d-time | repository contains D-TIME : Distributed Threadless | Dataset library

Updated formula:

=IF(VALUE(VLOOKUP($A2, Master!$A:$M, 13, 0)) > VALUE(VLOOKUP($A2, Master!$A:$M, 12, 0)), IF(ISBETWEEN(B$1, VALUE(VLOOKUP($A2, Master!$A:$M, 12, 0)), VALUE(VLOOKUP($A2, Master!$A:$M, 13, 0))), "Y", "N"), IF(OR(B$1 <= VALUE(VLOOKUP($A2, Master!$A:$M, 13, 0)), B$1 >= VALUE(VLOOKUP($A2, Master!$A:$M, 12, 0))), "Y", "N"))

Screenshot from the sheet you've shared with the formula working:

This version is an extension of the formula you shared. If someone is working from 4PM to 2AM then the way IFBETWEEN is being used will throw an error because 2AM is numerically less than 4PM and hence there is nothing in between.

So in cases where someone starts at a PM time and ends at AM time the formula checks for all slots between 12AM and the person working AM and marks them a Y. At the same time the formula also checks for all times in PM that are greater than the person working PM and marks them a Y as well.

If the person starts at a PM time and ends at a greater PM time then it uses your initial version of the formula.

I have made a slight modification to your formula and it should work now.

=IF($C9>$B9, IF(ISBETWEEN(B$1, VLOOKUP($A2, $A$8:$C, 2, 0), VLOOKUP($A2, $A$8:$C, 3, 0)), "Y", "N"), IF(OR(B$1 <= VLOOKUP($A2, $A$8:$C, 3, 0), B$1 >= VLOOKUP($A2, $A$8:$C, 2, 0)), "Y", "N"))

Please remember to remove the dates from some of the cells ex in your sheet the value in C2 is 12/31/1899 2:00:00 and it should be changed to just 2:00:00.

I am not sure what package you are using to convert into the required format, but if you are using 'moment.js' package, you can take a look at this website

Link to moment.js ==> https://momentjs.com/

What you want to do is something like this:

As of 6.0 you can simply append the CSVs to same table one by one given the table has designated timestamp and partitioned it will work.

If your CSVs are huge I think batching them in transactions with few million rows will be better than offloading billions at once.

Depending of how much data you have and your box memory you need to partition in a way that single partition fits memory several times. So you choose if you want daily or monthly partitions.

Once you decide with partitioning you can speed up the upload if you able to upload day by day batches (or month by month) from all CSVs.

You will not need to rebuild the table every time you add an instrument, table will be rewritten automatically partition by partition when you insert records out of order.

You can use dt.normalize() to get the dates without time and then use .loc to select the rows by filtering with a Timestamp with your selected date, as follows:

If you want to get only one particular date:

Or is wx unusable for now?

Yes, it's currently unmaintained, and the version bounds are more or less correct. The code on the GitHub repository is a bit more up to date than the code on Hackage, and compiles with a more recent GHC version, but still fails on the current one.

Unless you're willing to to bring wxHaskell up to date with the ecosystem (well, or to use an old GHC), you're probably better off trying another UI library.

you can do this by adding style="display:none" to the option you want to hide using nth-child, for example i did it to option 05 from your code by adding select option:nth-child(6){ display:none; } :

I was not able to manually set a bookmark or get a bookmark to manually progress and skip data using the methods in the question above.

However, I was able to get the Glue ETL job to skip data and progress its bookmark using the following steps:

1. Ensure any Glue ETL schedule is disabled

2. Add the files you'd like to skip to S3

3. Crawl S3 data

4. Comment out the processing steps of your Glue ETL job's Spark code. I just commented out all of the dynamic_frame steps after the initial dynamic frame creation, up until job.commit().

In your example you're using the type LocalDateTime. LocalDateTime can't be formatted with timezone pattern as it doesn't contains any timezone information...

Switch to ZonedDateTime will solve your problem.

The whole point of having a static build is to have all the generated files with no additional server Node.js server needed. It reduces heavily the costs, removes a point of failure, discard any notion of server charge (amount of users at the same time on your app) and probably some other advantages yeah.

Downside, you indeed need to actually yarn generate the whole app again if it's something that was added/changed in the codebase. Usually it's pretty fast and there are also incremental builds if I do remember properly (you will not regenerate all the 99 old blog posts but only the 100th, the new one).

Headless CMS like Strapi usually work with a webhook: you add a new CMS article or alike, Strapi will notify your JAMstack platform to rebuild your app. Even if no front-end code was changed, you can force to build it with the new data coming from the headless CMS' API.