr_address</literal> query to only those rows where the state column contains a
\r
649 value of <emphasis>Connecticut</emphasis> and the city column contains a value of <emphasis>Hartford</emphasis>,
\r
650 issue the following query:</simpara>
\r
651 <programlisting language="sql" linenumbering="unnumbered">
\r
652 SELECT city, county, state
\r
653 FROM actor.usr_address
\r
654 WHERE state = 'Connecticut'
\r
655 AND city = 'Hartford'
\r
656 ORDER BY city, county, post_code
\r
659 <note><simpara>To return rows where the state is <emphasis>Connecticut</emphasis> and the city is <emphasis>Hartford</emphasis> or
\r
660 <emphasis>New Haven</emphasis>, you must use parentheses to explicitly group the city value
\r
661 conditions together, or else the database will evaluate the <literal>OR city = 'New
\r
662 Haven'</literal> clause entirely on its own and match all rows where the city column is
\r
663 <emphasis>New Haven</emphasis>, even though the state might not be <emphasis>Connecticut</emphasis>.</simpara></note>
\r
664 <formalpara><title>Trouble with OR</title><para>
\r
665 <programlisting language="sql" linenumbering="unnumbered">
\r
666 SELECT city, county, state
\r
667 FROM actor.usr_address
\r
668 WHERE state = 'Connecticut'
\r
669 AND city = 'Hartford' OR city = 'New Haven'
\r
670 ORDER BY city, county, post_code
\r
673 -- Can return unwanted rows because the OR is not grouped!
\r
675 </para></formalpara>
\r
676 <formalpara><title>Grouped OR’ed conditions</title><para>
\r
677 <programlisting language="sql" linenumbering="unnumbered">
\r
678 SELECT city, county, state
\r
679 FROM actor.usr_address
\r
680 WHERE state = 'Connecticut'
\r
681 AND (city = 'Hartford' OR city = 'New Haven')
\r
682 ORDER BY city, county, post_code
\r
685 -- The parentheses ensure that the OR is applied to the cities, and the
\r
686 -- state in either case must be 'Connecticut'
\r
688 </para></formalpara>
\r
689 <simplesect id="_comparison_operators">
\r
690 <title>Comparison operators</title>
\r
691 <simpara>Here is a partial list of comparison operators that are commonly used in
\r
692 <literal>WHERE</literal> clauses:</simpara>
\r
693 <simplesect id="_comparing_two_scalar_values">
\r
694 <title>Comparing two scalar values</title>
\r
698 <literal>x = y</literal> (equal to)
\r
703 <literal>x != y</literal> (not equal to)
\r
708 <literal>x < y</literal> (less than)
\r
713 <literal>x > y</literal> (greater than)
\r
718 <literal>x LIKE y</literal> (TEXT value x matches a subset of TEXT y, where y is a string that
\r
719 can contain <emphasis>%</emphasis> as a wildcard for 0 or more characters, and <emphasis>_</emphasis> as a wildcard
\r
720 for a single character. For example, <literal>WHERE 'all you can eat fish and chips
\r
721 and a big stick' LIKE '%fish%stick'</literal> would return TRUE)
\r
726 <literal>x ILIKE y</literal> (like LIKE, but the comparison ignores upper-case / lower-case)
\r
731 <literal>x IN y</literal> (x is in the list of values y, where y can be a list or a SELECT
\r
732 statement that returns a list)
\r
739 <simplesect id="_null_values">
\r
740 <title>NULL values</title>
\r
741 <simpara>SQL databases have a special way of representing the value of a column that has
\r
742 no value: <literal>NULL</literal>. A <literal>NULL</literal> value is not equal to zero, and is not an empty
\r
743 string; it is equal to nothing, not even another <literal>NULL</literal>, because it has no value
\r
744 that can be compared.</simpara>
\r
745 <simpara>To return rows from a table where a given column is not <literal>NULL</literal>, use the
\r
746 <literal>IS NOT NULL</literal> comparison operator.</simpara>
\r
747 <formalpara><title>Retrieving rows where a column is not <literal>NULL</literal></title><para>
\r
748 <programlisting language="sql" linenumbering="unnumbered">
\r
749 SELECT id, first_given_name, family_name
\r
751 WHERE second_given_name IS NOT NULL
\r
754 </para></formalpara>
\r
755 <simpara>Similarly, to return rows from a table where a given column is <literal>NULL</literal>, use
\r
756 the <literal>IS NULL</literal> comparison operator.</simpara>
\r
757 <formalpara><title>Retrieving rows where a column is <literal>NULL</literal></title><para>
\r
758 <programlisting language="sql" linenumbering="unnumbered">
\r
759 SELECT id, first_given_name, second_given_name, family_name
\r
761 WHERE second_given_name IS NULL
\r
764 id | first_given_name | second_given_name | family_name
\r
765 ----+------------------+-------------------+----------------
\r
766 1 | Administrator | | System Account
\r
769 </para></formalpara>
\r
770 <simpara>Notice that the <literal>NULL</literal> value in the output is displayed as empty space,
\r
771 indistinguishable from an empty string; this is the default display method in
\r
772 <literal>psql</literal>. You can change the behaviour of <literal>psql</literal> using the <literal>pset</literal> command:</simpara>
\r
773 <formalpara><title>Changing the way <literal>NULL</literal> values are displayed in <literal>psql</literal></title><para>
\r
774 <programlisting language="sql" linenumbering="unnumbered">
\r
775 evergreen=# \pset null '(null)'
\r
776 Null display is '(null)'.
\r
778 SELECT id, first_given_name, second_given_name, family_name
\r
780 WHERE second_given_name IS NULL
\r
783 id | first_given_name | second_given_name | family_name
\r
784 ----+------------------+-------------------+----------------
\r
785 1 | Administrator | (null) | System Account
\r
788 </para></formalpara>
\r
789 <simpara>Database queries within programming languages such as Perl and C have
\r
790 special methods of checking for <literal>NULL</literal> values in returned results.</simpara>
\r
792 <simplesect id="_text_delimiter">
\r
793 <title>Text delimiter: '</title>
\r
794 <simpara>You might have noticed that we have been using the <literal>'</literal> character to delimit
\r
795 TEXT values and values such as dates and times that are TEXT values. Sometimes,
\r
796 however, your TEXT value itself contains a <literal>'</literal> character, such as the word
\r
797 <literal>you’re</literal>. To prevent the database from prematurely ending the TEXT value at the
\r
798 first <literal>'</literal> character and returning a syntax error, use another <literal>'</literal> character to
\r
799 escape the following <literal>'</literal> character.</simpara>
\r
800 <simpara>For example, to change the last name of a user in the <literal>actor.usr</literal> table to
\r
801 <literal>L’estat</literal>, issue the following SQL:</simpara>
\r
802 <formalpara><title>Escaping <literal>'</literal> in TEXT values</title><para>
\r
803 <programlisting language="sql" linenumbering="unnumbered">
\r
805 SET family_name = 'L''estat'
\r
808 FROM permission.grp_tree
\r
809 WHERE name = 'Vampire'
\r
812 </para></formalpara>
\r
813 <simpara>When you retrieve the row from the database, the value is displayed with just
\r
814 a single <literal>'</literal> character:</simpara>
\r
815 <programlisting language="sql" linenumbering="unnumbered">
\r
816 SELECT id, family_name
\r
818 WHERE family_name = 'L''estat'
\r
827 <simplesect id="_grouping_and_eliminating_results_with_the_group_by_and_having_clauses">
\r
828 <title>Grouping and eliminating results with the GROUP BY and HAVING clauses</title>
\r
829 <simpara>The GROUP BY clause returns a unique set of results for the desired columns.
\r
830 This is most often used in conjunction with an aggregate function to present
\r
831 results for a range of values in a single query, rather than requiring you to
\r
832 issue one query per target value.</simpara>
\r
833 <formalpara><title>Returning unique results of a single column with <literal>GROUP BY</literal></title><para>
\r
834 <programlisting language="sql" linenumbering="unnumbered">
\r
836 FROM permission.grp_perm_map
\r
852 </para></formalpara>
\r
853 <simpara>While <literal>GROUP BY</literal> can be useful for a single column, it is more often used
\r
854 to return the distinct results across multiple columns. For example, the
\r
855 following query shows us which groups have permissions at each depth in
\r
856 the library hierarchy:</simpara>
\r
857 <formalpara><title>Returning unique results of multiple columns with <literal>GROUP BY</literal></title><para>
\r
858 <programlisting language="sql" linenumbering="unnumbered">
\r
860 FROM permission.grp_perm_map
\r
861 GROUP BY grp, depth
\r
862 ORDER BY depth, grp;
\r
883 </para></formalpara>
\r
884 <simpara>Extending this further, you can use the <literal>COUNT()</literal> aggregate function to
\r
885 also return the number of times each unique combination of <literal>grp</literal> and <literal>depth</literal>
\r
886 appears in the table. <emphasis>Yes, this is a sneak peek at the use of aggregate
\r
887 functions! Keeners.</emphasis></simpara>
\r
888 <formalpara><title>Counting unique column combinations with <literal>GROUP BY</literal></title><para>
\r
889 <programlisting language="sql" linenumbering="unnumbered">
\r
890 SELECT grp, depth, COUNT(grp)
\r
891 FROM permission.grp_perm_map
\r
892 GROUP BY grp, depth
\r
893 ORDER BY depth, grp;
\r
895 grp | depth | count
\r
896 -----+-------+-------
\r
914 </para></formalpara>
\r
915 <simpara>You can use the <literal>WHERE</literal> clause to restrict the returned results before grouping
\r
916 is applied to the results. The following query restricts the results to those
\r
917 rows that have a depth of 0.</simpara>
\r
918 <formalpara><title>Using the <literal>WHERE</literal> clause with <literal>GROUP BY</literal></title><para>
\r
919 <programlisting language="sql" linenumbering="unnumbered">
\r
920 SELECT grp, COUNT(grp)
\r
921 FROM permission.grp_perm_map
\r
937 </para></formalpara>
\r
938 <simpara>To restrict results after grouping has been applied to the rows, use the
\r
939 <literal>HAVING</literal> clause; this is typically used to restrict results based on
\r
940 a comparison to the value returned by an aggregate function. For example,
\r
941 the following query restricts the returned rows to those that have more than
\r
942 5 occurrences of the same value for <literal>grp</literal> in the table.</simpara>
\r
943 <formalpara><title><literal>GROUP BY</literal> restricted by a <literal>HAVING</literal> clause</title><para>
\r
944 <programlisting language="sql" linenumbering="unnumbered">
\r
945 SELECT grp, COUNT(grp)
\r
946 FROM permission.grp_perm_map
\r
948 HAVING COUNT(grp) > 5
\r
961 </para></formalpara>
\r
963 <simplesect id="_eliminating_duplicate_results_with_the_distinct_keyword">
\r
964 <title>Eliminating duplicate results with the DISTINCT keyword</title>
\r
965 <simpara><literal>GROUP BY</literal> is one way of eliminating duplicate results from the rows returned
\r
966 by your query. The purpose of the <literal>DISTINCT</literal> keyword is to remove duplicate
\r
967 rows from the results of your query. However, it works, and it is easy - so if
\r
968 you just want a quick list of the unique set of values for a column or set of
\r
969 columns, the <literal>DISTINCT</literal> keyword might be appropriate.</simpara>
\r
970 <simpara>On the other hand, if you are getting duplicate rows back when you don’t expect
\r
971 them, then applying the <literal>DISTINCT</literal> keyword might be a sign that you are
\r
972 papering over a real problem.</simpara>
\r
973 <formalpara><title>Returning unique results of multiple columns with <literal>DISTINCT</literal></title><para>
\r
974 <programlisting language="sql" linenumbering="unnumbered">
\r
975 SELECT DISTINCT grp, depth
\r
976 FROM permission.grp_perm_map
\r
977 ORDER BY depth, grp
\r
999 </para></formalpara>
\r
1001 <simplesect id="_paging_through_results_with_the_limit_and_offset_clauses">
\r
1002 <title>Paging through results with the LIMIT and OFFSET clauses</title>
\r
1003 <simpara>The <literal>LIMIT</literal> clause restricts the total number of rows returned from your query
\r
1004 and is useful if you just want to list a subset of a large number of rows. For
\r
1005 example, in the following query we list the five most frequently used
\r
1006 circulation modifiers:</simpara>
\r
1007 <formalpara><title>Using the <literal>LIMIT</literal> clause to restrict results</title><para>
\r
1008 <programlisting language="sql" linenumbering="unnumbered">
\r
1009 SELECT circ_modifier, COUNT(circ_modifier)
\r
1011 GROUP BY circ_modifier
\r
1016 circ_modifier | count
\r
1017 ---------------+--------
\r
1025 </para></formalpara>
\r
1026 <simpara>When you use the <literal>LIMIT</literal> clause to restrict the total number of rows returned
\r
1027 by your query, you can also use the <literal>OFFSET</literal> clause to determine which subset
\r
1028 of the rows will be returned. The use of the <literal>OFFSET</literal> clause assumes that
\r
1029 you’ve used the <literal>ORDER BY</literal> clause to impose order on the results.</simpara>
\r
1030 <simpara>In the following example, we use the <literal>OFFSET</literal> clause to get results 6 through
\r
1031 10 from the same query that we prevously executed.</simpara>
\r
1032 <formalpara><title>Using the <literal>OFFSET</literal> clause to return a specific subset of rows</title><para>
\r
1033 <programlisting language="sql" linenumbering="unnumbered">
\r
1034 SELECT circ_modifier, COUNT(circ_modifier)
\r
1036 GROUP BY circ_modifier
\r
1042 circ_modifier | count
\r
1043 ---------------+--------
\r
1044 LAW SERIAL | 102758
\r
1051 </para></formalpara>
\r
1054 <section id="advanced_sql_queries">
\r
1055 <title>Advanced SQL queries</title>
\r
1056 <simplesect id="_transforming_column_values_with_functions">
\r
1057 <title>Transforming column values with functions</title>
\r
1058 <simpara>PostgreSQL includes many built-in functions for manipulating column data.
\r
1059 You can also create your own functions (and Evergreen does make use of
\r
1060 many custom functions). There are two types of functions used in
\r
1061 databases: scalar functions and aggregate functions.</simpara>
\r
1062 <simplesect id="_scalar_functions">
\r
1063 <title>Scalar functions</title>
\r
1064 <simpara>Scalar functions transform each value of the target column. If your query
\r
1065 would return 50 values for a column in a given query, and you modify your
\r
1066 query to apply a scalar function to the values returned for that column,
\r
1067 it will still return 50 values. For example, the UPPER() function,
\r
1068 used to convert text values to upper-case, modifies the results in the
\r
1069 following set of queries:</simpara>
\r
1070 <formalpara><title>Using the UPPER() scalar function to convert text values to upper-case</title><para>
\r
1071 <programlisting language="sql" linenumbering="unnumbered">
\r
1072 -- First, without the UPPER() function for comparison
\r
1073 SELECT shortname, name
\r
1074 FROM actor.org_unit
\r
1079 -----------+-----------------------
\r
1080 CONS | Example Consortium
\r
1081 SYS1 | Example System 1
\r
1082 SYS2 | Example System 2
\r
1085 -- Now apply the UPPER() function to the name column
\r
1086 SELECT shortname, UPPER(name)
\r
1087 FROM actor.org_unit
\r
1092 -----------+--------------------
\r
1093 CONS | EXAMPLE CONSORTIUM
\r
1094 SYS1 | EXAMPLE SYSTEM 1
\r
1095 SYS2 | EXAMPLE SYSTEM 2
\r
1098 </para></formalpara>
\r
1099 <simpara>There are so many scalar functions in PostgreSQL that we cannot cover them
\r
1100 all here, but we can list some of the most commonly used functions:</simpara>
\r
1104 || - concatenates two text values together
\r
1109 COALESCE() - returns the first non-NULL value from the list of arguments
\r
1114 LOWER() - returns a text value converted to lower-case
\r
1119 REPLACE() - returns a text value after replacing all occurrences of a given text value with a different text value
\r
1124 REGEXP_REPLACE() - returns a text value after being transformed by a regular expression
\r
1129 UPPER() - returns a text value converted to upper-case
\r
1133 <simpara>For a complete list of scalar functions, see
\r
1134 <ulink url="http://www.postgresql.org/docs/8.3/interactive/functions.html">the PostgreSQL function documentation</ulink>.</simpara>
\r
1136 <simplesect id="_aggregate_functions">
\r
1137 <title>Aggregate functions</title>
\r
1138 <simpara>Aggregate functions return a single value computed from the the complete set of
\r
1139 values returned for the specified column.</simpara>
\r
1169 <simplesect id="_sub_selects">
\r
1170 <title>Sub-selects</title>
\r
1171 <simpara>A sub-select is the technique of using the results of one query to feed
\r
1172 into another query. You can, for example, return a set of values from
\r
1173 one column in a SELECT statement to be used to satisfy the IN() condition
\r
1174 of another SELECT statement; or you could return the MAX() value of a
\r
1175 column in a SELECT statement to match the = condition of another SELECT
\r
1176 statement.</simpara>
\r
1177 <simpara>For example, in the following query we use a sub-select to restrict the copies
\r
1178 returned by the main SELECT statement to only those locations that have an
\r
1179 <literal>opac_visible</literal> value of <literal>TRUE</literal>:</simpara>
\r
1180 <formalpara><title>Sub-select example</title><para>
\r
1181 <programlisting language="sql" linenumbering="unnumbered">
\r
1182 SELECT call_number
\r
1184 WHERE deleted IS FALSE
\r
1187 FROM asset.copy_location
\r
1188 WHERE opac_visible IS TRUE
\r
1192 </para></formalpara>
\r
1193 <simpara>Sub-selects can be an approachable way to breaking down a problem that
\r
1194 requires matching values between different tables, and often result in
\r
1195 a clearly expressed solution to a problem. However, if you start writing
\r
1196 sub-selects within sub-selects, you should consider tackling the problem
\r
1197 with joins instead.</simpara>
\r
1199 <simplesect id="_joins">
\r
1200 <title>Joins</title>
\r
1201 <simpara>Joins enable you to access the values from multiple tables in your query
\r
1202 results and comparison operators. For example, joins are what enable you to
\r
1203 relate a bibliographic record to a barcoded copy via the <literal>biblio.record_entry</literal>,
\r
1204 <literal>asset.call_number</literal>, and <literal>asset.copy</literal> tables. In this section, we discuss the
\r
1205 most common kind of join—the inner join—as well as the less common outer join
\r
1206 and some set operations which can compare and contrast the values returned by
\r
1207 separate queries.</simpara>
\r
1208 <simpara>When we talk about joins, we are going to talk about the left-hand table and
\r
1209 the right-hand table that participate in the join. Every join brings together
\r
1210 just two tables - but you can use an unlimited (for our purposes) number
\r
1211 of joins in a single SQL statement. Each time you use a join, you effectively
\r
1212 create a new table, so when you add a second join clause to a statement,
\r
1213 table 1 and table 2 (which were the left-hand table and the right-hand table
\r
1214 for the first join) now act as a merged left-hand table and the new table
\r
1215 in the second join clause is the right-hand table.</simpara>
\r
1216 <simpara>Clear as mud? Okay, let’s look at some examples.</simpara>
\r
1217 <simplesect id="_inner_joins">
\r
1218 <title>Inner joins</title>
\r
1219 <simpara>An inner join returns all of the columns from the left-hand table in the join
\r
1220 with all of the columns from the right-hand table in the joins that match a
\r
1221 condition in the ON clause. Typically, you use the <literal>=</literal> operator to match the
\r
1222 foreign key of the left-hand table with the primary key of the right-hand
\r
1223 table to follow the natural relationship between the tables.</simpara>
\r
1224 <simpara>In the following example, we return all of columns from the <literal>actor.usr</literal> and
\r
1225 <literal>actor.org_unit</literal> tables, joined on the relationship between the user’s home
\r
1226 library and the library’s ID. Notice in the results that some columns, like
\r
1227 <literal>id</literal> and <literal>mailing_address</literal>, appear twice; this is because both the <literal>actor.usr</literal>
\r
1228 and <literal>actor.org_unit</literal> tables include columns with these names. This is also why
\r
1229 we have to fully qualify the column names in our queries with the schema and
\r
1230 table names.</simpara>
\r
1231 <formalpara><title>A simple inner join</title><para>
\r
1232 <programlisting language="sql" linenumbering="unnumbered">
\r
1235 INNER JOIN actor.org_unit ON actor.usr.home_ou = actor.org_unit.id
\r
1236 WHERE actor.org_unit.shortname = 'CONS'
\r
1239 -[ RECORD 1 ]------------------+---------------------------------
\r
1250 claims_never_checked_out_count | 0
\r
1256 mailing_address | 1
\r
1257 billing_address | 1
\r
1259 name | Example Consortium
\r
1263 fiscal_calendar | 1
\r
1265 </para></formalpara>
\r
1266 <simpara>Of course, you do not have to return every column from the joined tables;
\r
1267 you can (and should) continue to specify only the columns that you want to
\r
1268 return. In the following example, we count the number of borrowers for
\r
1269 every user profile in a given library by joining the <literal>permission.grp_tree</literal>
\r
1270 table where profiles are defined against the <literal>actor.usr</literal> table, and then
\r
1271 joining the <literal>actor.org_unit</literal> table to give us access to the user’s home
\r
1272 library:</simpara>
\r
1273 <formalpara><title>Borrower Count by Profile (Adult, Child, etc)/Library</title><para>
\r
1274 <programlisting language="sql" linenumbering="unnumbered">
\r
1275 SELECT permission.grp_tree.name, actor.org_unit.name, COUNT(permission.grp_tree.name)
\r
1277 INNER JOIN permission.grp_tree
\r
1278 ON actor.usr.profile = permission.grp_tree.id
\r
1279 INNER JOIN actor.org_unit
\r
1280 ON actor.org_unit.id = actor.usr.home_ou
\r
1281 WHERE actor.usr.deleted IS FALSE
\r
1282 GROUP BY permission.grp_tree.name, actor.org_unit.name
\r
1283 ORDER BY actor.org_unit.name, permission.grp_tree.name
\r
1286 name | name | count
\r
1287 -------+--------------------+-------
\r
1288 Users | Example Consortium | 1
\r
1291 </para></formalpara>
\r
1293 <simplesect id="_aliases">
\r
1294 <title>Aliases</title>
\r
1295 <simpara>So far we have been fully-qualifying all of our table names and column names to
\r
1296 prevent any confusion. This quickly gets tiring with lengthy qualified
\r
1297 table names like <literal>permission.grp_tree</literal>, so the SQL syntax enables us to assign
\r
1298 aliases to table names and column names. When you define an alias for a table
\r
1299 name, you can access its column throughout the rest of the statement by simply
\r
1300 appending the column name to the alias with a period; for example, if you assign
\r
1301 the alias <literal>au</literal> to the <literal>actor.usr</literal> table, you can access the <literal>actor.usr.id</literal>
\r
1302 column through the alias as <literal>au.id</literal>.</simpara>
\r
1303 <simpara>The formal syntax for declaring an alias for a column is to follow the column
\r
1304 name in the result columns clause with <literal>AS</literal> <emphasis>alias</emphasis>. To declare an alias for a table name,
\r
1305 follow the table name in the FROM clause (including any JOIN statements) with
\r
1306 <literal>AS</literal> <emphasis>alias</emphasis>. However, the <literal>AS</literal> keyword is optional for tables (and columns as
\r
1307 of PostgreSQL 8.4), and in practice most SQL statements leave it out. For
\r
1308 example, we can write the previous INNER JOIN statement example using aliases
\r
1309 instead of fully-qualified identifiers:</simpara>
\r
1310 <formalpara><title>Borrower Count by Profile (using aliases)</title><para>
\r
1311 <programlisting language="sql" linenumbering="unnumbered">
\r
1312 SELECT pgt.name AS "Profile", aou.name AS "Library", COUNT(pgt.name) AS "Count"
\r
1314 INNER JOIN permission.grp_tree pgt
\r
1315 ON au.profile = pgt.id
\r
1316 INNER JOIN actor.org_unit aou
\r
1317 ON aou.id = au.home_ou
\r
1318 WHERE au.deleted IS FALSE
\r
1319 GROUP BY pgt.name, aou.name
\r
1320 ORDER BY aou.name, pgt.name
\r
1323 Profile | Library | Count
\r
1324 ---------+--------------------+-------
\r
1325 Users | Example Consortium | 1
\r
1328 </para></formalpara>
\r
1329 <simpara>A nice side effect of declaring an alias for your columns is that the alias
\r
1330 is used as the column header in the results table. The previous version of
\r
1331 the query, which didn’t use aliased column names, had two columns named
\r
1332 <literal>name</literal>; this version of the query with aliases results in a clearer
\r
1333 categorization.</simpara>
\r
1335 <simplesect id="_outer_joins">
\r
1336 <title>Outer joins</title>
\r
1337 <simpara>An outer join returns all of the rows from one or both of the tables
\r
1338 participating in the join.</simpara>
\r
1342 For a LEFT OUTER JOIN, the join returns all of the rows from the left-hand
\r
1343 table and the rows matching the join condition from the right-hand table, with
\r
1344 NULL values for the rows with no match in the right-hand table.
\r
1349 A RIGHT OUTER JOIN behaves in the same way as a LEFT OUTER JOIN, with the
\r
1350 exception that all rows are returned from the right-hand table participating in
\r
1356 For a FULL OUTER JOIN, the join returns all the rows from both the left-hand
\r
1357 and right-hand tables, with NULL values for the rows with no match in either
\r
1358 the left-hand or right-hand table.
\r
1362 <formalpara><title>Base tables for the OUTER JOIN examples</title><para>
\r
1363 <programlisting language="sql" linenumbering="unnumbered">
\r
1364 SELECT * FROM aaa;
\r
1375 SELECT * FROM bbb;
\r
1378 ----+-------+----------
\r
1381 5 | five | fivefive
\r
1385 </para></formalpara>
\r
1386 <formalpara><title>Example of a LEFT OUTER JOIN</title><para>
\r
1387 <programlisting language="sql" linenumbering="unnumbered">
\r
1389 LEFT OUTER JOIN bbb ON aaa.id = bbb.id
\r
1391 id | stuff | id | stuff | foo
\r
1392 ----+-------+----+-------+----------
\r
1393 1 | one | 1 | one | oneone
\r
1394 2 | two | 2 | two | twotwo
\r
1397 5 | five | 5 | five | fivefive
\r
1400 </para></formalpara>
\r
1401 <formalpara><title>Example of a RIGHT OUTER JOIN</title><para>
\r
1402 <programlisting language="sql" linenumbering="unnumbered">
\r
1404 RIGHT OUTER JOIN bbb ON aaa.id = bbb.id
\r
1406 id | stuff | id | stuff | foo
\r
1407 ----+-------+----+-------+----------
\r
1408 1 | one | 1 | one | oneone
\r
1409 2 | two | 2 | two | twotwo
\r
1410 5 | five | 5 | five | fivefive
\r
1411 | | 6 | six | sixsix
\r
1414 </para></formalpara>
\r
1415 <formalpara><title>Example of a FULL OUTER JOIN</title><para>
\r
1416 <programlisting language="sql" linenumbering="unnumbered">
\r
1418 FULL OUTER JOIN bbb ON aaa.id = bbb.id
\r
1420 id | stuff | id | stuff | foo
\r
1421 ----+-------+----+-------+----------
\r
1422 1 | one | 1 | one | oneone
\r
1423 2 | two | 2 | two | twotwo
\r
1426 5 | five | 5 | five | fivefive
\r
1427 | | 6 | six | sixsix
\r
1430 </para></formalpara>
\r
1432 <simplesect id="_self_joins">
\r
1433 <title>Self joins</title>
\r
1434 <simpara>It is possible to join a table to itself. You can, in fact you must, use
\r
1435 aliases to disambiguate the references to the table.</simpara>
\r
1438 <simplesect id="_set_operations">
\r
1439 <title>Set operations</title>
\r
1440 <simpara>Relational databases are effectively just an efficient mechanism for
\r
1441 manipulating sets of values; they are implementations of set theory. There are
\r
1442 three operators for sets (tables) in which each set must have the same number
\r
1443 of columns with compatible data types: the union, intersection, and difference
\r
1444 operators.</simpara>
\r
1445 <formalpara><title>Base tables for the set operation examples</title><para>
\r
1446 <programlisting language="sql" linenumbering="unnumbered">
\r
1447 SELECT * FROM aaa;
\r
1458 SELECT * FROM bbb;
\r
1461 ----+-------+----------
\r
1464 5 | five | fivefive
\r
1468 </para></formalpara>
\r
1469 <simplesect id="_union">
\r
1470 <title>Union</title>
\r
1471 <simpara>The <literal>UNION</literal> operator returns the distinct set of rows that are members of
\r
1472 either or both of the left-hand and right-hand tables. The <literal>UNION</literal> operator
\r
1473 does not return any duplicate rows. To return duplicate rows, use the
\r
1474 <literal>UNION ALL</literal> operator.</simpara>
\r
1475 <formalpara><title>Example of a UNION set operation</title><para>
\r
1476 <programlisting language="sql" linenumbering="unnumbered">
\r
1477 -- The parentheses are not required, but are intended to help
\r
1478 -- illustrate the sets participating in the set operation
\r
1501 </para></formalpara>
\r
1503 <simplesect id="_intersection">
\r
1504 <title>Intersection</title>
\r
1505 <simpara>The <literal>INTERSECT</literal> operator returns the distinct set of rows that are common to
\r
1506 both the left-hand and right-hand tables. To return duplicate rows, use the
\r
1507 <literal>INTERSECT ALL</literal> operator.</simpara>
\r
1508 <formalpara><title>Example of an INTERSECT set operation</title><para>
\r
1509 <programlisting language="sql" linenumbering="unnumbered">
\r
1529 </para></formalpara>
\r
1531 <simplesect id="_difference">
\r
1532 <title>Difference</title>
\r
1533 <simpara>The <literal>EXCEPT</literal> operator returns the rows in the left-hand table that do not
\r
1534 exist in the right-hand table. You are effectively subtracting the common
\r
1535 rows from the left-hand table.</simpara>
\r
1536 <formalpara><title>Example of an EXCEPT set operation</title><para>
\r
1537 <programlisting language="sql" linenumbering="unnumbered">
\r
1556 -- Order matters: switch the left-hand and right-hand tables
\r
1557 -- and you get a different result
\r
1575 </para></formalpara>
\r
1578 <simplesect id="_views">
\r
1579 <title>Views</title>
\r
1580 <simpara>A view is a persistent <literal>SELECT</literal> statement that acts like a read-only table.
\r
1581 To create a view, issue the <literal>CREATE VIEW</literal> statement, giving the view a name
\r
1582 and a <literal>SELECT</literal> statement on which the view is built.</simpara>
\r
1583 <simpara>The following example creates a view based on our borrower profile count:</simpara>
\r
1584 <formalpara><title>Creating a view</title><para>
\r
1585 <programlisting language="sql" linenumbering="unnumbered">
\r
1586 CREATE VIEW actor.borrower_profile_count AS
\r
1587 SELECT pgt.name AS "Profile", aou.name AS "Library", COUNT(pgt.name) AS "Count"
\r
1589 INNER JOIN permission.grp_tree pgt
\r
1590 ON au.profile = pgt.id
\r
1591 INNER JOIN actor.org_unit aou
\r
1592 ON aou.id = au.home_ou
\r
1593 WHERE au.deleted IS FALSE
\r
1594 GROUP BY pgt.name, aou.name
\r
1595 ORDER BY aou.name, pgt.name
\r
1598 </para></formalpara>
\r
1599 <simpara>When you subsequently select results from the view, you can apply additional
\r
1600 <literal>WHERE</literal> clauses to filter the results, or <literal>ORDER BY</literal> clauses to change the
\r
1601 order of the returned rows. In the following examples, we issue a simple
\r
1602 <literal>SELECT *</literal> statement to show that the default results are returned in the
\r
1603 same order from the view as the equivalent SELECT statement would be returned.
\r
1604 Then we issue a <literal>SELECT</literal> statement with a <literal>WHERE</literal> clause to further filter the
\r
1605 results.</simpara>
\r
1606 <formalpara><title>Selecting results from a view</title><para>
\r
1607 <programlisting language="sql" linenumbering="unnumbered">
\r
1608 SELECT * FROM actor.borrower_profile_count;
\r
1610 Profile | Library | Count
\r
1611 ----------------------------+----------------------------+-------
\r
1612 Faculty | University Library | 208
\r
1613 Graduate | University Library | 16
\r
1614 Patrons | University Library | 62
\r
1617 -- You can still filter your results with WHERE clauses
\r
1619 FROM actor.borrower_profile_count
\r
1620 WHERE "Profile" = 'Faculty';
\r
1622 Profile | Library | Count
\r
1623 ---------+----------------------------+-------
\r
1624 Faculty | University Library | 208
\r
1625 Faculty | College Library | 64
\r
1626 Faculty | College Library 2 | 102
\r
1627 Faculty | University Library 2 | 776
\r
1630 </para></formalpara>
\r
1632 <simplesect id="_inheritance">
\r
1633 <title>Inheritance</title>
\r
1634 <simpara>PostgreSQL supports table inheritance: that is, a child table inherits its
\r
1635 base definition from a parent table, but can add additional columns to its
\r
1636 own definition. The data from any child tables is visible in queries against
\r
1637 the parent table.</simpara>
\r
1638 <simpara>Evergreen uses table inheritance in several areas:
\r
1639 * In the Vandelay MARC batch importer / exporter, Evergreen defines base
\r
1640 tables for generic queues and queued records for which authority record and
\r
1641 bibliographic record child tables
\r
1642 * Billable transactions are based on the <literal>money.billable_xact</literal> table;
\r
1643 child tables include <literal>action.circulation</literal> for circulation transactions
\r
1644 and <literal>money.grocery</literal> for general bills.
\r
1645 * Payments are based on the <literal>money.payment</literal> table; its child table is
\r
1646 <literal>money.bnm_payment</literal> (for brick-and-mortar payments), which in turn has child
\r
1647 tables of <literal>money.forgive_payment</literal>, <literal>money.work_payment</literal>, <literal>money.credit_payment</literal>,
\r
1648 <literal>money.goods_payment</literal>, and <literal>money.bnm_desk_payment</literal>. The
\r
1649 <literal>money.bnm_desk_payment</literal> table in turn has child tables of <literal>money.cash_payment</literal>,
\r
1650 <literal>money.check_payment</literal>, and <literal>money.credit_card_payment</literal>.
\r
1651 * Transits are based on the <literal>action.transit_copy</literal> table, which has a child
\r
1652 table of <literal>action.hold_transit_copy</literal> for transits initiated by holds.
\r
1653 * Generic acquisition line items are defined by the
\r
1654 <literal>acq.lineitem_attr_definition</literal> table, which in turn has a number of child
\r
1655 tables to define MARC attributes, generated attributes, user attributes, and
\r
1656 provider attributes.</simpara>
\r
1659 <section id="understanding_query_performance_with_explain">
\r
1660 <title>Understanding query performance with EXPLAIN</title>
\r
1661 <simpara>Some queries run for a long, long time. This can be the result of a poorly
\r
1662 written query—a query with a join condition that joins every
\r
1663 row in the <literal>biblio.record_entry</literal> table with every row in the <literal>metabib.full_rec</literal>
\r
1664 view would consume a massive amount of memory and disk space and CPU time—or
\r
1665 a symptom of a schema that needs some additional indexes. PostgreSQL provides
\r
1666 the <literal>EXPLAIN</literal> tool to estimate how long it will take to run a given query and
\r
1667 show you the <emphasis>query plan</emphasis> (how it plans to retrieve the results from the
\r
1668 database).</simpara>
\r
1669 <simpara>To generate the query plan without actually running the statement, simply
\r
1670 prepend the <literal>EXPLAIN</literal> keyword to your query. In the following example, we
\r
1671 generate the query plan for the poorly written query that would join every
\r
1672 row in the <literal>biblio.record_entry</literal> table with every row in the <literal>metabib.full_rec</literal>
\r
1674 <formalpara><title>Query plan for a terrible query</title><para>
\r
1675 <programlisting language="sql" linenumbering="unnumbered">
\r
1677 FROM biblio.record_entry
\r
1678 FULL OUTER JOIN metabib.full_rec ON 1=1
\r
1682 -------------------------------------------------------------------------------//
\r
1683 Merge Full Join (cost=0.00..4959156437783.60 rows=132415734100864 width=1379)
\r
1684 -> Seq Scan on record_entry (cost=0.00..400634.16 rows=2013416 width=1292)
\r
1685 -> Seq Scan on real_full_rec (cost=0.00..1640972.04 rows=65766704 width=87)
\r
1688 </para></formalpara>
\r
1689 <simpara>This query plan shows that the query would return 132415734100864 rows, and it
\r
1690 plans to accomplish what you asked for by sequentially scanning (<emphasis>Seq Scan</emphasis>)
\r
1691 every row in each of the tables participating in the join.</simpara>
\r
1692 <simpara>In the following example, we have realized our mistake in joining every row of
\r
1693 the left-hand table with every row in the right-hand table and take the saner
\r
1694 approach of using an <literal>INNER JOIN</literal> where the join condition is on the record ID.</simpara>
\r
1695 <formalpara><title>Query plan for a less terrible query</title><para>
\r
1696 <programlisting language="sql" linenumbering="unnumbered">
\r
1698 FROM biblio.record_entry bre
\r
1699 INNER JOIN metabib.full_rec mfr ON mfr.record = bre.id;
\r
1701 ----------------------------------------------------------------------------------------//
\r
1702 Hash Join (cost=750229.86..5829273.98 rows=65766704 width=1379)
\r
1703 Hash Cond: (real_full_rec.record = bre.id)
\r
1704 -> Seq Scan on real_full_rec (cost=0.00..1640972.04 rows=65766704 width=87)
\r
1705 -> Hash (cost=400634.16..400634.16 rows=2013416 width=1292)
\r
1706 -> Seq Scan on record_entry bre (cost=0.00..400634.16 rows=2013416 width=1292)
\r
1709 </para></formalpara>
\r
1710 <simpara>This time, we will return 65766704 rows - still way too many rows. We forgot
\r
1711 to include a <literal>WHERE</literal> clause to limit the results to something meaningful. In
\r
1712 the following example, we will limit the results to deleted records that were
\r
1713 modified in the last month.</simpara>
\r
1714 <formalpara><title>Query plan for a realistic query</title><para>
\r
1715 <programlisting language="sql" linenumbering="unnumbered">
\r
1717 FROM biblio.record_entry bre
\r
1718 INNER JOIN metabib.full_rec mfr ON mfr.record = bre.id
\r
1719 WHERE bre.deleted IS TRUE
\r
1720 AND DATE_TRUNC('MONTH', bre.edit_date) >
\r
1721 DATE_TRUNC ('MONTH', NOW() - '1 MONTH'::INTERVAL)
\r
1725 ----------------------------------------------------------------------------------------//
\r
1726 Hash Join (cost=5058.86..2306218.81 rows=201669 width=1379)
\r
1727 Hash Cond: (real_full_rec.record = bre.id)
\r
1728 -> Seq Scan on real_full_rec (cost=0.00..1640972.04 rows=65766704 width=87)
\r
1729 -> Hash (cost=4981.69..4981.69 rows=6174 width=1292)
\r
1730 -> Index Scan using biblio_record_entry_deleted on record_entry bre
\r
1731 (cost=0.00..4981.69 rows=6174 width=1292)
\r
1732 Index Cond: (deleted = true)
\r
1733 Filter: ((deleted IS TRUE) AND (date_trunc('MONTH'::text, edit_date)
\r
1734 > date_trunc('MONTH'::text, (now() - '1 mon'::interval))))
\r
1737 </para></formalpara>
\r
1738 <simpara>We can see that the number of rows returned is now only 201669; that’s
\r
1739 something we can work with. Also, the overall cost of the query is 2306218,
\r
1740 compared to 4959156437783 in the original query. The <literal>Index Scan</literal> tells us
\r
1741 that the query planner will use the index that was defined on the <literal>deleted</literal>
\r
1742 column to avoid having to check every row in the <literal>biblio.record_entry</literal> table.</simpara>
\r
1743 <simpara>However, we are still running a sequential scan over the
\r
1744 <literal>metabib.real_full_rec</literal> table (the table on which the <literal>metabib.full_rec</literal>
\r
1745 view is based). Given that linking from the bibliographic records to the
\r
1746 flattened MARC subfields is a fairly common operation, we could create a
\r
1747 new index and see if that speeds up our query plan.</simpara>
\r
1748 <formalpara><title>Query plan with optimized access via a new index</title><para>
\r
1749 <programlisting language="sql" linenumbering="unnumbered">
\r
1750 -- This index will take a long time to create on a large database
\r
1751 -- of bibliographic records
\r
1752 CREATE INDEX bib_record_idx ON metabib.real_full_rec (record);
\r
1755 FROM biblio.record_entry bre
\r
1756 INNER JOIN metabib.full_rec mfr ON mfr.record = bre.id
\r
1757 WHERE bre.deleted IS TRUE
\r
1758 AND DATE_TRUNC('MONTH', bre.edit_date) >
\r
1759 DATE_TRUNC ('MONTH', NOW() - '1 MONTH'::INTERVAL)
\r
1763 ----------------------------------------------------------------------------------------//
\r
1764 Nested Loop (cost=0.00..1558330.46 rows=201669 width=1379)
\r
1765 -> Index Scan using biblio_record_entry_deleted on record_entry bre
\r
1766 (cost=0.00..4981.69 rows=6174 width=1292)
\r
1767 Index Cond: (deleted = true)
\r
1768 Filter: ((deleted IS TRUE) AND (date_trunc('MONTH'::text, edit_date) >
\r
1769 date_trunc('MONTH'::text, (now() - '1 mon'::interval))))
\r
1770 -> Index Scan using bib_record_idx on real_full_rec
\r
1771 (cost=0.00..240.89 rows=850 width=87)
\r
1772 Index Cond: (real_full_rec.record = bre.id)
\r
1775 </para></formalpara>
\r
1776 <simpara>We can see that the resulting number of rows is still the same (201669), but
\r
1777 the execution estimate has dropped to 1558330 because the query planner can
\r
1778 use the new index (<literal>bib_record_idx</literal>) rather than scanning the entire table.
\r
1779 Success!</simpara>
\r
1780 <note><simpara>While indexes can significantly speed up read access to tables for common
\r
1781 filtering conditions, every time a row is created or updated the corresponding
\r
1782 indexes also need to be maintained - which can decrease the performance of
\r
1783 writes to the database. Be careful to keep the balance of read performance
\r
1784 versus write performance in mind if you plan to create custom indexes in your
\r
1785 Evergreen database.</simpara></note>
\r
1787 <section id="inserting_updating_and_deleting_data">
\r
1788 <title>Inserting, updating, and deleting data</title>
\r
1789 <simplesect id="_inserting_data">
\r
1790 <title>Inserting data</title>
\r
1791 <simpara>To insert one or more rows into a table, use the INSERT statement to identify
\r
1792 the target table and list the columns in the table for which you are going to
\r
1793 provide values for each row. If you do not list one or more columns contained
\r
1794 in the table, the database will automatically supply a <literal>NULL</literal> value for those
\r
1795 columns. The values for each row follow the <literal>VALUES</literal> clause and are grouped in
\r
1796 parentheses and delimited by commas. Each row, in turn, is delimited by commas
\r
1797 (<emphasis>this multiple row syntax requires PostgreSQL 8.2 or higher</emphasis>).</simpara>
\r
1798 <simpara>For example, to insert two rows into the <literal>permission.usr_grp_map</literal> table:</simpara>
\r
1799 <formalpara><title>Inserting rows into the <literal>permission.usr_grp_map</literal> table</title><para>
\r
1800 <programlisting language="sql" linenumbering="unnumbered">INSERT INTO permission.usr_grp_map (usr, grp)
\r
1801 VALUES (2, 10), (2, 4)
\r
1802 ;</programlisting>
\r
1803 </para></formalpara>
\r
1804 <simpara>Of course, as with the rest of SQL, you can replace individual column values
\r
1805 with one or more use sub-selects:</simpara>
\r
1806 <formalpara><title>Inserting rows using sub-selects instead of integers</title><para>
\r
1807 <programlisting language="sql" linenumbering="unnumbered">
\r
1808 INSERT INTO permission.usr_grp_map (usr, grp)
\r
1810 (SELECT id FROM actor.usr
\r
1811 WHERE family_name = 'Scott' AND first_given_name = 'Daniel'),
\r
1812 (SELECT id FROM permission.grp_tree
\r
1813 WHERE name = 'Local System Administrator')
\r
1815 (SELECT id FROM actor.usr
\r
1816 WHERE family_name = 'Scott' AND first_given_name = 'Daniel'),
\r
1817 (SELECT id FROM permission.grp_tree
\r
1818 WHERE name = 'Circulator')
\r
1822 </para></formalpara>
\r
1824 <simplesect id="_inserting_data_using_a_select_statement">
\r
1825 <title>Inserting data using a SELECT statement</title>
\r
1826 <simpara>Sometimes you want to insert a bulk set of data into a new table based on
\r
1827 a query result. Rather than a <literal>VALUES</literal> clause, you can use a <literal>SELECT</literal>
\r
1828 statement to insert one or more rows matching the column definitions. This
\r
1829 is a good time to point out that you can include explicit values, instead
\r
1830 of just column identifiers, in the return columns of the <literal>SELECT</literal> statement.
\r
1831 The explicit values are returned in every row of the result set.</simpara>
\r
1832 <simpara>In the following example, we insert 6 rows into the <literal>permission.usr_grp_map</literal>
\r
1833 table; each row will have a <literal>usr</literal> column value of 1, with varying values for
\r
1834 the <literal>grp</literal> column value based on the <literal>id</literal> column values returned from
\r
1835 <literal>permission.grp_tree</literal>:</simpara>
\r
1836 <formalpara><title>Inserting rows via a <literal>SELECT</literal> statement</title><para>
\r
1837 <programlisting language="sql" linenumbering="unnumbered">
\r
1838 INSERT INTO permission.usr_grp_map (usr, grp)
\r
1840 FROM permission.grp_tree
\r
1846 </para></formalpara>
\r
1848 <simplesect id="_deleting_rows">
\r
1849 <title>Deleting rows</title>
\r
1850 <simpara>Deleting data from a table is normally fairly easy. To delete rows from a table,
\r
1851 issue a <literal>DELETE</literal> statement identifying the table from which you want to delete
\r
1852 rows and a <literal>WHERE</literal> clause identifying the row or rows that should be deleted.</simpara>
\r
1853 <simpara>In the following example, we delete all of the rows from the
\r
1854 <literal>permission.grp_perm_map</literal> table where the permission maps to
\r
1855 <literal>UPDATE_ORG_UNIT_CLOSING</literal> and the group is anything other than administrators:</simpara>
\r
1856 <formalpara><title>Deleting rows from a table</title><para>
\r
1857 <programlisting language="sql" linenumbering="unnumbered">
\r
1858 DELETE FROM permission.grp_perm_map
\r
1861 FROM permission.grp_tree
\r
1862 WHERE name != 'Local System Administrator'
\r
1865 FROM permission.perm_list
\r
1866 WHERE code = 'UPDATE_ORG_UNIT_CLOSING'
\r
1870 </para></formalpara>
\r
1871 <note><simpara>There are two main reasons that a <literal>DELETE</literal> statement may not actually
\r
1872 delete rows from a table, even when the rows meet the conditional clause.</simpara></note>
\r
1873 <orderedlist numeration="arabic">
\r
1876 If the row contains a value that is the target of a relational constraint,
\r
1877 for example, if another table has a foreign key pointing at your target
\r
1878 table, you will be prevented from deleting a row with a value corresponding
\r
1879 to a row in the dependent table.
\r
1884 If the table has a rule that substitutes a different action for a <literal>DELETE</literal>
\r
1885 statement, the deletion will not take place. In Evergreen it is common for a
\r
1886 table to have a rule that substitutes the action of setting a <literal>deleted</literal> column
\r
1887 to <literal>TRUE</literal>. For example, if a book is discarded, deleting the row representing
\r
1888 the copy from the <literal>asset.copy</literal> table would severely affect circulation statistics,
\r
1889 bills, borrowing histories, and their corresponding tables in the database that
\r
1890 have foreign keys pointing at the <literal>asset.copy</literal> table (<literal>action.circulation</literal> and
\r
1891 <literal>money.billing</literal> and its children respectively). Instead, the <literal>deleted</literal> column
\r
1892 value is set to <literal>TRUE</literal> and Evergreen’s application logic skips over these rows
\r
1898 <simplesect id="_updating_rows">
\r
1899 <title>Updating rows</title>
\r
1900 <simpara>To update rows in a table, issue an <literal>UPDATE</literal> statement identifying the table
\r
1901 you want to update, the column or columns that you want to set with their
\r
1902 respective new values, and (optionally) a <literal>WHERE</literal> clause identifying the row or
\r
1903 rows that should be updated.</simpara>
\r
1904 <simpara>Following is the syntax for the <literal>UPDATE</literal> statement:</simpara>
\r
1906 <literallayout><literal>UPDATE</literal> [<emphasis>table-name</emphasis>]
\r
1907 <literal>SET</literal> [<emphasis>column</emphasis>] <literal>TO</literal> [<emphasis>new-value</emphasis>]
\r
1908 <literal>WHERE</literal> [<emphasis>condition</emphasis>]
\r
1913 <section id="query_requests">
\r
1914 <title>Query requests</title>
\r
1915 <simpara>The following queries were requested by Bibliomation, but might be reusable
\r
1916 by other libraries.</simpara>
\r
1917 <simplesect id="_monthly_circulation_stats_by_collection_code_library">
\r
1918 <title>Monthly circulation stats by collection code / library</title>
\r
1919 <formalpara><title>Monthly Circulation Stats by Collection Code/Library</title><para>
\r
1920 <programlisting language="sql" linenumbering="unnumbered">
\r
1921 SELECT COUNT(acirc.id) AS "COUNT", aou.name AS "Library", acl.name AS "Copy Location"
\r
1922 FROM asset.copy ac
\r
1923 INNER JOIN asset.copy_location acl ON ac.location = acl.id
\r
1924 INNER JOIN action.circulation acirc ON acirc.target_copy = ac.id
\r
1925 INNER JOIN actor.org_unit aou ON acirc.circ_lib = aou.id
\r
1926 WHERE DATE_TRUNC('MONTH', acirc.create_time) = DATE_TRUNC('MONTH', NOW() - INTERVAL '3 month')
\r
1927 AND acirc.desk_renewal IS FALSE
\r
1928 AND acirc.opac_renewal IS FALSE
\r
1929 AND acirc.phone_renewal IS FALSE
\r
1930 GROUP BY aou.name, acl.name
\r
1931 ORDER BY aou.name, acl.name, 1
\r
1934 </para></formalpara>
\r
1936 <simplesect id="_monthly_circulation_stats_by_borrower_stat_library">
\r
1937 <title>Monthly circulation stats by borrower stat / library</title>
\r
1938 <formalpara><title>Monthly Circulation Stats by Borrower Stat/Library</title><para>
\r
1939 <programlisting language="sql" linenumbering="unnumbered">
\r
1940 SELECT COUNT(acirc.id) AS "COUNT", aou.name AS "Library", asceum.stat_cat_entry AS "Borrower Stat"
\r
1941 FROM action.circulation acirc
\r
1942 INNER JOIN actor.org_unit aou ON acirc.circ_lib = aou.id
\r
1943 INNER JOIN actor.stat_cat_entry_usr_map asceum ON asceum.target_usr = acirc.usr
\r
1944 INNER JOIN actor.stat_cat astat ON asceum.stat_cat = astat.id
\r
1945 WHERE DATE_TRUNC('MONTH', acirc.create_time) = DATE_TRUNC('MONTH', NOW() - INTERVAL '3 month')
\r
1946 AND astat.name = 'Preferred language'
\r
1947 AND acirc.desk_renewal IS FALSE
\r
1948 AND acirc.opac_renewal IS FALSE
\r
1949 AND acirc.phone_renewal IS FALSE
\r
1950 GROUP BY aou.name, asceum.stat_cat_entry
\r
1951 ORDER BY aou.name, asceum.stat_cat_entry, 1
\r
1954 </para></formalpara>
\r
1956 <simplesect id="_monthly_intralibrary_loan_stats_by_library">
\r
1957 <title>Monthly intralibrary loan stats by library</title>
\r
1958 <formalpara><title>Monthly Intralibrary Loan Stats by Library</title><para>
\r
1959 <programlisting language="sql" linenumbering="unnumbered">
\r
1960 SELECT aou.name AS "Library", COUNT(acirc.id)
\r
1961 FROM action.circulation acirc
\r
1962 INNER JOIN actor.org_unit aou ON acirc.circ_lib = aou.id
\r
1963 INNER JOIN asset.copy ac ON acirc.target_copy = ac.id
\r
1964 INNER JOIN asset.call_number acn ON ac.call_number = acn.id
\r
1965 WHERE acirc.circ_lib != acn.owning_lib
\r
1966 AND DATE_TRUNC('MONTH', acirc.create_time) = DATE_TRUNC('MONTH', NOW() - INTERVAL '3 month')
\r
1967 AND acirc.desk_renewal IS FALSE
\r
1968 AND acirc.opac_renewal IS FALSE
\r
1969 AND acirc.phone_renewal IS FALSE
\r
1971 ORDER BY aou.name, 2
\r
1974 </para></formalpara>
\r
1976 <simplesect id="_monthly_borrowers_added_by_profile_adult_child_etc_library">
\r
1977 <title>Monthly borrowers added by profile (adult, child, etc) / library</title>
\r
1978 <formalpara><title>Monthly Borrowers Added by Profile (Adult, Child, etc)/Library</title><para>
\r
1979 <programlisting language="sql" linenumbering="unnumbered">
\r
1980 SELECT pgt.name AS "Profile", aou.name AS "Library", COUNT(pgt.name) AS "Count"
\r
1982 INNER JOIN permission.grp_tree pgt
\r
1983 ON au.profile = pgt.id
\r
1984 INNER JOIN actor.org_unit aou
\r
1985 ON aou.id = au.home_ou
\r
1986 WHERE au.deleted IS FALSE
\r
1987 AND DATE_TRUNC('MONTH', au.create_date) = DATE_TRUNC('MONTH', NOW() - '3 months'::interval)
\r
1988 GROUP BY pgt.name, aou.name
\r
1989 ORDER BY aou.name, pgt.name
\r
1992 </para></formalpara>
\r
1994 <simplesect id="_borrower_count_by_profile_adult_child_etc_library">
\r
1995 <title>Borrower count by profile (adult, child, etc) / library</title>
\r
1996 <formalpara><title>Borrower Count by Profile (Adult, Child, etc)/Library</title><para>
\r
1997 <programlisting language="sql" linenumbering="unnumbered">
\r
1998 SELECT pgt.name AS "Profile", aou.name AS "Library", COUNT(pgt.name) AS "Count"
\r
2000 INNER JOIN permission.grp_tree pgt
\r
2001 ON au.profile = pgt.id
\r
2002 INNER JOIN actor.org_unit aou
\r
2003 ON aou.id = au.home_ou
\r
2004 WHERE au.deleted IS FALSE
\r
2005 GROUP BY pgt.name, aou.name
\r
2006 ORDER BY aou.name, pgt.name
\r
2009 </para></formalpara>
\r
2011 <simplesect id="_monthly_items_added_by_collection_library">
\r
2012 <title>Monthly items added by collection / library</title>
\r
2013 <simpara>We define a <quote>collection</quote> as a shelving location in Evergreen.</simpara>
\r
2014 <formalpara><title>Monthly Items Added by Collection/Library</title><para>
\r
2015 <programlisting language="sql" linenumbering="unnumbered">
\r
2016 SELECT aou.name AS "Library", acl.name, COUNT(ac.barcode)
\r
2017 FROM actor.org_unit aou
\r
2018 INNER JOIN asset.call_number acn ON acn.owning_lib = aou.id
\r
2019 INNER JOIN asset.copy ac ON ac.call_number = acn.id
\r
2020 INNER JOIN asset.copy_location acl ON ac.location = acl.id
\r
2021 WHERE ac.deleted IS FALSE
\r
2022 AND acn.deleted IS FALSE
\r
2023 AND DATE_TRUNC('MONTH', ac.create_date) = DATE_TRUNC('MONTH', NOW() - '1 month'::interval)
\r
2024 GROUP BY aou.name, acl.name
\r
2025 ORDER BY aou.name, acl.name
\r
2028 </para></formalpara>
\r
2030 <simplesect id="_hold_purchase_alert_by_library">
\r
2031 <title>Hold purchase alert by library</title>
\r
2032 <simpara>in the following set of queries, we bring together the active title, volume,
\r
2033 and copy holds and display those that have more than a certain number of holds
\r
2034 per title. The goal is to UNION ALL the three queries, then group by the
\r
2035 bibliographic record ID and display the title / author information for those
\r
2036 records that have more than a given threshold of holds.</simpara>
\r
2037 <formalpara><title>Hold Purchase Alert by Library</title><para>
\r
2038 <programlisting language="sql" linenumbering="unnumbered">
\r
2040 SELECT all_holds.bib_id, aou.name, rmsr.title, rmsr.author, COUNT(all_holds.bib_id)
\r
2044 SELECT target, request_lib
\r
2045 FROM action.hold_request
\r
2046 WHERE hold_type = 'T'
\r
2047 AND fulfillment_time IS NULL
\r
2048 AND cancel_time IS NULL
\r
2053 SELECT bre.id, request_lib
\r
2054 FROM action.hold_request ahr
\r
2055 INNER JOIN asset.call_number acn ON ahr.target = acn.id
\r
2056 INNER JOIN biblio.record_entry bre ON acn.record = bre.id
\r
2057 WHERE ahr.hold_type = 'V'
\r
2058 AND ahr.fulfillment_time IS NULL
\r
2059 AND ahr.cancel_time IS NULL
\r
2064 SELECT bre.id, request_lib
\r
2065 FROM action.hold_request ahr
\r
2066 INNER JOIN asset.copy ac ON ahr.target = ac.id
\r
2067 INNER JOIN asset.call_number acn ON ac.call_number = acn.id
\r
2068 INNER JOIN biblio.record_entry bre ON acn.record = bre.id
\r
2069 WHERE ahr.hold_type = 'C'
\r
2070 AND ahr.fulfillment_time IS NULL
\r
2071 AND ahr.cancel_time IS NULL
\r
2073 ) AS all_holds(bib_id, request_lib)
\r
2074 INNER JOIN reporter.materialized_simple_record rmsr
\r
2075 INNER JOIN actor.org_unit aou ON aou.id = all_holds.request_lib
\r
2076 ON rmsr.id = all_holds.bib_id
\r
2077 GROUP BY all_holds.bib_id, aou.name, rmsr.id, rmsr.title, rmsr.author
\r
2078 HAVING COUNT(all_holds.bib_id) > 2
\r
2082 </para></formalpara>
\r
2084 <simplesect id="_update_borrower_records_with_a_different_home_library">
\r
2085 <title>Update borrower records with a different home library</title>
\r
2086 <simpara>In this example, the library has opened a new branch in a growing area,
\r
2087 and wants to reassign the home library for the patrons in the vicinity of
\r
2088 the new branch to the new branch. To accomplish this, we create a staging table
\r
2089 that holds a set of city names and the corresponding branch shortname for the home
\r
2090 library for each city.</simpara>
\r
2091 <simpara>Then we issue an <literal>UPDATE</literal> statement to set the home library for patrons with a
\r
2092 physical address with a city that matches the city names in our staging table.</simpara>
\r
2093 <formalpara><title>Update borrower records with a different home library</title><para>
\r
2094 <programlisting language="sql" linenumbering="unnumbered">
\r
2095 CREATE SCHEMA staging;
\r
2096 CREATE TABLE staging.city_home_ou_map (city TEXT, ou_shortname TEXT,
\r
2097 FOREIGN KEY (ou_shortname) REFERENCES actor.org_unit (shortname));
\r
2098 INSERT INTO staging.city_home_ou_map (city, ou_shortname)
\r
2099 VALUES ('Southbury', 'BR1'), ('Middlebury', 'BR2'), ('Hartford', 'BR3');
\r
2102 UPDATE actor.usr au SET home_ou = COALESCE(
\r
2105 FROM actor.org_unit aou
\r
2106 INNER JOIN staging.city_home_ou_map schom ON schom.ou_shortname = aou.shortname
\r
2107 INNER JOIN actor.usr_address aua ON aua.city = schom.city
\r
2108 WHERE au.id = aua.usr
\r
2113 FROM actor.org_unit aou
\r
2114 INNER JOIN staging.city_home_ou_map schom ON schom.ou_shortname = aou.shortname
\r
2115 INNER JOIN actor.usr_address aua ON aua.city = schom.city
\r
2116 WHERE au.id = aua.usr
\r
2120 </para></formalpara>
\r
projects / working / Evergreen.git / blob