I am using chap-links-library in the project I am working on. We are trying to show different kind of activities that a user performed. We want to display the activities and number of times that has been performed by the user.
The initial zoom will be for 12 months and the user can zoom in to day level. I want to group all activities of same type performed in a month and show the cumulative count on initial display. When user zooms in they should be able to see the split up of activities and its count based on the visible range.
Any pointers on how to handle this in chap-links-library will be useful.
You can listen for the rangechange or rangechanged events (see docs), and when the visible range exceeds a certain threshold, replace all data in the Timeline with more coarse grained data when above it, or with the detailed data when below the threshold.
You may want to have a look at the successor of chap-links-library, vis.js. You can find an overview of the main changes here: http://almende.github.io/chap-links-library/#successor.
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I'm continuously streaming the difference between two sensor values. I'd like to display the sum of those differences across a shift live while also logging the number at the end of the shift as well.
I've looked into tumbling windows but it seems I can't specify an actual time for those. I can specify the amount of time but not an actual time to start the window. If I could specify a time I could at least capture the historical values across shifts.
For the live data, I'd need to sum the data from start of tumbling window to the current data point, which to my knowledge is also not an option. Only the final aggregate is output after the window has ended.
I also took a look at using LAG() for this but that also does not allow specifying a timestamp and it would only allow comparing two values, not aggregate values.
Based on the documentation these are the two functions that are closest to having the functionality I need but neither accomplish the job.
Is there any way to aggregate all values from a certain start time to a current time (keep in mind the start time changes at the beginning of each shift)?
I need to keep a 28 day history for some dashboard data. Essentially I have an event/action that is recorded through our BI system. I want to count the number of events and the distinct users who do that event for the past 1 day, 7 days and 28 days. I also use grouping sets (cube) to get the fully segmented data by country/browser/platform etc.
The old way was to do this keeping a 28 day history per user, for all segments. So if a user accessed the site from mobile and desktop every day for all 28 days they would have 54 rows in the DB. This ends up being a large table and is time consuming even to calculate approx_distinct and not distinct. But the issue is that I also wish to calculate approx_percentiles.
So I started investigating the user of HyperLogLog https://prestodb.io/docs/current/functions/hyperloglog.html
This works great, its much more efficient storing the sketches daily rather than the entire list of unique users per day. As I am using approx_distinct the values are close enough and it works.
I then noticed a similar function for medians. Qdigest.
https://prestodb.io/docs/current/functions/qdigest.html
Unfortunately the documentation is not nearly as good on this page as it is on previous pages, so it took me a while to figure it out. This works great for calculating daily medians. But it does not work if I want to calculate the median actions per user over the longer time period. The examples in HyperLogLog demonstrate how to calculate approx_distinct users over a time period but the Qdigest docs do not give such an example.
The results that I get when I try something to the HLL example for date ranges with Qdigest I get results similar to 1 day results.
Because you're in need of medians that are aggregated (summed) across multiple days on a per user basis, you'll need to perform that aggregation prior to insertion into the qdigest in order for this to work for 7- and 28-day per-user counts. In other words, the units of the data need to be consistent, and if daily values are being inserted into qdigest, you can't use that qdigest for 7- or 28-day per-user counts of the events.
Consider an analytics where you need to find out repeat customers for a date range. Repeat customers are defined for date range as customers who use the service 3*(Given Date Range Interval) before the starting range and also used the service in given date range.
For example repeat customer for this week is all customers who used service 3 weeks before starting of this week and all such customers used it this week.
I am using influxdb. I haven't decided the series yet, I am looking for inputs into how I can define a series such that I can do available operations in influxdb to obtain this analytics.
Data available to me is the timestamp at which user used the facility, user_id , service_category, service_instance_id, and a json dump of further details about service.
may be my thought process is limited, I need some intervention on how to approach this and any input is welcome.
So I thought about this and came to a decent solution. I have to save the last time a user visited along with the entry. So at least one reference will be there for any time period if user is repeating for that time period.
This is similar to a linkedlist except that we have direct access to time based filtering of nodes.
How to Pass a Calculated Member/measure to a Drill-thru Target Report
In order to avoid using Calculated Members--because from googling some people were saying you could not pass them via Drill-thru--I went back to my FM model and created 3 new measures (High Risk, Low Risk and Medium Risk). Now these will show up in the drill-thru definitions parameter list . . . my only problem is that how can I do a check to see which of the three measures has been selected by a user?
Remember, I basically have a line chart with 3 lines, one for each measure above (High, Medium or Low Risk) by time frame. A user will select a data point, High risk for March or Medium Risk for Semester 2, for example. I then need to pass the value for that datapoint to my Target (2nd) report. How can I check for which of the three measure values they passed through?!?
I have several different store regions in a single table. Let's call them A, B, and C.
Right now, the master visualization shows the regions. When I drill down into a specific region, I can see all of the states within that region. The table that shows the states shows the unit percentage as out of 100%, but I want it to be out of the region's unit percentage.
Below is the region view and the current result I am gettting for the states view.
Current Result
I want to get the states view to look like this:
Desired Result
So esssentially, I want the units in a details visualization to automatically divide by the grand total of units in a master visualization in order to get a wholistic Unit % column.
Your details visualization will only contain data from the selection of your master visualization, therefore any calculations in your details visualization can only be based on this data.
However, you could store the value of all units, for all regions, into a property control Sum([Units])and reference it in your details visualization like Sum([Units]) / ${propControl} where here the units would only be for the selected region.