Reading rrd files

Installing RRDtool from your Linux package manager will usually also install this library. Once you have the system requirements in place, you can install the development version of the R package from GitHub using:. The package itself contains some built-in RRD files, so you should be able to run the following code directly. This function reports information about the names of each archive RRA file, the consolidation function, and the number of observations:.

To read an entire RRD file, i. This returns a list of tibble objects:. Since the resulting object is a list of tibble objects, you can easily use R functions to work with an individual archive:.

For example, the CPU metrics contains a time stamp and metrics for average user and sys usage, as well as the nice value, idle time, interrupt requests and soft interrupt requests :. Since the data is in tibble format, you can easily extract specific data, e. The underlying code in the rrd package is written in C, and is therefore blazingly fast. Reading an entire RRD file takes a fraction of a second, but sometimes you may want to extract a specific RRA archive immediately.

To use this function, you must specify several arguments that define the specific data to retrieve. This includes the consolidation function e. For example, you can easily plot these data using your favourite packages, like ggplot2 :. For more information on rrdtool and the rrd format please refer to the official rrdtool documentation and tutorials. You can also read a more in-depth description of the package in an R Views blog post Reading and analysing log files in the RRD database format.

Installation System requirements In order to build the package from source you need librrd. Load the package and assign the location of the cpu This function reports information about the names of each archive RRA file, the consolidation function, and the number of observations:.

To read an entire RRD file, i. This returns a list of tibble objects:. Since the resulting object is a list of tibble objects, you can easily use R functions to work with an individual archive:. For example, the CPU metrics contains a time stamp and metrics for average user and sys usage, as well as the nice value, idle time, interrupt requests and soft interrupt requests :.

Since the data is in tibble format, you can easily extract specific data, e. The underlying code in the rrd package is written in C, and is therefore blazingly fast. Reading an entire RRD file takes a fraction of a second, but sometimes you may want to extract a specific RRA archive immediately. To use this function, you must specify several arguments that define the specific data to retrieve. This includes the consolidation function e. For example, you can easily plot these data using your favourite packages, like ggplot2 :.

In fact, these metrics are used to power the administration dashboard of these products. I hope this can be done using rrdtool fetch. Any advice appreciate. Hi Tobi Oetiker, I use 'rrdtool fetch xxx. But I cannot file any similarities if I compare it with the data of log file the graphs are same. Please help! I cannot understand a single word of what your are trying to explain.

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