Update of /project/cl-prevalence/cvsroot/public_html In directory common-lisp.net:/tmp/cvs-serv15463

Modified Files: index.html Added Files: CL-PREVALENCE.html S-SERIALIZATION.html Log Message: added more info

Date: Mon Jun 21 07:34:01 2004 Author: scaekenberghe

Index: public_html/index.html diff -u public_html/index.html:1.3 public_html/index.html:1.4 --- public_html/index.html:1.3 Sun Jun 20 13:11:49 2004 +++ public_html/index.html Mon Jun 21 07:34:01 2004 @@ -15,12 +15,61 @@

<p>CL-PREVALENCE is an implementation of <a href="http://www.prevayler.org">Object Prevalence</a> for Common Lisp.</p>

+<p> + Object Prevalence is a simple but interesting concept first proposed by Klaus Wuestefeld in 2001. IBM developerWorks has a reasonable <a href="http://www-106.ibm.com/developerworks/library/wa-objprev/">Introduction to Object Prevalence</a> article. The main Java implementation is called <a href="http://www.prevayler.org">Prevayler</a>, with a (chaotic) wiki site with lots of information and discussions. Basically, the idea is this: +</p> +<ul> + <li>Most databases are only a couple of hundreds of megabytes big, often even less.</li> + <li>Most computers can easily take a couple of hundreds of megabytes of data in RAM, big servers can hold many gigabytes.</li> + <li>Mapping objects to databases is at least tedious and time consuming, but often also complex and error prone.</li> + <li>Let's throw away the database and just consider the domain model objects as the database.</li> + <li>Let's make sure we can serialize and deserialize our objects to and from a some presistent medium such as a file system.</li> + <li>If we store our complete set of domain model objects to a persistent medium we create a <em>snapshot</em>.</li> + <li>We query by using the data structure manipulation functionality of our programming language, running from RAM, queries will be extremely fast.</li> + <li>Let's agree to only change our object model using transaction objects that combine the data and the functionality to execute the transaction.</li> + <li>In order to preserve the ACID properties of our system, we log each transaction to some persistent medium by serializing it after we execute it. The is called the <em>transaction log</em>.</li> + <li>When the system goes down (intentionally or unintentionally) we restore its latest state by first reading in the latest snapshot and by re-executing each transaction from the transaction log.</li> + <li>Transactions must be deterministic and re-entrant (so they also need to record the current time if necessary).</li> + <li>In a multi-threaded system, transactions are globally serialized.</li> +</ul> +<p> +That is all there is to the concept of object prevalence. Here are some more details as well as some advantages and limitations: +</p> +<ul> + <li>A good implementation on a modern machine can achieve thousands of transactions per second, and recover them at about the same speed.</li> + <li>Transactions must be short because they block the system - since everything is in RAM this is not a problem.</li> + <li>Queries that need to see a completely consistent system state must also block on the system - other less critical queries could run in parallel.</li> + <li>It is practical for a transaction to first check its preconditions, throw an error if necessary, and to only modify the system when everything is consistent. During a transaction you are the sole active thread. Queries are as fast as they can get. In this implementation transactions are logged after succesful execution.</li> + <li>In this implementation there is an option to do a rollback (by doing a system restore) when an unexpected error occurs during transaction execution. You can specifiy that a condition doesn't need a rollback when it occurs inside a transaction by implementing the <tt>initiates-rollback</tt> to return false (or by using the <tt>no-rollback-error</tt> condition or inheriting from it).</li> + <li>Long running transactions are an open question.</li> + <li>Application server techniques are used to offer multiple clients access to the same prevalence system.</li> + <li>We can easily do replication (and query load balancing) by distributing the master transaction log stream to replica's that can host queries, execute backups (snapshots) or serve as hot fail-over. This implementation does not yet contain replication.</li> +</ul> +<p> + This code was written by Sven Van Caekenberghe. +</p> + <h3>Download</h3> + <p> This project is currently starting up, please use <a href="http://common-lisp.net/cgi-bin/viewcvs.cgi/?cvsroot=cl-prevalence">CVS</a> access for now, which also offers a tarball. </p>

+<h3>API</h3> + + <p> + You can consult the LispDoc generated API is the files <a href="CL-PREVALENCE.html">CL-PREVALENCE.html</a> + and <a href="S-SERIALIZATION.html">S-SERIALIZATION.html</a>. + </p> + +<h3>Release History</h3> + +<ul> + <li>release 3, today: move to common-lisp.net, added s-expression based serialization</li> + <li>release 2, Januari 13, 2004: added managed-prevalence layer, generic persistent preferences and a blob feature, as well as several useful functions to support development and deployment</li> + <li>release 1, June 10, 2003: first public release</li> +</ul>

<h3>Mailing Lists</h3>

@@ -30,7 +79,7 @@ <li><a href="http://common-lisp.net/mailman/listinfo/cl-prevalence-announce">CL-PREVALENCE-ANNOUNCE mailing list info</a></li> </ul>

- <p>CVS version $Id: index.html,v 1.3 2004/06/20 20:11:49 scaekenberghe Exp $</p> + <p>CVS version $Id: index.html,v 1.4 2004/06/21 14:34:01 scaekenberghe Exp $</p>

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