The easiest way to view high-level information about your Manticore node is by running status in the MySQL client. It will display information about various aspects, such as:
- Current version
- Whether SSL is in effect or not
- Current TCP port/Unix socket
- Uptime
- Number of threads
- Number of jobs in queue
- Number of connections (
clients) - Number of tasks being processed currently
- Number of queries executed since the start
- Number of jobs in queue and number of tasks, normalized by the number of threads
‹›
- SQL
SQL
📋
⚙
mysql> status
‹›
Response
--------------
mysql Ver 14.14 Distrib 5.7.30, for Linux (x86_64) using EditLine wrapper
Connection id: 378
Current database: Manticore
Current user: Usual
SSL: Not in use
Current pager: stdout
Using outfile: ''
Using delimiter: ;
Server version: 3.4.3 a48c61d6@200702 coroutines git branch coroutines_work_junk...origin/coroutines_work_junk
Protocol version: 10
Connection: 0 via TCP/IP
Server characterset:
Db characterset:
Client characterset: utf8
Conn. characterset: utf8
TCP port: 8306
Uptime: 23 hours 6 sec
Threads: 12 Queue: 3 Clients: 1 Vip clients: 0 Tasks: 5 Queries: 318967 Wall: 7h CPU: 0us
Queue/Th: 0.2 Tasks/Th: 0.4
--------------SHOW STATUS [ LIKE pattern ]SHOW STATUS is an SQL statement that presents various helpful performance counters. IO and CPU counters will only be available if searchd was started with the --iostats and --cpustats switches, respectively (or if they were enabled via SET GLOBAL iostats/cpustats=1).
‹›
- SQL
SQL
📋
⚙
SHOW STATUS;
‹›
Response
+-------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------+
| Counter | Value |
+-------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------+
| uptime | 182 |
| connections | 368 |
| maxed_out | 0 |
| version | 6.3.7 b10359434@24100213 dev (columnar 2.3.1 bd59d08@24093015) (secondary 2.3.1 bd59d08@24093015) (knn 2.3.1 bd59d08@24093015) (buddy v2.3.13) |
| mysql_version | 6.3.7 b10359434@24100213 dev (columnar 2.3.1 bd59d08@24093015) (secondary 2.3.1 bd59d08@24093015) (knn 2.3.1 bd59d08@24093015) |
| command_search | 4 |
| command_excerpt | 0 |
| command_update | 2 |
| command_keywords | 0 |
| command_persist | 0 |
| command_status | 8 |
| command_flushattrs | 0 |
| command_sphinxql | 0 |
| command_ping | 0 |
| command_delete | 3 |
| command_set | 0 |
| command_insert | 3 |
| command_replace | 3 |
| command_commit | 0 |
| command_suggest | 0 |
| command_json | 0 |
| command_callpq | 0 |
| command_cluster | 0 |
| command_getfield | 0 |
| insert_replace_stats_ms_avg | 42.625 35.895 35.895 |
| insert_replace_stats_ms_min | 0.096 0.096 0.096 |
| insert_replace_stats_ms_max | 85.154 85.154 85.154 |
| insert_replace_stats_ms_pct95 | 42.625 42.625 42.625 |
| insert_replace_stats_ms_pct99 | 42.625 42.625 42.625 |
| search_stats_ms_avg | 0.209 0.188 0.188 |
| search_stats_ms_min | 0.205 0.058 0.058 |
| search_stats_ms_max | 0.214 0.278 0.278 |
| search_stats_ms_pct95 | 0.214 0.278 0.278 |
| search_stats_ms_pct99 | 0.214 0.278 0.278 |
| update_stats_ms_avg | 0.024 0.024 0.024 |
| update_stats_ms_min | 0.007 0.007 0.007 |
| update_stats_ms_max | 0.042 0.042 0.042 |
| update_stats_ms_pct95 | 0.042 0.042 0.042 |
| update_stats_ms_pct99 | 0.042 0.042 0.042 |
| agent_connect | 0 |
| agent_tfo | 0 |
| agent_retry | 0 |
| queries | 6 |
| dist_queries | 0 |
| workers_total | 32 |
| workers_active | 3 |
| workers_clients | 1 |
| workers_clients_vip | 0 |
| workers_clients_buddy | 1 |
| work_queue_length | 6 |
| load | 0.03 0.03 0.03 |
| load_primary | 0.00 0.00 0.00 |
| load_secondary | 0.00 0.00 0.00 |
| query_wall | 0.000 |
| query_cpu | OFF |
| dist_wall | 0.000 |
| dist_local | 0.000 |
| dist_wait | 0.000 |
| query_reads | OFF |
| query_readkb | OFF |
| query_readtime | OFF |
| avg_query_wall | 0.000 |
| avg_query_cpu | OFF |
| avg_dist_wall | 0.000 |
| avg_dist_local | 0.000 |
| avg_dist_wait | 0.000 |
| avg_query_reads | OFF |
| avg_query_readkb | OFF |
| avg_query_readtime | OFF |
| qcache_max_bytes | 16777216 |
| qcache_thresh_msec | 3000 |
| qcache_ttl_sec | 60 |
| qcache_cached_queries | 0 |
| qcache_used_bytes | 0 |
| qcache_hits | 0 |
+-------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------+An optional LIKE clause is supported, allowing you to select only the variables that match a specific pattern. The pattern syntax follows standard SQL wildcards, where % represents any number of any characters, and _ represents a single character.
‹›
- qcache
- perf_stats
📋
⚙
SHOW STATUS LIKE 'qcache%';SHOW STATUS LIKE '%stats_ms%';
‹›
Response
+-----------------------+-------+
| Counter | Value |
+-----------------------+-------+
| qcache_max_bytes | 0 |
| qcache_thresh_msec | 3000 |
| qcache_ttl_sec | 60 |
| qcache_cached_queries | 0 |
| qcache_used_bytes | 0 |
| qcache_hits | 0 |
+-----------------------+-------++-------------------------------+-------------------+
| Counter | Value |
+-------------------------------+-------------------+
| insert_replace_stats_ms_avg | N/A 35.895 35.895 |
| insert_replace_stats_ms_min | N/A 0.096 0.096 |
| insert_replace_stats_ms_max | N/A 85.154 85.154 |
| insert_replace_stats_ms_pct95 | N/A 42.625 42.625 |
| insert_replace_stats_ms_pct99 | N/A 42.625 42.625 |
| search_stats_ms_avg | N/A 0.188 0.188 |
| search_stats_ms_min | N/A 0.058 0.058 |
| search_stats_ms_max | N/A 0.278 0.278 |
| search_stats_ms_pct95 | N/A 0.278 0.278 |
| search_stats_ms_pct99 | N/A 0.278 0.278 |
| update_stats_ms_avg | N/A 0.024 0.024 |
| update_stats_ms_min | N/A 0.007 0.007 |
| update_stats_ms_max | N/A 0.042 0.042 |
| update_stats_ms_pct95 | N/A 0.042 0.042 |
| update_stats_ms_pct99 | N/A 0.042 0.042 |
+-------------------------------+-------------------+The SHOW STATUS command gives a detailed report on various performance metrics in Manticore, including query time statistics for insert/replace, search, and update queries. These stats are calculated over sliding windows of 1, 5, and 15 minutes, showing average, minimum, maximum, and 95th/99th percentile values for query times.
These metrics help track performance over specific time intervals, making it easier to spot trends in query response times and find possible bottlenecks.
The following metrics are part of the SHOW STATUS output:
*_avg: The average query time for each type of query over the last 1, 5, and 15 minutes.*_min: The shortest query time recorded for each query type.*_max: The longest query time recorded for each query type.*_pct95: The time under which 95% of queries are completed.*_pct99: The time under which 99% of queries are completed.
These statistics are provided separately for insert/replace (insert_replace_stats_*), search (search_stats_*), and update (update_stats_*) queries, offering detailed insights into the performance of different operations.
If no queries are executed during the monitored interval, the system will display N/A.
‹›
- perf_stats
perf_stats
📋
⚙
SHOW STATUS LIKE '%stats_ms%';
‹›
Response
+-------------------------------+-------------------+
| Counter | Value |
+-------------------------------+-------------------+
| insert_replace_stats_ms_avg | N/A 35.895 35.895 |
| insert_replace_stats_ms_min | N/A 0.096 0.096 |
| insert_replace_stats_ms_max | N/A 85.154 85.154 |
| insert_replace_stats_ms_pct95 | N/A 42.625 42.625 |
| insert_replace_stats_ms_pct99 | N/A 42.625 42.625 |
| search_stats_ms_avg | N/A 0.188 0.188 |
| search_stats_ms_min | N/A 0.058 0.058 |
| search_stats_ms_max | N/A 0.278 0.278 |
| search_stats_ms_pct95 | N/A 0.278 0.278 |
| search_stats_ms_pct99 | N/A 0.278 0.278 |
| update_stats_ms_avg | N/A 0.024 0.024 |
| update_stats_ms_min | N/A 0.007 0.007 |
| update_stats_ms_max | N/A 0.042 0.042 |
| update_stats_ms_pct95 | N/A 0.042 0.042 |
| update_stats_ms_pct99 | N/A 0.042 0.042 |
+-------------------------------+-------------------+SHOW SETTINGS is an SQL statement that displays the current settings from your configuration file. The setting names are represented in the following format: 'config_section_name'.'setting_name'
The result also includes two additional values:
configuration_file- The path to the configuration fileworker_pid- The process ID of the runningsearchdinstance
‹›
- SQL
SQL
📋
⚙
SHOW SETTINGS;
‹›
Response
+--------------------------+-------------------------------------+
| Setting_name | Value |
+--------------------------+-------------------------------------+
| configuration_file | /etc/manticoresearch/manticore.conf |
| worker_pid | 658 |
| searchd.listen | 0.0.0:9312 |
| searchd.listen | 0.0.0:9306:mysql |
| searchd.listen | 0.0.0:9308:http |
| searchd.log | /var/log/manticore/searchd.log |
| searchd.query_log | /var/log/manticore/query.log |
| searchd.pid_file | /var/run/manticore/searchd.pid |
| searchd.data_dir | /var/lib/manticore |
| searchd.query_log_format | sphinxql |
| searchd.binlog_path | /var/lib/manticore/binlog |
| common.plugin_dir | /usr/local/lib/manticore |
| common.lemmatizer_base | /usr/share/manticore/morph/ |
+--------------------------+-------------------------------------+
13 rows in set (0.00 sec)SHOW AGENT ['agent_or_index'] STATUS [ LIKE pattern ]SHOW AGENT STATUS displays the statistics of remote agents or a distributed table. It includes values such as the age of the last request, last answer, the number of various types of errors and successes, and so on. Statistics are displayed for every agent for the last 1, 5, and 15 intervals, each consisting of ha_period_karma seconds.
‹›
- SQL
- PHP
- Python
- javascript
- Java
- C#
- TypeScript
- Go
📋
⚙
SHOW AGENT STATUS;$client->nodes()->agentstatus();utilsApi.sql('SHOW AGENT STATUS')res = await utilsApi.sql("SHOW AGENT STATUS");utilsApi.sql("SHOW AGENT STATUS");utilsApi.Sql("SHOW AGENT STATUS");res = await utilsApi.sql("SHOW AGENT STATUS");res := apiClient.UtilsAPI.Sql(context.Background()).Body("SHOW AGENT STATUS").Execute()
‹›
Response
+------------------------------------+----------------------------+
| Variable_name | Value |
+------------------------------------+----------------------------+
| status_period_seconds | 60 |
| status_stored_periods | 15 |
| ag_0_hostname | 192.168.0.202:6713 |
| ag_0_references | 2 |
| ag_0_lastquery | 0.41 |
| ag_0_lastanswer | 0.19 |
| ag_0_lastperiodmsec | 222 |
| ag_0_pingtripmsec | 10.521 |
| ag_0_errorsarow | 0 |
| ag_0_1periods_query_timeouts | 0 |
| ag_0_1periods_connect_timeouts | 0 |
| ag_0_1periods_connect_failures | 0 |
| ag_0_1periods_network_errors | 0 |
| ag_0_1periods_wrong_replies | 0 |
| ag_0_1periods_unexpected_closings | 0 |
| ag_0_1periods_warnings | 0 |
| ag_0_1periods_succeeded_queries | 27 |
| ag_0_1periods_msecsperquery | 232.31 |
| ag_0_5periods_query_timeouts | 0 |
| ag_0_5periods_connect_timeouts | 0 |
| ag_0_5periods_connect_failures | 0 |
| ag_0_5periods_network_errors | 0 |
| ag_0_5periods_wrong_replies | 0 |
| ag_0_5periods_unexpected_closings | 0 |
| ag_0_5periods_warnings | 0 |
| ag_0_5periods_succeeded_queries | 146 |
| ag_0_5periods_msecsperquery | 231.83 |
| ag_1_hostname | 192.168.0.202:6714 |
| ag_1_references | 2 |
| ag_1_lastquery | 0.41 |
| ag_1_lastanswer | 0.19 |
| ag_1_lastperiodmsec | 220 |
| ag_1_pingtripmsec | 10.004 |
| ag_1_errorsarow | 0 |
| ag_1_1periods_query_timeouts | 0 |
| ag_1_1periods_connect_timeouts | 0 |
| ag_1_1periods_connect_failures | 0 |
| ag_1_1periods_network_errors | 0 |
| ag_1_1periods_wrong_replies | 0 |
| ag_1_1periods_unexpected_closings | 0 |
| ag_1_1periods_warnings | 0 |
| ag_1_1periods_succeeded_queries | 27 |
| ag_1_1periods_msecsperquery | 231.24 |
| ag_1_5periods_query_timeouts | 0 |
| ag_1_5periods_connect_timeouts | 0 |
| ag_1_5periods_connect_failures | 0 |
| ag_1_5periods_network_errors | 0 |
| ag_1_5periods_wrong_replies | 0 |
| ag_1_5periods_unexpected_closings | 0 |
| ag_1_5periods_warnings | 0 |
| ag_1_5periods_succeeded_queries | 146 |
| ag_1_5periods_msecsperquery | 230.85 |
+------------------------------------+----------------------------+
50 rows in set (0.01 sec)Array(
[status_period_seconds] => 60
[status_stored_periods] => 15
[ag_0_hostname] => 192.168.0.202:6713
[ag_0_references] => 2
[ag_0_lastquery] => 0.41
[ag_0_lastanswer] => 0.19
[ag_0_lastperiodmsec] => 222
[ag_0_errorsarow] => 0
[ag_0_1periods_query_timeouts] => 0
[ag_0_1periods_connect_timeouts] => 0
[ag_0_1periods_connect_failures] => 0
[ag_0_1periods_network_errors] => 0
[ag_0_1periods_wrong_replies] => 0
[ag_0_1periods_unexpected_closings] => 0
[ag_0_1periods_warnings] => 0
[ag_0_1periods_succeeded_queries] => 27
[ag_0_1periods_msecsperquery] => 232.31
[ag_0_5periods_query_timeouts] => 0
[ag_0_5periods_connect_timeouts] => 0
[ag_0_5periods_connect_failures] => 0
[ag_0_5periods_network_errors] => 0
[ag_0_5periods_wrong_replies] => 0
[ag_0_5periods_unexpected_closings] => 0
[ag_0_5periods_warnings] => 0
[ag_0_5periods_succeeded_queries] => 146
[ag_0_5periods_msecsperquery] => 231.83
[ag_1_hostname 192.168.0.202:6714
[ag_1_references] => 2
[ag_1_lastquery] => 0.41
[ag_1_lastanswer] => 0.19
[ag_1_lastperiodmsec] => 220
[ag_1_errorsarow] => 0
[ag_1_1periods_query_timeouts] => 0
[ag_1_1periods_connect_timeouts] => 0
[ag_1_1periods_connect_failures] => 0
[ag_1_1periods_network_errors] => 0
[ag_1_1periods_wrong_replies] => 0
[ag_1_1periods_unexpected_closings] => 0
[ag_1_1periods_warnings] => 0
[ag_1_1periods_succeeded_queries] => 27
[ag_1_1periods_msecsperquery] => 231.24
[ag_1_5periods_query_timeouts] => 0
[ag_1_5periods_connect_timeouts] => 0
[ag_1_5periods_connect_failures] => 0
[ag_1_5periods_network_errors] => 0
[ag_1_5periods_wrong_replies] => 0
[ag_1_5periods_unexpected_closings
[ag_1_5periods_warnings] => 0
[ag_1_5periods_succeeded_queries] => 146
[ag_1_5periods_msecsperquery] => 230.85
){u'columns': [{u'Key': {u'type': u'string'}},
{u'Value': {u'type': u'string'}}],
u'data': [
{u'Key': u'status_period_seconds', u'Value': u'60'},
{u'Key': u'status_stored_periods', u'Value': u'15'},
{u'Key': u'ag_0_hostname', u'Value': u'192.168.0.202:6713'},
{u'Key': u'ag_0_references', u'Value': u'2'},
{u'Key': u'ag_0_lastquery', u'Value': u'0.41'},
{u'Key': u'ag_0_lastanswer', u'Value': u'0.19'},
{u'Key': u'ag_0_lastperiodmsec', u'Value': u'222'},
{u'Key': u'ag_0_errorsarow', u'Value': u'0'},
{u'Key': u'ag_0_1periods_query_timeouts', u'Value': u'0'},
{u'Key': u'ag_0_1periods_connect_timeouts', u'Value': u'0'},
{u'Key': u'ag_0_1periods_connect_failures', u'Value': u'0'},
{u'Key': u'ag_0_1periods_network_errors', u'Value': u'0'},
{u'Key': u'ag_0_1periods_wrong_replies', u'Value': u'0'},
{u'Key': u'ag_0_1periods_unexpected_closings', u'Value': u'0'},
{u'Key': u'ag_0_1periods_warnings', u'Value': u'0'},
{u'Key': u'ag_0_1periods_succeeded_queries', u'Value': u'27'},
{u'Key': u'ag_0_1periods_msecsperquery', u'Value': u'232.31'},
{u'Key': u'ag_0_5periods_query_timeouts', u'Value': u'0'},
{u'Key': u'ag_0_5periods_connect_timeouts', u'Value': u'0'},
{u'Key': u'ag_0_5periods_connect_failures', u'Value': u'0'},
{u'Key': u'ag_0_5periods_network_errors', u'Value': u'0'},
{u'Key': u'ag_0_5periods_wrong_replies', u'Value': u'0'},
{u'Key': u'ag_0_5periods_unexpected_closings', u'Value': u'0'},
{u'Key': u'ag_0_5periods_warnings', u'Value': u'0'},
{u'Key': u'ag_0_5periods_succeeded_queries', u'Value': u'146'},
{u'Key': u'ag_0_5periods_msecsperquery', u'Value': u'231.83'},
{u'Key': u'ag_1_hostname 192.168.0.202:6714'},
{u'Key': u'ag_1_references', u'Value': u'2'},
{u'Key': u'ag_1_lastquery', u'Value': u'0.41'},
{u'Key': u'ag_1_lastanswer', u'Value': u'0.19'},
{u'Key': u'ag_1_lastperiodmsec', u'Value': u'220'},
{u'Key': u'ag_1_errorsarow', u'Value': u'0'},
{u'Key': u'ag_1_1periods_query_timeouts', u'Value': u'0'},
{u'Key': u'ag_1_1periods_connect_timeouts', u'Value': u'0'},
{u'Key': u'ag_1_1periods_connect_failures', u'Value': u'0'},
{u'Key': u'ag_1_1periods_network_errors', u'Value': u'0'},
{u'Key': u'ag_1_1periods_wrong_replies', u'Value': u'0'},
{u'Key': u'ag_1_1periods_unexpected_closings', u'Value': u'0'},
{u'Key': u'ag_1_1periods_warnings', u'Value': u'0'},
{u'Key': u'ag_1_1periods_succeeded_queries', u'Value': u'27'},
{u'Key': u'ag_1_1periods_msecsperquery', u'Value': u'231.24'},
{u'Key': u'ag_1_5periods_query_timeouts', u'Value': u'0'},
{u'Key': u'ag_1_5periods_connect_timeouts', u'Value': u'0'},
{u'Key': u'ag_1_5periods_connect_failures', u'Value': u'0'},
{u'Key': u'ag_1_5periods_network_errors', u'Value': u'0'},
{u'Key': u'ag_1_5periods_wrong_replies', u'Value': u'0'},
{u'Key': u'ag_1_5periods_warnings', u'Value': u'0'},
{u'Key': u'ag_1_5periods_succeeded_queries', u'Value': u'146'},
{u'Key': u'ag_1_5periods_msecsperquery', u'Value': u'230.85'}],
u'error': u'',
u'total': 0,
u'warning': u''}{
"columns":
[{
"Key":
{
"type": "string"
}
},
{
"Value":
{
"type": "string"
}
}],
"data":
[
{"Key": "status_period_seconds", "Value": "60"},
{"Key": "status_stored_periods", "Value": "15"},
{"Key": "ag_0_hostname", "Value": "192.168.0.202:6713"},
{"Key": "ag_0_references", "Value": "2"},
{"Key": "ag_0_lastquery", "Value": "0.41"},
{"Key": "ag_0_lastanswer", "Value": "0.19"},
{"Key": "ag_0_lastperiodmsec", "Value": "222"},
{"Key": "ag_0_errorsarow", "Value": "0"},
{"Key": "ag_0_1periods_query_timeouts", "Value": "0"},
{"Key": "ag_0_1periods_connect_timeouts", "Value": "0"},
{"Key": "ag_0_1periods_connect_failures", "Value": "0"},
{"Key": "ag_0_1periods_network_errors", "Value": "0"},
{"Key": "ag_0_1periods_wrong_replies", "Value": "0"},
{"Key": "ag_0_1periods_unexpected_closings", "Value": "0"},
{"Key": "ag_0_1periods_warnings", "Value": "0"},
{"Key": "ag_0_1periods_succeeded_queries", "Value": "27"},
{"Key": "ag_0_1periods_msecsperquery", "Value": "232.31"},
{"Key": "ag_0_5periods_query_timeouts", "Value": "0"},
{"Key": "ag_0_5periods_connect_timeouts", "Value": "0"},
{"Key": "ag_0_5periods_connect_failures", "Value": "0"},
{"Key": "ag_0_5periods_network_errors", "Value": "0"},
{"Key": "ag_0_5periods_wrong_replies", "Value": "0"},
{"Key": "ag_0_5periods_unexpected_closings", "Value": "0"},
{"Key": "ag_0_5periods_warnings", "Value": "0"},
{"Key": "ag_0_5periods_succeeded_queries", "Value": "146"},
{"Key": "ag_0_5periods_msecsperquery", "Value": "231.83"},
{"Key": "ag_1_hostname 192.168.0.202:6714"},
{"Key": "ag_1_references", "Value": "2"},
{"Key": "ag_1_lastquery", "Value": "0.41"},
{"Key": "ag_1_lastanswer", "Value": "0.19"},
{"Key": "ag_1_lastperiodmsec", "Value": "220"},
{"Key": "ag_1_errorsarow", "Value": "0"},
{"Key": "ag_1_1periods_query_timeouts", "Value": "0"},
{"Key": "ag_1_1periods_connect_timeouts", "Value": "0"},
{"Key": "ag_1_1periods_connect_failures", "Value": "0"},
{"Key": "ag_1_1periods_network_errors", "Value": "0"},
{"Key": "ag_1_1periods_wrong_replies", "Value": "0"},
{"Key": "ag_1_1periods_unexpected_closings", "Value": "0"},
{"Key": "ag_1_1periods_warnings", "Value": "0"},
{"Key": "ag_1_1periods_succeeded_queries", "Value": "27"},
{"Key": "ag_1_1periods_msecsperquery", "Value": "231.24"},
{"Key": "ag_1_5periods_query_timeouts", "Value": "0"},
{"Key": "ag_1_5periods_connect_timeouts", "Value": "0"},
{"Key": "ag_1_5periods_connect_failures", "Value": "0"},
{"Key": "ag_1_5periods_network_errors", "Value": "0"},
{"Key": "ag_1_5periods_wrong_replies", "Value": "0"},
{"Key": "ag_1_5periods_warnings", "Value": "0"},
{"Key": "ag_1_5periods_succeeded_queries", "Value": "146"},
{"Key": "ag_1_5periods_msecsperquery", "Value": "230.85"}
],
"error": "",
"total": 0,
"warning": ""
}{columns=[{ Key : { type=string }},
{ Value : { type=string }}],
data : [
{ Key=status_period_seconds , Value=60 },
{ Key=status_stored_periods , Value=15 },
{ Key=ag_0_hostname , Value=192.168.0.202:6713 },
{ Key=ag_0_references , Value=2 },
{ Key=ag_0_lastquery , Value=0.41 },
{ Key=ag_0_lastanswer , Value=0.19 },
{ Key=ag_0_lastperiodmsec , Value=222 },
{ Key=ag_0_errorsarow , Value=0 },
{ Key=ag_0_1periods_query_timeouts , Value=0 },
{ Key=ag_0_1periods_connect_timeouts , Value=0 },
{ Key=ag_0_1periods_connect_failures , Value=0 },
{ Key=ag_0_1periods_network_errors , Value=0 },
{ Key=ag_0_1periods_wrong_replies , Value=0 },
{ Key=ag_0_1periods_unexpected_closings , Value=0 },
{ Key=ag_0_1periods_warnings , Value=0 },
{ Key=ag_0_1periods_succeeded_queries , Value=27 },
{ Key=ag_0_1periods_msecsperquery , Value=232.31 },
{ Key=ag_0_5periods_query_timeouts , Value=0 },
{ Key=ag_0_5periods_connect_timeouts , Value=0 },
{ Key=ag_0_5periods_connect_failures , Value=0 },
{ Key=ag_0_5periods_network_errors , Value=0 },
{ Key=ag_0_5periods_wrong_replies , Value=0 },
{ Key=ag_0_5periods_unexpected_closings , Value=0 },
{ Key=ag_0_5periods_warnings , Value=0 },
{ Key=ag_0_5periods_succeeded_queries , Value=146 },
{ Key=ag_0_5periods_msecsperquery , Value=231.83 },
{ Key=ag_1_hostname 192.168.0.202:6714 },
{ Key=ag_1_references , Value=2 },
{ Key=ag_1_lastquery , Value=0.41 },
{ Key=ag_1_lastanswer , Value=0.19 },
{ Key=ag_1_lastperiodmsec , Value=220 },
{ Key=ag_1_errorsarow , Value=0 },
{ Key=ag_1_1periods_query_timeouts , Value=0 },
{ Key=ag_1_1periods_connect_timeouts , Value=0 },
{ Key=ag_1_1periods_connect_failures , Value=0 },
{ Key=ag_1_1periods_network_errors , Value=0 },
{ Key=ag_1_1periods_wrong_replies , Value=0 },
{ Key=ag_1_1periods_unexpected_closings , Value=0 },
{ Key=ag_1_1periods_warnings , Value=0 },
{ Key=ag_1_1periods_succeeded_queries , Value=27 },
{ Key=ag_1_1periods_msecsperquery , Value=231.24 },
{ Key=ag_1_5periods_query_timeouts , Value=0 },
{ Key=ag_1_5periods_connect_timeouts , Value=0 },
{ Key=ag_1_5periods_connect_failures , Value=0 },
{ Key=ag_1_5periods_network_errors , Value=0 },
{ Key=ag_1_5periods_wrong_replies , Value=0 },
{ Key=ag_1_5periods_warnings , Value=0 },
{ Key=ag_1_5periods_succeeded_queries , Value=146 },
{ Key=ag_1_5periods_msecsperquery , Value=230.85 }],
error= ,
total=0,
warning= }{columns=[{ Key : { type=string }},
{ Value : { type=string }}],
data : [
{ Key=status_period_seconds , Value=60 },
{ Key=status_stored_periods , Value=15 },
{ Key=ag_0_hostname , Value=192.168.0.202:6713 },
{ Key=ag_0_references , Value=2 },
{ Key=ag_0_lastquery , Value=0.41 },
{ Key=ag_0_lastanswer , Value=0.19 },
{ Key=ag_0_lastperiodmsec , Value=222 },
{ Key=ag_0_errorsarow , Value=0 },
{ Key=ag_0_1periods_query_timeouts , Value=0 },
{ Key=ag_0_1periods_connect_timeouts , Value=0 },
{ Key=ag_0_1periods_connect_failures , Value=0 },
{ Key=ag_0_1periods_network_errors , Value=0 },
{ Key=ag_0_1periods_wrong_replies , Value=0 },
{ Key=ag_0_1periods_unexpected_closings , Value=0 },
{ Key=ag_0_1periods_warnings , Value=0 },
{ Key=ag_0_1periods_succeeded_queries , Value=27 },
{ Key=ag_0_1periods_msecsperquery , Value=232.31 },
{ Key=ag_0_5periods_query_timeouts , Value=0 },
{ Key=ag_0_5periods_connect_timeouts , Value=0 },
{ Key=ag_0_5periods_connect_failures , Value=0 },
{ Key=ag_0_5periods_network_errors , Value=0 },
{ Key=ag_0_5periods_wrong_replies , Value=0 },
{ Key=ag_0_5periods_unexpected_closings , Value=0 },
{ Key=ag_0_5periods_warnings , Value=0 },
{ Key=ag_0_5periods_succeeded_queries , Value=146 },
{ Key=ag_0_5periods_msecsperquery , Value=231.83 },
{ Key=ag_1_hostname 192.168.0.202:6714 },
{ Key=ag_1_references , Value=2 },
{ Key=ag_1_lastquery , Value=0.41 },
{ Key=ag_1_lastanswer , Value=0.19 },
{ Key=ag_1_lastperiodmsec , Value=220 },
{ Key=ag_1_errorsarow , Value=0 },
{ Key=ag_1_1periods_query_timeouts , Value=0 },
{ Key=ag_1_1periods_connect_timeouts , Value=0 },
{ Key=ag_1_1periods_connect_failures , Value=0 },
{ Key=ag_1_1periods_network_errors , Value=0 },
{ Key=ag_1_1periods_wrong_replies , Value=0 },
{ Key=ag_1_1periods_unexpected_closings , Value=0 },
{ Key=ag_1_1periods_warnings , Value=0 },
{ Key=ag_1_1periods_succeeded_queries , Value=27 },
{ Key=ag_1_1periods_msecsperquery , Value=231.24 },
{ Key=ag_1_5periods_query_timeouts , Value=0 },
{ Key=ag_1_5periods_connect_timeouts , Value=0 },
{ Key=ag_1_5periods_connect_failures , Value=0 },
{ Key=ag_1_5periods_network_errors , Value=0 },
{ Key=ag_1_5periods_wrong_replies , Value=0 },
{ Key=ag_1_5periods_warnings , Value=0 },
{ Key=ag_1_5periods_succeeded_queries , Value=146 },
{ Key=ag_1_5periods_msecsperquery , Value=230.85 }],
error="" ,
total=0,
warning="" }{
"columns":
[{
"Key":
{
"type": "string"
}
},
{
"Value":
{
"type": "string"
}
}],
"data":
[
{"Key": "status_period_seconds", "Value": "60"},
{"Key": "status_stored_periods", "Value": "15"},
{"Key": "ag_0_hostname", "Value": "192.168.0.202:6713"},
{"Key": "ag_0_references", "Value": "2"},
{"Key": "ag_0_lastquery", "Value": "0.41"},
{"Key": "ag_0_lastanswer", "Value": "0.19"},
{"Key": "ag_0_lastperiodmsec", "Value": "222"},
{"Key": "ag_0_errorsarow", "Value": "0"},
{"Key": "ag_0_1periods_query_timeouts", "Value": "0"},
{"Key": "ag_0_1periods_connect_timeouts", "Value": "0"},
{"Key": "ag_0_1periods_connect_failures", "Value": "0"},
{"Key": "ag_0_1periods_network_errors", "Value": "0"},
{"Key": "ag_0_1periods_wrong_replies", "Value": "0"},
{"Key": "ag_0_1periods_unexpected_closings", "Value": "0"},
{"Key": "ag_0_1periods_warnings", "Value": "0"},
{"Key": "ag_0_1periods_succeeded_queries", "Value": "27"},
{"Key": "ag_0_1periods_msecsperquery", "Value": "232.31"},
{"Key": "ag_0_5periods_query_timeouts", "Value": "0"},
{"Key": "ag_0_5periods_connect_timeouts", "Value": "0"},
{"Key": "ag_0_5periods_connect_failures", "Value": "0"},
{"Key": "ag_0_5periods_network_errors", "Value": "0"},
{"Key": "ag_0_5periods_wrong_replies", "Value": "0"},
{"Key": "ag_0_5periods_unexpected_closings", "Value": "0"},
{"Key": "ag_0_5periods_warnings", "Value": "0"},
{"Key": "ag_0_5periods_succeeded_queries", "Value": "146"},
{"Key": "ag_0_5periods_msecsperquery", "Value": "231.83"},
{"Key": "ag_1_hostname 192.168.0.202:6714"},
{"Key": "ag_1_references", "Value": "2"},
{"Key": "ag_1_lastquery", "Value": "0.41"},
{"Key": "ag_1_lastanswer", "Value": "0.19"},
{"Key": "ag_1_lastperiodmsec", "Value": "220"},
{"Key": "ag_1_errorsarow", "Value": "0"},
{"Key": "ag_1_1periods_query_timeouts", "Value": "0"},
{"Key": "ag_1_1periods_connect_timeouts", "Value": "0"},
{"Key": "ag_1_1periods_connect_failures", "Value": "0"},
{"Key": "ag_1_1periods_network_errors", "Value": "0"},
{"Key": "ag_1_1periods_wrong_replies", "Value": "0"},
{"Key": "ag_1_1periods_unexpected_closings", "Value": "0"},
{"Key": "ag_1_1periods_warnings", "Value": "0"},
{"Key": "ag_1_1periods_succeeded_queries", "Value": "27"},
{"Key": "ag_1_1periods_msecsperquery", "Value": "231.24"},
{"Key": "ag_1_5periods_query_timeouts", "Value": "0"},
{"Key": "ag_1_5periods_connect_timeouts", "Value": "0"},
{"Key": "ag_1_5periods_connect_failures", "Value": "0"},
{"Key": "ag_1_5periods_network_errors", "Value": "0"},
{"Key": "ag_1_5periods_wrong_replies", "Value": "0"},
{"Key": "ag_1_5periods_warnings", "Value": "0"},
{"Key": "ag_1_5periods_succeeded_queries", "Value": "146"},
{"Key": "ag_1_5periods_msecsperquery", "Value": "230.85"}
],
"error": "",
"total": 0,
"warning": ""
}An optional LIKE clause is supported, with the syntax being the same as in SHOW STATUS.
‹›
- SQL
- PHP
- Python
- javascript
- Java
- C#
- TypeScript
- Go
📋
⚙
SHOW AGENT STATUS LIKE '%5period%msec%';$client->nodes()->agentstatus(
['body'=>
['pattern'=>'%5period%msec%']
]
);utilsApi.sql('SHOW AGENT STATUS LIKE \'%5period%msec%\'')res = await utilsApi.sql("SHOW AGENT STATUS LIKE \"%5period%msec%\"");utilsApi.sql("SHOW AGENT STATUS LIKE \"%5period%msec%\"");utilsApi.Sql("SHOW AGENT STATUS LIKE \"%5period%msec%\"");res = await utilsApi.sql("SHOW AGENT STATUS LIKE \"%5period%msec%\"");apiClient.UtilsAPI.Sql(context.Background()).Body("SHOW AGENT STATUS LIKE \"%5period%msec%\"").Execute()
‹›
Response
+-----------------------------+--------+
| Key | Value |
+-----------------------------+--------+
| ag_0_5periods_msecsperquery | 234.72 |
| ag_1_5periods_msecsperquery | 233.73 |
| ag_2_5periods_msecsperquery | 343.81 |
+-----------------------------+--------+
3 rows in set (0.00 sec)Array(
[ag_0_5periods_msecsperquery] => 234.72
[ag_1_5periods_msecsperquery] => 233.73
[ag_2_5periods_msecsperquery] => 343.81
){u'columns': [{u'Key': {u'type': u'string'}},
{u'Value': {u'type': u'string'}}],
u'data': [
{u'Key': u'ag_0_5periods_msecsperquery', u'Value': u'234.72'},
{u'Key': u'ag_1_5periods_msecsperquery', u'Value': u'233.73'},
{u'Key': u'ag_2_5periods_msecsperquery', u'Value': u'343.81'}],
u'error': u'',
u'total': 0,
u'warning': u''}{"columns": [{"Key": {"type": "string"}},
{"Value": {"type": "string"}}],
"data": [
{"Key": "ag_0_5periods_msecsperquery", "Value": "234.72"},
{"Key": "ag_1_5periods_msecsperquery", "Value": "233.73"},
{"Key": "ag_2_5periods_msecsperquery", "Value": "343.81"}],
"error": "",
"total": 0,
"warning": ""}{columns: [{Key={type=string}},
{Value={type=string}}],
data: [
{Key=ag_0_5periods_msecsperquery, Value=234.72},
{Key=ag_1_5periods_msecsperquery, Value=233.73},
{Key=ag_2_5periods_msecsperquery, Value=343.81}],
error: ,
total: 0,
warning: }{columns: [{Key={type=string}},
{Value={type=string}}],
data: [
{Key=ag_0_5periods_msecsperquery, Value=234.72},
{Key=ag_1_5periods_msecsperquery, Value=233.73},
{Key=ag_2_5periods_msecsperquery, Value=343.81}],
error: "",
total: 0,
warning: ""}{
"columns":
[{
"Key": {"type": "string"}
},
{
"Value": {"type": "string"}
}],
"data":
[
{"Key": "ag_0_5periods_msecsperquery", "Value": "234.72"},
{"Key": "ag_1_5periods_msecsperquery", "Value": "233.73"},
{"Key": "ag_2_5periods_msecsperquery", "Value": "343.81"}
],
"error": "",
"total": 0,
"warning": ""
}{
"columns":
[{
"Key": {"type": "string"}
},
{
"Value": {"type": "string"}
}],
"data":
[
{"Key": "ag_0_5periods_msecsperquery", "Value": "234.72"},
{"Key": "ag_1_5periods_msecsperquery", "Value": "233.73"},
{"Key": "ag_2_5periods_msecsperquery", "Value": "343.81"}
],
"error": "",
"total": 0,
"warning": ""
}You can specify a particular agent by its address. In this case, only that agent's data will be displayed. Additionally, the agent_ prefix will be used instead of ag_N_:
‹›
- SQL
- PHP
- Python
- javascript
- Java
- C#
- TypeScript
- Go
📋
⚙
SHOW AGENT '192.168.0.202:6714' STATUS LIKE '%15periods%';$client->nodes()->agentstatus(
['body'=>
['agent'=>'192.168.0.202:6714'],
['pattern'=>'%5period%msec%']
]
);utilsApi.sql('SHOW AGENT \'192.168.0.202:6714\' STATUS LIKE \'%15periods%\'')res = await utilsApi.sql("SHOW AGENT \"192.168.0.202:6714\" STATUS LIKE \"%15periods%\"");utilsApi.sql("SHOW AGENT \"192.168.0.202:6714\" STATUS LIKE \"%15periods%\"");utilsApi.Sql("SHOW AGENT \"192.168.0.202:6714\" STATUS LIKE \"%15periods%\"");res = await utilsApi.sql("SHOW AGENT \"192.168.0.202:6714\" STATUS LIKE \"%15periods%\"");apiClient.UtilsAPI.Sql(context.Background()).Body("SHOW AGENT \"192.168.0.202:6714\" STATUS LIKE \"%15periods%\").Execute()
‹›
Response
+-------------------------------------+--------+
| Variable_name | Value |
+-------------------------------------+--------+
| agent_15periods_query_timeouts | 0 |
| agent_15periods_connect_timeouts | 0 |
| agent_15periods_connect_failures | 0 |
| agent_15periods_network_errors | 0 |
| agent_15periods_wrong_replies | 0 |
| agent_15periods_unexpected_closings | 0 |
| agent_15periods_warnings | 0 |
| agent_15periods_succeeded_queries | 439 |
| agent_15periods_msecsperquery | 231.73 |
+-------------------------------------+--------+
9 rows in set (0.00 sec)Array(
[agent_15periods_query_timeouts] => 0
[agent_15periods_connect_timeouts] => 0
[agent_15periods_connect_failures] => 0
[agent_15periods_network_errors] => 0
[agent_15periods_wrong_replies] => 0
[agent_15periods_unexpected_closings] => 0
[agent_15periods_warnings] => 0
[agent_15periods_succeeded_queries] => 439
[agent_15periods_msecsperquery] => 231.73
){u'columns': [{u'Key': {u'type': u'string'}},
{u'Value': {u'type': u'string'}}],
u'data': [
{u'Key': u'agent_15periods_query_timeouts', u'Value': u'0'},
{u'Key': u'agent_15periods_connect_timeouts', u'Value': u'0'},
{u'Key': u'agent_15periods_connect_failures', u'Value': u'0'},
{u'Key': u'agent_15periods_network_errors', u'Value': u'0'},
{u'Key': u'agent_15periods_connect_failures', u'Value': u'0'},
{u'Key': u'agent_15periods_wrong_replies', u'Value': u'0'},
{u'Key': u'agent_15periods_unexpected_closings', u'Value': u'0'},
{u'Key': u'agent_15periods_warnings', u'Value': u'0'},
{u'Key': u'agent_15periods_succeeded_queries', u'Value': u'439'},
{u'Key': u'agent_15periods_msecsperquery', u'Value': u'233.73'},
],
u'error': u'',
u'total': 0,
u'warning': u''}{"columns": [{"Key": {"type": "string"}},
{"Value": {"type": "string"}}],
"data": [
{"Key": "agent_15periods_query_timeouts", "Value": "0"},
{"Key": "agent_15periods_connect_timeouts", "Value": "0"},
{"Key": "agent_15periods_connect_failures", "Value": "0"},
{"Key": "agent_15periods_network_errors", "Value": "0"},
{"Key": "agent_15periods_connect_failures", "Value": "0"},
{"Key": "agent_15periods_wrong_replies", "Value": "0"},
{"Key": "agent_15periods_unexpected_closings", "Value": "0"},
{"Key": "agent_15periods_warnings", "Value": "0"},
{"Key": "agent_15periods_succeeded_queries", "Value": "439"},
{"Key": "agent_15periods_msecsperquery", "Value": "233.73"},
],
"error": "",
"total": 0,
"warning": ""}{columns=[{Key={type=string}},
{Value={type=string}}],
data=[
{Key=agent_15periods_query_timeouts, Value=0},
{Key=agent_15periods_connect_timeouts, Value=0},
{Key=agent_15periods_connect_failures, Value=0},
{Key=agent_15periods_network_errors, Value=0},
{Key=agent_15periods_connect_failures, Value=0},
{Key=agent_15periods_wrong_replies, Value=0},
{Key=agent_15periods_unexpected_closings, Value=0},
{Key=agent_15periods_warnings, Value=0},
{Key=agent_15periods_succeeded_queries, Value=439},
{Key=agent_15periods_msecsperquery, Value=233.73},
],
error=,
total=0,
warning=}{columns=[{Key={type=string}},
{Value={type=string}}],
data=[
{Key=agent_15periods_query_timeouts, Value=0},
{Key=agent_15periods_connect_timeouts, Value=0},
{Key=agent_15periods_connect_failures, Value=0},
{Key=agent_15periods_network_errors, Value=0},
{Key=agent_15periods_connect_failures, Value=0},
{Key=agent_15periods_wrong_replies, Value=0},
{Key=agent_15periods_unexpected_closings, Value=0},
{Key=agent_15periods_warnings, Value=0},
{Key=agent_15periods_succeeded_queries, Value=439},
{Key=agent_15periods_msecsperquery, Value=233.73},
],
error="",
total=0,
warning=""}{
"columns":
[{
{"Key": {"type": "string"}
},
{"Value": {"type": "string"}
}],
"data":
[
{"Key": "agent_15periods_query_timeouts", "Value": "0"},
{"Key": "agent_15periods_connect_timeouts", "Value": "0"},
{"Key": "agent_15periods_connect_failures", "Value": "0"},
{"Key": "agent_15periods_network_errors", "Value": "0"},
{"Key": "agent_15periods_connect_failures", "Value": "0"},
{"Key": "agent_15periods_wrong_replies", "Value": "0"},
{"Key": "agent_15periods_unexpected_closings", "Value": "0"},
{"Key": "agent_15periods_warnings", "Value": "0"},
{"Key": "agent_15periods_succeeded_queries", "Value": "439"},
{"Key": "agent_15periods_msecsperquery", "Value": "233.73"},
],
"error": "",
"total": 0,
"warning": ""
}{
"columns":
[{
{"Key": {"type": "string"}
},
{"Value": {"type": "string"}
}],
"data":
[
{"Key": "agent_15periods_query_timeouts", "Value": "0"},
{"Key": "agent_15periods_connect_timeouts", "Value": "0"},
{"Key": "agent_15periods_connect_failures", "Value": "0"},
{"Key": "agent_15periods_network_errors", "Value": "0"},
{"Key": "agent_15periods_connect_failures", "Value": "0"},
{"Key": "agent_15periods_wrong_replies", "Value": "0"},
{"Key": "agent_15periods_unexpected_closings", "Value": "0"},
{"Key": "agent_15periods_warnings", "Value": "0"},
{"Key": "agent_15periods_succeeded_queries", "Value": "439"},
{"Key": "agent_15periods_msecsperquery", "Value": "233.73"},
],
"error": "",
"total": 0,
"warning": ""
}Finally, you can check the status of the agents in a specific distributed table using the SHOW AGENT table_name STATUS statement. This statement displays the table's HA status (i.e., whether or not it uses agent mirrors at all) and provides information on the mirrors, including: address, blackhole and persistent flags, and the mirror selection probability used when one of the weighted probability strategies is in effect.
‹›
- SQL
- PHP
- Python
- javascript
- Java
- C#
- TypeScript
- Go
📋
⚙
SHOW AGENT dist_index STATUS;$client->nodes()->agentstatus(
['body'=>
['agent'=>'dist_index']
]
);utilsApi.sql('SHOW AGENT \'192.168.0.202:6714\' STATUS LIKE \'%15periods%\'')res = await utilsApi.sql("SHOW AGENT \"192.168.0.202:6714\" STATUS LIKE \"%15periods%\"");utilsApi.sql("SHOW AGENT \"192.168.0.202:6714\" STATUS LIKE \"%15periods%\"");utilsApi.Sql("SHOW AGENT \"192.168.0.202:6714\" STATUS LIKE \"%15periods%\"");res = await utilsApi.sql("SHOW AGENT \"192.168.0.202:6714\" STATUS LIKE \"%15periods%\"");apiClient.UtilsAPI.Sql(context.Background()).Body("SHOW AGENT \"192.168.0.202:6714\" STATUS LIKE \"%15periods%\"").Execute()
‹›
Response
+--------------------------------------+--------------------------------+
| Variable_name | Value |
+--------------------------------------+--------------------------------+
| dstindex_1_is_ha | 1 |
| dstindex_1mirror1_id | 192.168.0.202:6713:loc |
| dstindex_1mirror1_probability_weight | 0.372864 |
| dstindex_1mirror1_is_blackhole | 0 |
| dstindex_1mirror1_is_persistent | 0 |
| dstindex_1mirror2_id | 192.168.0.202:6714:loc |
| dstindex_1mirror2_probability_weight | 0.374635 |
| dstindex_1mirror2_is_blackhole | 0 |
| dstindex_1mirror2_is_persistent | 0 |
| dstindex_1mirror3_id | dev1.manticoresearch.com:6714:loc |
| dstindex_1mirror3_probability_weight | 0.252501 |
| dstindex_1mirror3_is_blackhole | 0 |
| dstindex_1mirror3_is_persistent | 0 |
+--------------------------------------+--------------------------------+
13 rows in set (0.00 sec)Array(
[dstindex_1_is_ha] => 1
[dstindex_1mirror1_id] => 192.168.0.202:6713:loc
[dstindex_1mirror1_probability_weight] => 0.372864
[dstindex_1mirror1_is_blackhole] => 0
[dstindex_1mirror1_is_persistent] => 0
[dstindex_1mirror2_id] => 192.168.0.202:6714:loc
[dstindex_1mirror2_probability_weight] => 0.374635
[dstindex_1mirror2_is_blackhole] => 0
[dstindex_1mirror2_is_persistent] => 0
[dstindex_1mirror3_id] => dev1.manticoresearch.com:6714:loc
[dstindex_1mirror3_probability_weight] => 0.252501
[dstindex_1mirror3_is_blackhole] => 0
[dstindex_1mirror3_is_persistent] => 0
){u'columns': [{u'Key': {u'type': u'string'}},
{u'Value': {u'type': u'string'}}],
u'data': [
{u'Key': u'dstindex_1_is_ha', u'Value': u'1'},
{u'Key': u'dstindex_1mirror1_id', u'Value': u'192.168.0.202:6713:loc'},
{u'Key': u'dstindex_1mirror1_probability_weight', u'Value': u'0.372864'},
{u'Key': u'dstindex_1mirror1_is_blackhole', u'Value': u'0'},
{u'Key': u'dstindex_1mirror1_is_persistent', u'Value': u'0'},
{u'Key': u'dstindex_1mirror2_id', u'Value': u'192.168.0.202:6714:loc'},
{u'Key': u'dstindex_1mirror2_probability_weight', u'Value': u'0.374635'},
{u'Key': u'dstindex_1mirror2_is_blackhole', u'Value': u'0'},
{u'Key': u'dstindex_1mirror2_is_persistent', u'Value': u'439'},
{u'Key': u'dstindex_1mirror3_id', u'Value': u'dev1.manticoresearch.com:6714:loc'},
{u'Key': u'dstindex_1mirror3_probability_weight', u'Value': u' 0.252501'},
{u'Key': u'dstindex_1mirror3_is_blackhole', u'Value': u'0'},
{u'Key': u'dstindex_1mirror3_is_persistent', u'Value': u'439'}
],
u'error': u'',
u'total': 0,
u'warning': u''}{"columns": [{"Key": {"type": "string"}},
{"Value": {"type": "string"}}],
"data": [
{"Key": "dstindex_1_is_ha", "Value": "1"},
{"Key": "dstindex_1mirror1_id", "Value": "192.168.0.202:6713:loc"},
{"Key": "dstindex_1mirror1_probability_weight", "Value": "0.372864"},
{"Key": "dstindex_1mirror1_is_blackhole", "Value": "0"},
{"Key": "dstindex_1mirror1_is_persistent", "Value": "0"},
{"Key": "dstindex_1mirror2_id", "Value": "192.168.0.202:6714:loc"},
{"Key": "dstindex_1mirror2_probability_weight", "Value": "0.374635"},
{"Key": "dstindex_1mirror2_is_blackhole", "Value": "0"},
{"Key": "dstindex_1mirror2_is_persistent", "Value": "439"},
{"Key": "dstindex_1mirror3_id", "Value": "dev1.manticoresearch.com:6714:loc"},
{"Key": "dstindex_1mirror3_probability_weight", "Value": " 0.252501"},
{"Key": "dstindex_1mirror3_is_blackhole", "Value": "0"},
{"Key": "dstindex_1mirror3_is_persistent", "Value": "439"}
],
"error": "",
"total": 0,
"warning": ""}{columns=[{Key={type=string}},
{Value={type=string}}],
data=[
{Key=dstindex_1_is_ha, Value=1},
{Key=dstindex_1mirror1_id, Value=192.168.0.202:6713:loc},
{Key=dstindex_1mirror1_probability_weight, Value=0.372864},
{Key=dstindex_1mirror1_is_blackhole, Value=0},
{Key=dstindex_1mirror1_is_persistent, Value=0},
{Key=dstindex_1mirror2_id, Value=192.168.0.202:6714:loc},
{Key=dstindex_1mirror2_probability_weight, Value=0.374635},
{Key=dstindex_1mirror2_is_blackhole, Value=0},
{Key=dstindex_1mirror2_is_persistent, Value=439},
{Key=dstindex_1mirror3_id, Value=dev1.manticoresearch.com:6714:loc},
{Key=dstindex_1mirror3_probability_weight, Value= 0.252501},
{Key=dstindex_1mirror3_is_blackhole, Value=0},
{Key=dstindex_1mirror3_is_persistent, Value=439}
],
error=,
total=0,
warning=}{columns=[{Key={type=string}},
{Value={type=string}}],
data=[
{Key=dstindex_1_is_ha, Value=1},
{Key=dstindex_1mirror1_id, Value=192.168.0.202:6713:loc},
{Key=dstindex_1mirror1_probability_weight, Value=0.372864},
{Key=dstindex_1mirror1_is_blackhole, Value=0},
{Key=dstindex_1mirror1_is_persistent, Value=0},
{Key=dstindex_1mirror2_id, Value=192.168.0.202:6714:loc},
{Key=dstindex_1mirror2_probability_weight, Value=0.374635},
{Key=dstindex_1mirror2_is_blackhole, Value=0},
{Key=dstindex_1mirror2_is_persistent, Value=439},
{Key=dstindex_1mirror3_id, Value=dev1.manticoresearch.com:6714:loc},
{Key=dstindex_1mirror3_probability_weight, Value= 0.252501},
{Key=dstindex_1mirror3_is_blackhole, Value=0},
{Key=dstindex_1mirror3_is_persistent, Value=439}
],
error="",
total=0,
warning=""}{
"columns":
[{
"Key": {"type": "string"}},
{"Value": {"type": "string"}
}],
"data":
[
{"Key": "dstindex_1_is_ha", "Value": "1"},
{"Key": "dstindex_1mirror1_id", "Value": "192.168.0.202:6713:loc"},
{"Key": "dstindex_1mirror1_probability_weight", "Value": "0.372864"},
{"Key": "dstindex_1mirror1_is_blackhole", "Value": "0"},
{"Key": "dstindex_1mirror1_is_persistent", "Value": "0"},
{"Key": "dstindex_1mirror2_id", "Value": "192.168.0.202:6714:loc"},
{"Key": "dstindex_1mirror2_probability_weight", "Value": "0.374635"},
{"Key": "dstindex_1mirror2_is_blackhole", "Value": "0"},
{"Key": "dstindex_1mirror2_is_persistent", "Value": "439"},
{"Key": "dstindex_1mirror3_id", "Value": "dev1.manticoresearch.com:6714:loc"},
{"Key": "dstindex_1mirror3_probability_weight", "Value": " 0.252501"},
{"Key": "dstindex_1mirror3_is_blackhole", "Value": "0"},
{"Key": "dstindex_1mirror3_is_persistent", "Value": "439"}
],
"error": "",
"total": 0,
"warning": ""
}{
"columns":
[{
"Key": {"type": "string"}},
{"Value": {"type": "string"}
}],
"data":
[
{"Key": "dstindex_1_is_ha", "Value": "1"},
{"Key": "dstindex_1mirror1_id", "Value": "192.168.0.202:6713:loc"},
{"Key": "dstindex_1mirror1_probability_weight", "Value": "0.372864"},
{"Key": "dstindex_1mirror1_is_blackhole", "Value": "0"},
{"Key": "dstindex_1mirror1_is_persistent", "Value": "0"},
{"Key": "dstindex_1mirror2_id", "Value": "192.168.0.202:6714:loc"},
{"Key": "dstindex_1mirror2_probability_weight", "Value": "0.374635"},
{"Key": "dstindex_1mirror2_is_blackhole", "Value": "0"},
{"Key": "dstindex_1mirror2_is_persistent", "Value": "439"},
{"Key": "dstindex_1mirror3_id", "Value": "dev1.manticoresearch.com:6714:loc"},
{"Key": "dstindex_1mirror3_probability_weight", "Value": " 0.252501"},
{"Key": "dstindex_1mirror3_is_blackhole", "Value": "0"},
{"Key": "dstindex_1mirror3_is_persistent", "Value": "439"}
],
"error": "",
"total": 0,
"warning": ""
}SHOW META [ LIKE pattern ]SHOW META is an SQL statement that displays additional meta-information about the processed query, including the query time, keyword statistics, and information about the secondary indexes used. The syntax is:
The included items are:
total: The number of matches that were actually retrieved and sent to the client. This value is typically limited by the LIMIT/size search option.total_found:- The estimated total number of matches for the query in the index. If you need the exact number of matches, use
SELECT COUNT(*)instead of relying on this value. - For queries with
GROUP BY,total_foundrepresents the number of groups instead of individual matches. - For GROUP N BY queries,
total_foundstill represents the number of groups, regardless of the value ofN.
- The estimated total number of matches for the query in the index. If you need the exact number of matches, use
total_relation: Indicates whether thetotal_foundvalue is exact or an estimate.- If Manticore cannot determine the precise
total_foundvalue, this field will displaytotal_relation: gte, meaning the actual number of matches is Greater Than or Equal to the reportedtotal_found. - If the
total_foundvalue is exact,total_relation: eqwill be displayed.
- If Manticore cannot determine the precise
time: The duration (in seconds) it took to process the search query.keyword[N]: The n-th keyword used in the search query. Note that the keyword can be presented as a wildcard, e.g.,abc*.docs[N]: The total number of documents (or records) containing the n-th keyword from the search query. If the keyword is presented as a wildcard, this value represents the sum of documents for all expanded sub-keywords, potentially exceeding the actual number of matched documents.hits[N]: The total number of occurrences (or hits) of the n-th keyword across all documents.index: Information about the utilized index (e.g., secondary index).
‹›
- SQL
SQL
📋
⚙
SELECT id, story_author FROM hn_small WHERE MATCH('one|two|three') and comment_ranking > 2 limit 5;
show meta;
‹›
Response
+---------+--------------+
| id | story_author |
+---------+--------------+
| 151171 | anewkid |
| 302758 | bks |
| 805806 | drRoflol |
| 1099245 | tnorthcutt |
| 303252 | whiten |
+---------+--------------+
5 rows in set (0.00 sec)
+----------------+---------------------------------------+
| Variable_name | Value |
+----------------+---------------------------------------+
| total | 5 |
| total_found | 2308 |
| total_relation | eq |
| time | 0.001 |
| keyword[0] | one |
| docs[0] | 224387 |
| hits[0] | 310327 |
| keyword[1] | three |
| docs[1] | 18181 |
| hits[1] | 21102 |
| keyword[2] | two |
| docs[2] | 63251 |
| hits[2] | 75961 |
| index | comment_ranking:SecondaryIndex (100%) |
+----------------+---------------------------------------+
14 rows in set (0.00 sec)SHOW META can display I/O and CPU counters, but they will only be available if searchd was started with the --iostats and --cpustats switches, respectively.
‹›
- SQL
SQL
📋
⚙
SELECT id,channel_id FROM records WHERE MATCH('one|two|three') limit 5;
SHOW META;
‹›
Response
+--------+--------------+
| id | story_author |
+--------+--------------+
| 300263 | throwaway37 |
| 713503 | mahmud |
| 716804 | mahmud |
| 776906 | jimbokun |
| 753332 | foxhop |
+--------+--------------+
5 rows in set (0.01 sec)
+-----------------------+--------+
| Variable_name | Value |
+-----------------------+--------+
| total | 5 |
| total_found | 266385 |
| total_relation | eq |
| time | 0.011 |
| cpu_time | 18.004 |
| agents_cpu_time | 0.000 |
| io_read_time | 0.000 |
| io_read_ops | 0 |
| io_read_kbytes | 0.0 |
| io_write_time | 0.000 |
| io_write_ops | 0 |
| io_write_kbytes | 0.0 |
| agent_io_read_time | 0.000 |
| agent_io_read_ops | 0 |
| agent_io_read_kbytes | 0.0 |
| agent_io_write_time | 0.000 |
| agent_io_write_ops | 0 |
| agent_io_write_kbytes | 0.0 |
| keyword[0] | one |
| docs[0] | 224387 |
| hits[0] | 310327 |
| keyword[1] | three |
| docs[1] | 18181 |
| hits[1] | 21102 |
| keyword[2] | two |
| docs[2] | 63251 |
| hits[2] | 75961 |
+-----------------------+--------+
27 rows in set (0.00 sec)Additional values, such as predicted_time, dist_predicted_time, local_fetched_docs, local_fetched_hits, local_fetched_skips, and their respective dist_fetched_* counterparts, will only be available if searchd was configured with predicted time costs and the query included predicted_time in the OPTION clause.
‹›
- SQL
SQL
📋
⚙
SELECT id,story_author FROM hn_small WHERE MATCH('one|two|three') limit 5 option max_predicted_time=100;
SHOW META;
‹›
Response
+--------+--------------+
| id | story_author |
+--------+--------------+
| 300263 | throwaway37 |
| 713503 | mahmud |
| 716804 | mahmud |
| 776906 | jimbokun |
| 753332 | foxhop |
+--------+--------------+
5 rows in set (0.01 sec)
mysql> show meta;
+---------------------+--------+
| Variable_name | Value |
+---------------------+--------+
| total | 5 |
| total_found | 266385 |
| total_relation | eq |
| time | 0.012 |
| local_fetched_docs | 307212 |
| local_fetched_hits | 407390 |
| local_fetched_skips | 24 |
| predicted_time | 56 |
| keyword[0] | one |
| docs[0] | 224387 |
| hits[0] | 310327 |
| keyword[1] | three |
| docs[1] | 18181 |
| hits[1] | 21102 |
| keyword[2] | two |
| docs[2] | 63251 |
| hits[2] | 75961 |
+---------------------+--------+
17 rows in set (0.00 sec)SHOW META must be executed immediately after the query in the same session. Since some MySQL connectors/libraries use connection pools, running SHOW META in a separate statement can lead to unexpected results, such as retrieving metadata from another query. In these cases (and generally recommended), run a multiple statement containing both the query and SHOW META. Some connectors/libraries support multi-queries within the same method for a single statement, while others may require the use of a dedicated method for multi-queries or setting specific options during connection setup.
‹›
- SQL
SQL
📋
⚙
SELECT id,story_author FROM hn_small WHERE MATCH('one|two|three') LIMIT 5; SHOW META;
‹›
Response
+--------+--------------+
| id | story_author |
+--------+--------------+
| 300263 | throwaway37 |
| 713503 | mahmud |
| 716804 | mahmud |
| 776906 | jimbokun |
| 753332 | foxhop |
+--------+--------------+
5 rows in set (0.01 sec)
+----------------+--------+
| Variable_name | Value |
+----------------+--------+
| total | 5 |
| total_found | 266385 |
| total_relation | eq |
| time | 0.011 |
| keyword[0] | one |
| docs[0] | 224387 |
| hits[0] | 310327 |
| keyword[1] | three |
| docs[1] | 18181 |
| hits[1] | 21102 |
| keyword[2] | two |
| docs[2] | 63251 |
| hits[2] | 75961 |
+----------------+--------+
13 rows in set (0.00 sec)You can also use the optional LIKE clause, which allows you to select only the variables that match a specific pattern. The pattern syntax follows standard SQL wildcards, where % represents any number of any characters, and _ represents a single character.
‹›
- SQL
SQL
📋
⚙
SHOW META LIKE 'total%';
‹›
Response
+----------------+--------+
| Variable_name | Value |
+----------------+--------+
| total | 5 |
| total_found | 266385 |
| total_relation | eq |
+----------------+--------+
3 rows in set (0.00 sec)When utilizing faceted search, you can examine the multiplier field in the SHOW META output to determine how many queries were executed in an optimized group.
‹›
- SQL
SQL
📋
⚙
SELECT * FROM facetdemo FACET brand_id FACET price FACET categories;
SHOW META LIKE 'multiplier';
‹›
Response
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
| id | price | brand_id | title | brand_name | property | j | categories |
+------+-------+----------+---------------------+-------------+-------------+---------------------------------------+------------+
| 1 | 306 | 1 | Product Ten Three | Brand One | Six_Ten | {"prop1":66,"prop2":91,"prop3":"One"} | 10,11 |
...
+----------+----------+
| brand_id | count(*) |
+----------+----------+
| 1 | 1013 |
...
+-------+----------+
| price | count(*) |
+-------+----------+
| 306 | 7 |
...
+------------+----------+
| categories | count(*) |
+------------+----------+
| 10 | 2436 |
...
+---------------+-------+
| Variable_name | Value |
+---------------+-------+
| multiplier | 4 |
+---------------+-------+
1 row in set (0.00 sec)When the cost-based query optimizer chooses to use DocidIndex, ColumnarScan, or SecondaryIndex instead of a plain filter, this is reflected in the SHOW META command.
The index variable displays the names and types of secondary indexes used during query execution. The percentage indicates how many disk chunks (in the case of an RT table) or pseudo shards (in the case of a plain table) utilized the secondary index.
‹›
- SQL
SQL
📋
⚙
SELECT count(*) FROM taxi1 WHERE tip_amount = 5;
SHOW META;
‹›
Response
+----------------+----------------------------------+
| Variable_name | Value |
+----------------+----------------------------------+
| total | 1 |
| total_found | 1 |
| total_relation | eq |
| time | 0.016 |
| index | tip_amount:SecondaryIndex (100%) |
+----------------+----------------------------------+
5 rows in set (0.00 sec)SHOW META can be used after executing a CALL PQ statement, in which case it provides different output.
SHOW META following a CALL PQ statement includes:
total- Total time spent on matching the document(s)queries_matched- Number of stored queries that match the document(s)document_matches- Number of documents that matched the queries stored in the tabletotal_queries_stored- Total number of queries stored in the tableterm_only_queries- Number of queries in the table that have terms; the remaining queries use extended query syntax.
‹›
- SQL
SQL
📋
⚙
CALL PQ ('pq', ('{"title":"angry", "gid":3 }')); SHOW META;
‹›
Response
+------+
| id |
+------+
| 2 |
+------+
1 row in set (0.00 sec)
+-----------------------+-----------+
| Variable name | Value |
+-----------------------+-----------+
| total | 0.000 sec |
| queries_matched | 1 |
| queries_failed | 0 |
| document_matched | 1 |
| total_queries_stored | 2 |
| term_only_queries | 2 |
| fast_rejected_queries | 1 |
+-----------------------+-----------+
7 rows in set (0.00 sec)Using CALL PQ with a verbose option provides more detailed output.
It includes the following additional entries:
Setup- Time spent on the initial setup of the matching process, such as parsing docs and setting optionsQueries failed- Number of queries that failedFast rejected queries- Number of queries that were not fully evaluated but quickly matched and rejected using filters or other conditionsTime per query- Detailed time for each queryTime of matched queries- Total time spent on queries that matched any documents
‹›
- SQL
SQL
📋
⚙
CALL PQ ('pq', ('{"title":"angry", "gid":3 }'), 1 as verbose); SHOW META;
‹›
Response
+------+
| id |
+------+
| 2 |
+------+
1 row in set (0.00 sec)
+-------------------------+-----------+
| Variable name | Value |
+-------------------------+-----------+
| total | 0.000 sec |
| setup | 0.000 sec |
| queries_matched | 1 |
| queries_failed | 0 |
| document_matched | 1 |
| total_queries_stored | 2 |
| term_only_queries | 2 |
| fast_rejected_queries | 1 |
| time_per_query | 69 |
| time_of_matched_queries | 69 |
+-------------------------+-----------+
10 rows in set (0.00 sec)SHOW THREADS [ OPTION columns=width[,format=sphinxql][,format=all] ]SHOW THREADS is an SQL statement that displays information about all threads and their current activities.
The resulting table contains the following columns:
TID: ID assigned to the thread by the kernelName: Thread name, also visible intop,htop,ps, and other process-viewing toolsProto: Connection protocol; possible values includesphinx,mysql,http,ssl,compressed,replication, or a combination (e.g.,http,sslorcompressed,mysql)State: Thread state; possible values arehandshake,net_read,net_write,query,net_idleConnection from: Client'sip:portConnID: Connection ID (starting from 0)This/prev job time: When the thread is busy - how long the current job has been running; when the thread is idling - previous job duration + suffixprevJobs done: Number of jobs completed by this threadThread status:idlingorworkingInfo: Information about the query, which may include multiple queries if the query targets a distributed table or a real-time table
‹›
- SQL
- JSON
- PHP
- Python
- javascript
- Java
- C#
- TypeScript
- Go
📋
⚙
SHOW THREADS;POST /cli -d "SHOW THREADS"require_once __DIR__ . '/vendor/autoload.php';
$config = ['host'=>'127.0.0.1','port'=>9308];
$client = new \Manticoresearch\Client($config);
print_r($client->nodes()->threads());import manticoresearch
config = manticoresearch.Configuration(
host = "http://127.0.0.1:9308"
)
client = manticoresearch.ApiClient(config)
utilsApi = manticoresearch.UtilsApi(client)
print(utilsApi.sql('SHOW THREADS'))var Manticoresearch = require('manticoresearch');
var utilsApi = new Manticoresearch.UtilsApi();
async function showThreads() {
res = await utilsApi.sql('SHOW THREADS');
console.log(JSON.stringify(res, null, 4));
}
showThreads();utilsApi.sql("SHOW THREADS");utilsApi.Sql("SHOW THREADS");res = await utilsApi.sql('SHOW THREADS');apiClient.UtilsAPI.Sql(context.Background()).Body("SHOW THREADS").Execute()
‹›
Response
*************************** 1. row ***************************
TID: 83
Name: work_1
Proto: mysql
State: query
Connection from: 172.17.0.1:43300
ConnID: 8
This/prev job time: 630us
CPU activity: 94.15%
Jobs done: 2490
Thread status: working
Info: SHOW THREADS
*************************** 2. row ***************************
TID: 84
Name: work_2
Proto: mysql
State: query
Connection from: 172.17.0.1:43301
ConnID: 9
This/prev job time: 689us
CPU activity: 89.23%
Jobs done: 1830
Thread status: working
Info: show threads
+--------+---------+-------+-------+-----------------+--------+-----------------------+-----------+---------------+--------------+
| TID | Name | Proto | State | Connection from | ConnID | This/prev job time, s | Jobs done | Thread status | Info |
+--------+---------+-------+-------+-----------------+--------+-----------------------+-----------+---------------+--------------+
| 501494 | work_23 | http | query | 127.0.0.1:41300 | 1473 | 249us | 1681 | working | show_threads |
+--------+---------+-------+-------+-----------------+--------+-----------------------+-----------+---------------+--------------+Array
(
[0] => Array
(
[TID] => 506960
[Name] => work_8
[Proto] => http
[State] => query
[Connection from] => 127.0.0.1:38072
[ConnID] => 17
[This/prev job time, s] => 231us
[CPU activity] => 93.54%
[Jobs done] => 8
[Thread status] => working
[Info] => show_threads
)
)[{'columns': [{'TID': {'type': 'long'}}, {'Name': {'type': 'string'}}, {'Proto': {'type': 'string'}}, {'State': {'type': 'string'}}, {'Connection from': {'type': 'string'}}, {'ConnID': {'type': 'long long'}}, {'This/prev job time, s': {'type': 'string'}}, {'CPU activity': {'type': 'float'}}, {'Jobs done': {'type': 'long'}}, {'Thread status': {'type': 'string'}}, {'Info': {'type': 'string'}}], 'data': [{'TID': 506958, 'Name': 'work_6', 'Proto': 'http', 'State': 'query', 'Connection from': '127.0.0.1:38600', 'ConnID': 834, 'This/prev job time, s': '206us', 'CPU activity': '91.85%', 'Jobs done': 943, 'Thread status': 'working', 'Info': 'show_threads'}], 'total': 1, 'error': '', 'warning': ''}][
{
"columns": [
{
"TID": {
"type": "long"
}
},
{
"Name": {
"type": "string"
}
},
{
"Proto": {
"type": "string"
}
},
{
"State": {
"type": "string"
}
},
{
"Connection from": {
"type": "string"
}
},
{
"ConnID": {
"type": "long long"
}
},
{
"This/prev job time, s": {
"type": "string"
}
},
{
"CPU activity": {
"type": "float"
}
},
{
"Jobs done": {
"type": "long"
}
},
{
"Thread status": {
"type": "string"
}
},
{
"Info": {
"type": "string"
}
}
],
"data": [
{
"TID": 506964,
"Name": "work_12",
"Proto": "http",
"State": "query",
"Connection from": "127.0.0.1:36656",
"ConnID": 2884,
"This/prev job time, s": "236us",
"CPU activity": "91.73%",
"Jobs done": 3328,
"Thread status": "working",
"Info": "show_threads"
}
],
"total": 1,
"error": "",
"warning": ""
}
]
{
columns=[
{
TID={
type=string
}
},
{
Name={
type=string
}
},
{
Proto={
type=string
}
},
{
State={
type=string
}
},
{
Connection from={
type=string
}
},
{
ConnID={
type=string
}
},
{
This/prev job time={
type=string
}
},
{
CPU activity={
type=string
}
},
{
Jobs done={
type=string
}
},
{
Thread status={
type=string
}
},
{
Info={
type=string
}
}
],
data=[
{
TID=82,
Name=work_0,
Proto=http,
State=query,
Connection from=172.17.0.1:60550,
ConnID=163,
This/prev job time=105us,
CPU activity=44.68%,
Jobs done=849,
Thread status=working,
Info=show_threads
}
],
total=0,
error=,
warning=
}
{
columns=[
{
TID={
type=string
}
},
{
Name={
type=string
}
},
{
Proto={
type=string
}
},
{
State={
type=string
}
},
{
Connection from={
type=string
}
},
{
ConnID={
type=string
}
},
{
This/prev job time= {
type=string
}
},
{
Jobs done={
type=string
}
},
{
Thread status={
type=string
}
},
{
Info={
type=string
}
}
],
data=[
{
TID=83,
Name=work_1,
Proto=http,
State=query,
Connection from=172.17.0.1:41410,
ConnID=6,
This/prev job time=689us,
Jobs done=159,
Thread status=working,
Info=show_threads
}
],
total=0,
error="",
warning=""
}[
{
"columns": [
{
"TID": {
"type": "long"
}
},
{
"Name": {
"type": "string"
}
},
{
"Proto": {
"type": "string"
}
},
{
"State": {
"type": "string"
}
},
{
"Connection from": {
"type": "string"
}
},
{
"ConnID": {
"type": "long long"
}
},
{
"This/prev job time, s": {
"type": "string"
}
},
{
"CPU activity": {
"type": "float"
}
},
{
"Jobs done": {
"type": "long"
}
},
{
"Thread status": {
"type": "string"
}
},
{
"Info": {
"type": "string"
}
}
],
"data": [
{
"TID": 506964,
"Name": "work_12",
"Proto": "http",
"State": "query",
"Connection from": "127.0.0.1:36656",
"ConnID": 2884,
"This/prev job time, s": "236us",
"CPU activity": "91.73%",
"Jobs done": 3328,
"Thread status": "working",
"Info": "show_threads"
}
],
"total": 1,
"error": "",
"warning": ""
}
][
{
"columns": [
{
"TID": {
"type": "long"
}
},
{
"Name": {
"type": "string"
}
},
{
"Proto": {
"type": "string"
}
},
{
"State": {
"type": "string"
}
},
{
"Connection from": {
"type": "string"
}
},
{
"ConnID": {
"type": "long long"
}
},
{
"This/prev job time, s": {
"type": "string"
}
},
{
"CPU activity": {
"type": "float"
}
},
{
"Jobs done": {
"type": "long"
}
},
{
"Thread status": {
"type": "string"
}
},
{
"Info": {
"type": "string"
}
}
],
"data": [
{
"TID": 506964,
"Name": "work_12",
"Proto": "http",
"State": "query",
"Connection from": "127.0.0.1:36656",
"ConnID": 2884,
"This/prev job time, s": "236us",
"CPU activity": "91.73%",
"Jobs done": 3328,
"Thread status": "working",
"Info": "show_threads"
}
],
"total": 1,
"error": "",
"warning": ""
}
]The Info column displays:
- Raw text of queries executed via the Manticore SQL interface
- Full text syntax, comments, and data size for queries run through the internal Manticore binary protocol (e.g., from a remote Manticore instance)
You can limit the maximum width of the Info column by specifying the columns=N option.
By default, queries are displayed in their original format. However, when the format=sphinxql option is used, queries will be shown in SQL format, regardless of the protocol used for execution.
Using format=all will show all threads, while idling and system threads are hidden without this option (e.g., those busy with OPTIMIZE).
‹›
- SQL
- JSON
- PHP
- Python
- javascript
- Java
- C#
- TypeScript
- Go
📋
⚙
SHOW THREADS OPTION columns=30\GPOST /cli -d "SHOW THREADS OPTION columns=30"$client->nodes()->threads(['body'=>['columns'=>30]]);utilsApi.sql('SHOW THREADS OPTION columns=30')res = await utilsApi.sql('SHOW THREADS OPTION columns=30');utilsApi.sql("SHOW THREADS OPTION columns=30");utilsApi.Sql("SHOW THREADS OPTION columns=30");res = await utilsApi.sql('SHOW THREADS OPTION columns=30');apiClient.UtilsAPI.Sql(context.Background()).Body("SHOW THREADS OPTION columns=30").Execute()SHOW QUERIESNOTE:
SHOW QUERIESrequires Manticore Buddy. If it doesn't work, make sure Buddy is installed.
SHOW QUERIES returns information about all currently running queries. The output is a table with the following structure:
id: Query ID that can be used in KILL to terminate the queryquery: Query statement or a portion of ittime: Time taken on command execution or how long ago the query was performed (in this case, the value will includeago)protocol: Connection protocol, with possible values beingsphinx,mysql,http,ssl,compressed,replication, or a combination (e.g.,http,sslorcompressed,mysql)host: Client'sip:port
‹›
- SQL
SQL
📋
⚙
mysql> SHOW QUERIES;
‹›
Response
+------+--------------+---------+----------+-----------------+
| id | query | time | protocol | host |
+------+--------------+---------+----------+-----------------+
| 111 | select | 5ms ago | http | 127.0.0.1:58986 |
| 96 | SHOW QUERIES | 255us | mysql | 127.0.0.1:33616 |
+------+--------------+---------+----------+-----------------+
2 rows in set (0.61 sec)Refer to SHOW THREADS if you'd like to gain insight from the perspective of the threads themselves.