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This will log all queries that take longer than 10 seconds to a log file at example.com-slow. log in MySQL s data directory. You can change the number of seconds and the log location as shown in this code, where we set the slow query threshold to 5 seconds and the filename to example-slow.log: # The MySQL server [mysqld] long_query_time = 5 log-slow-queries = /var/log/mysql/example-slow.log

To find out which pages are the most resource intensive, enable the statistics module that is included with Drupal. Although the statistics module increases the load on your server (since it records access statistics for your site into your database), it can be useful to see which pages are the most frequently viewed and thus the most ripe for query optimization. It also tracks total page generation time over a period, which you can specify in Administer Reports Access log settings. This is useful for identifying out-of-control web crawlers that are eating up system resources, which you can then ban on the spot by visiting Administer Reports Top visitors and clicking ban. Be careful though it s just as easy to ban a good crawler that drives traffic to your site as a bad one. Make sure you investigate the origin of the crawler before banning it.

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Note Not all element types use layout properties like padding or margins. Developers should consider the element type being modified when adjusting properties in the Layout pane.

Consider the following resource-hogging code: // Very expensive, silly way to get node titles. First we get the node IDs // of all published nodes. $sql = "SELECT n.nid FROM {node} n WHERE n.status = 1"; // We wrap our node query in db_rewrite_sql() so that node access is respected. $result = db_rewrite_sql(db_query($sql)); // Now we do a node_load() on each individual node. while ($data = db_fetch_object($result)) { $node = node_load($data->nid); // And save the titles. $titles[$node->nid] = check_plain($node->title); } Fully loading a node is an expensive operation: hooks run, modules perform database queries to add or modify the node, and memory is used to cache the node in node_load() s internal cache. If you are not depending on modification to the node by a module, it s much faster to do your own query of the node table directly. Certainly this is a contrived example, but the same pattern can often be found, that is, often data is retrieved via multiple queries that could be combined into a single query, or needless node loading is performed.

Figure 9-7. J2EE Project Explorer after XDoclet completes Figure 9-7 shows an expanded view of the TroubleTicket project after the Ticket entity bean has been added. Notice the new Ticket bean is under the Entity Beans node. Underneath the Ticket bean are the related Ticket interfaces and the TicketCMP bean; in addition, all the attributes, primary keys, and finder methods are listed. Within the source folders, you can see generated files including TicketBean.java, TicketCMP.java, ejb-jar.xml, jboss.xml, jbosscmp-jdbc.xml, TicketLocal.java, and TicketLocalHome.java.

s Drupal has an internal caching mechanism (using a static variable) when a node is loaded more than Tip once per request. For example, if node_load(1) was called, node number 1 is fully loaded and cached. When another call to node_load(1) is made during the same web request, Drupal will return the cached results for the previously loaded node having the same node ID.

The Attributes pane, described previously in the Inspecting Markup section, is useful for CSS properties as well. The drop-down list of attributes contains both HTML attributes and CSS properties; CSS properties added through the Attributes pane are added to an element s style attribute, as shown previously in Figure 5 7.

SQL slowness can result from poor implementation of SQL tables in contributed modules. For example, columns without indices may result in slow queries. A quick way to see how queries are executed by MySQL is to take one of the queries you ve captured in your slow query log, prepend the word EXPLAIN to it, and issue the query to MySQL. The result will be a table showing which indices were used. Consult a good book on MySQL for details.

Note It is important to implement version control for your source code so you can guarantee repeatable

If you have very expensive queries that must be performed, perhaps the results can be manually cached by your module. See 15 for details on Drupal s cache API.

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