insert into client_info client_id, username, access_token, os_name, os_version, java_version, app_version, hostname, ip_address, status, auth_time, last_active_time, online, cpu_usage, memory_usage, disk_usage, network_status, heartbeat_time, #{clientId}, #{username}, #{accessToken}, #{osName}, #{osVersion}, #{javaVersion}, #{appVersion}, #{hostname}, #{ipAddress}, #{status}, #{authTime}, #{lastActiveTime}, #{online}, #{cpuUsage}, #{memoryUsage}, #{diskUsage}, #{networkStatus}, #{heartbeatTime}, update client_info username = #{username}, access_token = #{accessToken}, os_name = #{osName}, os_version = #{osVersion}, java_version = #{javaVersion}, app_version = #{appVersion}, hostname = #{hostname}, ip_address = #{ipAddress}, status = #{status}, last_active_time = #{lastActiveTime}, online = #{online}, cpu_usage = #{cpuUsage}, memory_usage = #{memoryUsage}, disk_usage = #{diskUsage}, network_status = #{networkStatus}, heartbeat_time = #{heartbeatTime}, update_time = NOW() where client_id = #{clientId} insert into client_event_log( client_id, event_type, event_content, event_time, event_level, status )values( #{clientId}, #{eventType}, #{eventContent}, #{eventTime}, #{eventLevel}, #{status} ) insert into client_data_report client_id, data_type, data_count, collect_time, status, #{clientId}, #{dataType}, #{dataCount}, #{collectTime}, #{status}, select * from client_info where client_id = #{clientId} select * from client_info AND client_id like concat('%', #{clientId}, '%') AND username like concat('%', #{username}, '%') AND os_name like concat('%', #{osName}, '%') AND status = #{status} AND online = #{online} order by last_active_time desc select id, client_id, username, error_type, error_message, error_time, stack_trace, os_name, os_version, app_version from client_error_report AND client_id like concat('%', #{clientId}, '%') AND error_type = #{errorType} order by error_time desc select * from client_event_log AND client_id like concat('%', #{clientId}, '%') AND event_type = #{eventType} AND event_level = #{eventLevel} AND status = #{status} order by event_time desc select * from client_data_report AND client_id like concat('%', #{clientId}, '%') AND data_type = #{dataType} AND status = #{status} order by collect_time desc select count(*) from client_info where online = '1' SELECT COUNT(*) FROM client_info SELECT COUNT(*) FROM client_error_report WHERE DATE(error_time) = CURDATE() SELECT COALESCE(SUM(data_count), 0) FROM client_data_report WHERE DATE(collect_time) = CURDATE() AND data_type IN ('BANMA', 'RAKUTEN', 'AMAZON', 'ORDER', 'AMAZON_BATCH', 'RAKUTEN_BATCH') SELECT CASE WHEN data_type IN ('ORDER', 'BANMA') THEN 'BANMA' WHEN data_type LIKE 'AMAZON%' THEN 'AMAZON' WHEN data_type LIKE 'RAKUTEN%' THEN 'RAKUTEN' ELSE data_type END as dataType, COALESCE(SUM(data_count), 0) as count FROM client_data_report WHERE data_type IN ('ORDER', 'BANMA', 'RAKUTEN', 'AMAZON', 'AMAZON_BATCH', 'RAKUTEN_BATCH') AND DATE(collect_time) >= DATE_SUB(CURDATE(), INTERVAL 30 DAY) GROUP BY CASE WHEN data_type IN ('ORDER', 'BANMA') THEN 'BANMA' WHEN data_type LIKE 'AMAZON%' THEN 'AMAZON' WHEN data_type LIKE 'RAKUTEN%' THEN 'RAKUTEN' ELSE data_type END ORDER BY count DESC INSERT INTO client_error_report client_id, username, error_type, error_message, stack_trace, error_time, os_name, os_version, app_version, #{clientId}, #{username}, #{errorType}, #{errorMessage}, #{stackTrace}, #{errorTime}, #{osName}, #{osVersion}, #{appVersion}, update client_info set online = #{param2} where client_id = #{param1} update client_info last_active_time = #{lastActiveTime}, heartbeat_time = #{heartbeatTime}, online = #{online}, cpu_usage = #{cpuUsage}, memory_usage = #{memoryUsage}, disk_usage = #{diskUsage}, network_status = #{networkStatus} where client_id = #{clientId} update client_auth_info username = #{username}, access_token = #{accessToken}, os_name = #{osName}, os_version = #{osVersion}, java_version = #{javaVersion}, app_version = #{appVersion}, hostname = #{hostname}, ip_address = #{ipAddress}, status = #{status}, last_active_time = #{lastActiveTime}, online = #{online} where client_id = #{clientId} select id, client_id, username, access_token, os_name, os_version, java_version, app_version, hostname, ip_address, status, auth_time, last_active_time, online from client_auth_info select id, client_id, username, error_type, error_message, stack_trace, error_time, os_name, os_version, app_version from client_error_report select id, client_id, username, heartbeat_time, cpu_usage, memory_usage, disk_usage, network_status from client_heartbeat select id, client_id, username, data_type, data_count, collect_time, status from client_data_report SELECT days.date_str as date, IFNULL(counts.client_count, 0) as count FROM ( SELECT DATE_FORMAT(CURDATE() - INTERVAL 6 DAY, '%Y-%m-%d') as date_str UNION SELECT DATE_FORMAT(CURDATE() - INTERVAL 5 DAY, '%Y-%m-%d') UNION SELECT DATE_FORMAT(CURDATE() - INTERVAL 4 DAY, '%Y-%m-%d') UNION SELECT DATE_FORMAT(CURDATE() - INTERVAL 3 DAY, '%Y-%m-%d') UNION SELECT DATE_FORMAT(CURDATE() - INTERVAL 2 DAY, '%Y-%m-%d') UNION SELECT DATE_FORMAT(CURDATE() - INTERVAL 1 DAY, '%Y-%m-%d') UNION SELECT DATE_FORMAT(CURDATE(), '%Y-%m-%d') ) days LEFT JOIN ( SELECT DATE_FORMAT(auth_time, '%Y-%m-%d') as heartbeat_date, COUNT(DISTINCT client_id) as client_count FROM client_info WHERE auth_time >= DATE_SUB(CURDATE(), INTERVAL 6 DAY) GROUP BY DATE_FORMAT(auth_time, '%Y-%m-%d') ) counts ON days.date_str = counts.heartbeat_date ORDER BY days.date_str ASC SELECT a.client_id as clientId, a.username, a.os_name as osName, a.os_version as osVersion, a.java_version as javaVersion, a.app_version as appVersion, a.hostname, a.ip_address as ipAddress, CASE a.status WHEN '0' THEN '正常' ELSE '异常' END as status, DATE_FORMAT(a.auth_time, '%Y-%m-%d %H:%i:%s') as authTime, DATE_FORMAT(a.last_active_time, '%Y-%m-%d %H:%i:%s') as lastActiveTime, a.online FROM client_info a WHERE a.client_id = #{clientId} SELECT app_version as version, COUNT(*) as count FROM client_info GROUP BY app_version ORDER BY count DESC SELECT COUNT(*) as requestCount, 0 as avgResponseTime FROM client_data_report WHERE data_type = 'API_CALL' AND collect_time >= DATE_SUB(NOW(), INTERVAL 24 HOUR) INSERT INTO client_alibaba1688_monitor ( client_id, ip_address, event_type, event_time, duration, create_time ) VALUES ( #{clientId}, #{ipAddress}, #{eventType}, #{eventTime}, #{duration}, #{createTime} ) SELECT m.id, m.client_id, m.ip_address, m.event_type, m.event_time, m.duration, m.create_time, a.username, a.hostname FROM client_alibaba1688_monitor m LEFT JOIN client_info a ON m.client_id = a.client_id AND m.event_type != 'MOBILE_FIRST_ACCESS' AND m.client_id = #{clientId} AND m.ip_address LIKE concat('%', #{ipAddress}, '%') AND m.event_type = #{eventType} AND DATE_FORMAT(m.create_time, '%Y-%m-%d') >= #{beginTime} AND DATE_FORMAT(m.create_time, '%Y-%m-%d') <= #{endTime} ORDER BY m.create_time DESC SELECT COUNT(*) AS totalEvents, SUM(CASE WHEN event_type = 'MOBILE_BLOCKED' THEN 1 ELSE 0 END) AS mobileBlockedCount, SUM(CASE WHEN event_type = 'DESKTOP_BLOCKED' THEN 1 ELSE 0 END) AS desktopBlockedCount, COUNT(DISTINCT ip_address) AS uniqueIpCount, AVG(CASE WHEN event_type = 'MOBILE_BLOCKED' AND duration > 0 THEN duration ELSE NULL END) / 1000 AS avgMobileDuration, AVG(CASE WHEN event_type = 'DESKTOP_BLOCKED' AND duration > 0 THEN duration ELSE NULL END) / 1000 AS avgDesktopDuration FROM client_alibaba1688_monitor WHERE create_time >= DATE_SUB(NOW(), INTERVAL 30 DAY) AND event_type != 'MOBILE_FIRST_ACCESS' UPDATE client_info SET online = '0' WHERE online = '1' AND (heartbeat_time IS NULL OR heartbeat_time < DATE_SUB(NOW(), INTERVAL 7 DAY)) DELETE FROM client_error_report WHERE error_time < DATE_SUB(NOW(), INTERVAL 30 DAY) DELETE FROM client_event_log WHERE event_time < DATE_SUB(NOW(), INTERVAL 7 DAY) SELECT * FROM client_data_report WHERE client_id = #{clientId} AND data_type = #{dataType} AND status = #{status} AND DATE(collect_time) = DATE(NOW()) ORDER BY collect_time DESC LIMIT 1 UPDATE client_data_report SET data_count = #{newCount}, collect_time = NOW() WHERE id = #{id}