Maintaining, Operating, and Monitoring Historian | Historian 9.1 Documentation

Maintain, Operate, and Monitor Historian

To ensure reliable, error-free operation over a long period of time, develop and execute a consistent maintenance program for the Historian system and the data it collects. This chapter provides guidelines for setting up such a plan and for monitoring and interpreting system performance indicators.

Refer to the following topics for more specific information:

Data Types
Plan for Data Recovery
Develop a Maintenance Plan for Historian
Perform Routine Maintenance
Use ihArchiveBackup.exe to Back Up Archives Automatically
Control the Amount of Disk Space Usage
Review System Alerts and Messages
Audit System Connections
Evaluate Data Compression Performance
Monitor the Health of the Historian system

Data Types

Historian uses the following data types.


Data Type	Size	Description
Single Float	4 bytes	The single float data type stores decimal values up to 6 places. Valid ranges for the single float data type are 1.175494351e-38F to 3.402823466e+38F
Double Float	8 bytes	The double float data type stores decimal values up to 15 places. Valid values for the double float data type are 2.2250738585072014e-308 to 1.7976931348623158e+308
Single Integer	2 bytes	The single integer data type stores whole numbers, without decimal places. Valid values for the single integer data type are -32767 to +32767.
Double Integer	4 bytes	The double integer data type stores whole numbers, without decimal places. Valid values for the double integer data type are - 2147483648 to +2147483648.
Quad Integer	8 bytes	The quad integer data type stores whole numbers without decimal places. Valid values for the quad integer data type are -9,223,372,036,854,775,808 (negative 9 quintillion) to +9,223,372,036,854,775,807 (positive 9 quintillion).
Unsigned Single Integer	2 bytes	The unsigned single integer data type stores whole numbers without decimal places. Valid values for the unsigned single integer data type are 0 to 65535.
Unsigned Double Integer	4 bytes	The unsigned double integer data type stores whole numbers without decimal places. Valid values for the unsigned double integer data type are 0 to 4,294,967, 295 (4.2 billion).
Unsigned Quad Integer	8 bytes	The unsigned quad integer data type stores whole numbers without decimal places. Valid values for the unsigned quad integer data type are 0 to 18,446,744,073,709,551,615 (19 quintillion).
Byte	1 byte	The Byte data type stores integer values. Valid values for the byte data type are -128 to +127.
Boolean	1 byte	The Boolean data type stores boolean values. Valid values for the boolean data type are 0=FALSE and 1=TRUE. If the user sends zero, the value is taken as zero; any value other than zero is treated as one.
Fixed String	Configured by user	The fixed string data type stores string data of a fixed size. Valid values are between 0 and 255 bytes. See Fixed String Data Types for more information.
Variable String	No fixed size	The variable string data type stores string values of undetermined size. This data type is useful if you cannot rely on a constant string length from your data source.
Binary Object	No fixed size	The binary object data type stores binary data. This is useful for capturing data that can not be classified by any other data type.
Scaled	2 bytes	The scaled data type lets you store a 4 byte float as a 2 byte integer in the Historian archive. The scaled data type saves disk space but sacrifices data precision as a result. See Scaled Data Types for more information

Note: Tags associated with Quad Integer, Unsigned Double Integer, or Unsigned Quad Integer data types retrieved using Non-Web Admin, Excel Add-in, Calculation, ihSQL, or ihSDK may suffer a loss of precision value due to a Visual Basic limitation.

Note: The Calculation collector supports only calculations performed using the current value calculation. It does not support other calculations due to a Visual Basic script limitation.

Scaled Data Types

Historian uses the high and low EGU values to both store and retrieve archived values for the scaled data type. This allows you to store 4 byte floats as 2 byte integers in the Historian archive. Though this saves disk space, it sacrifices data precision. The smaller the span is between the high and low EGU limits, the more precise the retrieved value will be. When calculating the value of a scaled data type, you can use this formula:

ArchivedValue = (((RealWorldValue - EngUnits->Low) /
 (EngUnits->High - EngUnits->Low) * (float) HR_SCALED_MAX_VALUE) + .5);

For example: A value of 12.345 was stored in a scaled tag whose high EGU was 200 and low EGU was 0. When later retrieved from the Historian archive, a value of 12.34473 would be returned.

Important: Values that are outside of the EGU range of a scaled data type tag get stored as "bad, "scaledoutofrange" in Historian. Changing either the High or Low EGU tags does not affect existing data, but only affects the new data with new timestamps. You cannot correct values for scaled data types that were inserted while EGUs were incorrect. If necessary, contact technical support for additional information.

Quad Integer Data Types: The high and low EGU limits for Quad Integer, Unsigned Single Integer, Unsigned Double Integer, Unsigned Quad Integer are between 2.2250738585072014e-308 to 1.7976931348623158e+308.

Setting a Value for the Fixed String Data Type

About this task

The fixed string data type lets you store string data of a fixed size. This is useful when you know exactly what data will be received by Historian. If a value is larger than the size specified in the Data Length field, it will be truncated.

Procedure

In the Admin App, select Tags.
Select the tag you wish to configure. Refer to Searching for Tags for more information.
Select Collection.
In the Data Type drop-down list, select Fixed String.
Enter a value in bytes in the adjacent field.
This field is enabled only when the data type selected is Fixed String.

Plan for Data Recovery

Planning for data recovery means always having up-to-date backup files for important information that you can call up and restore quickly when the need arises.

The .IHC file, which contains all configuration information, is an important file to back up. The .IHC file is automatically backed up when, and only when, you back up the current archive .IHA file. With the .IHC file, you can always restore the system configuration to the state it was in before the event occurred.

It is also important to backup the current online archive files *.IHA. If you restore the archive files, along with the configuration, you can quickly pick up where you left off when the event occurred with a minimum loss of data.

By default, the .IHC backup path is the same as the archives path. The .IHC uses the following naming convention: ComputerName_Config-Backup.ihc. If the default backup path is different than the archives path, the .IHC file is copied to the backup folder with the standard .IHC naming convention: ComputerName_Config.ihc.

Develop a Maintenance Plan

The primary goal of a maintenance plan is to maintain integrity of the data collected. If you are successful in this regard, you will always be able to recover from a service interruption and continue operation with minimal or no loss of data. Since you can never ensure 100% system uptime, you must frequently and regularly back up current data and configuration files, and maintain non-current archive files in a read-only state, following the guidelines for backup and routine maintenance.

Daily Maintenance

On a daily schedule, perform the following backup operations, unless you use ihArchiveBackup.exe to back up archives automatically.

Use Historian Administrator to back up the current archive and most recent .IHA archived data file. This preserves data collected up to this moment in time. You do not need to back up any read-only archive files after they have been backed up once.
If you are doing more than a nightly backup, or backing up more than the last two archives, use the Microsoft Volume Shadow Copy Service (VSS) to preserve memory. Refer to the Back Up an Archive using Volume Shadow Copy Service section for more information.
Use Windows Explorer to back up the .IHC file if it has been modified, unless it is backed up automatically. This file contains all current configuration information (tag configuration, archive configuration, and collector configuration). Using this file, you can restore the system configuration after an unplanned shutdown.

Routine Maintenance: On a regular schedule, examine and analyze the system performance indicators displayed on the System Statistics page of Historian Administrator as follows.

Table 1. System Statistics Performance Indicators
Field	Recommended Action
Est. Days to Full	If time is growing short, make sure that the server has sufficient unused storage capacity to open a new archive when the active one fills up. Verify that the Create New Archives Automatically function is enabled. If it is disabled, you must manually create a new archive before the active archive fills up. Note: If you do not have enough unused storage capacity, you may have to enable the Overwrite Old Archives feature. Since this feature overwrites existing data, exercise caution in using it.
Consumption Rate of Archive Storage	If the rate is excessively high, reduce the rate at which data flows into the system or increase the filtering applied to the data to lower the rate of archiving. To reduce the collection rate, slow the polling rate on some or all tags. To increase filtering, enable compression at the collector and/or archiver and widen the compression deadbands.
Failed Writes	If the display shows a significant number of failed writes, investigate the cause and take corrective action to eliminate the malfunctions. Refer to the DataArchiver-XX.log file or query the message database to determine the tags for which failed writes occurred. For example, trying to write values to a deleted archive causes failed writes. Trying to archive data with a timestamp that precedes the start time of the first archive, trying to write to a read-only archive, or trying to write a value with a timestamp more than 15 minutes ahead of the current time on an archiver will produce a failed write.
System Alerts	Examine the messages and alerts and take appropriate action to correct any problems.

On a regular schedule, examine and analyze the performance indicators displayed in the Performance section.

Table 2. Collector Performance Indicators
Field	Recommended Actions
Avg. Event Rate Chart	Is the rate at a normal level? Does the chart exhibit an acceptable trend line? If not, determine why. Balance polling schedules, adjust scan frequencies (collection intervals), and modify compression deadbands to lighten load.
Compression Chart	Is compression effectiveness acceptable? If not, verify that compression is enabled and then widen the deadbands to increase the effect of compression.
Overruns Chart	If the value is anything other than zero, determine the severity and cause of the problem and take corrective action.

Evaluate and Control Data Compression

You can achieve optimum performance in Historian by carefully controlling the volume of dynamic data it collects and archives. You need enough information to tell you how the process is running, but you do not need to collect and store redundant or non-varying data values that provide no useful information. More information can be found in the Notes on Collector and Archive Compression reference.

Control Data Flow

You can control the amount of online or dynamic data the system handles at a given time by adjusting certain system parameters. The general principle is to control the flow of data into the archive either by adjusting the rate at which the collectors gather data or by adjusting the degree of filtering (compression) the system applies to the data collected.

This manual describes the detailed procedures for executing these adjustments in the sections: Configuring Archives, Configuring Tags, and Configuring Collectors.

Adjust the following parameters to reduce the rate of data flow into the server.

Reduce the polling rate by increasing the collection interval for unsolicited and polled collection.
Enable collector compression and optionally use compression timeout.
Set the compression deadband on the collectors to a wider value.
Use the collector compression timeout.

Adjust the following parameters to increase the filtering applied by the archiver in the server.

Enable archive (trend) compression.
Set the archive compression deadband to a wider value.
Where possible, use the scaled data type and enable input scaling on selected tags.
Where possible, select milliseconds or microseconds rather than seconds for time resolution. Seconds is optimum for most common devices. This affects disk space.

Evaluate Data Compression Performance

You can determine how effectively data compression is functioning at any given time by examining the system statistics displayed on the System Statistics page of Historian Administrator, as shown in Historian Administrator (System Statistics) Screen.

The compression field at the top of the page shows the current effect of archive compression. Values for this parameter should typically range from 0 to 9%. If the value is zero, it indicates that compression is either ineffective or turned off. If it shows a value other than zero, it indicates that archive compression is operating and effective. The value itself indicates how well it is functioning. To increase the effect of data compression, increase the value of archive compression deadband so that compression becomes more active.

Handle Value Step Changes with Collector Data Compression

Note: Individual tags can be configured to retrieve step value changes.

If you enable collector compression, the collector does not send values to the archiver any new input values if the value remains within its compression deadband. Occasionally, after several sample intervals inside the deadband, an input makes a rapid step change in value during a single sample interval. Since there have been no new data points recorded for several intervals, an additional sample is stored one interval before the step change with the last reported value to prevent this step change from being viewed as a slow ramp in value. This value marks the end of the steady-state, non-changing value period, and provides a data point from which to begin the step change in value.

The collector uses an algorithm that views the size of the step change and the number of intervals since the last reported value to determine if a marker value is needed. The following is an example of the algorithm:

BigDiff=abs(HI_EGU-LO_EGU)*(CompressionDeadbandPercent/(100.0*2.0))*4.0
If ( Collector Compression is Enabled ) 
If ( Elapsed time since LastReportedValue>=( SampleInterval * 5 ) ) 
If ( abs(CurrentValue-LastReportedValue) > BigDiff ) 
Write LastReportedValue,Timestamp=(CurrentTime-SampleInterval)

In the example above, if a new value was not reported for at least the last 4 sample intervals, and the new input value is at least 4 deltas away from the old value (where a single delta is equal to half of the compression deadband), then a marker value is written.

Note: These settings are also adjustable from the Registry. Please contact technical support for more information.

Value Spike with Collector Compression

For example, a collector reads a value X once per second, with a compression deadband of 1.0. If the value of X is 10.0 for a number of seconds starting at 0:00:00 and jumps to 20.0 at 0:00:10, the data samples read would be:


Time	X Value
0:00:00	10.0 (steady state value)
0:00:01	10.0
0:00:02	10.0
0:00:03	10.0
0:00:04	10.0
0:00:05	10.0
0:00:06	10.0
0:00:07	10.0
0:00:08	10.0
0:00:09	10.0
0:00:10	20.0 (new value after step change)

To increase efficiency, the straightforward compression would store only 2 of these 11 samples.


Time	X Value
0:00:00	10.0 (steady state value)
0:00:10	20.0 (new value after step change)

However, without the marker value, if this data were to be put into a chart, it would look like the data value ramped over 10 seconds from a value of 10.0 to 20.0, as shown in the following chart.

The addition of a marker value to the data being stored results in the following data values:


Time	X Value
0:00:00	10.0 (steady state value)
0:00:09	10.0 (inserted Marker value)
0:00:10	20.0 (new value after step change)

If you chart this data, the resulting trend accurately reflects the raw data and likely real world values during the time period as shown in the following chart.

Reviewing System Alerts and Messages

About this task

You can examine system alerts by scrolling through the Alerts panel of Historian Administrator System Statistics page or by examining the Message Search page for more detail. Refer to Searching for Messages for detailed instructions. You can diagnose most operating problems by examining the archiver LOG file.

You may also find the Windows Event Viewer to be useful in diagnosing a problem. To open the Event Viewer, use the following procedure.

Procedure

Launch search.
Type eventvwr.msc and select OK.
The Event Viewer window appears.
Highlight an item.
A window appears with an explanation of the event.
Select Previous or Next to step through the messages.

Monitor Historian Health and Status

Historian provides extensive functionality to determine the health and status of both the data archiver and the collectors. You can access this information through Historian Administrator or set up your Historian system to automatically alert you to any Historian change. The following sections describe procedures and hints for monitoring your Historian system, including:

Monitor Operating System Event Files
Monitor Collector Status Tags
Monitor Historian Subscriptions
Use Collector Status Tags
Subscribe to Historian Alerts and Messages
Create Subscriptions

Monitor Operating System Event Files

You can view the operating system event files through the Event Viewer. For more information on accessing the Event Viewer, refer to Review System Alerts and Messages. The operating system event files contain the Historian Status messages found in the application log. Entries in that file are similar to those found in the Alerts panel, but may contain multiple entries for certain items. Multiple entries occur as a result of distributing the components of Historian. Each component logs its critical status changes to the local event log. For example, a collector and the data archive will both log a collector going off-line.

Monitor Collector Status Tags

The iFIX and OPC Collectors contain three status fields that you can write back to the data source for monitoring. Additionally, the iFIX collectors allow you to display and alarm on the following three status fields.

Rate Output - The number of events per minute the collector processes.
Status Output - The status of the Collector as either Running or Stopped.
Heartbeat - Allows the data source to verify that the collector is working. The collector writes a value of one to this address once a minute.

Other collectors allow you to define tags to record the status of the collector. These tags give an indication of the health of a collector, not the health of the Historian The following figure displays the iFIX collector status tags.

The three tags referenced correspond to tag names within the SCADA node FIX.

NodeName.HIST_RATE.F_CV An AI block. The F_CV field gives the number of events per minute that the collector is reporting to the server.
NodeName.HIST_STATUS.A_CV A text block. The A_CV field displays a status such as Running or Stopped depending on the status on the collector. This field does not reflect whether or not the Collector program is running.
NodeName.HIST_HEARTBEAT.F_CV A digital alarm block that will alarm if the F_CV field remains OPEN for more than 60 seconds. The iFIX collector closes the F_CV field every 60 seconds. You must use a pro- gram block in conjunction with this block to automatically OPEN the block if it has been CLOSED. This provides for a momentary reset of the 60 second alarm timeout. Unlike the HIST_STATUS block that only updates the Collector status if the collection stops, the HIST_ HEARTBEAT detects that the collection has stopped or that the Collector application is no longer running.

Monitor Historian Subscriptions

Certain objects in the Historian SDK allow you to create subscriptions that fire an event back to the calling application whenever the object's status updates. These subscriptions allow for exception-based monitoring of the Historian status without resorting to intensive polling of the server.

The following table displays the objects and their supported subscription events:

Table 3. Historian Objects with Subscription Events
Object	Subscription Events
Messages Object	AlertReceived and MessageReceived Events
Tags Object	ChangeReceived Event
Data Object	CurrentDataReceived Event
Archives Object	StatusReceived Event
Collectors Object	StatusReceived Event

Subscribing to any of these Object's events allows you to receive direct notification of status changes. For example, using iFIX scripting, you could route this notification to any alarm queue in iFIX.

Subscribe to Historian Alerts and Messages

You can obtain a complete picture of the Historian Server's status by monitoring the server's Alerts and Messages. Additionally, if you are using iFIX with Historian, you can capture these subscriptions and forward them to iFIX alarm queues to ensure operator notification.

You can also use scripting in iFIX to subscribe to the Historian message queues using VBA. If you write a script as part of an iFIX picture, you will need to either keep the picture with the scripts running at all times or run the scripts in the FIXBackground Server application.

Creating Subscriptions in iFIX

To subscribe to messages or alerts in Historian, you must reference the SDK from within the VBA project. To access the References window, shown in the following figure, use the Tools menu in the iFIX VBA Editor.

Once you reference a VBA project to the Historian SDK, you must define two module level objects: a Server Object and a Messages Object. Declare these Objects to remain in scope for the duration that the subscription is active.

Note: You must declare the Messages Object using the WithEvents keyword. This keyword is only valid at the module or class level.

Typically, the Server and Messages Object are declared as private module level objects. Subscriptions are made during the module initialization or upon loading the method. You can subscribe to Alerts or Messages using either the SubscribeAlerts or SubscribeMessages Method of the Messages Object.

Specify Topics

When subscribing to Historian Messages you must specify which topics you are subscribing to. There are six topics.

Message Topics: Configuration Audit, Connections, General
Alert Topics: Performance, Security, ServiceControl

Once you make the subscription, the AlertReceived or MessagesReceived Event will fire when a new message is created on the Historian Server. The topic of the message determines which event fires. Additionally, the event receives a copy of the Message or Alert Object properties listed as follows:

MessageNumber The NLS string number.
MessageString Translated string, including substitutions for time stamp, user, or tag name.
Substitutions A collection of substitutions used to make the message string.
TimeStamp The time the message was created.
Topic The topic number of the message.
TopicName The string topic name of the message.
UserName The user name for the message.

You can also send Alerts and Messages to the iFIX Operator Message alarm queue using the SendOperatorMessage method of the System object. This method will send the alerts and messages to all alarm queues, but NOT the Alarm Summary queue. To send a message that will appear on an alarm summary, send the message to the Alarm Extension field of a digital alarm block and toggle the alarm state.

Monitor Historian Performance

Historian provides a variety of counters and tags that can be used to monitor how well the Historian components are performing. You can use performance tags or counters to determine the resource usage on the computer that runs the Historian application. Performance counters are also useful when Historian Administrator is not installed or cannot connect.

Use performance tags to view information in an Excel report or SDK program, possibly along with other Historian tags.
Use performance counters to view information using Windows Performance monitor, possibly along with non-Historian counter information.

Like any Windows performance counter, you must add the counters for collection to view history. Performance tags are always being collected and you can view past data any time.

Performance counters are updated in real time. Performance tags are updated once per minute with the activity over the last minute.

Performance counters contain more information than tags.

Any counter can be collected to a tag using the Historian Windows Performance Collector. Those tags will count against your licensed tag count.

For more information, refer to the following sections:

Historian Server Performance Tags
Historian Server Performance Counters

Historian Server Performance Tags

The following table provides information about the various Historian Server Performance tags.

Table 4. Server Performance Tags
Tag Name	Description
PerfTag_CompressionRatio	Specifies the current effect of archive data compression.
PerfTag_MinimumCompressionRatio	Specifies the minimum compression ratio.
PerfTag_MaximumCompressionRatio	Specifies the maximum compression ratio.
PerfTag_TotalEvents	Specifies the total number of data samples reported to the Historian archive from all sources.
PerfTag_TotalOutOfOrder	Specifies the total out of order data samples.
PerfTag_AverageEventRate	Specifies the average number of data samples per minute sent to archiver from all sources
PerfTag_MinimumEventRate	Specifies the minimum number of data samples per minute sent to archiver from all sources.
PerfTag_MaximumEventRate	Specifies the maximum number of data samples per minute sent to archiver from all sources.
PerfTag_WriteCacheHitRatio	Specifies the hit ratio of the write cache in percent of the total writes.
PerfTag_TotalFailedWrites	Specifies the total number of samples since startup that failed to be written.
PerfTag_TotalMessages	Specifies the total messages (for example, connection or audit messages) received by the archiver since startup
PerfTag_TotalAlerts	Specifies the total number of alerts received by the data archiver since startup.
PerfTag_FreeSpace	Indicates the free disk space left in the current archive.
PerfTag_SpaceConsumptionRate	Specifies an archive disk space consumption rate in megabytes per day.
PerfTag_PredictedDaysToFull	Indicates the approximate number of days required for an archive to fill.
PerfTag_MemoryUsage	Specifies the amount of RAM used by the Data Archiver.
PerfTag_MemoryVMSize	Specifies the amount of virtual memory used by the Data Archiver.
PerfTag_TotalAlarms	Specifies the total number of alarms received by the Data Archiver since starting up.
PerfTag_AverageAlarmRate	Specifies the average alarm rate in alarms per minute received by Data Archiver.
PerfTag_TotalFailedAlarms	Specifies the total number of alarms since startup that failed to be written.
Perftag_ReadQueueSize	Specifies the total number of messages present in the Read queue.
Perftag_AverageReadRate	Specifies the total number of data samples per minute returned from the Data Archiver for all read requests.
Perftag_ReadQueuePushRate	Specifies the number of read requests per minute that came into the archiver from all clients. A read request can return multiple data samples.
Perftag_WriteQueuePushRate	Specifies the number of write requests per minute that came into the archiver from all clients. A write request can contain multiple data samples.

View Data Trends for Tags

Procedure

On the Tag Maintenance page, select a tag.
Right-select the tag and select Trend.
The trend for the selected tag displays.

Add a Performance Tag

Procedure

In the Tag Maintenance page, select the Tags link on the toolbar.
The Tag Maintenance page appears.
Select the Add Tag Manually link on the toolbar.
The Add Tag window appears.
Enter the performance tag name.
Select OK
The Tag Maintenance page displays with the specified tag properties.

Historian Collector Performance Counters

The following table provides information about collector-specific performance counters.

Note: Replace the placeholder value %CollectorName% with the actual name of the collector.

Table 5. Collector Performance Counters
Counter Name	Description
PerfTag_`%CollectorName%`_InterfaceStatus	Specifies the status of an interface.
PerfTag_`%CollectorName%`_InterfaceTotalEventsCollected	Specifies the total number of events collected by an interface.
PerfTag_`%CollectorName%`_InterfaceTotalEventsReported	Specifies the total number of events reported by an interface.
PerfTag_`%CollectorName%`_InterfaceOutOfOrderEvents	Specifies the total out of order events.
PerfTag_`%CollectorName%`_InterfaceAverageEventRate	Specifies the average event rate of an interface.
PerfTag_`%CollectorName%`_InterfaceMinimumEventRate	Specifies the minimum event rate of an interface.
PerfTag_`%CollectorName%`_InterfaceMaximumEventRate	Specifies the maximum event rate of an interface.
PerfTag_`%CollectorName%`_InterfaceOverruns	Specifies the interface overruns.
PerfTag_`%CollectorName%`_InterfaceCompression	Specifies the compression of an interface.
PerfTag_`%CollectorName%`_InterfaceOverrunsPercent	Specifies the number of overruns in relation to the total events collected since startup.

Historian Server Performance Counters

The Windows performance counters are exposed as objects with counters. In the tables below, you can see each counter and the object to which it belongs.

Each object has one or more instances as shown in the Windows Performance Monitor. Counters belong to a specific instance of an object. For example, there is an instance of the Historian Archive object for each IHA in the system.

There is also a LatestArchive instance for each data store. The LatestArchive instance lets you collect the information from the newest archive even as archives become full and new archives are created. The LatestArchive is the newest archive receiving data, not the prepared archive.

To monitor performance counters, you must add the performance counter tags manually.

Table 6. Historian Archive Object
Archive Counter	Description
Cache Priority	Relative priority of items from the archive stored to the Windows Cache. A higher priority means the item is more likely to stay in cache. Disk Read Time (usec) Duration of last disk read in microseconds.
Disk Read Time (usec)	Duration of last disk read in microseconds.
Disk Read Time Max (usec)	Maximum duration across all disk reads from the archive in microseconds.
Disk Reads	Number of disk reads from archive.
Disk Write Time (usec)	Time of last disk write in microseconds.
Disk Write Time Max (usec)	Maximum duration of all disk writes to the archive in microseconds.
Disk Writes	Number of disk writes to archive.
File Size (MB)	Size of the archive file in MB.
Read Calls	Number of read calls to the archive since startup.
Read Rate (Calls/min)	Number of read calls to the archive per minute.
Write Count	Number of data samples written to archive since startup.
Write Count Rate	Number of data samples written to archive per minute.
Writes Compressed	Number of data samples since startup that were compressed writes to the archive.
Writes Expensive	Number of data samples since startup that were expensive or slow.
Writes Failed	Number of data samples that were failed writes to the archive.
Writes OutofOrder	Number of data samples that were out of time order writes to the archive.

Table 7. Historian Cache Object
Counter	Description
Hit Percentage	Hit rate percentage (0-100) for successful data retrieval calls to the cache. Higher numbers represent more efficiency.
Hits	Number of hits in the cache since startup. To reset the count, restart the Archiver.
Misses	Number of misses in the cache.
Num Adds	Total number objects added to cache.
Num Deletes	Total number of objects deleted from cache.
Num High Prio Objs	Number high priority objects available for deletion.
Num Low Prio Objs	Number of low priority objects available for deletion.
Num Med Prio Objs	Number of medium priority objects available for deletion.
Obj Count	Number of objects in the cache.
Size (KB)	Size of cache in KB.

Table 8. Historian DataStores Object
Counter	Description
Compression Ratio (Max)	Archive compression ratio for this data store.
Compression Ratio (Max)	Maximum archive compression ratio for the data store.
Compression Ratio (Min)	Minimum archive compression ratio for the data store.
Messages (Total Alerts)	Total alerts since startup
Messages (Total)	Total messages since startup.
Read Calls	Number of read calls to the data store.
Read Rate (Calls/min)	Average read rate across all archives in the data store. (Read Calls/Minute)
Read Samp Rate (Samp/min)	Average read rate across all archives in the data store. (Samples/Minute)
Space (Consumption MB/day)	Disk space consumption rate. (MB/day)
Space (Days To Full)	Number of days until current archive is full.
Space (Free in MB)	Free disk space in the current archive.
Write Rate (Average)	Average event rate across all archives. (Samples/Minute)
Write Rate (Max)	Maximum event rate across all archives. (Samples/Minute)
Write Rate (Min)	Minimum event rate across all archives. (Samples/Minute)
Writes (Cache Hit Ratio)	Write Cache hit ratio.
Writes (Compressed)	Total number of compressed data samples since startup.
Writes (Total Failed)	Total failed data sample writes since startup.
Writes (Total OutOfOrder)	Total out of order data samples since startup.
Writes (Total)	Total data samples across all archives since startup.

Table 9. Historian Overview Object
Counter	Description
Compression Ratio (Average)	Average archive compression ratio of all data stores.
Compression Ratio (Max)	Average maximum compression ratio of all data stores.
Compression Ratio (Min)	Average minimum compression ratio of all data stores.
Memory Usage (KB)	Private bytes memory usage for Data Archiver.
Memory VM Size (KB)	Virtual Bytes memory usage for Data Archiver.
Messages (Total Alerts)	Sum of total alerts of all data stores since startup.
Messages (Total)	Sum of total messages of all data stores since startup.
Read Rate (Calls/min)	Sum of all average read rates of all data stores. (Samples/Minute)
Read Samp Rate (Samp/min)	Average read rate across all archives. (Samples/Minute)
Space (Consumption MB/day)	Sum of space consumption rate (MB/day) of all data stores.
Space (Days To Full)	Minimum number of days until current archive is full for all data stores.
Space (Free in MB)	Sum of all free space in the current archive of all data stores.
Write Rate (Average)	Sum of all average event rates of all data stores. (Samples/Minute)
Write Rate (Max)	Sum of all maximum event rates of all data stores.
Write Rate (Min)	Sum of all minimum event rates of all data stores.
Writes (Cache Hit Ratio)	Average write Cache hit ratio of all data stores.
Writes (Compressed)	Sum of total number of compressed data samples of all data stores.
Writes (Expensive)	Sum of total number of expensive writes data samples of all data stores. One of the reasons for expensive writes is out-of-order data.
Writes (Total Failed)	Sum of total failed data sample writes of all data stores.
Writes (Total OutOfOrder)	Sum of total out of order data samples of all data stores.
Writes (Total)	Sum of total data samples across all archives of all data stores.

Table 10. Historian Queue Object
Counter	Description
ClientQueues with Msgs	The number of client queues with messages current on them. A lower number means all clients are up to date. A higher number means that the archiver is not up to date with incoming network traffic
Count (Max)	Maximum number of messages on the queue. (memory and disk)
Count (Total)	Number of messages on the queue. (memory and disk)
Disk Buf Msg Reads	Number of messages read from the disk buffer file.
Disk Buf Msg Writes	Number of messages written to the disk buffer file.
Processed Count	Number of messages processed from the queue since startup.
Processed Rate (msg/min)	Recent rate at which messages have been processed for the queue.
Processing Time (Ave)	Average time in milliseconds to process a message.
Processing Time (Last)	Time in milliseconds to process the last message.
Processing Time (Max)	Maximum time in milliseconds to process a message.
Recv Count (msgs)	Number of messages received into the queue.
Recv Rate (msgs/min)	Recent rate at which messages have been received for the queue.
Size Kb (Mem&Disk Max)	Max size of messages in Kb on the queue. (memory and disk).
Size Kb (Mem&Disk)	Size of messages in Kb on the queue. (memory and disk)
Size Kb (Mem&Disk)	Size of messages in Kb on the queue. (memory only)
Threads	Number of worker threads allocated to process this queue. This is the number of created threads but they may be idle.
Threads Working	Number of queue processing worker threads currently processing messages.
Time in Queue (Ave)	Average time in milliseconds that a message was in the queue, waiting to be processed.
Time in Queue (Last)	Time in milliseconds that the last message was in the queue, waiting to be processed.
Time in Queue (Max)	Maximum time in milliseconds that a message was in the queue, waiting to be processed.

Table 11. Historian Config Counters
Counter	Description
File Size	The size of the Configuration File in MB
Hist Tags(Actual)	Number of the Historical tags in the system
Hist Tags (Licensed)	Total licensed Historian tags.
Hist Tags (Used)	Effective number of Historical Licensed Tags in the system. Can be greater than the number of tags because some tags count as more than one Licensed Tag.
Hist Tags (UsedByArrays)	Effective number of Historical Licensed Array Tags in the system (Not the raw tag count, the effective licensed count).
Hist Tags (UsedByUserDef)	Effective number of Historical Licensed User Defined Tags in the system (Not the raw tag count, the effective licensed count).
Number of Collectors	Number of collectors defined on the system.
Number of EnumSets	Number of enumerated sets defined on the system.
Number of UserDefTypes	Number of user defined types defined on the system.
SCADA Tags (Actual)	Number of SCADA Tags in the system.
SCADA Tags (Licensed)	Total Licensed SCADA tags.
SCADA Tags (Used)	Effective number of SCADA Licensed Tags in the system. Can be greater than the number of tags because some tags count as more than one Licensed Tag.
SCADA Tags (UsedByArrays)	Effective number of SCADA Licensed Array Tags in the system (Not the raw tag count, the effective licensed count).
SCADA Tags (UsedByUserDef)	Effective number of SCADA Licensed User Defined Tags in the system (Not the raw tag count, the effective licensed count).