| import{_ as r,C as n,O as i,P as s,ah as u,Q as t,U as e,ai as d,aW as a}from"./framework-62ad666a.js";const c={},m=a('<p>Along with IoTDB running, we hope to observe the status of IoTDB, so as to troubleshoot system problems or discover potential system risks in time. A series of metrics that can <strong>reflect the operating status of the system</strong> are system monitoring metrics.</p><h2 id="_1-when-to-use-metric-framework" tabindex="-1"><a class="header-anchor" href="#_1-when-to-use-metric-framework" aria-hidden="true">#</a> 1. When to use metric framework?</h2><p>Belows are some typical application scenarios</p><ol><li><p>System is running slowly</p><p>When system is running slowly, we always hope to have information about system's running status as detail as possible, such as:</p><ul><li>JVM：Is there FGC? How long does it cost? How much does the memory usage decreased after GC? Are there lots of threads?</li><li>System：Is the CPU usage too hi？Are there many disk IOs？</li><li>Connections：How many connections are there in the current time？</li><li>Interface：What is the TPS and latency of every interface？</li><li>Thread Pool：Are there many pending tasks？</li><li>Cache Hit Ratio</li></ul></li><li><p>No space left on device</p><p>When meet a "no space left on device" error, we really want to know which kind of data file had a rapid rise in the past hours.</p></li><li><p>Is the system running in abnormal status</p><p>We could use the count of error logs、the alive status of nodes in cluster, etc, to determine whether the system is running abnormally.</p></li></ol><h2 id="_2-who-will-use-metric-framework" tabindex="-1"><a class="header-anchor" href="#_2-who-will-use-metric-framework" aria-hidden="true">#</a> 2. Who will use metric framework?</h2><p>Any person cares about the system's status, including but not limited to RD, QA, SRE, DBA, can use the metrics to work more efficiently.</p><h2 id="_3-what-is-metrics" tabindex="-1"><a class="header-anchor" href="#_3-what-is-metrics" aria-hidden="true">#</a> 3. What is metrics?</h2><h3 id="_3-1-key-concept" tabindex="-1"><a class="header-anchor" href="#_3-1-key-concept" aria-hidden="true">#</a> 3.1. Key Concept</h3><p>In IoTDB's metric module, each metrics is uniquely identified by <code>Metric Name</code> and <code>Tags</code>.</p><ul><li><code>Metric Name</code>: Metric type name, such as <code>logback_events</code> means log events.</li><li><code>Tags</code>: indicator classification, in the form of Key-Value pairs, each indicator can have 0 or more categories, common Key-Value pairs: <ul><li><code>name = xxx</code>: The name of the monitored object, which is the description of <strong>business logic</strong>. For example, for a monitoring item of type <code>Metric Name = entry_seconds_count</code>, the meaning of name refers to the monitored business interface.</li><li><code>type = xxx</code>: Monitoring indicator type subdivision, which is a description of <strong>monitoring indicator</strong> itself. For example, for monitoring items of type <code>Metric Name = point</code>, the meaning of type refers to the specific type of monitoring points.</li><li><code>status = xxx</code>: The status of the monitored object is a description of <strong>business logic</strong>. For example, for monitoring items of type <code>Metric Name = Task</code>, this parameter can be used to distinguish the status of the monitored object.</li><li><code>user = xxx</code>: The relevant user of the monitored object is a description of <strong>business logic</strong>. For example, count the total points written by the <code>root</code> user.</li><li>Customize according to the specific situation: For example, there is a level classification under logback_events_total, which is used to indicate the number of logs under a specific level.</li></ul></li><li><code>Metric Level</code>: The level of metric managing level, The default startup level is <code>Core</code> level, the recommended startup level is <code>Important level</code>, and the audit strictness is <code>Core > Important > Normal > All</code><ul><li><code>Core</code>: Core metrics of the system, used by the <strong>operation and maintenance personnel</strong>, which is related to the * <em>performance, stability, and security</em>* of the system, such as the status of the instance, the load of the system, etc.</li><li><code>Important</code>: Important metrics of the module, which is used by <strong>operation and maintenance and testers</strong>, and is directly related to <strong>the running status of each module</strong>, such as the number of merged files, execution status, etc.</li><li><code>Normal</code>: Normal metrics of the module, used by <strong>developers</strong> to facilitate <strong>locating the module</strong> when problems occur, such as specific key operation situations in the merger.</li><li><code>All</code>: All metrics of the module, used by <strong>module developers</strong>, often used when the problem is reproduced, so as to solve the problem quickly.</li></ul></li></ul><h3 id="_3-2-external-data-format-for-metrics" tabindex="-1"><a class="header-anchor" href="#_3-2-external-data-format-for-metrics" aria-hidden="true">#</a> 3.2. External data format for metrics</h3><ul><li>IoTDB provides metrics in JMX, Prometheus and IoTDB formats: <ul><li>For JMX, metrics can be obtained through <code>org.apache.iotdb.metrics</code>.</li><li>For Prometheus, the value of the metrics can be obtained through the externally exposed port</li><li>External exposure in IoTDB mode: metrics can be obtained by executing IoTDB queries</li></ul></li></ul><h2 id="_4-the-detail-of-metrics" tabindex="-1"><a class="header-anchor" href="#_4-the-detail-of-metrics" aria-hidden="true">#</a> 4. The detail of metrics</h2><p>Currently, IoTDB provides metrics for some main modules externally, and with the development of new functions and system optimization or refactoring, metrics will be added and updated synchronously.</p>',14),l={href:"https://github.com/apache/iotdb/tree/master/metrics",target:"_blank",rel:"noopener noreferrer"},h=a('<h3 id="_4-1-core-level-metrics" tabindex="-1"><a class="header-anchor" href="#_4-1-core-level-metrics" aria-hidden="true">#</a> 4.1. Core level metrics</h3><p>Core-level metrics are enabled by default during system operation. The addition of each Core-level metrics needs to be carefully evaluated. The current Core-level metrics are as follows:</p><h4 id="_4-1-1-cluster" tabindex="-1"><a class="header-anchor" href="#_4-1-1-cluster" aria-hidden="true">#</a> 4.1.1. Cluster</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>up_time</td><td>-</td><td>AutoGauge</td><td>The time IoTDB has been running</td></tr><tr><td>config_node</td><td>name="total",status="Registered/Online/Unknown"</td><td>AutoGauge</td><td>The number of registered/online/unknown confignodes</td></tr><tr><td>data_node</td><td>name="total",status="Registered/Online/Unknown"</td><td>AutoGauge</td><td>The number of registered/online/unknown datanodes</td></tr><tr><td>cluster_node_leader_count</td><td>name="{ip}:{port}"</td><td>Gauge</td><td>The count of consensus group leader on each node</td></tr><tr><td>cluster_node_status</td><td>name="{ip}:{port}",type="ConfigNode/DataNode"</td><td>Gauge</td><td>The current node status, 0=Unkonwn 1=online</td></tr><tr><td>entry</td><td>name="{interface}"</td><td>Timer</td><td>The time consumed of thrift operations</td></tr><tr><td>mem</td><td>name="IoTConsensus"</td><td>AutoGauge</td><td>The memory usage of IoTConsensus, Unit: byte</td></tr></tbody></table><h4 id="_4-1-2-interface" tabindex="-1"><a class="header-anchor" href="#_4-1-2-interface" aria-hidden="true">#</a> 4.1.2. Interface</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>thrift_connections</td><td>name="ConfigNodeRPC"</td><td>AutoGauge</td><td>The number of thrift internal connections in ConfigNode</td></tr><tr><td>thrift_connections</td><td>name="InternalRPC"</td><td>AutoGauge</td><td>The number of thrift internal connections in DataNode</td></tr><tr><td>thrift_connections</td><td>name="MPPDataExchangeRPC"</td><td>AutoGauge</td><td>The number of thrift internal connections in MPP</td></tr><tr><td>thrift_connections</td><td>name="ClientRPC"</td><td>AutoGauge</td><td>The number of thrift connections of Client</td></tr><tr><td>thrift_active_threads</td><td>name="ConfigNodeRPC-Service"</td><td>AutoGauge</td><td>The number of thrift active internal connections in ConfigNode</td></tr><tr><td>thrift_active_threads</td><td>name="DataNodeInternalRPC-Service"</td><td>AutoGauge</td><td>The number of thrift active internal connections in DataNode</td></tr><tr><td>thrift_active_threads</td><td>name="MPPDataExchangeRPC-Service"</td><td>AutoGauge</td><td>The number of thrift active internal connections in MPP</td></tr><tr><td>thrift_active_threads</td><td>name="ClientRPC-Service"</td><td>AutoGauge</td><td>The number of thrift active connections of client</td></tr><tr><td>session_idle_time</td><td>name = "sessionId"</td><td>Histogram</td><td>The distribution of idle time of different sessions</td></tr></tbody></table><h4 id="_4-1-2-node-statistics" tabindex="-1"><a class="header-anchor" href="#_4-1-2-node-statistics" aria-hidden="true">#</a> 4.1.2. Node Statistics</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>quantity</td><td>name="database"</td><td>AutoGauge</td><td>The number of database</td></tr><tr><td>quantity</td><td>name="timeSeries"</td><td>AutoGauge</td><td>The number of timeseries</td></tr><tr><td>quantity</td><td>name="pointsIn"</td><td>Counter</td><td>The number of write points</td></tr><tr><td>points</td><td>database="{database}", type="flush"</td><td>Gauge</td><td>The point number of last flushed memtable</td></tr></tbody></table><h4 id="_4-1-3-cluster-tracing" tabindex="-1"><a class="header-anchor" href="#_4-1-3-cluster-tracing" aria-hidden="true">#</a> 4.1.3. Cluster Tracing</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>performance_overview</td><td>interface="{interface}", type="{statement_type}"</td><td>Timer</td><td>The time consumed of operations in client</td></tr><tr><td>performance_overview_detail</td><td>stage="authority"</td><td>Timer</td><td>The time consumed on authority authentication</td></tr><tr><td>performance_overview_detail</td><td>stage="parser"</td><td>Timer</td><td>The time consumed on parsing statement</td></tr><tr><td>performance_overview_detail</td><td>stage="analyzer"</td><td>Timer</td><td>The time consumed on analyzing statement</td></tr><tr><td>performance_overview_detail</td><td>stage="planner"</td><td>Timer</td><td>The time consumed on planning</td></tr><tr><td>performance_overview_detail</td><td>stage="scheduler"</td><td>Timer</td><td>The time consumed on scheduling</td></tr><tr><td>performance_overview_schedule_detail</td><td>stage="local_scheduler"</td><td>Timer</td><td>The time consumed on local scheduler</td></tr><tr><td>performance_overview_schedule_detail</td><td>stage="remote_scheduler"</td><td>Timer</td><td>The time consumed on remote scheduler</td></tr><tr><td>performance_overview_local_detail</td><td>stage="schema_validate"</td><td>Timer</td><td>The time consumed on schema validation</td></tr><tr><td>performance_overview_local_detail</td><td>stage="trigger"</td><td>Timer</td><td>The time consumed on trigger</td></tr><tr><td>performance_overview_local_detail</td><td>stage="storage"</td><td>Timer</td><td>The time consumed on consensus</td></tr><tr><td>performance_overview_storage_detail</td><td>stage="engine"</td><td>Timer</td><td>The time consumed on write stateMachine</td></tr><tr><td>performance_overview_engine_detail</td><td>stage="lock"</td><td>Timer</td><td>The time consumed on grabbing lock in DataRegion</td></tr><tr><td>performance_overview_engine_detail</td><td>stage="create_memtable_block"</td><td>Timer</td><td>The time consumed on creating new memtable</td></tr><tr><td>performance_overview_engine_detail</td><td>stage="memory_block"</td><td>Timer</td><td>The time consumed on insert memory control</td></tr><tr><td>performance_overview_engine_detail</td><td>stage="wal"</td><td>Timer</td><td>The time consumed on writing wal</td></tr><tr><td>performance_overview_engine_detail</td><td>stage="memtable"</td><td>Timer</td><td>The time consumed on writing memtable</td></tr><tr><td>performance_overview_engine_detail</td><td>stage="last_cache"</td><td>Timer</td><td>The time consumed on updating last cache</td></tr></tbody></table><h4 id="_4-1-5-task-statistics" tabindex="-1"><a class="header-anchor" href="#_4-1-5-task-statistics" aria-hidden="true">#</a> 4.1.5. Task Statistics</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>queue</td><td>name="compaction_inner", status="running/waiting"</td><td>Gauge</td><td>The number of inner compaction tasks</td></tr><tr><td>queue</td><td>name="compaction_cross", status="running/waiting"</td><td>Gauge</td><td>The number of cross compatcion tasks</td></tr><tr><td>queue</td><td>name="flush",status="running/waiting"</td><td>AutoGauge</td><td>The number of flush tasks</td></tr><tr><td>cost_task</td><td>name="inner_compaction/cross_compaction/flush"</td><td>Gauge</td><td>The time consumed of compaction tasks</td></tr></tbody></table><h4 id="_4-1-6-iotdb-process" tabindex="-1"><a class="header-anchor" href="#_4-1-6-iotdb-process" aria-hidden="true">#</a> 4.1.6. IoTDB process</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>process_cpu_load</td><td>name="process"</td><td>AutoGauge</td><td>The current CPU usage of IoTDB process, Unit: %</td></tr><tr><td>process_cpu_time</td><td>name="process"</td><td>AutoGauge</td><td>The total CPU time occupied of IoTDB process, Unit: ns</td></tr><tr><td>process_max_mem</td><td>name="memory"</td><td>AutoGauge</td><td>The maximum available memory of IoTDB process</td></tr><tr><td>process_total_mem</td><td>name="memory"</td><td>AutoGauge</td><td>The current requested memory for IoTDB process</td></tr><tr><td>process_free_mem</td><td>name="memory"</td><td>AutoGauge</td><td>The free available memory of IoTDB process</td></tr></tbody></table><h4 id="_4-1-7-system" tabindex="-1"><a class="header-anchor" href="#_4-1-7-system" aria-hidden="true">#</a> 4.1.7. System</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>sys_cpu_load</td><td>name="system"</td><td>AutoGauge</td><td>The current CPU usage of system, Unit: %</td></tr><tr><td>sys_cpu_cores</td><td>name="system"</td><td>Gauge</td><td>The available number of CPU cores</td></tr><tr><td>sys_total_physical_memory_size</td><td>name="memory"</td><td>Gauge</td><td>The maximum physical memory of system</td></tr><tr><td>sys_free_physical_memory_size</td><td>name="memory"</td><td>AutoGauge</td><td>The current available memory of system</td></tr><tr><td>sys_total_swap_space_size</td><td>name="memory"</td><td>AutoGauge</td><td>The maximum swap space of system</td></tr><tr><td>sys_free_swap_space_size</td><td>name="memory"</td><td>AutoGauge</td><td>The available swap space of system</td></tr><tr><td>sys_committed_vm_size</td><td>name="memory"</td><td>AutoGauge</td><td>The space of virtual memory available to running processes</td></tr><tr><td>sys_disk_total_space</td><td>name="disk"</td><td>AutoGauge</td><td>The total disk space</td></tr><tr><td>sys_disk_free_space</td><td>name="disk"</td><td>AutoGauge</td><td>The available disk space</td></tr></tbody></table><h4 id="_4-1-8-log" tabindex="-1"><a class="header-anchor" href="#_4-1-8-log" aria-hidden="true">#</a> 4.1.8. Log</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>logback_events</td><td>level="trace/debug/info/warn/error"</td><td>Counter</td><td>The number of log events</td></tr></tbody></table><h4 id="_4-1-9-file" tabindex="-1"><a class="header-anchor" href="#_4-1-9-file" aria-hidden="true">#</a> 4.1.9. File</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>file_size</td><td>name="wal"</td><td>AutoGauge</td><td>The size of WAL file, Unit: byte</td></tr><tr><td>file_size</td><td>name="seq"</td><td>AutoGauge</td><td>The size of sequence TsFile, Unit: byte</td></tr><tr><td>file_size</td><td>name="unseq"</td><td>AutoGauge</td><td>The size of unsequence TsFile, Unit: byte</td></tr><tr><td>file_size</td><td>name="inner-seq-temp"</td><td>AutoGauge</td><td>The size of inner sequence space compaction temporal file</td></tr><tr><td>file_size</td><td>name="inner-unseq-temp"</td><td>AutoGauge</td><td>The size of inner unsequence space compaction temporal file</td></tr><tr><td>file_size</td><td>name="cross-temp"</td><td>AutoGauge</td><td>The size of cross space compaction temoporal file</td></tr><tr><td>file_size</td><td>name="mods</td><td>AutoGauge</td><td>The size of modification files</td></tr><tr><td>file_count</td><td>name="wal"</td><td>AutoGauge</td><td>The count of WAL file</td></tr><tr><td>file_count</td><td>name="seq"</td><td>AutoGauge</td><td>The count of sequence TsFile</td></tr><tr><td>file_count</td><td>name="unseq"</td><td>AutoGauge</td><td>The count of unsequence TsFile</td></tr><tr><td>file_count</td><td>name="inner-seq-temp"</td><td>AutoGauge</td><td>The count of inner sequence space compaction temporal file</td></tr><tr><td>file_count</td><td>name="inner-unseq-temp"</td><td>AutoGauge</td><td>The count of inner unsequence space compaction temporal file</td></tr><tr><td>file_count</td><td>name="cross-temp"</td><td>AutoGauge</td><td>The count of cross space compaction temporal file</td></tr><tr><td>file_count</td><td>name="open_file_handlers"</td><td>AutoGauge</td><td>The count of open files of the IoTDB process, only supports Linux and MacOS</td></tr><tr><td>file_count</td><td>name="mods</td><td>AutoGauge</td><td>The count of modification file</td></tr></tbody></table><h4 id="_4-1-10-jvm-memory" tabindex="-1"><a class="header-anchor" href="#_4-1-10-jvm-memory" aria-hidden="true">#</a> 4.1.10. JVM Memory</h4>',21),q=t("table",null,[t("thead",null,[t("tr",null,[t("th",null,"Metric"),t("th",null,"Tags"),t("th",null,"Type"),t("th",null,"Description")])]),t("tbody",null,[t("tr",null,[t("td",null,"jvm_buffer_memory_used_bytes"),t("td",null,'id="direct/mapped"'),t("td",null,"AutoGauge"),t("td",null,"The used size of buffer")]),t("tr",null,[t("td",null,"jvm_buffer_total_capacity_bytes"),t("td",null,'id="direct/mapped"'),t("td",null,"AutoGauge"),t("td",null,"The max size of buffer")]),t("tr",null,[t("td",null,"jvm_buffer_count_buffers"),t("td",null,'id="direct/mapped"'),t("td",null,"AutoGauge"),t("td",null,"The number of buffer")]),t("tr",null,[t("td",null,"jvm_memory_committed_bytes"),t("td",{area:'heap/nonheap,id="xxx",'}),t("td",null,"AutoGauge"),t("td",null,"The committed memory of JVM")]),t("tr",null,[t("td",null,"jvm_memory_max_bytes"),t("td",{area:'heap/nonheap,id="xxx",'}),t("td",null,"AutoGauge"),t("td",null,"The max memory of JVM")]),t("tr",null,[t("td",null,"jvm_memory_used_bytes"),t("td",{area:'heap/nonheap,id="xxx",'}),t("td",null,"AutoGauge"),t("td",null,"The used memory of JVM")])])],-1),g=a('<h4 id="_4-1-11-jvm-thread" tabindex="-1"><a class="header-anchor" href="#_4-1-11-jvm-thread" aria-hidden="true">#</a> 4.1.11. JVM Thread</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>jvm_threads_live_threads</td><td></td><td>AutoGauge</td><td>The number of live thread</td></tr><tr><td>jvm_threads_daemon_threads</td><td></td><td>AutoGauge</td><td>The number of daemon thread</td></tr><tr><td>jvm_threads_peak_threads</td><td></td><td>AutoGauge</td><td>The number of peak thread</td></tr><tr><td>jvm_threads_states_threads</td><td>state="runnable/blocked/waiting/timed-waiting/new/terminated"</td><td>AutoGauge</td><td>The number of thread in different states</td></tr></tbody></table><h4 id="_4-1-12-jvm-gc" tabindex="-1"><a class="header-anchor" href="#_4-1-12-jvm-gc" aria-hidden="true">#</a> 4.1.12. JVM GC</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>jvm_gc_pause</td><td>action="end of major GC/end of minor GC",cause="xxxx"</td><td>Timer</td><td>The number and time consumed of Young GC/Full Gc caused by different reason</td></tr><tr><td></td><td></td><td></td><td></td></tr><tr><td>jvm_gc_concurrent_phase_time</td><td>action="{action}",cause="{cause}"</td><td>Timer</td><td>The number and time consumed of Young GC/Full Gc caused by different</td></tr><tr><td></td><td></td><td></td><td></td></tr><tr><td>jvm_gc_max_data_size_bytes</td><td></td><td>AutoGauge</td><td>The historical maximum value of old memory</td></tr><tr><td>jvm_gc_live_data_size_bytes</td><td></td><td>AutoGauge</td><td>The usage of old memory</td></tr><tr><td>jvm_gc_memory_promoted_bytes</td><td></td><td>Counter</td><td>The accumulative value of positive memory growth of old memory</td></tr><tr><td>jvm_gc_memory_allocated_bytes</td><td></td><td>Counter</td><td>The accumulative value of positive memory growth of allocated memory</td></tr></tbody></table><h3 id="_4-2-important-level-metrics" tabindex="-1"><a class="header-anchor" href="#_4-2-important-level-metrics" aria-hidden="true">#</a> 4.2. Important level metrics</h3><h4 id="_4-2-1-node" tabindex="-1"><a class="header-anchor" href="#_4-2-1-node" aria-hidden="true">#</a> 4.2.1. Node</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>region</td><td>name="total",type="SchemaRegion"</td><td>AutoGauge</td><td>The total number of SchemaRegion in PartitionTable</td></tr><tr><td>region</td><td>name="total",type="DataRegion"</td><td>AutoGauge</td><td>The total number of DataRegion in PartitionTable</td></tr><tr><td>region</td><td>name="{ip}:{port}",type="SchemaRegion"</td><td>Gauge</td><td>The number of SchemaRegion in PartitionTable of specific node</td></tr><tr><td>region</td><td>name="{ip}:{port}",type="DataRegion"</td><td>Gauge</td><td>The number of DataRegion in PartitionTable of specific node</td></tr></tbody></table><h4 id="_4-2-2-ratisconsensus" tabindex="-1"><a class="header-anchor" href="#_4-2-2-ratisconsensus" aria-hidden="true">#</a> 4.2.2. RatisConsensus</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>ratis_consensus_write</td><td>stage="writeLocally"</td><td>Timer</td><td>The time cost of writing locally stage</td></tr><tr><td>ratis_consensus_write</td><td>stage="writeRemotely"</td><td>Timer</td><td>The time cost of writing remotely stage</td></tr><tr><td>ratis_consensus_write</td><td>stage="writeStateMachine"</td><td>Timer</td><td>The time cost of writing state machine stage</td></tr><tr><td>ratis_server</td><td>clientWriteRequest</td><td>Timer</td><td>Time taken to process write requests from client</td></tr><tr><td>ratis_server</td><td>followerAppendEntryLatency</td><td>Timer</td><td>Time taken for followers to append log entries</td></tr><tr><td>ratis_log_worker</td><td>appendEntryLatency</td><td>Timer</td><td>Total time taken to append a raft log entry</td></tr><tr><td>ratis_log_worker</td><td>queueingDelay</td><td>Timer</td><td>Time taken for a Raft log operation to get into the queue after being requested, waiting queue to be non-full</td></tr><tr><td>ratis_log_worker</td><td>enqueuedTime</td><td>Timer</td><td>Time spent by a Raft log operation in the queue</td></tr><tr><td>ratis_log_worker</td><td>writelogExecutionTime</td><td>Timer</td><td>Time taken for a Raft log write operation to complete execution</td></tr><tr><td>ratis_log_worker</td><td>flushTime</td><td>Timer</td><td>Time taken to flush log</td></tr><tr><td>ratis_log_worker</td><td>closedSegmentsSizeInBytes</td><td>Gauge</td><td>Size of closed raft log segments in bytes</td></tr><tr><td>ratis_log_worker</td><td>openSegmentSizeInBytes</td><td>Gauge</td><td>Size of open raft log segment in bytes</td></tr></tbody></table><h4 id="_4-2-3-iotconsensus" tabindex="-1"><a class="header-anchor" href="#_4-2-3-iotconsensus" aria-hidden="true">#</a> 4.2.3. IoTConsensus</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>mutli_leader</td><td>name="logDispatcher-{IP}:{Port}", region="{region}", type="currentSyncIndex"</td><td>AutoGauge</td><td>The sync index of synchronization thread in replica group</td></tr><tr><td>mutli_leader</td><td>name="logDispatcher-{IP}:{Port}", region="{region}", type="cachedRequestInMemoryQueue"</td><td>AutoGauge</td><td>The size of cache requests of synchronization thread in replica group</td></tr><tr><td>mutli_leader</td><td>name="IoTConsensusServerImpl", region="{region}", type="searchIndex"</td><td>AutoGauge</td><td>The write process of main process in replica group</td></tr><tr><td>mutli_leader</td><td>name="IoTConsensusServerImpl", region="{region}", type="safeIndex"</td><td>AutoGauge</td><td>The sync index of replica group</td></tr><tr><td>mutli_leader</td><td>name="IoTConsensusServerImpl", region="{region}", type="syncLag"</td><td>AutoGauge</td><td>The sync lag of replica group</td></tr><tr><td>mutli_leader</td><td>name="IoTConsensusServerImpl", region="{region}", type="LogEntriesFromWAL"</td><td>AutoGauge</td><td>The number of logEntries from wal in Batch</td></tr><tr><td>mutli_leader</td><td>name="IoTConsensusServerImpl", region="{region}", type="LogEntriesFromQueue"</td><td>AutoGauge</td><td>The number of logEntries from queue in Batch</td></tr><tr><td>stage</td><td>name="iot_consensus", region="{region}", type="getStateMachineLock"</td><td>Histogram</td><td>The time consumed to get statemachine lock in main process</td></tr><tr><td>stage</td><td>name="iot_consensus", region="{region}", type="checkingBeforeWrite"</td><td>Histogram</td><td>The time consumed to precheck before write in main process</td></tr><tr><td>stage</td><td>name="iot_consensus", region="{region}", type="writeStateMachine"</td><td>Histogram</td><td>The time consumed to write statemachine in main process</td></tr><tr><td>stage</td><td>name="iot_consensus", region="{region}", type="offerRequestToQueue"</td><td>Histogram</td><td>The time consumed to try to offer request to queue in main process</td></tr><tr><td>stage</td><td>name="iot_consensus", region="{region}", type="consensusWrite"</td><td>Histogram</td><td>The time consumed to the whole write in main process</td></tr><tr><td>stage</td><td>name="iot_consensus", region="{region}", type="constructBatch"</td><td>Histogram</td><td>The time consumed to construct batch in synchronization thread</td></tr><tr><td>stage</td><td>name="iot_consensus", region="{region}", type="syncLogTimePerRequest"</td><td>Histogram</td><td>The time consumed to sync log in asynchronous callback process</td></tr></tbody></table><h4 id="_4-2-4-cache" tabindex="-1"><a class="header-anchor" href="#_4-2-4-cache" aria-hidden="true">#</a> 4.2.4. Cache</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>cache_hit</td><td>name="chunk"</td><td>AutoGauge</td><td>The cache hit ratio of ChunkCache, Unit: %</td></tr><tr><td>cache_hit</td><td>name="schema"</td><td>AutoGauge</td><td>The cache hit ratio of SchemaCache, Unit: %</td></tr><tr><td>cache_hit</td><td>name="timeSeriesMeta"</td><td>AutoGauge</td><td>The cache hit ratio of TimeseriesMetadataCache, Unit: %</td></tr><tr><td>cache_hit</td><td>name="bloomFilter"</td><td>AutoGauge</td><td>The interception rate of bloomFilter in TimeseriesMetadataCache, Unit: %</td></tr><tr><td>cache</td><td>name="Database", type="hit"</td><td>Counter</td><td>The hit number of Database Cache</td></tr><tr><td>cache</td><td>name="Database", type="all"</td><td>Counter</td><td>The access number of Database Cache</td></tr><tr><td>cache</td><td>name="SchemaPartition", type="hit"</td><td>Counter</td><td>The hit number of SchemaPartition Cache</td></tr><tr><td>cache</td><td>name="SchemaPartition", type="all"</td><td>Counter</td><td>The access number of SchemaPartition Cache</td></tr><tr><td>cache</td><td>name="DataPartition", type="hit"</td><td>Counter</td><td>The hit number of DataPartition Cache</td></tr><tr><td>cache</td><td>name="DataPartition", type="all"</td><td>Counter</td><td>The access number of DataPartition Cache</td></tr><tr><td>cache</td><td>name="SchemaCache", type="hit"</td><td>Counter</td><td>The hit number of Schema Cache</td></tr><tr><td>cache</td><td>name="SchemaCache", type="all"</td><td>Counter</td><td>The access number of Schema Cache</td></tr></tbody></table><h4 id="_4-2-5-memory" tabindex="-1"><a class="header-anchor" href="#_4-2-5-memory" aria-hidden="true">#</a> 4.2.5. Memory</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>mem</td><td>name="database_{name}"</td><td>AutoGauge</td><td>The memory usage of DataRegion in DataNode, Unit: byte</td></tr><tr><td>mem</td><td>name="chunkMetaData_{name}"</td><td>AutoGauge</td><td>The memory usage of chunkMetaData when writting TsFile, Unit: byte</td></tr><tr><td>mem</td><td>name="IoTConsensus"</td><td>AutoGauge</td><td>The memory usage of IoTConsensus, Unit: byte</td></tr><tr><td>mem</td><td>name="IoTConsensusQueue"</td><td>AutoGauge</td><td>The memory usage of IoTConsensus Queue, Unit: byte</td></tr><tr><td>mem</td><td>name="IoTConsensusSync"</td><td>AutoGauge</td><td>The memory usage of IoTConsensus SyncStatus, Unit: byte</td></tr><tr><td>mem</td><td>name="schema_region_total_usage"</td><td>AutoGauge</td><td>The memory usage of all SchemaRegion, Unit: byte</td></tr></tbody></table><h4 id="_4-2-6-compaction" tabindex="-1"><a class="header-anchor" href="#_4-2-6-compaction" aria-hidden="true">#</a> 4.2.6. Compaction</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>data_written</td><td>name="compaction", type="aligned/not-aligned/total"</td><td>Counter</td><td>The written size of compaction</td></tr><tr><td>data_read</td><td>name="compaction"</td><td>Counter</td><td>The read size of compaction</td></tr><tr><td>compaction_task_count</td><td>name = "inner_compaction", type="sequence"</td><td>Counter</td><td>The number of inner sequence compction</td></tr><tr><td>compaction_task_count</td><td>name = "inner_compaction", type="unsequence"</td><td>Counter</td><td>The number of inner sequence compction</td></tr><tr><td>compaction_task_count</td><td>name = "cross_compaction", type="cross"</td><td>Counter</td><td>The number of corss compction</td></tr></tbody></table><h4 id="_4-2-7-iotdb-process" tabindex="-1"><a class="header-anchor" href="#_4-2-7-iotdb-process" aria-hidden="true">#</a> 4.2.7. IoTDB Process</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>process_used_mem</td><td>name="memory"</td><td>AutoGauge</td><td>The used memory of IoTDB process</td></tr><tr><td>process_mem_ratio</td><td>name="memory"</td><td>AutoGauge</td><td>The used memory ratio of IoTDB process</td></tr><tr><td>process_threads_count</td><td>name="process"</td><td>AutoGauge</td><td>The number of thread of IoTDB process</td></tr><tr><td>process_status</td><td>name="process"</td><td>AutoGauge</td><td>The status of IoTDB process, 1=live, 0=dead</td></tr></tbody></table><h4 id="_4-2-8-jvm-class" tabindex="-1"><a class="header-anchor" href="#_4-2-8-jvm-class" aria-hidden="true">#</a> 4.2.8. JVM Class</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>jvm_classes_unloaded_classes</td><td></td><td>AutoGauge</td><td>The number of unloaded class</td></tr><tr><td>jvm_classes_loaded_classes</td><td></td><td>AutoGauge</td><td>The number of loaded class</td></tr></tbody></table><h4 id="_4-2-9-jvm-compilation" tabindex="-1"><a class="header-anchor" href="#_4-2-9-jvm-compilation" aria-hidden="true">#</a> 4.2.9. JVM Compilation</h4>',22),p=t("table",null,[t("thead",null,[t("tr",null,[t("th",null,"Metric"),t("th",null,"Tags"),t("th",null,"Type"),t("th",null,"Description")])]),t("tbody",null,[t("tr",null,[t("td",null,"jvm_compilation_time_ms"),t("td",{compiler:"HotSpot 64-Bit Tiered Compilers,"}),t("td",null,"AutoGauge"),t("td",null,"The time consumed in compilation")])])],-1),_=a(`<h4 id="_4-2-10-query-planning" tabindex="-1"><a class="header-anchor" href="#_4-2-10-query-planning" aria-hidden="true">#</a> 4.2.10. Query Planning</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>query_plan_cost</td><td>stage="analyzer"</td><td>Timer</td><td>The query statement analysis time-consuming</td></tr><tr><td>query_plan_cost</td><td>stage="logical_planner"</td><td>Timer</td><td>The query logical plan planning time-consuming</td></tr><tr><td>query_plan_cost</td><td>stage="distribution_planner"</td><td>Timer</td><td>The query distribution plan planning time-consuming</td></tr><tr><td>query_plan_cost</td><td>stage="partition_fetcher"</td><td>Timer</td><td>The partition information fetching time-consuming</td></tr><tr><td>query_plan_cost</td><td>stage="schema_fetcher"</td><td>Timer</td><td>The schema information fetching time-consuming</td></tr></tbody></table><h4 id="_4-2-11-plan-dispatcher" tabindex="-1"><a class="header-anchor" href="#_4-2-11-plan-dispatcher" aria-hidden="true">#</a> 4.2.11. Plan Dispatcher</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>dispatcher</td><td>stage="wait_for_dispatch"</td><td>Timer</td><td>The distribution plan dispatcher time-consuming</td></tr><tr><td>dispatcher</td><td>stage="dispatch_read"</td><td>Timer</td><td>The distribution plan dispatcher time-consuming (only query)</td></tr></tbody></table><h4 id="_4-2-12-query-resource" tabindex="-1"><a class="header-anchor" href="#_4-2-12-query-resource" aria-hidden="true">#</a> 4.2.12. Query Resource</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>query_resource</td><td>type="sequence_tsfile"</td><td>Rate</td><td>The access frequency of sequence tsfiles</td></tr><tr><td>query_resource</td><td>type="unsequence_tsfile"</td><td>Rate</td><td>The access frequency of unsequence tsfiles</td></tr><tr><td>query_resource</td><td>type="flushing_memtable"</td><td>Rate</td><td>The access frequency of flushing memtables</td></tr><tr><td>query_resource</td><td>type="working_memtable"</td><td>Rate</td><td>The access frequency of working memtables</td></tr></tbody></table><h4 id="_4-2-13-data-exchange" tabindex="-1"><a class="header-anchor" href="#_4-2-13-data-exchange" aria-hidden="true">#</a> 4.2.13. Data Exchange</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>data_exchange_cost</td><td>operation="source_handle_get_tsblock", type="local/remote"</td><td>Timer</td><td>The time-consuming that source handles receive TsBlock</td></tr><tr><td>data_exchange_cost</td><td>operation="source_handle_deserialize_tsblock", type="local/remote"</td><td>Timer</td><td>The time-consuming that source handles deserialize TsBlock</td></tr><tr><td>data_exchange_cost</td><td>operation="sink_handle_send_tsblock", type="local/remote"</td><td>Timer</td><td>The time-consuming that sink handles send TsBlock</td></tr><tr><td>data_exchange_cost</td><td>operation="send_new_data_block_event_task", type="server/caller"</td><td>Timer</td><td>The RPC time-consuming that sink handles send TsBlock</td></tr><tr><td>data_exchange_cost</td><td>operation="get_data_block_task", type="server/caller"</td><td>Timer</td><td>The RPC time-consuming that source handles receive TsBlock</td></tr><tr><td>data_exchange_cost</td><td>operation="on_acknowledge_data_block_event_task", type="server/caller"</td><td>Timer</td><td>The RPC time-consuming that source handles ack received TsBlock</td></tr><tr><td>data_exchange_count</td><td>name="send_new_data_block_num", type="server/caller"</td><td>Histogram</td><td>The number of sent TsBlocks by sink handles</td></tr><tr><td>data_exchange_count</td><td>name="get_data_block_num", type="server/caller"</td><td>Histogram</td><td>The number of received TsBlocks by source handles</td></tr><tr><td>data_exchange_count</td><td>name="on_acknowledge_data_block_num", type="server/caller"</td><td>Histogram</td><td>The number of acknowledged TsBlocks by source handles</td></tr><tr><td>data_exchange_count</td><td>name="shuffle_sink_handle_size"</td><td>AutoGauge</td><td>The number of shuffle sink handle</td></tr><tr><td>data_exchange_count</td><td>name="source_handle_size"</td><td>AutoGauge</td><td>The number of source handle</td></tr></tbody></table><h4 id="_4-2-14-query-task-schedule" tabindex="-1"><a class="header-anchor" href="#_4-2-14-query-task-schedule" aria-hidden="true">#</a> 4.2.14. Query Task Schedule</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>driver_scheduler</td><td>name="ready_queued_time"</td><td>Timer</td><td>The queuing time of ready queue</td></tr><tr><td>driver_scheduler</td><td>name="block_queued_time"</td><td>Timer</td><td>The queuing time of blocking queue</td></tr><tr><td>driver_scheduler</td><td>name="ready_queue_task_count"</td><td>AutoGauge</td><td>The number of tasks queued in the ready queue</td></tr><tr><td>driver_scheduler</td><td>name="block_queued_task_count"</td><td>AutoGauge</td><td>The number of tasks queued in the blocking queue</td></tr><tr><td>driver_scheduler</td><td>name="timeout_queued_task_count"</td><td>AutoGauge</td><td>The number of tasks queued in the timeout queue</td></tr><tr><td>driver_scheduler</td><td>name="query_map_size"</td><td>AutoGauge</td><td>The number of queries recorded in DriverScheduler</td></tr></tbody></table><h4 id="_4-2-15-query-execution" tabindex="-1"><a class="header-anchor" href="#_4-2-15-query-execution" aria-hidden="true">#</a> 4.2.15. Query Execution</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>query_execution</td><td>stage="local_execution_planner"</td><td>Timer</td><td>The time-consuming of operator tree construction</td></tr><tr><td>query_execution</td><td>stage="query_resource_init"</td><td>Timer</td><td>The time-consuming of query resource initialization</td></tr><tr><td>query_execution</td><td>stage="get_query_resource_from_mem"</td><td>Timer</td><td>The time-consuming of query resource memory query and construction</td></tr><tr><td>query_execution</td><td>stage="driver_internal_process"</td><td>Timer</td><td>The time-consuming of driver execution</td></tr><tr><td>query_execution</td><td>stage="wait_for_result"</td><td>Timer</td><td>The time-consuming of getting query result from result handle</td></tr><tr><td>operator_execution_cost</td><td>name="{operator_name}"</td><td>Timer</td><td>The operator execution time</td></tr><tr><td>operator_execution_count</td><td>name="{operator_name}"</td><td>Counter</td><td>The number of operator calls (counted by the number of next method calls)</td></tr><tr><td>aggregation</td><td>from="raw_data"</td><td>Timer</td><td>The time-consuming of performing an aggregation calculation from a batch of raw data</td></tr><tr><td>aggregation</td><td>from="statistics"</td><td>Timer</td><td>The time-consuming of updating an aggregated value with statistics</td></tr><tr><td>series_scan_cost</td><td>stage="load_timeseries_metadata", type="aligned/non_aligned", from="mem/disk"</td><td>Timer</td><td>The time-consuming of loading TimeseriesMetadata</td></tr><tr><td>series_scan_cost</td><td>stage="read_timeseries_metadata", type="", from="cache/file"</td><td>Timer</td><td>The time-consuming of reading TimeseriesMetadata of a tsfile</td></tr><tr><td>series_scan_cost</td><td>stage="timeseries_metadata_modification", type="aligned/non_aligned", from="null"</td><td>Timer</td><td>The time-consuming of filtering TimeseriesMetadata by mods</td></tr><tr><td>series_scan_cost</td><td>stage="load_chunk_metadata_list", type="aligned/non_aligned", from="mem/disk"</td><td>Timer</td><td>The time-consuming of loading ChunkMetadata list</td></tr><tr><td>series_scan_cost</td><td>stage="chunk_metadata_modification", type="aligned/non_aligned", from="mem/disk"</td><td>Timer</td><td>The time-consuming of filtering ChunkMetadata by mods</td></tr><tr><td>series_scan_cost</td><td>stage="chunk_metadata_filter", type="aligned/non_aligned", from="mem/disk"</td><td>Timer</td><td>The time-consuming of filtering ChunkMetadata by query filter</td></tr><tr><td>series_scan_cost</td><td>stage="construct_chunk_reader", type="aligned/non_aligned", from="mem/disk"</td><td>Timer</td><td>The time-consuming of constructing ChunkReader</td></tr><tr><td>series_scan_cost</td><td>stage="read_chunk", type="", from="cache/file"</td><td>Timer</td><td>The time-consuming of reading Chunk</td></tr><tr><td>series_scan_cost</td><td>stage="init_chunk_reader", type="aligned/non_aligned", from="mem/disk"</td><td>Timer</td><td>The time-consuming of initializing ChunkReader (constructing PageReader)</td></tr><tr><td>series_scan_cost</td><td>stage="build_tsblock_from_page_reader", type="aligned/non_aligned", from="mem/disk"</td><td>Timer</td><td>The time-consuming of constructing Tsblock from PageReader</td></tr><tr><td>series_scan_cost</td><td>stage="build_tsblock_from_merge_reader", type="aligned/non_aligned", from="null"</td><td>Timer</td><td>The time-consuming of constructing Tsblock from MergeReader (handling overlapping data)</td></tr></tbody></table><h4 id="_4-2-16-coordinator" tabindex="-1"><a class="header-anchor" href="#_4-2-16-coordinator" aria-hidden="true">#</a> 4.2.16. Coordinator</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>coordinator</td><td>name="query_execution_map_size"</td><td>AutoGauge</td><td>The number of queries recorded on current DataNode</td></tr></tbody></table><h4 id="_4-2-17-fragmentinstancemanager" tabindex="-1"><a class="header-anchor" href="#_4-2-17-fragmentinstancemanager" aria-hidden="true">#</a> 4.2.17. FragmentInstanceManager</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>fragment_instance_manager</td><td>name="instance_context_size"</td><td>AutoGauge</td><td>The number of query fragment context on current DataNode</td></tr><tr><td>fragment_instance_manager</td><td>name="instance_execution_size"</td><td>AutoGauge</td><td>The number of query fragment on current DataNode</td></tr></tbody></table><h4 id="_4-2-18-memorypool" tabindex="-1"><a class="header-anchor" href="#_4-2-18-memorypool" aria-hidden="true">#</a> 4.2.18. MemoryPool</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>memory_pool</td><td>name="max_bytes"</td><td>Gauge</td><td>Maximum memory for data exchange</td></tr><tr><td>memory_pool</td><td>name="remaining_bytes"</td><td>AutoGauge</td><td>Remaining memory for data exchange</td></tr><tr><td>memory_pool</td><td>name="query_memory_reservation_size"</td><td>AutoGauge</td><td>Size of query reserved memory</td></tr><tr><td>memory_pool</td><td>name="memory_reservation_size"</td><td>AutoGauge</td><td>Size of sink handle and source handle trying to reserve memory</td></tr></tbody></table><h4 id="_4-2-19-localexecutionplanner" tabindex="-1"><a class="header-anchor" href="#_4-2-19-localexecutionplanner" aria-hidden="true">#</a> 4.2.19. LocalExecutionPlanner</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>local_execution_planner</td><td>name="free_memory_for_operators"</td><td>AutoGauge</td><td>The remaining memory can allocate for query fragments on current DataNode</td></tr></tbody></table><h4 id="_4-2-20-schema-engine" tabindex="-1"><a class="header-anchor" href="#_4-2-20-schema-engine" aria-hidden="true">#</a> 4.2.20. Schema Engine</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>schema_engine</td><td>name="schema_region_total_mem_usage"</td><td>AutoGauge</td><td>Memory usgae for all SchemaRegion</td></tr><tr><td>schema_engine</td><td>name="schema_region_mem_capacity"</td><td>AutoGauge</td><td>Memory capacity for all SchemaRegion</td></tr><tr><td>schema_engine</td><td>name="schema_engine_mode"</td><td>Gauge</td><td>Mode of SchemaEngine</td></tr><tr><td>schema_engine</td><td>name="schema_region_consensus"</td><td>Gauge</td><td>Consensus protocol of SchemaRegion</td></tr><tr><td>schema_engine</td><td>name="schema_region_number"</td><td>AutoGauge</td><td>Number of SchemaRegion</td></tr><tr><td>quantity</td><td>name="template_series_cnt"</td><td>AutoGauge</td><td>Number of template series</td></tr><tr><td>schema_region</td><td>name="schema_region_mem_usage", region="SchemaRegion[{regionId}]"</td><td>AutoGauge</td><td>Memory usgae for each SchemaRegion</td></tr><tr><td>schema_region</td><td>name="schema_region_series_cnt", region="SchemaRegion[{regionId}]"</td><td>AutoGauge</td><td>Number of total timeseries for each SchemaRegion</td></tr><tr><td>schema_region</td><td>name="activated_template_cnt", region="SchemaRegion[{regionId}]"</td><td>AutoGauge</td><td>Number of Activated template for each SchemaRegion</td></tr><tr><td>schema_region</td><td>name="template_series_cnt", region="SchemaRegion[{regionId}]"</td><td>AutoGauge</td><td>Number of template series for each SchemaRegion</td></tr></tbody></table><h4 id="_4-2-21-write-performance" tabindex="-1"><a class="header-anchor" href="#_4-2-21-write-performance" aria-hidden="true">#</a> 4.2.21. Write Performance</h4><table><thead><tr><th>Metric</th><th style="text-align:left;">Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>wal_node_num</td><td style="text-align:left;">name="wal_nodes_num"</td><td>AutoGauge</td><td>Num of WALNode</td></tr><tr><td>wal_cost</td><td style="text-align:left;">stage="make_checkpoint" type="<checkpoint_type>"</td><td>Timer</td><td>Time cost of make checkpoints for all checkpoint type</td></tr><tr><td>wal_cost</td><td style="text-align:left;">type="serialize_one_wal_info_entry"</td><td>Timer</td><td>Time cost of serialize one WALInfoEntry</td></tr><tr><td>wal_cost</td><td style="text-align:left;">stage="sync_wal_buffer" type="<force_flag>"</td><td>Timer</td><td>Time cost of sync WALBuffer</td></tr><tr><td>wal_buffer</td><td style="text-align:left;">name="used_ratio"</td><td>Histogram</td><td>Used ratio of WALBuffer</td></tr><tr><td>wal_buffer</td><td style="text-align:left;">name="entries_count"</td><td>Histogram</td><td>Entries Count of WALBuffer</td></tr><tr><td>wal_cost</td><td style="text-align:left;">stage="serialize_wal_entry" type="serialize_wal_entry_total"</td><td>Timer</td><td>Time cost of WALBuffer serialize task</td></tr><tr><td>wal_node_info</td><td style="text-align:left;">name="effective_info_ratio" type="<wal_node_id>"</td><td>Histogram</td><td>Effective info ratio of WALNode</td></tr><tr><td>wal_node_info</td><td style="text-align:left;">name="oldest_mem_table_ram_when_cause_snapshot" type="<wal_node_id>"</td><td>Histogram</td><td>Ram of oldest memTable when cause snapshot</td></tr><tr><td>wal_node_info</td><td style="text-align:left;">name="oldest_mem_table_ram_when_cause_flush" type="<wal_node_id>"</td><td>Histogram</td><td>Ram of oldest memTable when cause flush</td></tr><tr><td>flush_sub_task_cost</td><td style="text-align:left;">type="sort_task"</td><td>Timer</td><td>Time cost of sort series in flush sort stage</td></tr><tr><td>flush_sub_task_cost</td><td style="text-align:left;">type="encoding_task"</td><td>Timer</td><td>Time cost of sub encoding task in flush encoding stage</td></tr><tr><td>flush_sub_task_cost</td><td style="text-align:left;">type="io_task"</td><td>Timer</td><td>Time cost of sub io task in flush io stage</td></tr><tr><td>flush_cost</td><td style="text-align:left;">stage="write_plan_indices"</td><td>Timer</td><td>Time cost of write plan indices</td></tr><tr><td>flush_cost</td><td style="text-align:left;">stage="sort"</td><td>Timer</td><td>Time cost of flush sort stage</td></tr><tr><td>flush_cost</td><td style="text-align:left;">stage="encoding"</td><td>Timer</td><td>Time cost of flush encoding stage</td></tr><tr><td>flush_cost</td><td style="text-align:left;">stage="io"</td><td>Timer</td><td>Time cost of flush io stage</td></tr><tr><td>pending_flush_task</td><td style="text-align:left;">type="pending_task_num"</td><td>AutoGauge</td><td>Num of pending flush task num</td></tr><tr><td>pending_flush_task</td><td style="text-align:left;">type="pending_sub_task_num"</td><td>AutoGauge</td><td>Num of pending flush sub task num</td></tr><tr><td>flushing_mem_table_status</td><td style="text-align:left;">name="mem_table_size" region="DataRegion[<data_region_id>]"</td><td>Histogram</td><td>Size of flushing memTable</td></tr><tr><td>flushing_mem_table_status</td><td style="text-align:left;">name="total_point_num" region="DataRegion[<data_region_id>]"</td><td>Histogram</td><td>Point num of flushing memTable</td></tr><tr><td>flushing_mem_table_status</td><td style="text-align:left;">name="series_num" region="DataRegion[<data_region_id>]"</td><td>Histogram</td><td>Series num of flushing memTable</td></tr><tr><td>flushing_mem_table_status</td><td style="text-align:left;">name="avg_series_points_num" region="DataRegion[<data_region_id>]"</td><td>Histogram</td><td>Point num of flushing memChunk</td></tr><tr><td>flushing_mem_table_status</td><td style="text-align:left;">name="tsfile_compression_ratio" region="DataRegion[<data_region_id>]"</td><td>Histogram</td><td>TsFile Compression ratio of flushing memTable</td></tr><tr><td>flushing_mem_table_status</td><td style="text-align:left;">name="flush_tsfile_size" region="DataRegion[<data_region_id>]"</td><td>Histogram</td><td>TsFile size of flushing memTable</td></tr><tr><td>data_region_mem_cost</td><td style="text-align:left;">name="data_region_mem_cost"</td><td>AutoGauge</td><td>Mem cost of data regions</td></tr></tbody></table><h3 id="_4-3-normal-level-metrics" tabindex="-1"><a class="header-anchor" href="#_4-3-normal-level-metrics" aria-hidden="true">#</a> 4.3. Normal level Metrics</h3><h4 id="_4-3-1-cluster" tabindex="-1"><a class="header-anchor" href="#_4-3-1-cluster" aria-hidden="true">#</a> 4.3.1. Cluster</h4><table><thead><tr><th>Metric</th><th>Tags</th><th>Type</th><th>Description</th></tr></thead><tbody><tr><td>region</td><td>name="{DatabaseName}",type="SchemaRegion/DataRegion"</td><td>AutoGauge</td><td>The number of DataRegion/SchemaRegion of database in specific node</td></tr><tr><td>slot</td><td>name="{DatabaseName}",type="schemaSlotNumber/dataSlotNumber"</td><td>AutoGauge</td><td>The number of DataSlot/SchemaSlot of database in specific node</td></tr></tbody></table><h3 id="_4-4-all-metric" tabindex="-1"><a class="header-anchor" href="#_4-4-all-metric" aria-hidden="true">#</a> 4.4. All Metric</h3><p>Currently there is no All level metrics, and it will continue to be added in the future.</p><h2 id="_5-how-to-get-these-metrics" tabindex="-1"><a class="header-anchor" href="#_5-how-to-get-these-metrics" aria-hidden="true">#</a> 5. How to get these metrics？</h2><p>The relevant configuration of the metric module is in <code>conf/iotdb-{datanode/confignode}.properties</code>, and all configuration items support hot loading through the <code>load configuration</code> command.</p><h3 id="_5-1-jmx" tabindex="-1"><a class="header-anchor" href="#_5-1-jmx" aria-hidden="true">#</a> 5.1. JMX</h3><p>For metrics exposed externally using JMX, you can view them through Jconsole. After entering the Jconsole monitoring page, you will first see an overview of various running conditions of IoTDB. Here you can see heap memory information, thread information, class information, and the server's CPU usage.</p><h4 id="_5-1-1-obtain-metric-data" tabindex="-1"><a class="header-anchor" href="#_5-1-1-obtain-metric-data" aria-hidden="true">#</a> 5.1.1. Obtain metric data</h4><p>After connecting to JMX, you can find the "MBean" named "org.apache.iotdb.metrics" through the "MBeans" tab, and you can view the specific values of all monitoring metrics in the sidebar.</p><img style="width:100%;max-width:800px;max-height:600px;margin-left:auto;margin-right:auto;display:block;" alt="metric-jmx" src="https://alioss.timecho.com/docs/img/github/204018765-6fda9391-ebcf-4c80-98c5-26f34bd74df0.png"><h4 id="_5-1-2-get-other-relevant-data" tabindex="-1"><a class="header-anchor" href="#_5-1-2-get-other-relevant-data" aria-hidden="true">#</a> 5.1.2. Get other relevant data</h4><p>After connecting to JMX, you can find the "MBean" named "org.apache.iotdb.service" through the "MBeans" tab, as shown in the image below, to understand the basic status of the service</p><p><img style="width:100%;max-width:800px;max-height:600px;margin-left:auto;margin-right:auto;display:block;" src="https://alioss.timecho.com/docs/img/github/149951720-707f1ee8-32ee-4fde-9252-048caebd232e.png"> <br></p><p>In order to improve query performance, IOTDB caches ChunkMetaData and TsFileMetaData. Users can use MXBean and expand the sidebar <code>org.apache.iotdb.db.service</code> to view the cache hit ratio:</p><img style="width:100%;max-width:800px;max-height:600px;margin-left:auto;margin-right:auto;display:block;" src="https://alioss.timecho.com/docs/img/github/112426760-73e3da80-8d73-11eb-9a8f-9232d1f2033b.png"><h3 id="_5-2-prometheus" tabindex="-1"><a class="header-anchor" href="#_5-2-prometheus" aria-hidden="true">#</a> 5.2. Prometheus</h3><h4 id="_5-2-1-the-mapping-from-metric-type-to-prometheus-format" tabindex="-1"><a class="header-anchor" href="#_5-2-1-the-mapping-from-metric-type-to-prometheus-format" aria-hidden="true">#</a> 5.2.1. The mapping from metric type to prometheus format</h4><blockquote><p>For metrics whose Metric Name is name and Tags are K1=V1, ..., Kn=Vn, the mapping is as follows, where value is a specific value</p></blockquote><table><thead><tr><th>Metric Type</th><th>Mapping</th></tr></thead><tbody><tr><td>Counter</td><td>name_total{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn"} value</td></tr><tr><td>AutoGauge、Gauge</td><td>name{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn"} value</td></tr><tr><td>Histogram</td><td>name_max{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn"} value <br> name_sum{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn"} value <br> name_count{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn"} value <br> name{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", quantile="0.0"} value <br> name{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", quantile="0.5"} value <br> name{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", quantile="0.99"} value <br> name{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", quantile="0.999"} value</td></tr><tr><td>Rate</td><td>name_total{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn"} value <br> name_total{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", rate="m1"} value <br> name_total{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", rate="m5"} value <br> name_total{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", rate="m15"} value <br> name_total{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", rate="mean"} value</td></tr><tr><td>Timer</td><td>name_seconds_max{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn"} value <br> name_seconds_sum{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn"} value <br> name_seconds_count{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn"} value <br> name_seconds{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", quantile="0.0"} value <br> name_seconds{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", quantile="0.5"} value <br> name_seconds{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", quantile="0.99"} value <br> name_seconds{cluster="clusterName", nodeType="nodeType", nodeId="nodeId", k1="V1", ..., Kn="Vn", quantile="0.999"} value</td></tr></tbody></table><h4 id="_5-2-2-config-file" tabindex="-1"><a class="header-anchor" href="#_5-2-2-config-file" aria-hidden="true">#</a> 5.2.2. Config File</h4><ol><li>Taking DataNode as an example, modify the iotdb-datanode.properties configuration file as follows:</li></ol><div class="language-properties line-numbers-mode" data-ext="properties"><pre class="language-properties"><code><span class="token key attr-name">dn_metric_reporter_list</span><span class="token punctuation">=</span><span class="token value attr-value">PROMETHEUS</span> |
