发布于 2015-09-14 15:08:32 | 191 次阅读 | 评论: 0 | 来源: 网络整理
The serverStatus command returns a collection of information that reflects the database’s status. These data are useful for diagnosing and assessing the performance of your MongoDB instance. This reference catalogs each datum included in the output of this command and provides context for using this data to more effectively administer your database.
也可以参考
Much of the output of serverStatus is also displayed dynamically by mongostat. See the mongostat command for more information.
For examples of the serverStatus output, see 服务器状态输出索引.
The host field contains the system’s hostname. In Unix/Linux systems, this should be the same as the output of the hostname command.
The version field contains the version of MongoDB running on the current mongod or mongos instance.
The process field identifies which kind of MongoDB instance is running. Possible values are:
The value of the uptime field corresponds to the number of seconds that the mongos or mongod process has been active.
uptimeEstimate provides the uptime as calculated from MongoDB’s internal course-grained time keeping system.
2.1.2 新版功能: All locks statuses first appeared in the 2.1.2 development release for the 2.2 series.
Example
The locks document contains sub-documents that provides a granular report on MongoDB database-level lock use. All values are of the NumberLong() type.
Generally, fields named:
If a document does not have any fields, it means that no locks have existed with this context since the last time the mongod started.
A field named . holds the first document in locks that contains information about the global lock.
The timeLockedMicros document reports the amount of time in microseconds that a lock has existed in all databases in this mongod instance.
The R field reports the amount of time in microseconds that any database has held the global read lock.
The W field reports the amount of time in microseconds that any database has held the global write lock.
The r field reports the amount of time in microseconds that any database has held the local read lock.
The w field reports the amount of time in microseconds that any database has held the local write lock.
The timeAcquiringMicros document reports the amount of time in microseconds that operations have spent waiting to acquire a lock in all databases in this mongod instance.
The R field reports the amount of time in microseconds that any database has spent waiting for the global read lock.
The W field reports the amount of time in microseconds that any database has spent waiting for the global write lock.
The admin document contains two sub-documents that report data regarding lock use in the admin database.
The timeLockedMicros document reports the amount of time in microseconds that locks have existed in the context of the admin database.
The r field reports the amount of time in microseconds that the admin database has held the read lock.
The w field reports the amount of time in microseconds that the admin database has held the write lock.
The timeAcquiringMicros document reports on the amount of field time in microseconds that operations have spent waiting to acquire a lock for the admin database.
The r field reports the amount of time in microseconds that operations have spent waiting to acquire a read lock on the admin database.
The w field reports the amount of time in microseconds that operations have spent waiting to acquire a write lock on the admin database.
The local document contains two sub-documents that report data regarding lock use in the local database. The local database contains a number of instance specific data, including the oplog for replication.
The timeLockedMicros document reports on the amount of time in microseconds that locks have existed in the context of the local database.
The r field reports the amount of time in microseconds that the local database has held the read lock.
The w field reports the amount of time in microseconds that the local database has held the write lock.
The timeAcquiringMicros document reports on the amount of time in microseconds that operations have spent waiting to acquire a lock for the local database.
The r field reports the amount of time in microseconds that operations have spent waiting to acquire a read lock on the local database.
The w field reports the amount of time in microseconds that operations have spent waiting to acquire a write lock on the local database.
For each additional database locks includes a document that reports on the lock use for this database. The names of these documents reflect the database name itself.
The timeLockedMicros document reports on the amount of time in microseconds that locks have existed in the context of the <database> database.
The r field reports the amount of time in microseconds that the <database> database has held the read lock.
The w field reports the amount of time in microseconds that the <database> database has held the write lock.
The timeAcquiringMicros document reports on the amount of time in microseconds that operations have spent waiting to acquire a lock for the <database> database.
The r field reports the amount of time in microseconds that operations have spent waiting to acquire a read lock on the <database> database.
The w field reports the amount of time in microseconds that operations have spent waiting to acquire a write lock on the <database> database.
Example
The globalLock data structure contains information regarding the database’s current lock state, historical lock status, current operation queue, and the number of active clients.
The value of totalTime represents the time, in microseconds, since the database last started and creation of the globalLock. This is roughly equivalent to total server uptime.
The value of lockTime represents the time, in microseconds, since the database last started, that the globalLock has been held.
Consider this value in combination with the value of totalTime. MongoDB aggregates these values in the ratio value. If the ratio value is small but totalTime is high the globalLock has typically been held frequently for shorter periods of time, which may be indicative of a more normal use pattern. If the lockTime is higher and the totalTime is smaller (relatively,) then fewer operations are responsible for a greater portion of server’s use (relatively.)
在 2.2 版更改: ratio was removed. See locks.
The value of ratio displays the relationship between lockTime and totalTime.
Low values indicate that operations have held the globalLock frequently for shorter periods of time. High values indicate that operations have held globalLock infrequently for longer periods of time.
The currentQueue data structure value provides more granular information concerning the number of operations queued because of a lock.
The value of total provides a combined total of operations queued waiting for the lock.
A consistently small queue, particularly of shorter operations should cause no concern. Also, consider this value in light of the size of queue waiting for the read lock (e.g. readers) and write-lock (e.g. writers) individually.
The activeClients data structure provides more granular information about the number of connected clients and the operation types (e.g. read or write) performed by these clients.
Use this data to provide context for the currentQueue data.
The value of total is the total number of active client connections to the database. This combines clients that are performing read operations (e.g. readers) and clients that are performing write operations (e.g. writers).
Example
The mem data structure holds information regarding the target system architecture of mongod and current memory use.
The value of bits is either 64 or 32, depending on which target architecture specified during the mongod compilation process. In most instances this is 64, and this value does not change over time.
The value of resident is roughly equivalent to the amount of RAM, in megabytes (MB), currently used by the database process. In normal use this value tends to grow. In dedicated database servers this number tends to approach the total amount of system memory.
virtual displays the quantity, in megabytes (MB), of virtual memory used by the mongod process. In typical deployments this value is slightly larger than mapped. If this value is significantly (i.e. gigabytes) larger than mapped, this could indicate a memory leak.
With journaling enabled, the value of virtual is twice the value of mapped.
supported is true when the underlying system supports extended memory information. If this value is false and the system does not support extended memory information, then other mem values may not be accessible to the database server.
The value of mapped provides the amount of mapped memory, in megabytes (MB), by the database. Because MongoDB uses memory-mapped files, this value is likely to be to be roughly equivalent to the total size of your database or databases.
mappedWithJournal provides the amount of mapped memory, in megabytes (MB), including the memory used for journaling. This value will always be twice the value of mapped. This field is only included if journaling is enabled.
Example
The connections sub document data regarding the current connection status and availability of the database server. Use these values to asses the current load and capacity requirements of the server.
The value of current corresponds to the number of connections to the database server from clients. This number includes the current shell session. Consider the value of available to add more context to this datum.
This figure will include the current shell connection as well as any inter-node connections to support a replica set or sharded cluster.
available provides a count of the number of unused available connections that the database can provide. Consider this value in combination with the value of current to understand the connection load on the database, and the Linux ulimit Settings document for more information about system thresholds on available connections.
Example
The extra_info data structure holds data collected by the mongod instance about the underlying system. Your system may only report a subset of these fields.
The field note reports that the data in this structure depend on the underlying platform, and has the text: “fields vary by platform.”
The heap_usage_bytes field is only available on Unix/Linux systems, and reports the total size in bytes of heap space used by the database process.
The page_faults field is only available on Unix/Linux systems, and reports the total number of page faults that require disk operations. Page faults refer to operations that require the database server to access data which isn’t available in active memory. The page_faults counter may increase dramatically during moments of poor performance and may correlate with limited memory environments and larger data sets. Limited and sporadic page faults do not necessarily indicate an issue.
Example
在 2.2 版更改: Previously, data in the indexCounters document reported sampled data, and were only useful in relative comparison to each other, because they could not reflect absolute index use. In 2.2 and later, these data reflect actual index use.
The indexCounters data structure reports information regarding the state and use of indexes in MongoDB.
The btree data structure contains data regarding MongoDB’s btree indexes.
accesses reports the number of times that operations have accessed indexes. This value is the combination of the hits and misses. Higher values indicate that your database has indexes and that queries are taking advantage of these indexes. If this number does not grow over time, this might indicate that your indexes do not effectively support your use.
The hits value reflects the number of times that an index has been accessed and mongod is able to return the index from memory.
A higher value indicates effective index use. hits values that represent a greater proportion of the accesses value, tend to indicate more effective index configuration.
The misses value represents the number of times that an operation attempted to access an index that was not in memory. These “misses,” do not indicate a failed query or operation, but rather an inefficient use of the index. Lower values in this field indicate better index use and likely overall performance as well.
The resets value reflects the number of times that the index counters have been reset since the database last restarted. Typically this value is 0, but use this value to provide context for the data specified by other indexCounters values.
mongod periodically flushes writes to disk. In the default configuration, this happens every 60 seconds. The backgroundFlushing data structure contains data regarding these operations. Consider these values if you have concerns about write performance and journaling.
flushes is a counter that collects the number of times the database has flushed all writes to disk. This value will grow as database runs for longer periods of time.
The total_ms value provides the total number of milliseconds (ms) that the mongod processes have spent writing (i.e. flushing) data to disk. Because this is an absolute value, consider the value of flushes and average_ms to provide better context for this datum.
The average_ms value describes the relationship between the number of flushes and the total amount of time that the database has spent writing data to disk. The larger flushes is, the more likely this value is likely to represent a “normal,” time; however, abnormal data can skew this value.
Use the last_ms to ensure that a high average is not skewed by transient historical issue or a random write distribution.
The value of the last_ms field is the amount of time, in milliseconds, that the last flush operation took to complete. Use this value to verify that the current performance of the server and is in line with the historical data provided by average_ms and total_ms.
The last_finished field provides a timestamp of the last completed flush operation in the ISODate format. If this value is more than a few minutes old relative to your server’s current time and accounting for differences in time zone, restarting the database may result in some data loss.
Also consider ongoing operations that might skew this value by routinely block write operations.
Example
output of the cursors fields.
Example
The value of the bytesIn field reflects the amount of network traffic, in bytes, received by this database. Use this value to ensure that network traffic sent to the mongod process is consistent with expectations and overall inter-application traffic.
The value of the bytesOut field reflects the amount of network traffic, in bytes, sent from this database. Use this value to ensure that network traffic sent by the mongod process is consistent with expectations and overall inter-application traffic.
The numRequests field is a counter of the total number of distinct requests that the server has received. Use this value to provide context for the bytesIn and bytesOut values to ensure that MongoDB’s network utilization is consistent with expectations and application use.
Example
The repl data structure contains status information for MongoDB’s replication (i.e. “replica set”) configuration. These values only appear when the current host has replication enabled.
See 副本集基本概念 for more information on replication.
The setName field contains a string with the name of the current replica set. This value reflects the --replSet command line argument, or replSet value in the configuration file.
See 副本集基本概念 for more information on replication.
The value of the ismaster field is either true or false and reflects whether the current node is the master or primary node in the replica set.
See 副本集基本概念 for more information on replication.
Example
The opcountersRepl data structure, similar to the opcounters data structure, provides an overview of database replication operations by type and makes it possible to analyze the load on the replica in more granular manner. These values only appear when the current host has replication enabled.
These values will differ from the opcounters values because of how MongoDB serializes operations during replication. See 副本集基本概念 for more information on replication.
These numbers will grow over time in response to database use. Analyze these values over time to track database utilization.
insert provides a counter of the total number of replicated insert operations since the mongod instance last started.
query provides a counter of the total number of replicated queries since the mongod instance last started.
update provides a counter of the total number of replicated update operations since the mongod instance last started.
delete provides a counter of the total number of replicated delete operations since the mongod instance last started.
2.1.2 新版功能.
The replNetworkQueue document reports on the network replication buffer, which permits replication operations to happen in the background. This feature is internal.
This document only appears on secondary members of replica sets.
waitTimeMs reports the amount of time that a secondary waits to add operations to network queue. This value is cumulative.
Example
The opcounters data structure provides an overview of database operations by type and makes it possible to analyze the load on the database in more granular manner.
These numbers will grow over time and in response to database use. Analyze these values over time to track database utilization.
insert provides a counter of the total number of insert operations since the mongod instance last started.
query provides a counter of the total number of queries since the mongod instance last started.
update provides a counter of the total number of update operations since the mongod instance last started.
delete provides a counter of the total number of delete operations since the mongod instance last started.
Example
The asserts document reports the number of asserts on the database. While assert errors are typically uncommon, if there are non-zero values for the asserts, you should check the log file for the mongod process for more information. In many cases these errors are trivial, but are worth investigating.
The regular counter tracks the number of regular assertions raised since the server process started. Check the log file for more information about these messages.
The warning counter tracks the number of warnings raised since the server process started. Check the log file for more information about these warnings.
The msg counter tracks the number of message assertions raised since the server process started. Check the log file for more information about these messages.
The user counter reports the number of “user asserts” that have occurred since the last time the server process started. These are errors that user may generate, such as out of disk space or duplicate key. You can prevent these assertions by fixing a problem with your application or deployment. Check the MongoDB log for more information.
The rollovers counter displays the number of times that the rollover counters have rolled over since the last time the server process started. The counters will rollover to zero after 230 assertions. Use this value to provide context to the other values in the asserts data structure.
The value of writeBacksQueued is true when there are operations from a mongos instance queued for retrying. Typically this option is false.
也可以参考
1.8 新版功能.
Example
The dur (for “durability”) document contains data regarding the mongod‘s journaling-related operations and performance. mongod must be running with journaling for these data to appear in the output of “serverStatus”.
注解
The data values are not cumulative but are reset on a regular basis as determined by the journal group commit interval. This interval is ~100 milliseconds (ms) by default (or 30ms if the journal file is on the same file system as your data files) and is cut by 1/3 when there is a getLastError command pending. The interval is configurable using the --journalCommitInterval option.
也可以参考
“日志” for more information about journaling operations.
The commits provides the number of transactions written to the journal during the last journal group commit interval.
The journaledMB provides the amount of data in megabytes (MB) written to journal during the last journal group commit interval.
The writeToDataFilesMB provides the amount of data in megabytes (MB) written from journal to the data files during the last journal group commit interval.
2.0 新版功能.
The compression represents the compression ratio of the data written to the journal:
( journaled_size_of_data / uncompressed_size_of_data )
The commitsInWriteLock provides a count of the commits that occurred while a write lock was held. Commits in a write lock indicate a MongoDB node under a heavy write load and call for further diagnosis.
The earlyCommits value reflects the number of times MongoDB requested a commit before the scheduled journal group commit interval. Use this value to ensure that your journal group commit interval is not too long for your deployment.
The timeMS document provides information about the performance of the mongod instance during the various phases of journaling in the last journal group commit interval.
The dt value provides, in milliseconds, the amount of time over which MongoDB collected the timeMS data. Use this field to provide context to the other timeMS field values.
The prepLogBuffer value provides, in milliseconds, the amount of time spent preparing to write to the journal. Smaller values indicate better journal performance.
The writeToJournal value provides, in milliseconds, the amount of time spent actually writing to the journal. File system speeds and device interfaces can affect performance.
The writeToDataFiles value provides, in milliseconds, the amount of time spent writing to data files after journaling. File system speeds and device interfaces can affect performance.
The remapPrivateView value provides, in milliseconds, the amount of time spent remapping copy-on-write memory mapped views. Smaller values indicate better journal performance.
Example
output of the recordStats fields.
The recordStats document provides fine grained reporting on page faults on a per database level.
accessesNotInMemory reflects the number of times mongod needed to access a memory page that was not resident in memory for all databases managed by this mongod instance.
pageFaultExceptionsThrown reflects the number of page fault exceptions thrown by mongod when accessing data for all databases managed by this mongod instance.
accessesNotInMemory reflects the number of times mongod needed to access a memory page that was not resident in memory for the local database.
pageFaultExceptionsThrown reflects the number of page fault exceptions thrown by mongod when accessing data for the local database.
accessesNotInMemory reflects the number of times mongod needed to access a memory page that was not resident in memory for the admin database.
pageFaultExceptionsThrown reflects the number of page fault exceptions thrown by mongod when accessing data for the admin database.
accessesNotInMemory reflects the number of times mongod needed to access a memory page that was not resident in memory for the <database> database.
pageFaultExceptionsThrown reflects the number of page fault exceptions thrown by mongod when accessing data for the <database> database.