Measuring cache efficiency
PECL/mysqlnd_qc offers three ways to measure the cache efficiency. The function mysqlnd_qc_get_normalized_query_trace_log() returns statistics aggregated by the normalized query string, mysqlnd_qc_get_cache_info() gives storage handler specific information which includes a list of all cached items, depending on the storage handler. Additionally, the core of PECL/mysqlnd_qc collects high-level summary statistics aggregated per PHP process. The high-level statistics are returned by mysqlnd_qc_get_core_stats().
The functions mysqlnd_qc_get_normalized_query_trace_log() and mysqlnd_qc_get_core_stats() will not collect data unless data collection has been enabled through their corresponding PHP configuration directives. Data collection is disabled by default for performance considerations. It is configurable with the mysqlnd_qc.time_statistics option, which determines if timing information should be collected. Collection of time statistics is enabled by default but only performed if data collection as such has been enabled. Recording time statistics causes extra system calls. In most cases, the benefit of the monitoring outweighs any potential performance penalty of the additional system calls.
Example #1 Collecting statistics data with the mysqlnd_qc.time_statistics ini setting
mysqlnd_qc.enable_qc=1 mysqlnd_qc.collect_statistics=1
<?php
/* connect to MySQL */
$mysqli = new mysqli("host", "user", "password", "schema", "port", "socket");
$mysqli->query("DROP TABLE IF EXISTS test");
$mysqli->query("CREATE TABLE test(id INT)");
$mysqli->query("INSERT INTO test(id) VALUES (1), (2), (3)");
/* dummy queries */
for ($i = 1; $i <= 4; $i++) {
$query = sprintf("/*%s*/SELECT id FROM test WHERE id = %d", MYSQLND_QC_ENABLE_SWITCH, $i % 2);
$res = $mysqli->query($query);
$res->free();
}
var_dump(mysqlnd_qc_get_core_stats());
?>
The above examples will output something similar to:
array(26) {
["cache_hit"]=>
string(1) "2"
["cache_miss"]=>
string(1) "2"
["cache_put"]=>
string(1) "2"
["query_should_cache"]=>
string(1) "4"
["query_should_not_cache"]=>
string(1) "3"
["query_not_cached"]=>
string(1) "3"
["query_could_cache"]=>
string(1) "4"
["query_found_in_cache"]=>
string(1) "2"
["query_uncached_other"]=>
string(1) "0"
["query_uncached_no_table"]=>
string(1) "0"
["query_uncached_no_result"]=>
string(1) "0"
["query_uncached_use_result"]=>
string(1) "0"
["query_aggr_run_time_cache_hit"]=>
string(2) "28"
["query_aggr_run_time_cache_put"]=>
string(3) "900"
["query_aggr_run_time_total"]=>
string(3) "928"
["query_aggr_store_time_cache_hit"]=>
string(2) "14"
["query_aggr_store_time_cache_put"]=>
string(2) "40"
["query_aggr_store_time_total"]=>
string(2) "54"
["receive_bytes_recorded"]=>
string(3) "136"
["receive_bytes_replayed"]=>
string(3) "136"
["send_bytes_recorded"]=>
string(2) "84"
["send_bytes_replayed"]=>
string(2) "84"
["slam_stale_refresh"]=>
string(1) "0"
["slam_stale_hit"]=>
string(1) "0"
["request_counter"]=>
int(1)
["process_hash"]=>
int(1929695233)
}
For a quick overview, call mysqlnd_qc_get_core_stats(). It delivers cache usage, cache timing and traffic related statistics. Values are aggregated on a per process basis for all queries issued by any PHP MySQL API call.
Some storage handler, such as the default handler, can report cache entries, statistics related to the entries and meta data for the underlying query through the mysqlnd_qc_get_cache_info() function. Please note, that the information returned depends on the storage handler. Values are aggregated on a per process basis.
Example #2 Example mysqlnd_qc_get_cache_info() usage
mysqlnd_qc.enable_qc=1
<?php
/* connect to MySQL */
$mysqli = new mysqli("host", "user", "password", "schema", "port", "socket");
$mysqli->query("DROP TABLE IF EXISTS test");
$mysqli->query("CREATE TABLE test(id INT)");
$mysqli->query("INSERT INTO test(id) VALUES (1), (2), (3)");
/* dummy queries to fill the query trace */
for ($i = 1; $i <= 4; $i++) {
$query = sprintf("/*%s*/SELECT id FROM test WHERE id = %d", MYSQLND_QC_ENABLE_SWITCH, $i % 2);
$res = $mysqli->query($query);
$res->free();
}
var_dump(mysqlnd_qc_get_cache_info());
?>
The above examples will output something similar to:
array(4) {
["num_entries"]=>
int(2)
["handler"]=>
string(7) "default"
["handler_version"]=>
string(5) "1.0.0"
["data"]=>
array(2) {
["Localhost via UNIX socket
3306
root
test|/*qc=on*/SELECT id FROM test WHERE id = 1"]=>
array(2) {
["statistics"]=>
array(11) {
["rows"]=>
int(1)
["stored_size"]=>
int(71)
["cache_hits"]=>
int(1)
["run_time"]=>
int(391)
["store_time"]=>
int(27)
["min_run_time"]=>
int(16)
["max_run_time"]=>
int(16)
["min_store_time"]=>
int(8)
["max_store_time"]=>
int(8)
["avg_run_time"]=>
int(8)
["avg_store_time"]=>
int(4)
}
["metadata"]=>
array(1) {
[0]=>
array(8) {
["name"]=>
string(2) "id"
["orig_name"]=>
string(2) "id"
["table"]=>
string(4) "test"
["orig_table"]=>
string(4) "test"
["db"]=>
string(4) "test"
["max_length"]=>
int(1)
["length"]=>
int(11)
["type"]=>
int(3)
}
}
}
["Localhost via UNIX socket
3306
root
test|/*qc=on*/SELECT id FROM test WHERE id = 0"]=>
array(2) {
["statistics"]=>
array(11) {
["rows"]=>
int(0)
["stored_size"]=>
int(65)
["cache_hits"]=>
int(1)
["run_time"]=>
int(299)
["store_time"]=>
int(13)
["min_run_time"]=>
int(11)
["max_run_time"]=>
int(11)
["min_store_time"]=>
int(6)
["max_store_time"]=>
int(6)
["avg_run_time"]=>
int(5)
["avg_store_time"]=>
int(3)
}
["metadata"]=>
array(1) {
[0]=>
array(8) {
["name"]=>
string(2) "id"
["orig_name"]=>
string(2) "id"
["table"]=>
string(4) "test"
["orig_table"]=>
string(4) "test"
["db"]=>
string(4) "test"
["max_length"]=>
int(0)
["length"]=>
int(11)
["type"]=>
int(3)
}
}
}
}
}
It is possible to further break down the granularity of statistics to the level of the normalized statement string. The normalized statement string is the statements string with all parameters replaced with question marks. For example, the two statements SELECT id FROM test WHERE id = 0 and SELECT id FROM test WHERE id = 1 are normalized into SELECT id FROM test WHERE id = ?. Their both statistics are aggregated into one entry for SELECT id FROM test WHERE id = ?.
Example #3 Example mysqlnd_qc_get_normalized_query_trace_log() usage
mysqlnd_qc.enable_qc=1 mysqlnd_qc.collect_normalized_query_trace=1
<?php
/* connect to MySQL */
$mysqli = new mysqli("host", "user", "password", "schema", "port", "socket");
$mysqli->query("DROP TABLE IF EXISTS test");
$mysqli->query("CREATE TABLE test(id INT)");
$mysqli->query("INSERT INTO test(id) VALUES (1), (2), (3)");
/* dummy queries to fill the query trace */
for ($i = 1; $i <= 4; $i++) {
$query = sprintf("/*%s*/SELECT id FROM test WHERE id = %d", MYSQLND_QC_ENABLE_SWITCH, $i % 2);
$res = $mysqli->query($query);
$res->free();
}
var_dump(mysqlnd_qc_get_normalized_query_trace_log());
?>
The above examples will output something similar to:
array(4) {
[0]=>
array(9) {
["query"]=>
string(25) "DROP TABLE IF EXISTS test"
["occurences"]=>
int(0)
["eligible_for_caching"]=>
bool(false)
["avg_run_time"]=>
int(0)
["min_run_time"]=>
int(0)
["max_run_time"]=>
int(0)
["avg_store_time"]=>
int(0)
["min_store_time"]=>
int(0)
["max_store_time"]=>
int(0)
}
[1]=>
array(9) {
["query"]=>
string(27) "CREATE TABLE test (id INT )"
["occurences"]=>
int(0)
["eligible_for_caching"]=>
bool(false)
["avg_run_time"]=>
int(0)
["min_run_time"]=>
int(0)
["max_run_time"]=>
int(0)
["avg_store_time"]=>
int(0)
["min_store_time"]=>
int(0)
["max_store_time"]=>
int(0)
}
[2]=>
array(9) {
["query"]=>
string(46) "INSERT INTO test (id ) VALUES (? ), (? ), (? )"
["occurences"]=>
int(0)
["eligible_for_caching"]=>
bool(false)
["avg_run_time"]=>
int(0)
["min_run_time"]=>
int(0)
["max_run_time"]=>
int(0)
["avg_store_time"]=>
int(0)
["min_store_time"]=>
int(0)
["max_store_time"]=>
int(0)
}
[3]=>
array(9) {
["query"]=>
string(31) "SELECT id FROM test WHERE id =?"
["occurences"]=>
int(4)
["eligible_for_caching"]=>
bool(true)
["avg_run_time"]=>
int(179)
["min_run_time"]=>
int(11)
["max_run_time"]=>
int(393)
["avg_store_time"]=>
int(12)
["min_store_time"]=>
int(7)
["max_store_time"]=>
int(25)
}
}
The source distribution of PECL/mysqlnd_qc contains a directory web/ in which web based monitoring scripts can be found which give an example how to write a cache monitor. Please, follow the instructions given in the source.
Since PECL/mysqlnd_qc 1.1.0 it is possible to write statistics into a log file. Please, see mysqlnd_qc.collect_statistics_log_file.
English translation
You have asked to visit this site in English. For now, only the interface is translated, but not all the content yet.If you want to help me in translations, your contribution is welcome. All you need to do is register on the site, and send me a message asking me to add you to the group of translators, which will give you the opportunity to translate the pages you want. A link at the bottom of each translated page indicates that you are the translator, and has a link to your profile.
Thank you in advance.
Document created the 30/01/2003, last modified the 26/10/2018
Source of the printed document:https://www.gaudry.be/en/php-rf-mysqlnd-qc.cache-efficiency.html
The infobrol is a personal site whose content is my sole responsibility. The text is available under CreativeCommons license (BY-NC-SA). More info on the terms of use and the author.
References
These references and links indicate documents consulted during the writing of this page, or which may provide additional information, but the authors of these sources can not be held responsible for the content of this page.
The author This site is solely responsible for the way in which the various concepts, and the freedoms that are taken with the reference works, are presented here. Remember that you must cross multiple source information to reduce the risk of errors.
