This topic describes how to use the performance trend feature to view the performance metrics of your PolarDB-X instance.

PolarDB-X is integrated with the performance trend feature that is provided by Data Autonomy Service (DAS). You can use this feature to view the details of each performance metric of compute nodes, data nodes, and Global Meta Service (GMS) nodes of your PolarDB-X instance. You can use multiple methods to view the performance trends of your PolarDB-X instance. You can specify a time range to view the performance metrics that are collected in the specified period of time. You can specify two dates to view the comparison between the performance metrics that are collected on the specified days. You can also use custom dashboards to display the performance metrics that you want to view.

View performance trends

  1. Log on to the PolarDB-X console.
  2. On the Instance List page, click the PolarDB-X 2.0 tab.
  3. In the top navigation bar, select the region where the instance whose performance trends you want to view is deployed.
  4. On the page that appears, click the ID of the instance.
  5. In the left-side navigation pane, choose Diagnosis and optimization > Performance trend. 456789
  6. On the page that appears, you can view the performance metrics of the compute nodes, data nodes, and GMS nodes. For information about each metric, see Metric description.
  7. In the Nodes section of each tab, you can view information of the nodes, including the specifications, CPU utilization, and memory usage.
  8. Click the Performance Trends tab, specify a node and a time range, and then click Search to view performance monitoring data in each chart.
  9. Click the Performance Trend Comparison tab. Specify a node, two dates, and a time range, and then click Search to view the comparison between the performance metrics that are collected on the specified days.
  10. Click Custom Chart. You can create dashboards to display the performance metrics that you want to view. When you create a chart, you can specify multiple performance metrics that you want to display on the chart. This way, you can analyze metrics that are displayed on the dashboards and troubleshoot performance issues.
    Note You must create dashboards before you create charts. For more information, see Monitoring dashboards.

Diagnose node performance

PolarDB-X provides the performance diagnostics feature. In a performance trend chart of a node, select a time range to diagnose the performance of the node based on resource usage and slow SQL queries.

Note Compute nodes and data nodes support the performance diagnostics feature. GMS nodes do not support this feature.
  1. Log on to the PolarDB-X console.
  2. On the Instance List page, click the PolarDB-X 2.0 tab.
  3. In the top navigation bar, select the region where the instance for which you want to diagnose performance is deployed.
  4. On the page that appears, click the ID of the instance.
  5. In the left-side navigation pane, choose Diagnosis and optimization > Performance trend.
  6. In a performance trend chart, select a time range and click Diagnose. 456789
  7. On the Details page that appears, you can view the statistical information about resource usage and slow SQL queries. 456789456789

Metric description

Compute nodes
Metric Unit Description
polardbx.cpu_usage % The average CPU utilization within a specified period of time.
polardbx.mem_usage % The memory usage of the Java Virtual Machine (JVM). In specific scenarios, the memory usage fluctuates.
polardbx.active_connection Count The total number of connections.
polardbx.running_thread Count The number of active connections.
polardbx.network_in_bytes Byte The total amount of inbound traffic.
polardbx.network_out_bytes Byte The total amount of outbound traffic.
polardbx.logic_qps Per Second The total number of logical SQL query statements that are executed per second. Logical SQL query statements are SQL statements that are sent from your business application to your PolarDB-X database.
polardbx.physical_qps Per Second The total number of physical SQL query statements that are executed per second. Physical SQL query statements are executed on the read-only nodes of your database.
polardbx.logic_rt Ms The average response time of logical SQL queries.
polardbx.physical_rt Ms The average response time of physical SQL queries.
polardbx.slow_request_count Per Second The number of slow logical SQL queries.
polardbx.physical_slow_reuquest_count Per Second The number of slow physical SQL queries.
Data nodes and GMS nodes
Metric Unit Description
mysql.tps Per Second The number of transactions that are executed on the node per second.
mysql.qps Per Second The number of queries that are executed on the node per second.
mysql.total_session Count The total number of sessions.
mysql.active_session Count The number of active sessions.
mysql.bytes_received KByte The average number of bytes in the data that the node receives from all clients per second.
mysql.bytes_sent KByte The average number of bytes in the data that is sent from the node to all clients per second.
mysql.tb.tmp.disk Count The number of temporary tables that are automatically created on the disk of the node when SQL statements are executed.
mysql.insert_ps Per Second The average number of INSERT statements that are executed per second.
mysql.select_ps Per Second The average number of SELECT statements that are executed per second.
mysql.update_ps Per Second The average number of UPDATE statements that are executed per second.
mysql.delete_ps Per Second The average number of DELETE statements that are executed per second.
mysql.replace_ps Per Second The average number of REPLACE statements that are executed per second.
mysql.innodb_data_written KByte The average number of bytes in the data that is written to InnoDB per second.
mysql.innodb_data_read KByte The average number of bytes in the data that is read from InnoDB per second.
mysql.innodb_buffer_pool_reads_requests Count The average number of logical reads that read data pages from the InnoDB buffer pool per second.
mysql.innodb_bp_dirty_pct % The ratio of dirty pages in the InnoDB buffer pool. Calculation formula: Innodb_buffer_pool_pages_dirty/Innodb_buffer_pool_pages_data × 100%.
mysql.innodb_bp_hit % The read hit ratio of the InnoDB buffer pool. Calculation formula: (Innodb_buffer_pool_read_requests - Innodb_buffer_pool_reads)/Innodb_buffer_pool_read_requests × 100%.
mysql.innodb_bp_usage_pct % The utilization of the InnoDB buffer pool. Calculation formula: Innodb_buffer_pool_pages_data/(Innodb_buffer_pool_pages_data + innodb_buffer_pool_pages_free) × 100%.
mysql.innodb_log_writes Per Second The average number of physical writes to the InnoDB redo log file per second.
mysql.innodb_os_log_fsyncs Per Second The average number of fsync() writes to log files per second.
mysql.innodb_rows_deleted Per Second The average number of InnoDB rows from which data is deleted per second.
mysql.innodb_rows_read Per Second The average number of InnoDB rows from which data is read per second.
mysql.innodb_rows_inserted Per Second The average number of InnoDB rows into which data is inserted per second.
mysql.innodb_rows_updated Per Second The average number of InnoDB rows in which data is updated per second.
mysql.mem_usage % The memory usage of the MySQL instance in the entire operating system.
mysql.cpu_usage % The CPU utilization of MySQL processes. This metric can reach up to 100% for Alibaba Cloud database instances.
mysql.data.size MByte The size of the data space.
mysql.tmp.size MByte The size of the temporary tablespace.
mysql.other.size MByte The size of the system file space.
mysql.instance.size MByte The total used space of the MySQL database instance.
mysql.log.size MByte The size of the log space.
mysql.iops Count The IOPS of the MySQL database instance.