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Hi All,<div><br class="webkit-block-placeholder"></div><div>I'm an academic neuroscientist who is looking for an efficient way to store and retrieve recorded neuronal data for use in an intranet data browser app. After an initial read through the documentation and tutorials, RRD seems to be very close to what I had been thinking of with one exception, our data is recorded at 5-25KHz, so we need time steps of 50-200 nanoseconds. So I am wondering... has anyone modified RRD to work with smaller time steps? If not, I am curious about how much coding would be required to do this (i.e. how deeply embedded is the time structure currently used in the database)</div><div><br class="webkit-block-placeholder"></div><div>My alternatives would be to use a BLOB system in MySQL, or just use file references in a database and build a custom system to scan the binary data files and return the requested chunks. So I would also be curious if anyone has any opinions (performance, scalability, etc.) of different ways of building time series data browsers. </div><div><br class="webkit-block-placeholder"></div><div>By the way, our files are large - each experiment is recorded on 60 channels for 2 hours, which we break into consecutive 2 minute files(~ 70Mb for a 5Khz recording) for ease of use. I would ideally like to have an RRD for each 2 hour experiment, with each channel as one GAUGE DS containing 36-180M data points (in the native format theses are 2 byte unsigned integers). Are these sorts of numbers worrisome in terms of performance?</div><div><br class="webkit-block-placeholder"></div><div>Thanks,</div><div>Peter </div><div><br><div> <span class="Apple-style-span" style="border-collapse: separate; color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-align: auto; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-border-horizontal-spacing: 0px; -webkit-border-vertical-spacing: 0px; -webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0; "><span class="Apple-style-span" style="border-collapse: separate; border-spacing: 0px 0px; color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: normal; text-align: auto; -khtml-text-decorations-in-effect: none; text-indent: 0px; -apple-text-size-adjust: auto; text-transform: none; orphans: 2; white-space: normal; widows: 2; word-spacing: 0px; "><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px; "><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px; ">Peter Passaro</div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px; ">Research Officer</div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px; ">Dept of Informatics/Dept of Biology</div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px; ">Pevensey III</div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px; ">University of Sussex</div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px; ">Falmer, Brighton BN1 9QH, UK</div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px; ">Office + 44 (0)1273 877590</div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px; "><a href="mailto:P.A.Passaro@sussex.ac.uk">P.A.Passaro@sussex.ac.uk</a></div></div><br class="Apple-interchange-newline"></span></span> </div><br></div></body></html>