Examples
Measuring cache efficiency
Measuring cache efficiency
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.