When using memcached you can use a number of different potential deployment strategies and topologies. The exact strategy you use will depend on your application and environment. When developing a system for deploying memcached within your system, you should keep in mind the following points:

When you first start memcached, the memory that you have configured is not automatically allocated. Instead, memcached only starts allocating and reserving physical memory once you start saving information into the cache.

When you start to store data into the cache, memcached does not allocate the memory for the data on an item by item basis. Instead, a slab allocation is used to optimize memory usage and prevent memory fragmentation when information expires from the cache.

With slab allocation, memory is reserved in blocks of 1MB. The slab is divided up into a number of blocks of equal size. When you try to store a value into the cache, memcached checks the size of the value that you are adding to the cache and determines which slab contains the right size allocation for the item. If a slab with the item size already exists, the item is written to the block within the slab.

If the new item is bigger than the size of any existing blocks, then a new slab is created, divided up into blocks of a suitable size. If an existing slab with the right block size already exists, but there are no free blocks, a new slab is created. If you update an existing item with data that is larger than the existing block allocation for that key, then the key is reallocated into a suitable slab.

For example, the default size for the smallest block is 88 bytes (40 bytes of value, and the default 48 bytes for the key and flag data). If the size of the first item you store into the cache is less than 40 bytes, then a slab with a block size of 88 bytes is created and the value stored.

If the size of the data that you want to store is larger than this value, then the block size is increased by the chunk size factor until a block size large enough to hold the value is determined. The block size is always a function of the scale factor, rounded up to a block size which is exactly divisible into the chunk size.

For a sample of the structure, see Figure 15.2, “memcached memory allocation”.

Figure 15.2. memcached memory allocation

The result is that you have multiple pages allocated within the range of memory allocated to memcached. Each page is 1MB in size (by default), and will be split into different number of chunks, according to the chunk size required to store the key/value pairs. Each instance will have multiple pages allocated, and a page will always be created when a new item needs to be created requiring a chunk of a particular size. A slab may consist of multiple pages, and each page within a slab will contain an equal number of chunks.

The chunk size of a new slab is determined by the base chunk size combined with the chunk size growth factor. For example, if the initial chunks are 104 bytes in size, and the default chunk size growth factor is used (1.25), then the next chunk size allocated would be the best power of 2 fit for 104*1.25, or 136 bytes.

Allocating the pages in this way ensures that memory does not get fragmented. However, depending on the distribution of the objects that you want to store, it may lead to an inefficient distribution of the slabs and chunks if you have significantly different sized items. For example, having a relatively small number of items within each chunk size may waste a lot of memory with just few chunks in each allocated page.

You can tune the growth factor to reduce this effect by using the -f command line option. This will adapt the growth factor applied to make more effective use of the chunks and slabs allocated. For information on how to determine the current slab allocation statistics, see Section 15.4.2, “memcached Slabs Statistics”.

If your operating system supports it, you can also start memcached with the -L command line option. With this option enabled, it will preallocate all the memory during startup using large memory pages. This can improve performance by reducing the number of misses in the CPU memory cache.

The memcached cache is a very simple massive key/value storage system, and as such there is no way of compartmentalizing data automatically into different sections. For example, if you are storing information by the unique ID returned from a MySQL database, then storing the data from two different tables will run into issues because the same ID will probably be valid in both tables.

Some interfaces provide an automated mechanism for creating namespaces when storing information into the cache. In practice, these namespaces are merely a prefix before a given ID that is applied every time a value is stored or retrieve from the cache.

You can implement the same basic principle by using keys that describe the object and the unique identifier within the key that you supply when the object is stored. For example, when storing user data, prefix the ID of the user with user: or user-.

There are two types of data expiry within a memcached instance. The first type is applied at the point when you store a new key/value pair into the memcached instance. If there is not enough space within a suitable slab to store the value, then an existing least recently used (LRU) object is removed (evicted) from the cache to make room for the new item.

The LRU algorithm ensures that the object that is removed is one that is either no longer in active use or that was used so long ago that its data is potentially out of date or of little value. However, in a system where the memory allocated to memcached is smaller than the number of regularly used objects required in the cache you will see a lot of expired items being removed from the cache even though they are in active use. You use the statistics mechanism to get a better idea of the level of evictions (expired objects). For more information, see Section 15.4, “Getting memcached Statistics”.

You can change this eviction behavior by setting the -M command-line option when starting memcached. This option forces an error to be returned when the memory has been exhausted, instead of automatically evicting older data.

The second type of expiry system is an explicit mechanism that you can set when a key/value pair is inserted into the cache, or when deleting an item from the cache. Using an expiration time can be a useful way of ensuring that the data in the cache is up to date and in line with your application needs and requirements.

A typical scenario for explicitly setting the expiry time might include caching session data for a user when accessing a website. memcached uses a lazy expiry mechanism where the explicit expiry time that has been set is compared with the current time when the object is requested. Only objects that have not expired are returned.

You can also set the expiry time when explicitly deleting an object from the cache. In this case, the expiry time is really a timeout and indicates the period when any attempts to set the value for a given key are rejected.

The memcached client interface supports a number of different hashing types that are used in multi-server configurations to determine which host should be used when setting or getting data from a given memcached instance. When you get or set a value, a hash is constructed from the supplied key and then used to select a host from the list of configured servers. Because the hashing mechanism uses the supplied key as the basis for the hash, the selected server will be the same during both set and get operations.

For example, if you have three servers, A, B, and C, and you set the value myid, then the memcached client will create a hash based on the ID and select server B. When the same key is requested, the same hash is generated, and the same server, B, will be selected to request the value.

Because the hashing mechanism is part of the client interface, not the server interface, the hashing process and selection is very fast. By performing the hashing on the client, it also means that if you want to access the same data by the same ID from the same list of servers but from different client interfaces, you must use the same or compatible hashing mechanisms. If you do not use the same hashing mechanism then the same data may be recorded on different servers by different interfaces, both wasting space on your memcached and leading to potential differences in the information.

One issue with the client-side hashing mechanism is that when using multiple servers and extending or shrinking the list of servers that you have configured for use with memcached, the resulting hash may change. For example, if you have servers A, B, and C; the computed hash for key myid may equate to server B. If you add another server, D, into this list, then computing the hash for the same ID again may result in the selection of server D for that key.

This means that servers B and D both contain the information for key myid, but there may be differences between the data held by the two instances. A more significant problem is that you will get a much higher number of cache-misses when retrieving data as the addition of a new server will change the distribution of keys, and this will in turn require rebuilding the cached data on the memcached instances and require an increase in database reads.

For this reason, there are two common types of hashing algorithm, consistent and modula.

With consistent hashing algorithms, the same key when applied to a list of servers will always use the same server to store or retrieve the keys, even if the list of configured servers changes. This means that you can add and remove servers from the configure list and always use the same server for a given key. There are two types of consistent hashing algorithms available, Ketama and Wheel. Both types are supported by libmemcached, and implementations are available for PHP and Java.

There are some limitations with any consistent hashing algorithm. When adding servers to an existing list of configured servers, then keys will be distributed to the new servers as part of the normal distribution. When removing servers from the list, the keys will be re-allocated to another server within the list, which will mean that the cache will need to be re-populated with the information. Also, a consistent hashing algorithm does not resolve the issue where you want consistent selection of a server across multiple clients, but where each client contains a different list of servers. The consistency is enforced only within a single client.

With a modula hashing algorithm, the client will select a server by first computing the hash and then choosing a server from the list of configured servers. As the list of servers changes, so the server selected when using a modula hashing algorithm will also change. The result is the behavior described above; changes to the list of servers will mean different servers are selected when retrieving data leading to cache misses and increase in database load as the cache is re-seeded with information.

If you use only a single memcached instance for each client, or your list of memcached servers configured for a client never changes, then the selection of a hashing algorithm is irrelevant, as you will not notice the effect.

If you change your servers regularly, or you use a common set of servers that are shared among a large number of clients, then using a consistent hashing algorithm should help to ensure that your cache data is not duplicated and the data is evenly distributed.

The libmemcached library provides both C and C++ interfaces to memcached and is also the basis for a number of different additional API implementations, including Perl, Python and Ruby. Understanding the core libmemcached functions can help when using these other interfaces.

The C library is the most comprehensive interface library for memcached and provides a wealth of functions and operational systems not always exposed in the other interfaces not based on the libmemcached library.

The different functions can be divided up according to their basic operation. In addition to functions that interface to the core API, there are a number of utility functions that provide extended functionality, such as appending and prepending data.

To build and install libmemcached, download the libmemcached package, run configure, and then build and install:

shell> tar xjf libmemcached-0.21.tar.gz
shell> cd libmemcached-0.21
shell> ./configure
shell> make
shell> make install

On many Linux operating systems, you can install the corresponding libmemcached package through the usual yum, apt-get or similar commands. On OpenSolaris, use pkg to install the SUNWlibmemcached package.

To build an application that uses the library, you need to first set the list of servers. You can do this either by directly manipulating the servers configured within the main memcached_st structure, or by separately populating a list of servers, and then adding this list to the memcached_st structure. The latter method is used in the example below. Once the server list has been set, you can call the functions to store or retrieve data. A simple application for setting a preset value to localhost is provided below:

root-shell>include <stdio.h>
#include <string.h>
#include <unistd.h>
#include <libmemcached/memcached.h>

int main(int argc, char *argv[])
{
  memcached_server_st *servers = NULL;
  memcached_st *memc;
  memcached_return rc;
  char *key= "keystring";
  char *value= "keyvalue";

  memcached_server_st *memcached_servers_parse (char *server_strings);
  memc= memcached_create(NULL);

  servers= memcached_server_list_append(servers, "localhost", 11211, &rc);
  rc= memcached_server_push(memc, servers);

  if (rc == MEMCACHED_SUCCESS)
    fprintf(stderr,"Added server successfully\n");
  else
    fprintf(stderr,"Couldn't add server: %s\n",memcached_strerror(memc, rc));

  rc= memcached_set(memc, key, strlen(key), value, strlen(value), (time_t)0, (uint32_t)0);

  if (rc == MEMCACHED_SUCCESS)
    fprintf(stderr,"Key stored successfully\n");
  else
    fprintf(stderr,"Couldn't store key: %s\n",memcached_strerror(memc, rc));

  return 0;
}

You can test the success of an operation by using the return value, or populated result code, for a given function. The value will always be set to MEMCACHED_SUCCESS if the operation succeeded. In the event of a failure, use the memcached_strerror() function to translate the result code into a printable string.

To build the application, you must specify the memcached library:

shell> gcc -o memc_basic memc_basic.c -lmemcached

Running the above sample application, after starting a memcached server, should return a success message:

shell> memc_basic 
Added server successfully
Key stored successfully

memcached_st *memcached_create (memcached_st *ptr);

void memcached_free (memcached_st *ptr);

memcached_st *memcached_clone(memcached_st *clone, memcached_st *source);

memcached_return
           memcached_server_add (memcached_st *ptr,
                                 char *hostname,
                                 unsigned int port);

memcached_return
           memcached_server_add_unix_socket (memcached_st *ptr,
                                             char *socket);

unsigned int memcached_server_count (memcached_st *ptr);

memcached_server_st *
           memcached_server_list (memcached_st *ptr);

memcached_return
           memcached_server_push (memcached_st *ptr,
                                  memcached_server_st *list);

memcached_server_st *
           memcached_server_list_append (memcached_server_st *ptr,
                                         char *hostname,
                                         unsigned int port,
                                         memcached_return *error);

 unsigned int memcached_server_list_count (memcached_server_st *ptr);

void memcached_server_list_free (memcached_server_st *ptr);

memcached_server_st *memcached_servers_parse (char *server_strings);

memcached_return
           memcached_set (memcached_st *ptr,
                          const char *key, 
                          size_t key_length,
                          const char *value, 
                          size_t value_length,
                          time_t expiration,
                          uint32_t flags);

memcached_return
           memcached_set_by_key(memcached_st *ptr,
                                const char *master_key, 
                                size_t master_key_length,
                                const char *key,
                                size_t key_length,
                                const char *value, 
                                size_t value_length,
                                time_t expiration,
                                uint32_t flags);

char *memcached_get (memcached_st *ptr,
                     const char *key, size_t key_length,
                     size_t *value_length,
                     uint32_t *flags,
                     memcached_return *error);

memcached_return
         memcached_mget (memcached_st *ptr,
                         char **keys, size_t *key_length,
                         unsigned int number_of_keys);

char *memcached_fetch (memcached_st *ptr,
                         const char *key, size_t *key_length,
                         size_t *value_length,
                         uint32_t *flags,
                         memcached_return *error);

root-shell>include <stdio.h>
#include <sstring.h>
#include <unistd.h>
#include <libmemcached/memcached.h>

int main(int argc, char *argv[])
{
  memcached_server_st *servers = NULL;
  memcached_st *memc;
  memcached_return rc;
  char *keys[]= {"huey", "dewey", "louie"};
  size_t key_length[3];
  char *values[]= {"red", "blue", "green"};
  size_t value_length[3];
  unsigned int x;
  uint32_t flags;

  char return_key[MEMCACHED_MAX_KEY];
  size_t return_key_length;
  char *return_value;
  size_t return_value_length;

  memc= memcached_create(NULL);

  servers= memcached_server_list_append(servers, "localhost", 11211, &rc);
  rc= memcached_server_push(memc, servers);

  if (rc == MEMCACHED_SUCCESS)
    fprintf(stderr,"Added server successfully\n");
  else
    fprintf(stderr,"Couldn't add server: %s\n",memcached_strerror(memc, rc));

  for(x= 0; x < 3; x++)
    {
      key_length[x] = strlen(keys[x]);
      value_length[x] = strlen(values[x]);

      rc= memcached_set(memc, keys[x], key_length[x], values[x],
                        value_length[x], (time_t)0, (uint32_t)0);
      if (rc == MEMCACHED_SUCCESS)
        fprintf(stderr,"Key %s stored successfully\n",keys[x]);
      else
        fprintf(stderr,"Couldn't store key: %s\n",memcached_strerror(memc, rc));
    }

  rc= memcached_mget(memc, keys, key_length, 3);

  if (rc == MEMCACHED_SUCCESS)
    {
      while ((return_value= memcached_fetch(memc, return_key, &return_key_length,
                                            &return_value_length, &flags, &rc)) != NULL)
        {
          if (rc == MEMCACHED_SUCCESS)
            {
              fprintf(stderr,"Key %s returned %s\n",return_key, return_value);
            }
        }
    }

  return 0;
}

shell> memc_multi_fetch 
Added server successfully
Key huey stored successfully
Key dewey stored successfully
Key louie stored successfully
Key huey returned red
Key dewey returned blue
Key louie returned green

memcached_return
           memcached_behavior_set (memcached_st *ptr,
                                   memcached_behavior flag,
                                   uint64_t data);

uint64_t
           memcached_behavior_get (memcached_st *ptr,
                                   memcached_behavior flag);

The Cache::Memcached module provides a native interface to the Memcache protocol, and provides support for the core functions offered by memcached. You should install the module using your hosts native package management system. Alternatively, you can install the module using CPAN:

root-shell> perl -MCPAN -e 'install Cache::Memcached'

To use memcached from Perl through Cache::Memcached module, you first need to create a new Cache::Memcached object that defines the list of servers and other parameters for the connection. The only argument is a hash containing the options for the cache interface. For example, to create a new instance that uses three memcached servers:

use Cache::Memcached;

my $cache = new Cache::Memcached {
    'servers' => [
        '192.168.0.100:11211',
        '192.168.0.101:11211',
        '192.168.0.102:11211',
	],
};

You can set additional properties on the cache object instance when it is created by specifying the option as part of the option hash. Alternatively, you can use a corresponding method on the instance:

Once the Cache::Memcached object instance has been configured you can use the set() and get() methods to store and retrieve information from the memcached servers. Objects stored in the cache are automatically serialized and deserialized using the Storable module.

The Cache::Memcached interface supports the following methods for storing/retrieving data, and relate to the generic methods as shown in the table.

Below is a complete example for using memcached with Perl and the Cache::Memcached module:

root-shell>!/usr/bin/perl

use Cache::Memcached;
use DBI;
use Data::Dumper;

# Configure the memcached server

my $cache = new Cache::Memcached {
    'servers' => [
                   'localhost:11211',
                   ],
    };

# Get the film name from the command line
# memcached keys must not contain spaces, so create
# a key name by replacing spaces with underscores

my $filmname = shift or die "Must specify the film name\n";
my $filmkey = $filmname;
$filmkey =~ s/ /_/;

# Load the data from the cache

my $filmdata = $cache->get($filmkey);

# If the data wasn't in the cache, then we load it from the database

if (!defined($filmdata))
{
    $filmdata = load_filmdata($filmname);

    if (defined($filmdata))
    {

# Set the data into the cache, using the key

	if ($cache->set($filmkey,$filmdata))
        {
            print STDERR "Film data loaded from database and cached\n";
        }
        else
        {
            print STDERR "Couldn't store to cache\n";
	}
    }
    else
    {
     	die "Couldn't find $filmname\n";
    }
}
else
{
    print STDERR "Film data loaded from Memcached\n";
}

sub load_filmdata
{
    my ($filmname) = @_;

    my $dsn = "DBI:mysql:database=sakila;host=localhost;port=3306";

    $dbh = DBI->connect($dsn, 'sakila','password');

    my ($filmbase) = $dbh->selectrow_hashref(sprintf('select * from film where title = %s',
                                                     $dbh->quote($filmname)));

    if (!defined($filmname))
    {
     	return (undef);
    }

    $filmbase->{stars} =
	$dbh->selectall_arrayref(sprintf('select concat(first_name," ",last_name) ' .
                                         'from film_actor left join (actor) ' .
                                         'on (film_actor.actor_id = actor.actor_id) ' .
                                         ' where film_id=%s',
                                         $dbh->quote($filmbase->{film_id})));

    return($filmbase);
}

The example uses the Sakila database, obtaining film data from the database and writing a composite record of the film and actors to memcache. When calling it for a film does not exist, you should get this result:

shell> memcached-sakila.pl "ROCK INSTINCT"
Film data loaded from database and cached

When accessing a film that has already been added to the cache:

shell> memcached-sakila.pl "ROCK INSTINCT"
Film data loaded from Memcached

The Python memcache module interfaces to memcached servers, and is written in pure python (i.e. without using one of the C APIs). You can download and install a copy from Python Memcached.

To install, download the package and then run the Python installer:

python setup.py install
running install
running bdist_egg
running egg_info
creating python_memcached.egg-info
...
removing 'build/bdist.linux-x86_64/egg' (and everything under it)
Processing python_memcached-1.43-py2.4.egg
creating /usr/lib64/python2.4/site-packages/python_memcached-1.43-py2.4.egg
Extracting python_memcached-1.43-py2.4.egg to /usr/lib64/python2.4/site-packages
Adding python-memcached 1.43 to easy-install.pth file

Installed /usr/lib64/python2.4/site-packages/python_memcached-1.43-py2.4.egg
Processing dependencies for python-memcached==1.43
Finished processing dependencies for python-memcached==1.43

Once installed, the memcache module provides a class-based interface to your memcached servers. Serialization of Python structures is handled by using the Python cPickle or pickle modules.

To create a new memcache interface, import the memcache module and create a new instance of the memcache.Client class:

import memcache
memc = memcache.Client(['127.0.0.1:11211'])

The first argument should be an array of strings containing the server and port number for each memcached instance you want to use. You can enable debugging by setting the optional debug parameter to 1.

By default, the hashing mechanism used is crc32. This provides a basic module hashing algorithm for selecting among multiple servers. You can change the function used by setting the value of memcache.serverHashFunction to the alternate function you want to use. For example:

from zlib import adler32
memcache.serverHashFunction = adler32

Once you have defined the servers to use within the memcache instance, the core functions provide the same functionality as in the generic interface specification. A summary of the supported functions is provided in the table below.

memc.get_multi(['a','b'], key_prefix='users:')

An example showing the storage and retrieval of information to a memcache instance, loading the raw data from MySQL, is shown below:

import sys
import MySQLdb
import memcache

memc = memcache.Client(['127.0.0.1:11211'], debug=1);

try:
    conn = MySQLdb.connect (host = "localhost",
                            user = "sakila",
                            passwd = "password",
                            db = "sakila")
except MySQLdb.Error, e:
     print "Error %d: %s" % (e.args[0], e.args[1])
     sys.exit (1)

popularfilms = memc.get('top5films')

if not popularfilms:
    cursor = conn.cursor()
    cursor.execute('select film_id,title from film order by rental_rate desc limit 5')
    rows = cursor.fetchall()
    memc.set('top5films',rows,60)
    print "Updated memcached with MySQL data"
else:
    print "Loaded data from memcached"
    for row in popularfilms:
        print "%s, %s" % (row[0], row[1])

When executed for the first time, the data is loaded from the MySQL database and stored to the memcached server.

shell> python memc_python.py
Updated memcached with MySQL data

The data is automatically serialized using cPickle/pickle. This means when you load the data back from memcached, you can use the object directly. In the example above, the information stored to memcached is in the form of rows from a Python DB cursor. When accessing the information (within the 60 second expiry time), the data is loaded from memcached and dumped:

shell> python memc_python.py
Loaded data from memcached
2, ACE GOLDFINGER
7, AIRPLANE SIERRA
8, AIRPORT POLLOCK
10, ALADDIN CALENDAR
13, ALI FOREVER

The serialization and deserialization happens automatically, but be aware that serialization of Python data may be incompatible with other interfaces and languages. You can change the serialization module used during initialization, for example to use JSON, which will be more easily exchanged.

PHP provides support for the Memcache functions through a PECL extension. To enable the PHP memcache extensions, you must build PHP using the --enable-memcache option to configure when building from source.

If you are installing on a RedHat based server, you can install the php-pecl-memcache RPM:

root-shell> yum --install php-pecl-memcache

On Debian based distributions, use the php-memcache package.

You can set global runtime configuration options by specifying the values in the following table within your php.ini file.

To create a connection to a memcached server, you need to create a new Memcache object and then specifying the connection options. For example:

<?php

$cache = new Memcache;
$cache->connect('localhost',11121);
?>

This opens an immediate connection to the specified server.

To use multiple memcached servers, you need to add servers to the memcache object using addServer():

bool Memcache::addServer ( string $host [, int $port [, bool $persistent 
                 [, int $weight [, int $timeout [, int $retry_interval 
                 [, bool $status [, callback $failure_callback 
                 ]]]]]]] )

The server management mechanism within the php-memcache module is a critical part of the interface as it controls the main interface to the memcached instances and how the different instances are selected through the hashing mechanism.

To create a simple connection to two memcached instances:

<?php

$cache = new Memcache;
$cache->addServer('192.168.0.100',11211);
$cache->addServer('192.168.0.101',11211);
?>

In this scenario the instance connection is not explicitly opened, but only opened when you try to store or retrieve a value. You can enable persistent connections to memcached instances by setting the $persistent argument to true. This is the default setting, and will cause the connections to remain open.

To help control the distribution of keys to different instances, you should use the global memcache.hash_strategy setting. This sets the hashing mechanism used to select. You can also add an additional weight to each server, which effectively increases the number of times the instance entry appears in the instance list, therefore increasing the likelihood of the instance being chosen over other instances. To set the weight, set the value of the $weight argument to more than one.

The functions for setting and retrieving information are identical to the generic functional interface offered by memcached, as shown in this table.

A full example of the PECL memcache interface is provided below. The code loads film data from the Sakila database when the user provides a film name. The data stored into the memcached instance is recorded as a mysqli result row, and the API automatically serializes the information for you.

<?php

$memc = new Memcache;
$memc->addServer('localhost','11211');
?>

<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en">
<head>
 <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
 <title>Simple Memcache Lookup</title>
</head>
<body>
<form method="post">
  <p><b>Film</b>: <input type="text" size="20" name="film"></p>
<input type="submit">
</form>
<hr/>

<?php

  echo "Loading data...\n";

$value = $memc->get($_REQUEST['film']);

if ($value)
  {
    printf("<p>Film data for %s loaded from memcache</p>",$value['title']);

    foreach (array_keys($value) as $key)
      { 
	printf("<p><b>%s</b>: %s</p>",$key, $value[$key]);
      } 
  }
 else
   {
     $con = new mysqli('localhost','sakila','password','sakila') or
       die ("<h1>Database problem</h1>" . mysqli_connect_error());

     $result = $con->query(sprintf('select * from film where title ="%s"',$_REQUEST['film']));

     $row = $result->fetch_array(MYSQLI_ASSOC);

     $memc->set($row['title'],$row);

     printf("<p>Loaded %s from MySQL</p>",$row['title']);
   }

?>

With PHP, the connections to the memcached instances are kept open as long as the PHP and associated Apache instance remain running. When adding a removing servers from the list in a running instance (for example, when starting another script that mentions additional servers), the connections will be shared, but the script will only select among the instances explicitly configured within the script.

To ensure that changes to the server list within a script do not cause problems, make sure to use the consistent hashing mechanism.

There are a number of different modules for interfacing to memcached within Ruby. The Ruby-MemCache client library provides a native interface to memcached that does not require any external libraries, such as libmemcached. You can obtain the installer package from http://www.deveiate.org/projects/RMemCache.

To install, extract the package and then run install.rb:

shell> install.rb

If you have RubyGems, you can install the Ruby-MemCache gem:

shell> gem install Ruby-MemCache
Bulk updating Gem source index for: http://gems.rubyforge.org
Install required dependency io-reactor? [Yn]  y
Successfully installed Ruby-MemCache-0.0.1
Successfully installed io-reactor-0.05
Installing ri documentation for io-reactor-0.05...
Installing RDoc documentation for io-reactor-0.05...

To use a memcached instance from within Ruby, create a new instance of the MemCache object.

require 'memcache'
memc = MemCache::new '192.168.0.100:11211'

You can add a weight to each server to increase the likelihood of the server being selected during hashing by appending the weight count to the server hostname/port string:

require 'memcache'
memc = MemCache::new '192.168.0.100:11211:3'

To add servers to an existing list, you can append them directly to the MemCache object:

memc += ["192.168.0.101:11211"]

To set data into the cache, you can just assign a value to a key within the new cache object, which works just like a standard Ruby hash object:

memc["key"] = "value"

Or to retrieve the value:

print memc["key"]

For more explicit actions, you can use the method interface, which mimics the main memcached API functions, as summarized in the table below.

The com.danga.MemCached class within Java provides a native interface to memcached instances. You can obtain the client from http://whalin.com/memcached/. The Java class uses hashes that are compatible with libmemcached, so you can mix and match Java and libmemcached applications accessing the same memcached instances. The serialization between Java and other interfaces will not be compatible. If this is a problem, use JSON or a similar non-binary serialization format.

On most systems you can download the package and use the jar directly. On OpenSolaris, use pkg to install the SUNWmemcached-java package.

To use the com.danga.MemCached interface, you create a MemCachedClient instance and then configure the list of servers by configuring the SockIOPool. Through the pool specification you set up the server list, weighting, and the connection parameters to optimized the connections between your client and the memcached instances that you configure.

Generally you can configure the memcached interface once within a single class and then use this interface throughout the rest of your application.

For example, to create a basic interface, first configure the MemCachedClient and base SockIOPool settings:

public class MyClass {
                                        
    protected static MemCachedClient mcc = new MemCachedClient();
                                      
    static {
	                                      
        String[] servers =
            {
                "localhost:11211",
            };
	
        Integer[] weights = { 1 };
	                                      
        SockIOPool pool = SockIOPool.getInstance();
	                                      
        pool.setServers( servers );
        pool.setWeights( weights );

In the above sample, the list of servers is configured by creating an array of the memcached instances that you want to use. You can then configure individual weights for each server.

The remainder of the properties for the connection are optional, but you can set the connection numbers (initial connections, minimum connections, maximum connections, and the idle timeout) by setting the pool parameters:

pool.setInitConn( 5 );
pool.setMinConn( 5 );
pool.setMaxConn( 250 );
pool.setMaxIdle( 1000 * 60 * 60 * 6 

Once the parameters have been configured, initialize the connection pool:

pool.initialize();

The pool, and the connection to your memcached instances should now be ready to use.

To set the hashing algorithm used to select the server used when storing a given key you can use pool.setHashingAlg():

pool.setHashingAlg( SockIOPool.NEW_COMPAT_HASH );

Valid values ares NEW_COMPAT_HASH, OLD_COMPAT_HASH and NATIVE_HASH are also basic modula hashing algorithms. For a consistent hashing algorithm, use CONSISTENT_HASH. These constants are equivalent to the corresponding hash settings within libmemcached.

The memcached MySQL User Defined Functions (UDFs) enable you to set and retrieve objects from within MySQL 5.0 or greater.

To install the MySQL memcached UDFs, download the UDF package from http://tangent.org/586/Memcached_Functions_for_MySQL.html. You will need to unpack the package and run configure to configure the build process. When running configure, use the --with-mysql option and specify the location of the mysql_config command. Note that you must be running :

shell> tar zxf memcached_functions_mysql-0.5.tar.gz
shell> cd memcached_functions_mysql-0.5
shell> ./configure --with-mysql-config=/usr/local/mysql/bin/mysql_config

Now build and install the functions:

shell> make
shell> make install

You may want to copy the MySQL memcached UDFs into your MySQL plugins directory:

shell> cp /usr/local/lib/libmemcached_functions_mysql* /usr/local/mysql/lib/mysql/plugins/

Once installed, you must initialize the function within MySQL using CREATE and specifying the return value and library. For example, to add the memc_get() function:

mysql> CREATE FUNCTION memc_get RETURNS STRING SONAME "libmemcached_functions_mysql.so";

You must repeat this process for each function that you want to provide access to within MySQL. Once you have created the association, the information will be retained, even over restarts of the MySQL server. You can simplify the process by using the SQL script provided in the memcached UDFs package:

shell> mysql <sql/install_functions.sql

Alternatively, if you have Perl installed, then you can use the supplied Perl script, which will check for the existence of each function and create the function/library association if it has not already been defined:

shell> utils/install.pl --silent

The --silent option installs everything automatically. Without this option, the script will ask whether you want to install each of the available functions.

The interface remains consistent with the other APIs and interfaces. To set up a list of servers, use the memc_servers_set() function, which accepts a single string containing and comma-separated list of servers:

mysql> SELECT memc_servers_set('192.168.0.1:11211,192.168.0.2:11211');

To set a value, use memc_set:

mysql> SELECT memc_set('myid', 'myvalue');

To retrieve a stored value:

mysql> SELECT memc_get('myid');

The list of functions supported by the UDFs, in relation to the standard protocol functions, is shown in the table below.

The memcached UDFs also support the different behaviors as provided by the libmemcached library. You can set these by using the memc_servers_behavior_set() function. For more information on libmemcached behaviors, see Section 15.3.1, “Using libmemcached”.

The output of the general statistics provides an overview of the performance and use of the memcached instance. The statistics returned by the command and their meaning is shown in the table below.

The most useful statistics from those given here are the number of cache hits, misses, and evictions.

A large number of get_misses may just be an indication that the cache is still being populated with information. The number should, over time, decrease in comparison to the number of cache get_hits. If, however, you have a large number of cache misses compared to cache hits after an extended period of execution, it may be an indication that the size of the cache is too small and you either need to increase the total memory size, or increase the number of the memcached instances to improve the hit ratio.

A large number of evictions from the cache, particularly in comparison to the number of items stored is a sign that your cache is too small to hold the amount of information that you regularly want to keep cached. Instead of items being retained in the cache, items are being evicted to make way for new items keeping the turnover of items in the cache high, reducing the efficiency of the cache.

To get the slabs statistics, use the stats slabs command, or the API equivalent.

The slab statistics provide you with information about the slabs that have created and allocated for storing information within the cache. You get information both on each individual slab-class and total statistics for the whole slab.

STAT 1:chunk_size 104
STAT 1:chunks_per_page 10082
STAT 1:total_pages 1
STAT 1:total_chunks 10082
STAT 1:used_chunks 10081
STAT 1:free_chunks 1
STAT 1:free_chunks_end 10079
STAT 9:chunk_size 696
STAT 9:chunks_per_page 1506
STAT 9:total_pages 63
STAT 9:total_chunks 94878
STAT 9:used_chunks 94878
STAT 9:free_chunks 0
STAT 9:free_chunks_end 0
STAT active_slabs 2
STAT total_malloced 67083616
END

Individual stats for each slab class are prefixed with the slab ID. A unique ID is given to each allocated slab from the smallest size up to the largest. The prefix number indicates the slab class number in relation to the calculated chunk from the specified growth factor. Hence in the example, 1 is the first chunk size and 9 is the 9th chunk allocated size.

The different parameters returned for each chunk size and the totals are shown in the table below:

The key values in the slab statistics are the chunk_size, and the corresponding total_chunks and used_chunks parameters. These given an indication of the size usage of the chunks within the system. Remember that one key/value pair will be placed into a chunk of a suitable size.

From these stats you can get an idea of your size and chunk allocation and distribution. If you are storing many items with a number of largely different sizes, then you may want to adjust the chunk size growth factor to increase in larger steps to prevent chunk and memory wastage. A good indication of a bad growth factor is a high number of different slab classes, but with relatively few chunks actually in use within each slab. Increasing the growth factor will create fewer slab classes and therefore make better use of the allocated pages.

To get the items statistics, use the stats items command, or the API equivalent.

The items statistics give information about the individual items allocated within a given slab class.

STAT items:2:number 1
STAT items:2:age 452
STAT items:2:evicted 0
STAT items:2:outofmemory 0
STAT items:27:number 1
STAT items:27:age 452
STAT items:27:evicted 0
STAT items:27:outofmemory 0

The prefix number against each statistics relates to the corresponding chunk size, as returned by the stats slabs statistics. The result is a display of the number of items stored within each chunk within each slab size, and specific statistics about their age, eviction counts, and out of memory counts. A summary of the statistics is given in the table below.

Item level statistics can be used to determine how many items are stored within a given slab and their freshness and recycle rate. You can use this to help identify whether there are certain slab classes that are triggering a much larger number of evictions that others.

To get size statistics, use the stats sizes command, or the API equivalent.

The size statistics provide information about the sizes and number of items of each size within the cache. The information is returned as two columns, the first column is the size of the item (rounded up to the nearest 32 byte boundary), and the second column is the count of the number of items of that size within the cache:

96 35
128 38
160 807
192 804
224 410
256 222
288 83
320 39
352 53
384 33
416 64
448 51
480 30
512 54
544 39
576 10065

The item size statistics are useful only to determine the sizes of the objects you are storing. Since the actual memory allocation is relevant only in terms of the chunk size and page size, the information will only be useful during a careful debugging or diagnostic session.