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另外,为什么存储日志会有拆分过程,而不是rotation方式? ...
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你好,params.keys,params.values以及# ...
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qindongliang1922 写道AM中其它与内存相关的参 ...
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AM中其它与内存相关的参数,还有JVM相关的参数,这些参数可以 ...
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原网址:http://hbase.apache.org/book.html#hbase_metrics
HBase emits metrics which adhere to the Hadoop metrics API. Starting with HBase 0.95[3], HBase is configured to emit a default set of metrics with a default sampling period of every 10 seconds. You can use HBase metrics in conjunction with Ganglia. You can also filter which metrics are emitted and extend the metrics framework to capture custom metrics appropriate for your environment.
17.4.1. Metric Setup
For HBase 0.95 and newer, HBase ships with a default metrics configuration, or sink. This includes a wide variety of individual metrics, and emits them every 10 seconds by default. To configure metrics for a given region server, edit the conf/hadoop-metrics2-hbase.properties file. Restart the region server for the changes to take effect.
To change the sampling rate for the default sink, edit the line beginning with *.period. To filter which metrics are emitted or to extend the metrics framework, see http://hadoop.apache.org/docs/current/api/org/apache/hadoop/metrics2/package-summary.html
HBase Metrics and Ganglia
By default, HBase emits a large number of metrics per region server. Ganglia may have difficulty processing all these metrics. Consider increasing the capacity of the Ganglia server or reducing the number of metrics emitted by HBase. See Metrics Filtering.
17.4.2. Disabling Metrics
To disable metrics for a region server, edit the conf/hadoop-metrics2-hbase.properties file and comment out any uncommented lines. Restart the region server for the changes to take effect.
17.4.3. Discovering Available Metrics
Rather than listing each metric which HBase emits by default, you can browse through the available metrics, either as a JSON output or via JMX. Different metrics are exposed for the Master process and each region server process.
Procedure 17.1. Access a JSON Output of Available Metrics
After starting HBase, access the region server's web UI, at http://REGIONSERVER_HOSTNAME:60030 by default (or port 16030 in HBase 1.0+).
Click the Metrics Dump link near the top. The metrics for the region server are presented as a dump of the JMX bean in JSON format. This will dump out all metrics names and their values. To include metrics descriptions in the listing — this can be useful when you are exploring what is available — add a query string of ?description=true so your URL becomes http://REGIONSERVER_HOSTNAME:60030/jmx?description=true. Not all beans and attributes have descriptions.
To view metrics for the Master, connect to the Master's web UI instead (defaults to http://localhost:60010 or port 16010 in HBase 1.0+) and click its Metrics Dump link. To include metrics descriptions in the listing — this can be useful when you are exploring what is available — add a query string of ?description=true so your URL becomes http://REGIONSERVER_HOSTNAME:60010/jmx?description=true. Not all beans and attributes have descriptions.
Procedure 17.2. Browse the JMX Output of Available Metrics
You can use many different tools to view JMX content by browsing MBeans. This procedure uses jvisualvm, which is an application usually available in the JDK.
Start HBase, if it is not already running.
Run the command jvisualvm command on a host with a GUI display. You can launch it from the command line or another method appropriate for your operating system.
Be sure the VisualVM-MBeans plugin is installed. Browse to Tools → Plugins. Click Installed and check whether the plugin is listed. If not, click Available Plugins, select it, and click Install. When finished, click Close.
To view details for a given HBase process, double-click the process in the Local sub-tree in the left-hand panel. A detailed view opens in the right-hand panel. Click the MBeans tab which appears as a tab in the top of the right-hand panel.
To access the HBase metrics, navigate to the appropriate sub-bean:
Master: Hadoop → HBase → Master → Server
RegionServer: Hadoop → HBase → RegionServer → Server
The name of each metric and its current value is displayed in the Attributes tab. For a view which includes more details, including the description of each attribute, click the Metadata tab.
17.4.4. Units of Measure for Metrics
Different metrics are expressed in different units, as appropriate. Often, the unit of measure is in the name (as in the metric shippedKBs). Otherwise, use the following guidelines. When in doubt, you may need to examine the source for a given metric.
Metrics that refer to a point in time are usually expressed as a timestamp.
Metrics that refer to an age (such as ageOfLastShippedOp) are usually expressed in milliseconds.
Metrics that refer to memory sizes are in bytes.
Sizes of queues (such as sizeOfLogQueue) are expressed as the number of items in the queue. Determine the size by multiplying by the block size (default is 64 MB in HDFS).
Metrics that refer to things like the number of a given type of operations (such as logEditsRead) are expressed as an integer.
17.4.5. Most Important Master Metrics
Note: Counts are usually over the last metrics reporting interval.
hbase.master.numRegionServers
Number of live regionservers
hbase.master.numDeadRegionServers
Number of dead regionservers
hbase.master.ritCount
The number of regions in transition
hbase.master.ritCountOverThreshold
The number of regions that have been in transition longer than a threshold time (default: 60 seconds)
hbase.master.ritOldestAge
The age of the longest region in transition, in milliseconds
17.4.6. Most Important RegionServer Metrics
Note: Counts are usually over the last metrics reporting interval.
hbase.regionserver.regionCount
The number of regions hosted by the regionserver
hbase.regionserver.storeFileCount
The number of store files on disk currently managed by the regionserver
hbase.regionserver.storeFileSize
Aggregate size of the store files on disk
hbase.regionserver.hlogFileCount
The number of write ahead logs not yet archived
hbase.regionserver.totalRequestCount
The total number of requests received
hbase.regionserver.readRequestCount
The number of read requests received
hbase.regionserver.writeRequestCount
The number of write requests received
hbase.regionserver.numOpenConnections
The number of open connections at the RPC layer
hbase.regionserver.numActiveHandler
The number of RPC handlers actively servicing requests
hbase.regionserver.numCallsInGeneralQueue
The number of currently enqueued user requests
hbase.regionserver.numCallsInReplicationQueue
The number of currently enqueued operations received from replication
hbase.regionserver.numCallsInPriorityQueue
The number of currently enqueued priority (internal housekeeping) requests
hbase.regionserver.flushQueueLength
Current depth of the memstore flush queue. If increasing, we are falling behind with clearing memstores out to HDFS.
hbase.regionserver.updatesBlockedTime
Number of milliseconds updates have been blocked so the memstore can be flushed
hbase.regionserver.compactionQueueLength
Current depth of the compaction request queue. If increasing, we are falling behind with storefile compaction.
hbase.regionserver.blockCacheHitCount
The number of block cache hits
hbase.regionserver.blockCacheMissCount
The number of block cache misses
hbase.regionserver.blockCacheExpressHitPercent
The percent of the time that requests with the cache turned on hit the cache
hbase.regionserver.percentFilesLocal
Percent of store file data that can be read from the local DataNode, 0-100
hbase.regionserver.<op>_<measure>
Operation latencies, where <op> is one of Append, Delete, Mutate, Get, Replay, Increment; and where <measure> is one of min, max, mean, median, 75th_percentile, 95th_percentile, 99th_percentile
hbase.regionserver.slow<op>Count
The number of operations we thought were slow, where <op> is one of the list above
hbase.regionserver.GcTimeMillis
Time spent in garbage collection, in milliseconds
hbase.regionserver.GcTimeMillisParNew
Time spent in garbage collection of the young generation, in milliseconds
hbase.regionserver.GcTimeMillisConcurrentMarkSweep
Time spent in garbage collection of the old generation, in milliseconds
hbase.regionserver.authenticationSuccesses
Number of client connections where authentication succeeded
hbase.regionserver.authenticationFailures
Number of client connection authentication failures
hbase.regionserver.mutationsWithoutWALCount
Count of writes submitted with a flag indicating they should bypass the write ahead log
HBase emits metrics which adhere to the Hadoop metrics API. Starting with HBase 0.95[3], HBase is configured to emit a default set of metrics with a default sampling period of every 10 seconds. You can use HBase metrics in conjunction with Ganglia. You can also filter which metrics are emitted and extend the metrics framework to capture custom metrics appropriate for your environment.
17.4.1. Metric Setup
For HBase 0.95 and newer, HBase ships with a default metrics configuration, or sink. This includes a wide variety of individual metrics, and emits them every 10 seconds by default. To configure metrics for a given region server, edit the conf/hadoop-metrics2-hbase.properties file. Restart the region server for the changes to take effect.
To change the sampling rate for the default sink, edit the line beginning with *.period. To filter which metrics are emitted or to extend the metrics framework, see http://hadoop.apache.org/docs/current/api/org/apache/hadoop/metrics2/package-summary.html
HBase Metrics and Ganglia
By default, HBase emits a large number of metrics per region server. Ganglia may have difficulty processing all these metrics. Consider increasing the capacity of the Ganglia server or reducing the number of metrics emitted by HBase. See Metrics Filtering.
17.4.2. Disabling Metrics
To disable metrics for a region server, edit the conf/hadoop-metrics2-hbase.properties file and comment out any uncommented lines. Restart the region server for the changes to take effect.
17.4.3. Discovering Available Metrics
Rather than listing each metric which HBase emits by default, you can browse through the available metrics, either as a JSON output or via JMX. Different metrics are exposed for the Master process and each region server process.
Procedure 17.1. Access a JSON Output of Available Metrics
After starting HBase, access the region server's web UI, at http://REGIONSERVER_HOSTNAME:60030 by default (or port 16030 in HBase 1.0+).
Click the Metrics Dump link near the top. The metrics for the region server are presented as a dump of the JMX bean in JSON format. This will dump out all metrics names and their values. To include metrics descriptions in the listing — this can be useful when you are exploring what is available — add a query string of ?description=true so your URL becomes http://REGIONSERVER_HOSTNAME:60030/jmx?description=true. Not all beans and attributes have descriptions.
To view metrics for the Master, connect to the Master's web UI instead (defaults to http://localhost:60010 or port 16010 in HBase 1.0+) and click its Metrics Dump link. To include metrics descriptions in the listing — this can be useful when you are exploring what is available — add a query string of ?description=true so your URL becomes http://REGIONSERVER_HOSTNAME:60010/jmx?description=true. Not all beans and attributes have descriptions.
Procedure 17.2. Browse the JMX Output of Available Metrics
You can use many different tools to view JMX content by browsing MBeans. This procedure uses jvisualvm, which is an application usually available in the JDK.
Start HBase, if it is not already running.
Run the command jvisualvm command on a host with a GUI display. You can launch it from the command line or another method appropriate for your operating system.
Be sure the VisualVM-MBeans plugin is installed. Browse to Tools → Plugins. Click Installed and check whether the plugin is listed. If not, click Available Plugins, select it, and click Install. When finished, click Close.
To view details for a given HBase process, double-click the process in the Local sub-tree in the left-hand panel. A detailed view opens in the right-hand panel. Click the MBeans tab which appears as a tab in the top of the right-hand panel.
To access the HBase metrics, navigate to the appropriate sub-bean:
Master: Hadoop → HBase → Master → Server
RegionServer: Hadoop → HBase → RegionServer → Server
The name of each metric and its current value is displayed in the Attributes tab. For a view which includes more details, including the description of each attribute, click the Metadata tab.
17.4.4. Units of Measure for Metrics
Different metrics are expressed in different units, as appropriate. Often, the unit of measure is in the name (as in the metric shippedKBs). Otherwise, use the following guidelines. When in doubt, you may need to examine the source for a given metric.
Metrics that refer to a point in time are usually expressed as a timestamp.
Metrics that refer to an age (such as ageOfLastShippedOp) are usually expressed in milliseconds.
Metrics that refer to memory sizes are in bytes.
Sizes of queues (such as sizeOfLogQueue) are expressed as the number of items in the queue. Determine the size by multiplying by the block size (default is 64 MB in HDFS).
Metrics that refer to things like the number of a given type of operations (such as logEditsRead) are expressed as an integer.
17.4.5. Most Important Master Metrics
Note: Counts are usually over the last metrics reporting interval.
hbase.master.numRegionServers
Number of live regionservers
hbase.master.numDeadRegionServers
Number of dead regionservers
hbase.master.ritCount
The number of regions in transition
hbase.master.ritCountOverThreshold
The number of regions that have been in transition longer than a threshold time (default: 60 seconds)
hbase.master.ritOldestAge
The age of the longest region in transition, in milliseconds
17.4.6. Most Important RegionServer Metrics
Note: Counts are usually over the last metrics reporting interval.
hbase.regionserver.regionCount
The number of regions hosted by the regionserver
hbase.regionserver.storeFileCount
The number of store files on disk currently managed by the regionserver
hbase.regionserver.storeFileSize
Aggregate size of the store files on disk
hbase.regionserver.hlogFileCount
The number of write ahead logs not yet archived
hbase.regionserver.totalRequestCount
The total number of requests received
hbase.regionserver.readRequestCount
The number of read requests received
hbase.regionserver.writeRequestCount
The number of write requests received
hbase.regionserver.numOpenConnections
The number of open connections at the RPC layer
hbase.regionserver.numActiveHandler
The number of RPC handlers actively servicing requests
hbase.regionserver.numCallsInGeneralQueue
The number of currently enqueued user requests
hbase.regionserver.numCallsInReplicationQueue
The number of currently enqueued operations received from replication
hbase.regionserver.numCallsInPriorityQueue
The number of currently enqueued priority (internal housekeeping) requests
hbase.regionserver.flushQueueLength
Current depth of the memstore flush queue. If increasing, we are falling behind with clearing memstores out to HDFS.
hbase.regionserver.updatesBlockedTime
Number of milliseconds updates have been blocked so the memstore can be flushed
hbase.regionserver.compactionQueueLength
Current depth of the compaction request queue. If increasing, we are falling behind with storefile compaction.
hbase.regionserver.blockCacheHitCount
The number of block cache hits
hbase.regionserver.blockCacheMissCount
The number of block cache misses
hbase.regionserver.blockCacheExpressHitPercent
The percent of the time that requests with the cache turned on hit the cache
hbase.regionserver.percentFilesLocal
Percent of store file data that can be read from the local DataNode, 0-100
hbase.regionserver.<op>_<measure>
Operation latencies, where <op> is one of Append, Delete, Mutate, Get, Replay, Increment; and where <measure> is one of min, max, mean, median, 75th_percentile, 95th_percentile, 99th_percentile
hbase.regionserver.slow<op>Count
The number of operations we thought were slow, where <op> is one of the list above
hbase.regionserver.GcTimeMillis
Time spent in garbage collection, in milliseconds
hbase.regionserver.GcTimeMillisParNew
Time spent in garbage collection of the young generation, in milliseconds
hbase.regionserver.GcTimeMillisConcurrentMarkSweep
Time spent in garbage collection of the old generation, in milliseconds
hbase.regionserver.authenticationSuccesses
Number of client connections where authentication succeeded
hbase.regionserver.authenticationFailures
Number of client connection authentication failures
hbase.regionserver.mutationsWithoutWALCount
Count of writes submitted with a flag indicating they should bypass the write ahead log
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HADOOP中mapreduce开启压缩功能
2015-10-14 14:26 3648最近给热云公 ... -
HIVE跑mapjoin时所有任务失败--问题分析及解决
2015-09-22 16:40 8826今天有个需求,就是:指定200W用 ... -
hadoop、hbase节点下线
2015-09-17 16:21 4806hadoop节点在磁盘坏掉的时候需要 ... -
HADOOP中设置map个数
2015-06-11 09:08 1231很多文档中描述,Mapper的数量在默认情况下不可直接控制 ... -
hadoop安全机制
2015-05-22 18:04 9991.背景 1.1 共享Hadoop集群 当前大一点的公司 ... -
CDH对hadoop的一些配置指南,包括THP
2015-04-28 17:16 2236Tips and Guidelines Sele ... -
MAP运行过程
2015-04-23 16:46 977Anatomy of a MapReduce Job ... -
MAP/REDUCE TASK作业状态转移图
2015-04-23 13:37 1236Task Attempt Table of con ... -
YARN常见问题
2015-04-23 00:40 927本文汇总了几个hadoop yarn中常见问题以及解决方案,注 ... -
转载--淘宝hadoop升级遇到的问题
2015-04-22 18:03 1160搜索离线dump集群(hadoop&hbase)20 ... -
mapreduce数据流配置
2015-04-15 21:15 926Hadoop配置文件设定了Ha ... -
HADOOP2 yarn相关参数
2015-04-15 20:45 917注意,配置这些参数前,应充分理解这几个参数的含义,以防止误配 ... -
HADOOP2 mapreduce配置(转)
2015-04-15 20:42 1408MapReduce相关配置参数分为两部分,分别是JobHis ... -
(转)hadoop yarn 内存相关配置
2015-06-11 09:09 14671.YARN中处理能力的基本单元是什么?2.什么是保留内存 ... -
YARN的一些常见错误
2015-06-12 13:58 1987问题导读1、Hadoop YARN常见问题有哪些?2、你是 ... -
(转) hadoop2安装LZO
2015-04-04 15:00 4801.为什么使用lzo?2.如何安装配置lzo?3.如何使用l ... -
(转)提高mapreduce性能的几点建议-cloudera
2015-04-04 14:55 1054前言 Cloudera提供给客户的服务内容之一就是调整和优 ... -
(转)YARN内存配置
2015-04-04 11:01 1036问题导读1、Yarn对MRv1的 ... -
(转)HADOOP2.6基于标签的调度
2015-04-04 10:32 851在最新的hadoop 2.6.0版本中,YARN引入了一种 ... -
HADOOP平台优化综述(转自董的博客)
2015-04-03 15:56 8601. 概述 随着 ...
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