{"id":820,"date":"2020-10-29T00:00:00","date_gmt":"2020-10-29T00:00:00","guid":{"rendered":"https:\/\/en.pingcap.com\/blog\/metrics-relation-graph-helps-dba-quickly-locate-performance-problems\/"},"modified":"2024-08-21T06:49:09","modified_gmt":"2024-08-21T13:49:09","slug":"metrics-relation-graph-helps-dba-quickly-locate-performance-problems","status":"publish","type":"post","link":"https:\/\/www.pingcap.com\/ko\/blog\/metrics-relation-graph-helps-dba-quickly-locate-performance-problems\/","title":{"rendered":"Metrics Relation Graph Helps DBAs Quickly Locate Performance Problems in TiDB"},"content":{"rendered":"<p><a href=\"\/ko\/tidb\/\">\ud2f0DB<\/a>, an open-source, distributed SQL database, provides detailed monitoring metrics through Prometheus and Grafana. These metrics are often the key to troubleshooting performance problems in the cluster.<\/p>\n\n\n\n<p>However, for novice TiDB users, understanding hundreds of monitoring metrics can be overwhelming. You may wonder:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>How do these hundreds of metrics relate to each other?<\/li>\n\n\n\n<li>How can I quickly find which operations are the slowest?<\/li>\n\n\n\n<li>When I discover a slow write, how can I locate the cause?<\/li>\n<\/ul>\n\n\n\n<p>TiDB 4.0.7 introduces a new feature in its web UI <a href=\"https:\/\/docs.pingcap.com\/tidb\/stable\/dashboard-intro\">TiDB Dashboard<\/a>: the <a href=\"https:\/\/docs.pingcap.com\/tidb\/stable\/dashboard-metrics-relation\">metrics relation graph<\/a>. It provides a tree diagram of the TiDB cluster performance metrics, enabling users to quickly see the relationships between TiDB internal processes and to get a new perspective on the cluster status.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Overview\"><\/span>Overview<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>The metrics relation graph presents database metrics as parent-child relationships. In the graph, each box represents a monitoring item, and it includes:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The name of the item<\/li>\n\n\n\n<li>The total duration of the item<\/li>\n\n\n\n<li>The percentage the item duration takes up in the whole query duration<\/li>\n<\/ul>\n\n\n\n<p>In each parent box, the total duration = its own duration + its child box&#8217;s duration. Take the following box as an example:<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"134\" src=\"https:\/\/static.pingcap.com\/files\/2024\/05\/18000503\/monitoring-metrics-relation-graph-parent-box-1024x134.png\" alt=\"monitoring-metrics-relation-graph-parent-box\" class=\"wp-image-16891\" srcset=\"https:\/\/static.pingcap.com\/files\/2024\/05\/18000503\/monitoring-metrics-relation-graph-parent-box-1024x134.png 1024w, https:\/\/static.pingcap.com\/files\/2024\/05\/18000503\/monitoring-metrics-relation-graph-parent-box-300x39.png 300w, https:\/\/static.pingcap.com\/files\/2024\/05\/18000503\/monitoring-metrics-relation-graph-parent-box-768x101.png 768w, https:\/\/static.pingcap.com\/files\/2024\/05\/18000503\/monitoring-metrics-relation-graph-parent-box-1440x189.png 1440w, https:\/\/static.pingcap.com\/files\/2024\/05\/18000503\/monitoring-metrics-relation-graph-parent-box.png 1500w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<div class=\"caption-center\">A parent box<\/div>\n\n\n\n<p>The <code>tidb_execute<\/code> item&#8217;s total duration is 19,306.46 s, accounting for 89.40% of the total query duration. Of this duration, the <code>tidb_execute<\/code> item itself only consumes 9,070.18 s, and its child items consume the rest.<\/p>\n\n\n\n<p>If you hover the cursor over this box, you can see the detailed information about this monitoring item: its description, total count, average time, average P99 (99th percentile) duration, and so on.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img loading=\"lazy\" decoding=\"async\" width=\"1312\" height=\"250\" src=\"https:\/\/en.pingcap.com\/wp-content\/uploads\/2020\/10\/monitoring-metrics-relation-graph-detailed-info.png\" alt=\"The metrics relation graph detailed information\" class=\"wp-image-821\" srcset=\"https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-detailed-info.png 1312w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-detailed-info-300x57.png 300w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-detailed-info-1024x195.png 1024w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-detailed-info-768x146.png 768w\" sizes=\"auto, (max-width: 1312px) 100vw, 1312px\" \/><\/figure>\n\n\n\n<div class=\"caption-center\">The detailed information of a monitoring item<\/div>\n\n\n\n<p>The size and color of each box is proportional to the percentage of the item&#8217;s duration in the total query duration. Therefore, the items that take up too much time clearly stand out in the diagram. You can easily focus on these items and follow the parent-child link to locate the root cause of the problem.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Example 1 &#8211; investigating slow cluster response time<\/h3>\n\n\n\n<p>Assume that your company just launched a new application. You notice that the cluster response gets much slower, even though the server CPU load is quite low. To find out the cause, you generate a metrics relation graph:<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img loading=\"lazy\" decoding=\"async\" width=\"1600\" height=\"931\" src=\"https:\/\/en.pingcap.com\/wp-content\/uploads\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-1.png\" alt=\"tidb_query_total_time example 1\" class=\"wp-image-822\" srcset=\"https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-1.png 1600w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-1-300x175.png 300w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-1-1024x596.png 1024w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-1-768x447.png 768w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-1-1536x894.png 1536w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-1-1440x838.png 1440w\" sizes=\"auto, (max-width: 1600px) 100vw, 1600px\" \/><\/figure>\n\n\n\n<div class=\"caption-center\">tidb_query_total_time example 1<\/div>\n\n\n\n<p>From the metrics relation graph, you get the following findings in a glance:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Box<\/strong><\/td><td><strong>Description<\/strong><\/td><\/tr><tr><td><code>tidb_query.Update<\/code><\/td><td>The <code>UPDATE<\/code> statement takes up 99.59% of the total query duration.<\/td><\/tr><tr><td><code>tidb_execute <\/code><\/td><td>The TiDB execution engine takes up 68.69% of the total duration.<\/td><\/tr><tr><td><code>tidb_txn_cmd.commit<\/code><\/td><td>Committing the transaction takes up 30.66% of the total duration.<\/td><\/tr><tr><td><code>tidb_kv_backoff.txnLock<\/code><\/td><td>When the transaction encounters lock conflict, the backoff operation takes up 15%, which is much higher than the <code>tidb_kv_request<\/code> that sends Prewrite and Commit RPC requests.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>By now, you can say for sure that the <code>UPDATE<\/code> statement has a severe write conflict. The next step is to find out <a href=\"https:\/\/docs.pingcap.com\/tidb\/stable\/troubleshoot-write-conflicts\">which table and SQL statement causes the conflict<\/a>, and then work with the application developers to avoid the write conflict.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Example 2 &#8211; finding out why data import is slow<\/h3>\n\n\n\n<p>Assume that you need to load a large batch of data into your TiDB cluster, but the import rate is slow. You want to know why, so again you generate a metrics relation graph:<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img loading=\"lazy\" decoding=\"async\" width=\"1558\" height=\"1600\" src=\"https:\/\/en.pingcap.com\/wp-content\/uploads\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-2.png\" alt=\"tidb_query_total_time example 2\" class=\"wp-image-823\" srcset=\"https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-2.png 1558w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-2-292x300.png 292w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-2-997x1024.png 997w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-2-768x789.png 768w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-2-1496x1536.png 1496w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-tidb_query_total_time-2-1440x1479.png 1440w\" sizes=\"auto, (max-width: 1558px) 100vw, 1558px\" \/><\/figure>\n\n\n\n<div class=\"caption-center\">tidb_query_total_time example 2<\/div>\n\n\n\n<p>Note the shaded box near the bottom of the tree: &#8216;tikv_raftstore_propose_wait&#8217;. This box indicates that the &#8220;propose&#8221; process of TiKV&#8217;s Raftstore has a long wait duration. This usually means that Raftstore has hit a bottleneck. Next, you can check the metrics of Raftstore CPU and the latency of the append log and apply log. If Raftstore&#8217;s thread CPU utilization is low, then the root cause may be in the disk. For more troubleshooting information, you can refer to <a href=\"https:\/\/asktug.com\/_\/tidb-performance-map\/#\/tikv\">TiKV Performance Map<\/a> \ub610\ub294 <a href=\"https:\/\/docs.pingcap.com\/tidb\/stable\/troubleshoot-high-disk-io\">Troubleshoot High Disk I\/O Usage in TiDB<\/a>. You may also check <a href=\"https:\/\/docs.pingcap.com\/tidb\/stable\/troubleshoot-hot-spot-issues\">whether there&#8217;s a hotspot<\/a> in the cluster.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Try_it_out\"><\/span>Try it out<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>To generate a metrics relation graph, you need to deploy TiDB 4.0.7 (or later) and <a href=\"https:\/\/prometheus.io\/\">Prometheus<\/a>, an open-source monitoring system. We recommend you <a href=\"https:\/\/docs.pingcap.com\/tidb\/stable\/production-deployment-using-tiup\">deploy TiDB using TiUP<\/a>, which automatically deploys Prometheus along with the cluster.<\/p>\n\n\n\n<p>Once you&#8217;ve deployed TiDB, you can login to <a href=\"https:\/\/docs.pingcap.com\/tidb\/stable\/dashboard-intro\">TiDB Dashboard<\/a> to view the overall status of the cluster. In the <strong>Cluster Diagnostics<\/strong> page, configure the range start time and range duration, and click <strong>Generate Metrics Relation<\/strong>. Your metrics relation graph is ready!<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img loading=\"lazy\" decoding=\"async\" width=\"1600\" height=\"622\" src=\"https:\/\/en.pingcap.com\/wp-content\/uploads\/2020\/10\/monitoring-metrics-relation-graph-generate.png\" alt=\"Generate a metrics relation graph\" class=\"wp-image-824\" srcset=\"https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-generate.png 1600w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-generate-300x117.png 300w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-generate-1024x398.png 1024w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-generate-768x299.png 768w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-generate-1536x597.png 1536w, https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph-generate-1440x560.png 1440w\" sizes=\"auto, (max-width: 1600px) 100vw, 1600px\" \/><\/figure>\n\n\n\n<div class=\"caption-center\">Generate a metrics relation graph<\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Our_next_step\"><\/span>Our next step<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>The metrics relation graph is aimed to help users quickly grasp the relationship between TiDB cluster load and numerous monitoring items.<\/p>\n\n\n\n<p>In the future, we plan to integrate this feature with the <a href=\"https:\/\/asktug.com\/_\/tidb-performance-map\/#\/\">TiDB Performance Map<\/a> so that it can show the relationships between other associated monitoring items and even with their configurations. With this powerful feature, DBAs will be able to diagnose TiDB clusters with less effort and more efficiency.<\/p>\n\n\n\n<p>If you&#8217;re interested in the metics relation graph, feel free to visit <a href=\"https:\/\/github.com\/pingcap-incubator\/tidb-dashboard\">our repository<\/a> to contribute to the code or raise your question.<\/p>","protected":false},"excerpt":{"rendered":"<p>TiDB v4.0.7 introduced a new feature: the metrics relation graph. It helps users clearly see the relationship between different performance metrics in a database cluster and thus quickly locate the root causes of performance problems.<\/p>","protected":false},"author":40,"featured_media":826,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"ub_ctt_via":"","footnotes":""},"categories":[13],"tags":[49],"class_list":["post-820","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-product","tag-troubleshooting"],"acf":[],"featured_image_src":"https:\/\/static.pingcap.com\/files\/2020\/10\/monitoring-metrics-relation-graph.png","author_info":{"display_name":"Shuang Chen","author_link":"https:\/\/www.pingcap.com\/ko\/blog\/author\/shuang-chen\/"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Metrics Relation Graph Helps Locate Performance Issues in 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