Large-Scale Web Site Infrastructure and Drupal
Search is resource-intensive. Optimizing search will contribute to overall site performance and is a great process to outsource to another box. Solr can help ease an over-burdened Web server. Solr is a project from the Apache Foundation that takes the power of Lucene, a fantastic indexer and searcher, and exposes it as a Web service. Using HTTP POST and GET requests, you can feed documents to Solr for indexing and issue queries for searching. In Drupal, the Views module serves as a visual query-builder and handles search. With Views 3, in Drupal, you can plug in Solr to handle the search heavy-lifting instead of having Drupal hit MySQL for this, alleviating a load on your database server best left to a document indexer like Lucene.
Apache's MaxClients setting is a limit on the number of simultaneous requests that can be served. If this limit is reached, users have to wait until a child process is freed up until they can connect. If this number is increased too much, however, there is a risk that the Web head will run out of memory. There's a standard formula for figuring out what this setting should be based upon the RAM available to the machine:
formula: RAM/Average Apache Memory Size in Use = # max clients
example: 2GB/20MB = 100 MaxClients
Apache's mod_expires setting controls the HTTP header information for anything served through Apache to your machine. If a resource has been cached on a user's computer, this setting can tell any subsequent request to that resource if it has expired and needs to be downloaded again. It's a good idea to have this turned on for text/HTML header types:
<IfModule mod_expires.c> ExpiresActive On ExpiresDefault A1209600 ExpiresByType text/html A1 </IfModule>
The KeepAlive setting is a way to tell Apache to keep an HTTP connection alive for a period of time so that it can be reused. This has been shown to result in an almost 50% speed increase in latency times for HTML documents with many images. Turn this on and set the KeepAliveTimeout to 2 seconds:
KeepAlive On KeepAliveTimeout 2
MySQL is the most widely used database for Drupal, although Drupal 6 also supports Postgres. Drupal 7 has an object-oriented database abstraction layer that allows drivers to be written for many other database systems. There are some key things to keep in mind within MySQL's configuration that can help optimize your application for performance.
MySQL has a built-in query cache that is turned on by default. Make sure to afford a liberal amount of memory to this cache:
Once your application is built, it's a good idea to log slow queries for a short amount of time to get a list of queries that are taking a long time and can be examined with an EXPLAIN and then optimized:
log-slow-queries = /var/log/slow_query.log long_query_time = 5 #log-queries-not-using-indexes
MySQL's EXPLAIN command is a great way to find out exactly what a particular query is doing in order to get some clues as to why it may be taking a long time to evaluate and return a result. One of the key things to look at is the number of rows that EXPLAIN tells you it had to search through. This may indicate that one of your tables, bursting at the seams, is a good candidate for a new index.
Taking a look at the following query, we see there are three fields that could have an index placed upon them in order to reduce the number of rows that a query has to search through in order to find the desired result:
... FROM node node WHERE node.status = 1 AND node.type IN ('story') ORDER BY node.created DESC
The status, type and created fields are key to this query's result and can be indexed so that they are seen as a group:
mysql> ALTER TABLE node ADD INDEX (status, type, created);
Table locking can be a performance headache. By default, Drupal's MySQL database tables are all set to MyISAM. Because MyISAM locks the entire table down during a query, high traffic may cause MySQL errors when a certain table is unavailable or locked. If you start seeing these errors, look at which tables are giving the error and evaluate whether they should be set to InnoDB instead. InnoDB does row locking instead of table locking. When evaluating, look to see if the table has any auto_increment fields, and keep in mind that converting this table may cause slow-downs on INSERTs, as InnoDB does a full table lock on INSERTs to avoid key duplication.
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
Join Linux Journal's Mike Diehl and Pat Cameron of Help Systems.
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With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide