Echelon SmartServer 2.2 - Manual (Page 411)

412 Scheduling
Data Logging Overview
The SmartServer contains a Data Logger application that you can use to record data point values and
store them to a log file. To use a data logger, you select the type of log file to store the data point
values (historical or cyclical), select the data points to be tracked, and then select the method used to
record data point values (polling and/or event-driven updates). You can also have the data logger
trigger an alarm when the log file is becoming full. You can view log entries using the Data Logger:
View Web page. You can also view, chart, and update data points using the View – Data Points Web
page.
You store data point values in a historical or circular log. A historical log stops recording data point
updates when the log file is full. A circular log file removes the records for older updates when new
updates occur and the log file is full. You can save the historical and circular logs to an ASCII text
(.csv) or binary (.bin) file. In addition, you can save a historical log as a compressed ASCII text
(.csv.gz) file. Saving a historical log to a .csv.gz file reduces the size of the log to approximately half
of that of the .csv file. To view a log in a compressed ASCII text file, you just extract the .csv file
from the .csv.gz file. By default, the log file is stored in the /data/Net/LON/i.LON App (Internal)
folder, and it is named Data Logger [x], where x is the index number of the Data Logger functional
block. You can remove data from a log file by specifying a percentage of the log file to be cleared,
sending an update to the clear point on the data logger (nviDlClear[x] data point, where x is the index
number of the data logger).
For each data point you are tracking, you can select whether the data logger uses polling and/or
event-driven updates to record its value. With event-driven updates, the data point is only recorded
when its value is updated. You can filter event-driven updates by specifying a minimum period of
time that must elapse between log entries and the minimum change in value required between log
entries to record the data point. With polling, the data point value is recorded at a specified rate,
regardless of any event-driven filters that you may have set.
You can also have the data logger trigger an alarm when the log file is becoming full. To do this, you
specify a limit for the log file that, when reached, causes the data logger to trigger an alarm. You can
have an Alarm Notifier monitor the alarm data point and send a notification when the data point
receives an alarm condition. This is particularly useful if you are using a historical log file because it
becomes disabled once it is full.
You can have the SmartServer automatically transfer data log files (binary or CSV format) to a remote
server and extract the selected data to a CSV or XML file. You can view and chart log entries using
the Data Logger: View Web page. You can access the data in a log by manually opening the log file
or by using a SOAP function. You can also monitor, chart, and control data point using the View –
Data Points Web page.
You can create up to 10 Data Loggers per SmartServer if you are using the default SmartServer v12
static interface. You can add more than 10 Data Loggers if you activate the v40 dynamic interface,
which features a dynamic external interface, on your SmartServer. See Activating the SmartServer
V40 XIF in Chapter 3, Configuring and Managing the SmartServer, for more information on loading
the V40 interface on the SmartServer.
Creating a Data Logger
To create a Data Logger, do the following:
1. Open a Data Logger application.
2. Select and configure a log file.
3. Select and configure the data points to be logged.
4. Set the alarm limit.