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    1. POProblems getting RabbitMQ and Django-Celery Running: Target Machine actively refused connection
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    1. POWhat is the most efficient way to store large arrays of floating point data in mysql for access through django?
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    2. POServing a dynamically generated MS Excel files using django and xlwt fails in Internet Explorer
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    3. POIs it good practice to consolidate small static tables in a database?
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    1. COthanks. those both sound like helpful suggestions. I will read the documentation on the celery site to see how to implement that. Can you elaborate on the ajax suggestion or point me to an example? Also do you think this problem will occur when multiple users are accessing the site simultaneously? Can I moderate the requests by multiple users in the same way?
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    2. CO(Start with the comment above) And thanks for directing me to Map Reduce. With a first glance at the data, the full resolution is not required, but if need be you could zoom in. The data will be plotted using flot. Either the Max or Average over a window or perhaps just every kth sample will be plotted. Finding the max or average might be very slow, so I wanted to get a sense of how fast queries are to see if this is possible or whether it would take too much time. Any idea if the data is stored in order? if returning results in order of timestamp instead of id can be done quickly?
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    3. COThanks Russel. We do want to store the data forever, that is one of the reasons mongodb is being considered, for its scalability. The sensors are relatively similar, some of them have different sample rates and are recorded by different machines. This means that there is a slight chance of misalignment in the timestamps. So the different sensors will probably be stored in separate collections. I am curious to know if mongodb naturally stores results in the order of being recorded? I am trying to get an idea of how snappy queries for particular time ranges will be once we have a lot of data.
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Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

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