My organisation is facing issues with running out of slots allocated Monday morning running GCP queries and we suspect this is partially due to the number of autofresh connected sheets that have been set and forgotten. We may need to ask Google to get a list of all the autofresh queries and the creators, but before we get to that, is there a way for users to check themselves first ?(Personally I have got a few queries set up as autofresh last year but now I can't remember what they are, let alone cancelling them. )
Thanks in advance.
Related
I've been trying to do this for a while but can't find a solution. At work there is a special task that needs to be done daily by different people, on rotating shifts. I am trying to create a simple file in sheets in which you can go and clearly see who should be doing that tasks that day.
The data comes from a schedule that is located within the same file. Every day different people are supposed to do these tasks
So what I am trying to do is basically a formula (s) that will recognize what day is today and present it so everyone knows who is supposed to do those tasks today. This should update itself everyday, taking the data from the database. So if today is Friday 20/08/2022 it will show whatever is on the database for that date. If today is Saturday 21/08/2022 it will update and reflect what the schedule/database has.
Sounds pretty easy but I dont know where to start.
Thanks for your help!
try:
=FILTER(C:G; A:A=TODAY())
I have a topic derived from a MySQL users table and now want to create a table in ksqldb that always contains all users registered within the last 50 days. After spending some time in the docs I still can't find a solution for this. Windowing doesn't seem to work because it only applies to stream-stream joins as far as I can see. Is this sort of thing even possible using purely ksql, or do I need to look for other solutions?
Thanks!
I don't think this is currently possible with ksqlDB. This because a filter, such as WHERE DATEDIFF('days', user.registerDate, now()) < 50 would only be evaluated at the time the source row was received.
This isn't too different to standard SQL dbs, where a materialized view built with a similar filter would also not update automagically as time advanced.
You could likely build a system using Kafka Streams that could use punctuation to evict old entries.
Some enhancement requests on ksqlDB may also be of use:
Table over topic with time based retention
View updates
I would like to sync my db (tasks on my db, that have a decription, a date, a start time and an end time, and a user) with Google calendar.
For sync with google i plan to use these components (of course I could somehow write the whole stuff on my own but this is something I can plan for the future now I am short of time, or in alternative can you suggest some working code that connects to google calendar to send/recieve data?).
Now my main problem is not really linked to Delphi programming anyway I must ask a Delphi related questions because other questions get unviewd (like this one i asked).
So I wonder how to do the sync. Note: I do one way sync and the generated calendar will be a read only calendar.
I can set a max number in the past and future to be synced (like 10 days in past and 100 in the future for example). Then the idea I have is this:
as I start the sync app I comletely read the google calendar itmes in the range, I compare one by one with what I have in db and then I "merge" changes. Then on timer I check for differences in my db and i upload changes.
But I am not sure that these is the best solution.
A simplification of the real case is this: imagine it is a CRM with some task assigend to every user. Since beyond every task there is a logic i want to managea that logic only in my application, but the idea of pulishing the calendar to google is that it is then easily available from any mobile device. This is way there is a one way sync. Ic ould also let the calendar not be readonly anyway at every sync I wil "download" the newly inserted tasks but I will ignore the deleted ones and the edited ones. In this second case it is not enough to track changes in db, but I shuold also track changes on google, at least to "intercept" the newly added tasks.
I am aware this is gerneic question but I would like to trigger an answer that can be useful, etiher redirecting me to a sync algorithm or to Delphi sample code or anything that can help me progress on this issue. Thanks.
Google: "calendar sync algorithms"
https://wiki.mozilla.org/Calendar:Syncing_Algorithm
http://today.java.net/pub/a/today/2007/01/16/synchronizing-web-client-database.html
Synchronisation algorithms
The last one actually is funny because it leads right back to StackOverflow ;) Point is: I think there is no need to reinvent the wheel. Ps: The first link contains some useful thoughts similar to yours.
I am trying to retrieve a list of opened work items for a given project programmatically. In searching through the web, the only way that I can see to do this is to use the WorkItemStore API and execute a query.
The major issue that I am having is that retrieving the workitemstore takes almost 2 minutes. I subsequently caches it, but the first hit is unacceptable. Beyond that, my application needs to refresh it every x number of minutes in case new work items are added.
Is there any way to get a list of opened work items associated with a project without using the WorkItemStore. I only need the work item number and optionally the title. I don't need any other information.
If not, is there something that I am doing wrong or something wrong with the TFS server (index missing perhaps) that makes the performance so slow. I have tried different ways of getting it by the way. They are all extremely slow.
WorkItemStore store = (WorkItemStore)tfs.GetService(typeof(WorkItemStore));
or
workItemStore = new WorkItemStore(tfsTeamProjectCollection);
or
workItemStore = new WorkItemStore(tfsServerName);
Any help in this matter would be greatly appreciated.
Even with an incredibly large DB you shouldn't experience two minutes delays.
I would load up SQL Profiler and take a look at the query generated to get work items. From there, you can probably identify what part of the query is causing the delay.
You can also consider running the query on the same box that the TFS DBs are on and see if that is the issue. As the comment above points out, remote connections can certainly cause delays.
If none of this resolves the issue then hopefully you can provide some more information like size of the project (shouldn't matter), TFS installation configuration (where are your servers and how are they setup) and what hardware it is on.
I have a site with several pages for each company and I want to show how their page is performing in terms of number of people coming to this profile.
We have already made sure that bots are excluded.
Currently, we are recording each hit in a DB with either insert (for the first request in a day to a profile) or update (for the following requests in a day to a profile). But, given that requests have gone from few thousands per days to tens of thousands per day, these inserts/updates are causing major performance issues.
Assuming no JS solution, what will be the best way to handle this?
I am using Ruby on Rails, MySQL, Memcache, Apache, HaProxy for running overall show.
Any help will be much appreciated.
Thx
http://www.scribd.com/doc/49575/Scaling-Rails-Presentation-From-Scribd-Launch
you should start reading from slide 17.
i think the performance isnt a problem, if it's possible to build solution like this for website as big as scribd.
Here are 4 ways to address this, from easy estimates to complex and accurate:
Track only a percentage (10% or 1%) of users, then multiply to get an estimate of the count.
After the first 50 counts for a given page, start updating the count 1/13th of the time by a count of 13. This helps if it's a few page doing many counts while keeping small counts accurate. (use 13 as it's hard to notice that the incr isn't 1).
Save exact counts in a cache layer like memcache or local server memory and save them all to disk when they hit 10 counts or have been in the cache for a certain amount of time.
Build a separate counting layer that 1) always has the current count available in memory, 2) persists the count to it's own tables/database, 3) has calls that adjust both places