Received: from malur.postgresql.org ([217.196.149.56]) by arkaria.postgresql.org with esmtp (Exim 4.84_2) (envelope-from ) id 1ast9z-0003BG-H0 for pgsql-docs@arkaria.postgresql.org; Wed, 20 Apr 2016 14:31:19 +0000 Received: from localhost ([127.0.0.1] helo=postgresql.org) by malur.postgresql.org with smtp (Exim 4.84_2) (envelope-from ) id 1ast9z-00068I-2j for pgsql-docs@arkaria.postgresql.org; Wed, 20 Apr 2016 14:31:19 +0000 Received: from makus.postgresql.org ([2001:4800:1501:1::229]) by malur.postgresql.org with esmtps (TLS1.2:ECDHE_RSA_AES_256_CBC_SHA384:256) (Exim 4.84_2) (envelope-from ) id 1ast9P-00059d-Td for pgsql-docs@postgresql.org; Wed, 20 Apr 2016 14:30:44 +0000 Received: from mout.kundenserver.de ([212.227.17.24]) by makus.postgresql.org with esmtps (TLS1.2:DHE_RSA_AES_256_CBC_SHA256:256) (Exim 4.84_2) (envelope-from ) id 1ast9H-0006w3-J9 for pgsql-docs@postgresql.org; Wed, 20 Apr 2016 14:30:42 +0000 Received: from [192.168.178.26] ([84.165.210.121]) by mrelayeu.kundenserver.de (mreue102) with ESMTPSA (Nemesis) id 0M7Kru-1bdYFm26Jq-00x4su for ; Wed, 20 Apr 2016 16:30:33 +0200 From: =?UTF-8?Q?J=c3=bcrgen_Purtz?= Subject: Docbook 5.x To: pgsql-docs@postgresql.org Message-ID: <57179283.6080704@purtz.de> Date: Wed, 20 Apr 2016 16:30:27 +0200 User-Agent: Mozilla/5.0 (X11; Linux x86_64; rv:38.0) Gecko/20100101 Thunderbird/38.6.0 MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="------------090201030506000100060508" X-Provags-ID: V03:K0:fouFx4s0hiwsxk4wr/I8BZ31XVk0VK08JGCGRQKTV6C+TPdRqvl gneQDhDmRvR+3BfVIL5W2BPLeUmpxyafNEzvdBMU4epdiI3psEL6ImUsgifuxLPX1ENDdQ+ LPIE6jdpFwaH3dbHnF8u4bH+S+faeS5K+sfEDpDf27eyhUrZUR50DubGq/dgvwmx/ckvMjH SVI7PZzdb4eJao/TBU6Lg== X-UI-Out-Filterresults: notjunk:1;V01:K0:ASs6ouQXSTE=:edtNSTar/vnBoCgAskGhII wossr/jfSkkVp3oWLJVHWwt3Xoaxok+yrLOcCJNuPqGk1+HNv2jcSj2yJb94n7lUUXlHpDlkn FV3ggVCiIh1PWeMc1WSroe6mfNLsmSbqlWAjqTkr8WgHgaPKmS/nZCykUrnDV2ESpaASg/xuq UJ45nxTXyBeKqecISC0zyXU4GEsNxqW0VMW6N0Y9rn1ABcRcXp/qL45NFRVL5O9mq3PA3DHjY 8sHI8uU/OM+toMyxr3Ldhn2aZ+ct0TDtzfwclVa+egOxBn8Nia/1mGm2GidMmVF61/vrLao/s SPP1c6ErZxfb/u6DpyeXDds+Dq4mhFG3uMykmZaCb/UO7Rv7lDoxiSoBeFZQt3g24Bqcx0DbR sFR2hecWgTpYrNuaEpkVKojBp98RishBd4FrZbvPW+UF0S8etMgwwic7OCg/n3IjV5JIDtyXt QEzebjl9jk1nTS7jQYkFt4a9/6/UzQNiykeKJRvKtCS0wWPfNtOTtsgCV7PBSiJB+9ogI78cq DtRaXLdUbc2umcHsW/RUY1a8xepGA39yogeyUX5Swp0Tx3ZAqPkI/dExHHvdgi2dsjFfpvYFr iIZcJ+D+MEm3DDd+Tkj38HQQqtNqgXiGBR7gbw4RIpu6If8Z/5WEwiRerf0KMmq7DcsisMHHt XGsUO5b4pkcbMQftGgZDon2ac8Mtg5KSCJL+wd0zjVWwjog== X-Pg-Spam-Score: -0.6 (/) List-Archive: List-Help: List-ID: List-Owner: List-Post: List-Subscribe: List-Unsubscribe: X-Mailing-List: pgsql-docs Precedence: bulk Sender: pgsql-docs-owner@postgresql.org This is a multi-part message in MIME format. --------------090201030506000100060508 Content-Type: multipart/alternative; boundary="------------090303060901050508020706" --------------090303060901050508020706 Content-Type: text/plain; charset=utf-8; format=flowed Content-Transfer-Encoding: 8bit Hi, actually we use DocBook V4.2 for the PostgreSQL manuals. I suggest an upgrade to DocBook 5.x. This sounds simple, but it will be a long process with many sub-tasks. Rationale: * Sooner or later we MUST migrate as the 4.x series is outdated: V4.2 dates back to 2002. The 4.x series is no longer actively developed since 2006. See: http://www.docbook.org/tdg5/en/html/ch01.html "In October 2006, the DocBook Technical Committee released DocBook V4.5, the last release planned in the 4.x series." * V5.0 is available since 2009. See: http://www.docbook.org/tdg5/en/html/ch01.html: "DocBook V5.0 became an official Committee Specification in June 2009 and became an official OASIS Standard in October 2009." * Actually the technical committee has the third Candidate Release for V5.1. PROs: * The formal part of the migration is supported by existing tools: http://docbook.org/docs/howto/#convert4to5 (nevertheless some scripts written by ourself will be necessary). * The normative schema for Docbook 5.x is written in RELAX NG. Additionally the technical committee converts this normative schema to a XSD schema and to DTD, which are not normative but very near to RELAX NG and will fit for most applications. Hence, we have the choice between three schema syntaxes and everybody can use his favourite one. * Our source file format will switch from SGML to XML. This implies that we have access to all XML features like XLink, XPath, XSLT, XSL-FO, SVG, MathML, namespaces, ... . CONs: * The migration from 4.x to 5.x implies major changes at 3 different levels. o DocBook structure: Previously it was defined in SGML syntax (DTD). Now it is defined in RELAX NG schema language plus Schematron rules. o DocBook files: Previously we used SGML syntax for our files. We must convert them to a valid XML syntax, eg: tag omission. o Tools and style sheets: All tools which operate at the native SGML-level (editors, conversions, ...) must be replaced by XML conforming tools. As valid XML implicitly conforms to a valid SGML syntax this step may be accomplished by reconfiguring some of the tools, eg.: .emacs. What I have done so far is: * Conversion of sgml files to valid xml syntax with a perl skript. I failed to use 'osx' or 'spam'. * Conversion of these xml files to Docbook5.x format using xsltproc and Docbooks xslt-migration skripts. * Creation of html files using xsltproc and Docbooks xslt skripts. * Creation of fo files using xsltproc and Docbooks xslt skripts. * Creation of pdf files using fop. * The conversions needs less than 10 minutes on a Intel i5 processor. This is a very first raw round-trip with one output file per sgml file and output type. Not supported: entities (__gt__ as a surrogate), <[CDATA and similar SGML constructs, PostgreSQL specific style sheets, Makefile, additional errors occur, .... . I append one file of every new format for the chapter "Advanced Features": xml (the new source), html, fo, pdf. Any ideas or suggestions? Shall we go further on this way? Has anybody more experiences in SGML-->XML conversions or Docbook 4.x --> 5.x conversions? Kind regards Jürgen Purtz --------------090303060901050508020706 Content-Type: text/html; charset=utf-8 Content-Transfer-Encoding: 8bit Hi,
actually we use DocBook V4.2 for the PostgreSQL manuals. I suggest an upgrade to DocBook 5.x. This sounds simple, but it will be a long process with many sub-tasks.

Rationale:
  • Sooner or later we MUST migrate as the 4.x series is outdated: V4.2 dates back to 2002. The 4.x series is no longer actively developed since 2006. See: http://www.docbook.org/tdg5/en/html/ch01.html "In October 2006, the DocBook Technical Committee released DocBook V4.5, the last release planned in the 4.x series."
  • V5.0 is available since 2009. See: http://www.docbook.org/tdg5/en/html/ch01.html: "DocBook V5.0 became an official Committee Specification in June 2009 and became an official OASIS Standard in October 2009."
  • Actually the technical committee has the third Candidate Release for V5.1.

PROs:
  • The formal part of the migration is supported by existing tools: http://docbook.org/docs/howto/#convert4to5 (nevertheless some scripts written by ourself will be necessary).
  • The normative schema for Docbook 5.x is written in RELAX NG. Additionally the technical committee converts this normative schema to a XSD schema and to DTD, which are not normative but very near to RELAX NG and will fit for most applications. Hence, we have the choice between three schema syntaxes and everybody can use his favourite one.
  • Our source file format will switch from SGML to XML. This implies that we have access to all XML features like XLink, XPath, XSLT, XSL-FO, SVG, MathML, namespaces, ... .
CONs:
  • The migration from 4.x to 5.x implies major changes at 3 different levels.
    • DocBook structure: Previously it was defined in SGML syntax (DTD). Now it is defined in RELAX NG schema language plus Schematron rules.
    • DocBook files: Previously we used SGML syntax for our files. We must convert them to a valid XML syntax, eg: tag omission.
    • Tools and style sheets: All tools which operate at the native SGML-level (editors, conversions, ...) must be replaced by XML conforming tools. As valid XML implicitly conforms to a valid SGML syntax this step may be accomplished by reconfiguring some of the tools, eg.: .emacs.
What I have done so far is:
  • Conversion of sgml files to valid xml syntax with a perl skript. I failed to use 'osx' or 'spam'.
  • Conversion of these xml files to Docbook5.x format using xsltproc and Docbooks xslt-migration skripts.
  • Creation of html files using xsltproc and Docbooks xslt skripts.
  • Creation of fo files using xsltproc and Docbooks xslt skripts.
  • Creation of pdf files using fop.
  • The conversions needs less than 10 minutes on a Intel i5 processor.
This is a very first raw round-trip with one output file per sgml file and output type. Not supported: entities (__gt__ as a surrogate), <[CDATA and similar SGML constructs, PostgreSQL specific style sheets, Makefile, additional errors occur, .... .  I append one file of every new format for the chapter "Advanced Features": xml (the new source), html, fo, pdf.

Any ideas or suggestions? Shall we go further on this way? Has anybody more experiences in SGML-->XML conversions or Docbook 4.x --> 5.x conversions?

Kind regards
Jürgen Purtz

 --------------090303060901050508020706-- --------------090201030506000100060508 Content-Type: text/xml; name="advanced.xml" Content-Transfer-Encoding: 7bit Content-Disposition: attachment; filename="advanced.xml" Advanced Features
Introduction In the previous chapter we have covered the basics of using SQL to store and access your data in PostgreSQL. We will now discuss some more advanced features of SQL that simplify management and prevent loss or corruption of your data. Finally, we will look at some PostgreSQL extensions. This chapter will on occasion refer to examples found in to change or improve them, so it will be useful to have read that chapter. Some examples from this chapter can also be found in advanced.sql in the tutorial directory. This file also contains some sample data to load, which is not repeated here. (Refer to for how to use the file.)
Views view Refer back to the queries in . Suppose the combined listing of weather records and city location is of particular interest to your application, but you do not want to type the query each time you need it. You can create a view over the query, which gives a name to the query that you can refer to like an ordinary table: CREATE VIEW myview AS SELECT city, temp_lo, temp_hi, prcp, date, location FROM weather, cities WHERE city = name; SELECT * FROM myview; Making liberal use of views is a key aspect of good SQL database design. Views allow you to encapsulate the details of the structure of your tables, which might change as your application evolves, behind consistent interfaces. Views can be used in almost any place a real table can be used. Building views upon other views is not uncommon.
Foreign Keys foreign key referential integrity Recall the weather and cities tables from . Consider the following problem: You want to make sure that no one can insert rows in the weather table that do not have a matching entry in the cities table. This is called maintaining the referential integrity of your data. In simplistic database systems this would be implemented (if at all) by first looking at the cities table to check if a matching record exists, and then inserting or rejecting the new weather records. This approach has a number of problems and is very inconvenient, so PostgreSQL can do this for you. The new declaration of the tables would look like this: CREATE TABLE cities ( city varchar(80) primary key, location point ); CREATE TABLE weather ( city varchar(80) references cities(city), temp_lo int, temp_hi int, prcp real, date date ); Now try inserting an invalid record: INSERT INTO weather VALUES ('Berkeley', 45, 53, 0.0, '1994-11-28'); ERROR: insert or update on table "weather" violates foreign key constraint "weather_city_fkey" DETAIL: Key (city)=(Berkeley) is not present in table "cities". The behavior of foreign keys can be finely tuned to your application. We will not go beyond this simple example in this tutorial, but just refer you to for more information. Making correct use of foreign keys will definitely improve the quality of your database applications, so you are strongly encouraged to learn about them.
Transactions transaction Transactions are a fundamental concept of all database systems. The essential point of a transaction is that it bundles multiple steps into a single, all-or-nothing operation. The intermediate states between the steps are not visible to other concurrent transactions, and if some failure occurs that prevents the transaction from completing, then none of the steps affect the database at all. For example, consider a bank database that contains balances for various customer accounts, as well as total deposit balances for branches. Suppose that we want to record a payment of $100.00 from Alice's account to Bob's account. Simplifying outrageously, the SQL commands for this might look like: UPDATE accounts SET balance = balance - 100.00 WHERE name = 'Alice'; UPDATE branches SET balance = balance - 100.00 WHERE name = (SELECT branch_name FROM accounts WHERE name = 'Alice'); UPDATE accounts SET balance = balance + 100.00 WHERE name = 'Bob'; UPDATE branches SET balance = balance + 100.00 WHERE name = (SELECT branch_name FROM accounts WHERE name = 'Bob'); The details of these commands are not important here; the important point is that there are several separate updates involved to accomplish this rather simple operation. Our bank's officers will want to be assured that either all these updates happen, or none of them happen. It would certainly not do for a system failure to result in Bob receiving $100.00 that was not debited from Alice. Nor would Alice long remain a happy customer if she was debited without Bob being credited. We need a guarantee that if something goes wrong partway through the operation, none of the steps executed so far will take effect. Grouping the updates into a transaction gives us this guarantee. A transaction is said to be atomic: from the point of view of other transactions, it either happens completely or not at all. We also want a guarantee that once a transaction is completed and acknowledged by the database system, it has indeed been permanently recorded and won't be lost even if a crash ensues shortly thereafter. For example, if we are recording a cash withdrawal by Bob, we do not want any chance that the debit to his account will disappear in a crash just after he walks out the bank door. A transactional database guarantees that all the updates made by a transaction are logged in permanent storage (i.e., on disk) before the transaction is reported complete. Another important property of transactional databases is closely related to the notion of atomic updates: when multiple transactions are running concurrently, each one should not be able to see the incomplete changes made by others. For example, if one transaction is busy totalling all the branch balances, it would not do for it to include the debit from Alice's branch but not the credit to Bob's branch, nor vice versa. So transactions must be all-or-nothing not only in terms of their permanent effect on the database, but also in terms of their visibility as they happen. The updates made so far by an open transaction are invisible to other transactions until the transaction completes, whereupon all the updates become visible simultaneously. In PostgreSQL, a transaction is set up by surrounding the SQL commands of the transaction with BEGIN and COMMIT commands. So our banking transaction would actually look like: BEGIN; UPDATE accounts SET balance = balance - 100.00 WHERE name = 'Alice'; -- etc etc COMMIT; If, partway through the transaction, we decide we do not want to commit (perhaps we just noticed that Alice's balance went negative), we can issue the command ROLLBACK instead of COMMIT, and all our updates so far will be canceled. PostgreSQL actually treats every SQL statement as being executed within a transaction. If you do not issue a BEGIN command, then each individual statement has an implicit BEGIN and (if successful) COMMIT wrapped around it. A group of statements surrounded by BEGIN and COMMIT is sometimes called a transaction block. Some client libraries issue BEGIN and COMMIT commands automatically, so that you might get the effect of transaction blocks without asking. Check the documentation for the interface you are using. It's possible to control the statements in a transaction in a more granular fashion through the use of savepoints. Savepoints allow you to selectively discard parts of the transaction, while committing the rest. After defining a savepoint with SAVEPOINT, you can if needed roll back to the savepoint with ROLLBACK TO. All the transaction's database changes between defining the savepoint and rolling back to it are discarded, but changes earlier than the savepoint are kept. After rolling back to a savepoint, it continues to be defined, so you can roll back to it several times. Conversely, if you are sure you won't need to roll back to a particular savepoint again, it can be released, so the system can free some resources. Keep in mind that either releasing or rolling back to a savepoint will automatically release all savepoints that were defined after it. All this is happening within the transaction block, so none of it is visible to other database sessions. When and if you commit the transaction block, the committed actions become visible as a unit to other sessions, while the rolled-back actions never become visible at all. Remembering the bank database, suppose we debit $100.00 from Alice's account, and credit Bob's account, only to find later that we should have credited Wally's account. We could do it using savepoints like this: BEGIN; UPDATE accounts SET balance = balance - 100.00 WHERE name = 'Alice'; SAVEPOINT my_savepoint; UPDATE accounts SET balance = balance + 100.00 WHERE name = 'Bob'; -- oops ... forget that and use Wally's account ROLLBACK TO my_savepoint; UPDATE accounts SET balance = balance + 100.00 WHERE name = 'Wally'; COMMIT; This example is, of course, oversimplified, but there's a lot of control possible in a transaction block through the use of savepoints. Moreover, ROLLBACK TO is the only way to regain control of a transaction block that was put in aborted state by the system due to an error, short of rolling it back completely and starting again.
Window Functions window function A window function performs a calculation across a set of table rows that are somehow related to the current row. This is comparable to the type of calculation that can be done with an aggregate function. But unlike regular aggregate functions, use of a window function does not cause rows to become grouped into a single output row __mdash__ the rows retain their separate identities. Behind the scenes, the window function is able to access more than just the current row of the query result. Here is an example that shows how to compare each employee's salary with the average salary in his or her department: SELECT depname, empno, salary, avg(salary) OVER (PARTITION BY depname) FROM empsalary; depname | empno | salary | avg -----------+-------+--------+----------------------- develop | 11 | 5200 | 5020.0000000000000000 develop | 7 | 4200 | 5020.0000000000000000 develop | 9 | 4500 | 5020.0000000000000000 develop | 8 | 6000 | 5020.0000000000000000 develop | 10 | 5200 | 5020.0000000000000000 personnel | 5 | 3500 | 3700.0000000000000000 personnel | 2 | 3900 | 3700.0000000000000000 sales | 3 | 4800 | 4866.6666666666666667 sales | 1 | 5000 | 4866.6666666666666667 sales | 4 | 4800 | 4866.6666666666666667 (10 rows) The first three output columns come directly from the table empsalary, and there is one output row for each row in the table. The fourth column represents an average taken across all the table rows that have the same depname value as the current row. (This actually is the same function as the regular avg aggregate function, but the OVER clause causes it to be treated as a window function and computed across an appropriate set of rows.) A window function call always contains an OVER clause directly following the window function's name and argument(s). This is what syntactically distinguishes it from a regular function or aggregate function. The OVER clause determines exactly how the rows of the query are split up for processing by the window function. The PARTITION BY list within OVER specifies dividing the rows into groups, or partitions, that share the same values of the PARTITION BY expression(s). For each row, the window function is computed across the rows that fall into the same partition as the current row. You can also control the order in which rows are processed by window functions using ORDER BY within OVER. (The window ORDER BY does not even have to match the order in which the rows are output.) Here is an example: SELECT depname, empno, salary, rank() OVER (PARTITION BY depname ORDER BY salary DESC) FROM empsalary; depname | empno | salary | rank -----------+-------+--------+------ develop | 8 | 6000 | 1 develop | 10 | 5200 | 2 develop | 11 | 5200 | 2 develop | 9 | 4500 | 4 develop | 7 | 4200 | 5 personnel | 2 | 3900 | 1 personnel | 5 | 3500 | 2 sales | 1 | 5000 | 1 sales | 4 | 4800 | 2 sales | 3 | 4800 | 2 (10 rows) As shown here, the rank function produces a numerical rank within the current row's partition for each distinct ORDER BY value, in the order defined by the ORDER BY clause. rank needs no explicit parameter, because its behavior is entirely determined by the OVER clause. The rows considered by a window function are those of the virtual table produced by the query's FROM clause as filtered by its WHERE, GROUP BY, and HAVING clauses if any. For example, a row removed because it does not meet the WHERE condition is not seen by any window function. A query can contain multiple window functions that slice up the data in different ways by means of different OVER clauses, but they all act on the same collection of rows defined by this virtual table. We already saw that ORDER BY can be omitted if the ordering of rows is not important. It is also possible to omit PARTITION BY, in which case there is just one partition containing all the rows. There is another important concept associated with window functions: for each row, there is a set of rows within its partition called its window frame. Many (but not all) window functions act only on the rows of the window frame, rather than of the whole partition. By default, if ORDER BY is supplied then the frame consists of all rows from the start of the partition up through the current row, plus any following rows that are equal to the current row according to the ORDER BY clause. When ORDER BY is omitted the default frame consists of all rows in the partition. There are options to define the window frame in other ways, but this tutorial does not cover them. See for details. Here is an example using sum: SELECT salary, sum(salary) OVER () FROM empsalary; salary | sum --------+------- 5200 | 47100 5000 | 47100 3500 | 47100 4800 | 47100 3900 | 47100 4200 | 47100 4500 | 47100 4800 | 47100 6000 | 47100 5200 | 47100 (10 rows) Above, since there is no ORDER BY in the OVER clause, the window frame is the same as the partition, which for lack of PARTITION BY is the whole table; in other words each sum is taken over the whole table and so we get the same result for each output row. But if we add an ORDER BY clause, we get very different results: SELECT salary, sum(salary) OVER (ORDER BY salary) FROM empsalary; salary | sum --------+------- 3500 | 3500 3900 | 7400 4200 | 11600 4500 | 16100 4800 | 25700 4800 | 25700 5000 | 30700 5200 | 41100 5200 | 41100 6000 | 47100 (10 rows) Here the sum is taken from the first (lowest) salary up through the current one, including any duplicates of the current one (notice the results for the duplicated salaries). Window functions are permitted only in the SELECT list and the ORDER BY clause of the query. They are forbidden elsewhere, such as in GROUP BY, HAVING and WHERE clauses. This is because they logically execute after the processing of those clauses. Also, window functions execute after regular aggregate functions. This means it is valid to include an aggregate function call in the arguments of a window function, but not vice versa. If there is a need to filter or group rows after the window calculations are performed, you can use a sub-select. For example: SELECT depname, empno, salary, enroll_date FROM (SELECT depname, empno, salary, enroll_date, rank() OVER (PARTITION BY depname ORDER BY salary DESC, empno) AS pos FROM empsalary ) AS ss WHERE pos __lt__ 3; The above query only shows the rows from the inner query having rank less than 3. When a query involves multiple window functions, it is possible to write out each one with a separate OVER clause, but this is duplicative and error-prone if the same windowing behavior is wanted for several functions. Instead, each windowing behavior can be named in a WINDOW clause and then referenced in OVER. For example: SELECT sum(salary) OVER w, avg(salary) OVER w FROM empsalary WINDOW w AS (PARTITION BY depname ORDER BY salary DESC); More details about window functions can be found in , , , and the reference page.
Inheritance inheritance Inheritance is a concept from object-oriented databases. It opens up interesting new possibilities of database design. Let's create two tables: A table cities and a table capitals. Naturally, capitals are also cities, so you want some way to show the capitals implicitly when you list all cities. If you're really clever you might invent some scheme like this: CREATE TABLE capitals ( name text, population real, altitude int, -- (in ft) state char(2) ); CREATE TABLE non_capitals ( name text, population real, altitude int -- (in ft) ); CREATE VIEW cities AS SELECT name, population, altitude FROM capitals UNION SELECT name, population, altitude FROM non_capitals; This works OK as far as querying goes, but it gets ugly when you need to update several rows, for one thing. A better solution is this: CREATE TABLE cities ( name text, population real, altitude int -- (in ft) ); CREATE TABLE capitals ( state char(2) ) INHERITS (cities); In this case, a row of capitals inherits all columns (name, population, and altitude) from its parent, cities. The type of the column name is text, a native PostgreSQL type for variable length character strings. State capitals have an extra column, state, that shows their state. In PostgreSQL, a table can inherit from zero or more other tables. For example, the following query finds the names of all cities, including state capitals, that are located at an altitude over 500 feet: SELECT name, altitude FROM cities WHERE altitude __gt__ 500; which returns: name | altitude -----------+---------- Las Vegas | 2174 Mariposa | 1953 Madison | 845 (3 rows) On the other hand, the following query finds all the cities that are not state capitals and are situated at an altitude over 500 feet: SELECT name, altitude FROM ONLY cities WHERE altitude __gt__ 500; name | altitude -----------+---------- Las Vegas | 2174 Mariposa | 1953 (2 rows) Here the ONLY before cities indicates that the query should be run over only the cities table, and not tables below cities in the inheritance hierarchy. Many of the commands that we have already discussed __mdash__ SELECT, UPDATE, and DELETE __mdash__ support this ONLY notation. Although inheritance is frequently useful, it has not been integrated with unique constraints or foreign keys, which limits its usefulness. See for more detail.
Conclusion PostgreSQL has many features not touched upon in this tutorial introduction, which has been oriented toward newer users of SQL. These features are discussed in more detail in the remainder of this book. If you feel you need more introductory material, please visit the PostgreSQL web site for links to more resources.
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aXY+PC9kaXY+PC9ib2R5PjwvaHRtbD4K --------------090201030506000100060508 Content-Type: text/x-xslfo; name="advanced.fo" Content-Transfer-Encoding: quoted-printable Content-Disposition: attachment; filename="advanced.fo" = = Advanced Featur= es= = Advanced Features<= fo:block>= = = <= fo:table-column column-number=3D"3" column-width=3D"proportional-column-wid= th(1)"/>Chapter=C2=A01.=C2=A0Advanced FeaturesTable of ContentsIntroductionViews<= /fo:inline>Foreign KeysTransactionsWindow FunctionsInheritanceConclusion<= fo:marker marker-class-name=3D"section.head.marker">IntroductionIntroduction In the previous chapter we have covered the basics of using SQL to store and access your data in PostgreSQL. We will now discuss some more advanced features of SQL that simplify management and prevent loss or corruption of your data. Finally, we will look at some PostgreSQL extensions. This chapter will on occasion refer to examples found in ???= to change or improve them, so it will be useful to have read that chapter. Some examples from this chapter can also be found in advanced.sql in the tu= torial directory. This file also contains some sample data to load, which is not repeated here. (Refer to ??? for how to use the file.) Views= Views Refer back to the queries in ???. Suppose the combined listing of weather records and city location is of particular interest to your application, but you do not want to type the query each time you need it. You can create a view over the query, which= gives a name to the query that you can refer to like an ordinary table: CREATE VIEW myview AS SELECT city, temp_lo, temp_hi, prcp, date, location FROM weather, cities WHERE city =3D name; SELECT * FROM myview; Making liberal use of views is a key aspect of good SQL database design. Views allow you to encapsulate the details of the structure of your tables, which might change as your application evolves, behind consistent interfaces. Views can be used in almost any place a real table can be used. Building views upon other views is not uncommon. <= fo:block margin-left=3D"0pt" font-family=3D"sans-serif,Symbol,ZapfDingbats"= keep-together.within-column=3D"always">Foreign KeysForeign Keys<= fo:wrapper id=3D"idm45796159878016"> Recall the weather and cities tables from ???. Consider the following problem: You want to make sure that no one can insert rows in the weather table that do = not have a matching entry in the cities ta= ble. This is called maintaining the referential integrity<= /fo:inline> of your data. In simplistic database systems this would be implemented (if at all) by first looking at the cities table to check = if a matching record exists, and then inserting or rejecting the new weather records. This= approach has a number of problems and is very inconvenient, so PostgreSQL can do this for you. The new declaration of the tables would look like this: CREATE TABLE cities ( city varchar(80) primary key, location point ); CREATE TABLE weather ( city varchar(80) references cities(city), temp_lo int, temp_hi int, prcp real, date date ); Now try inserting an invalid record: INSERT INTO weather VALUES ('Berkeley', 45, 53, 0.0, '1994-11-28'); ERROR: insert or update on table "weather" violates foreign key constraint= "weather_city_fkey" DETAIL: Key (city)=3D(Berkeley) is not present in table "cities". The behavior of foreign keys can be finely tuned to your application. We will not go beyond this simple example in this tutorial, but just refer you to ??? for more information. Making correct use of foreign keys will definitely improve the quality of your database applications, so you are strongly encouraged to learn about them. <= fo:block>TransactionsTransactions Transactions are a fundame= ntal concept of all database systems. The essential point of a transaction is that it bundles multiple steps into a single, all-or-nothing operation. The intermedia= te states between the steps are not visible to other concurrent transactio= ns, and if some failure occurs that prevents the transaction from completin= g, then none of the steps affect the database at all. For example, consider a bank database that contains balances for various customer accounts, as well as total deposit balances for branches. Suppose that we want to record a payment of $100.00 from Alice's account to Bob's account. Simplifying outrageously, the SQL commands for this might look like: UPDATE accounts SET balance =3D balance - 100.00 WHERE name =3D 'Alice'; UPDATE branches SET balance =3D balance - 100.00 WHERE name =3D (SELECT branch_name FROM accounts WHERE name =3D 'Alice'= ); UPDATE accounts SET balance =3D balance + 100.00 WHERE name =3D 'Bob'; UPDATE branches SET balance =3D balance + 100.00 WHERE name =3D (SELECT branch_name FROM accounts WHERE name =3D 'Bob'); The details of these commands are not important here; the important point is that there are several separate updates involved to accomplish this rather simple operation. Our bank's officers will want to be assured that either all these updates happen, or none of them happen. It would certainly not do for a system failure to result in Bob receiving $100.00 that was not debited from Alice. Nor would Alice long remain a happy customer if she was debited without Bob being credited. We need a guarantee that if something goes wrong partway through the operation, none of the steps executed so far will take effect. Grouping the updates into a transaction gives us this guarantee. A transaction is said to be atomic: from the point of view of other transactions, it either happens completely or not at all. We also want a guarantee that once a transaction is completed and acknowledged by the database system, it has indeed been permanently recorded and won't be lost even if a crash ensues shortly thereafter. For example, if we are recording a cash withdrawal by Bob, we do not want any chance that the debit to his account will disappear in a crash just after he walks out the bank door. A transactional database guarantees that all the updates made by a transaction are logged in permanent storage (i.e., on disk) before the transaction is reported complete. Another important property of transactional databases is closely related to the notion of atomic updates: when multiple transactions are running concurrently, each one should not be able to see the incomplete changes made by others. For example, if one transaction is busy totalling all the branch balances, it would not do for it to include the debit from Alice's branch but not the credit to Bob's branch, nor vice versa. So transactions must be all-or-nothing not only in terms of their permanent effect on the database, but also in terms of their visibility as they happen. The updates made so far by an open transaction are invisible to other transactions until the transaction completes, whereupon all the updates become visible simultaneously. In PostgreSQL, a transaction is set up by surrounding the SQL commands of the transaction with BEGIN and COMMIT commands. So our banking transaction would actually look like: BEGIN; UPDATE accounts SET balance =3D balance - 100.00 WHERE name =3D 'Alice'; -- etc etc COMMIT; If, partway through the transaction, we decide we do not want to commit (perhaps we just noticed that Alice's balance went negative), we can issue the command ROLLBACK instead of COMMIT, and all our updates= so far will be canceled. PostgreSQL actually treats every SQL statement as being executed within a transaction. If you do not issue a BEGIN command, then each individual statement has an implicit BEGIN and (if successful) COMMIT wrap= ped around it. A group of statements surrounded by BEGIN and COMMIT is sometimes called a transaction bloc= k. Not= e Some client libraries issue BEGIN and COMMIT commands automatically, so that you might get the effect of transaction blocks without asking. Check the documentation for the interface you are using. It's possible to control the statements in a transaction in a more granular fashion through the use of sa= vepoints. Savepoints allow you to selectively discard parts of the transaction, while committing the rest. After defining a savepoint with SAVEPOINT, you can if neede= d roll back to the savepoint with ROLLBACK TO. All the = transaction's database changes between defining the savepoint and rolling back to it are discarded, but changes earlier than the savepoint are kept. After rolling back to a savepoint, it continues to be defined, so you c= an roll back to it several times. Conversely, if you are sure you won't n= eed to roll back to a particular savepoint again, it can be released, so the system can free some resources. Keep in mind that either releasing or rolling back to a savepoint will automatically release all savepoints that were defined after it. All this is happening within the transaction block, so none of it is visible to other database sessions. When and if you commit the transaction block, the committed actions become visible as a unit to other sessions, while the rolled-back actions never become visible at all. Remembering the bank database, suppose we debit $100.00 from Alice's account, and credit Bob's account, only to find later that we should have credited Wally's account. We could do it using savepoints like this: BEGIN; UPDATE accounts SET balance =3D balance - 100.00 WHERE name =3D 'Alice'; SAVEPOINT my_savepoint; UPDATE accounts SET balance =3D balance + 100.00 WHERE name =3D 'Bob'; -- oops ... forget that and use Wally's account ROLLBACK TO my_savepoint; UPDATE accounts SET balance =3D balance + 100.00 WHERE name =3D 'Wally'; COMMIT; This example is, of course, oversimplified, but there's a lot of control possible in a transaction block through the use of savepoints. Moreover, ROLLBACK TO is th= e only way to regain control of a transaction block that was put in aborted state by the system due to an error, short of rolling it back completely and starting again. Window FunctionsWindow Functions Inheritance is a concept from object-oriented databases. It opens up interesting new possibilities of database design. Let's create two tables: A table = cities and a table capitals. = Naturally, capitals are also cities, so you want some way to show the capitals implicitly when you list all cities. If you're really clever you might invent some scheme like this: CREATE TABLE capitals ( name text, population real, altitude int, -- (in ft) state char(2) ); CREATE TABLE non_capitals ( name text, population real, altitude int -- (in ft) ); CREATE VIEW cities AS SELECT name, population, altitude FROM capitals UNION SELECT name, population, altitude FROM non_capitals; This works OK as far as querying goes, but it gets ugly when you need to update several rows, for one thing. A better solution is this: CREATE TABLE cities ( name text, population real, altitude int -- (in ft) ); CREATE TABLE capitals ( state char(2) ) INHERITS (cities); In this case, a row of capitals inherits all columns (name, population, and altitude) from its parent, cities. The type of the column name is text, a native PostgreSQL type for variable length character strings. State capitals have an extra column, state= , that shows their state. In PostgreSQL, a table can inherit from zero or more other tables. For example, the following query finds the names of all cities, including state capitals, that are located at an altitude over 500 feet: SELECT name, altitude FROM cities WHERE altitude __gt__ 500; which returns: name | altitude -----------+---------- Las Vegas | 2174 Mariposa | 1953 Madison | 845 (3 rows) On the other hand, the following query finds all the cities that are not state capitals and are situated at an altitude over 500 feet: SELECT name, altitude FROM ONLY cities WHERE altitude __gt__ 500; name | altitude -----------+---------- Las Vegas | 2174 Mariposa | 1953 (2 rows) Here the ONLY before <= fo:inline font-family=3D"monospace">cities indicates that the query should be run over only the cities table, and not = tables below cities in the inherita= nce hierarchy. Many of the commands that we have already discussed __mdash__ SELECT, UPDATE, and DELETE __mdash__ support th= is ONLY notation. Not= e Although inheritance is frequently useful, it has not been integrated with unique constraints or foreign keys, which limits its usefulness. See ??? for more detail. <= fo:marker marker-class-name=3D"section.head.marker">Conclusion<= fo:block font-size=3D"20.736pt">Conclusion= PostgreSQL has many features not touched upon in this tutorial introduction, which has been oriented toward newer users of SQL. These features are discussed in more detail in the remainder of this book. If you feel you need more introductory material, please visit the Postg= reSQL = web site [http://www.postgresql.= org] for links to more resources. = --------------090201030506000100060508 Content-Type: application/pdf; name="advanced.pdf" Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="advanced.pdf" JVBERi0xLjQKJaqrrK0KNCAwIG9iago8PAovQ3JlYXRvciAoQXBhY2hlIEZP UCBWZXJzaW9uIDEuMSkKL1Byb2R1Y2VyIChBcGFjaGUgRk9QIFZlcnNpb24g MS4xKQovQ3JlYXRpb25EYXRlIChEOjIwMTYwNDIwMTI0NTE2KzAyJzAwJykK Pj4KZW5kb2JqCjUgMCBvYmoKPDwKICAvTiAzCiAgL0xlbmd0aCAxMSAwIFIK ICAvRmlsdGVyIC9GbGF0ZURlY29kZQo+PgpzdHJlYW0KeJztmWdQVFkWgO97 r3OgobtpMjQ5SZTQgOScJEgWFehuMi00OZiQwREYQUQkKYKIAg44OgQZRUUU A6KggHkaGQSUcXAUUVFZwB+zVbu1W1u1tX+2z4/3vjrn1jvnvrpV76t6AMiQ 4tkJybA+AAm8FL6vsx0zKDiEib0PcIAMSIAKMOHs5ERbb28PsBwra8E/xPtR AK3c7+n88/q/DBIngccBAKIvcyyHm8xe5p3LHM1J4Kzkp1c4PSUxBQDYe5np /OUBl5mzwhHfOGOFo75x0eoaP1/7ZT4KAI4UtcqEUyscscrUrhVmR/MTAJDu 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