I am working on a system where 200,000+ records have been created in the past year and I need to plot their creation on a time series with various added filters. At this present, this requires performing lots of count queries (30 for each month plotted). How should these dates be stored for maximum speed?
One idea: store the most commonly-visualized data in a number of serialized fields containing counts for each day over the past month. Update each day with cron and serve up as necessary. (Where should these be stored - some new database table or a separate file accessible by Heroku cron?)
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I have been asked to model a star diagram.
I have 3 dimensions:
Date (day,month, year, week, quarter, ...)
place (500 distinct values)
Product (80k different products)
The main question is how many items (products) are stored at the end of a day in every place.
After some study-time with regards to dimensional modeling. I think I should implement a Periodic snapshot table. However reading trough the Kimball Docs, I noticed that a periodic snapshot demands an entry for every combination of the dimensions. This means I should add 40M rows every day (80k*500).
Knowing that the products are (real) slow movers and that many places store zero products during long periods, this sounds like an extreme overkill.
FYI the transactions in the source DB are 150k rows after three years.
So should I really add 40M rows every day, or could I just add the non-empty stores with their products specified? Also if for whatever reason one day all stores are empty, should I make an entry for that day (with dimensions N/A for store and product)?
You modeled correctly. It depends from the specifications, but normally you store only the products that are present in a location (you do not store zeroes), which could yield a number substantially lower than the maximum 80k.
If you want to further reduce your numbers, you could store the last N days and then start to move data in a "cold" table. You store (say) last 10 day snapshot, then only monthly snapshots in the main "hot" Fact Table.
Do not exclude the possibility to calculate the snapshot on the fly in report system, depending on your environment it could be easy (in MDX or DAX for example it is). Mixed solutions are also possible (i.e only the last month calculated on the fly).
We need to get the daily data from the "Microsoft.VSTS.Scheduling.CompletedWork"field (which is detailed in Workload, scheduling and time tracking field references). However I get data from the Analysis database and found that it only records one last new data,and can't get the historical data.
For example the task of ID 3356, who's "CompletedWork" is 3 hours in 2016/8/4, and I get the exact 3 hours-data from the Analysis database in the second day, 2016/8/5, as the pictures in this post show.
Then on the 2016/8/5, I update the "CompletedWork" from 3 hours to 4 hours and I get the exact 4 hours-data from the Analysis database in the second day, 2016/8/6. However the 3 hours-data of 2016/8/4 is lost. Well, How can I get the historical data of "Microsoft.VSTS.Scheduling.CompletedWork"?
First of all, it's important to understand that the CompletedWork is a cumulatieve data field. So when one user enters 3 and another enters 4, the total number of hours worked on the field is 4 not 7.
The warehouse has a granularity of a day and keeps that data int he cube, though the relational warehouse tables will store all the changes to the reportable fields on a per-revision bases. You can't easily query this data using the qube or Excel Power Pivot and they're lost in the Dim* and fact* tables, but you can write a SQL query against tfs_warehouse and iterate through the tables containing the workitem data (tbl_workitems[are|were|latest]). This is much slower and much harder to build unfortunately.
Your other alternative is to use the TFS Client Object Model and query the WorkItemStore object directly. You'll be able to query all work items of interest and iterate through them and their revisions. The API for workitems is relatively easy to use and is well documented.
If you're on TFS 2015 you can also use the new REST api to query workitem data and revisions.
I am writing a rails app that deals with product inventory. I would like to include the following features, and am struggling with developing an efficient algorithm:
View stock history (how many were in stock on each date)
Quantity removed from warehouse, and quantity added to warehouse over specific periods of time
Amount of time the product was out of stock in any given period
My questions are as follows:
What is the best way of tracking changes? In addition to my Products
table, should I create another table called
HistoricProductQuantities, and insert a new record each time there
is a change in the quantity?
What number should I track? The historic stock quantity (i.e. 50 in
stock on this day, 24 in stock on that day), or the CHANGE in stock
quantity i.e. -5 (5 sold) or 15 (15 added to inventory)? Or do I
track both in separate tables?
Thanks for your help.
First of all I recommend implementing Date Dimensions on your application, as it seems like you will be doing a lot of Time related calculations. Search on Google for date dimensions as it's beyond the scope of your questions. That said, I believe it will be of great benefit for your app to implement and use date dimensions.
As far as your direct questions go:
What is the best way of tracking changes? In addition to my Products table, should I create another table called HistoricProductQuantities, and insert a new record each time there is a change in the quantity?
Yes you could do this, I would probably call it HistoricProductSnapshot and keep track of the product activity in there on daily basis. With this information as well as time dimensions you could do calculations such as "how many of Product X Did we have 5 days ago or a month ago etc etc."
What number should I track? The historic stock quantity (i.e. 50 in stock on this day, 24 in stock on that day), or the CHANGE in stock quantity i.e. -5 (5 sold) or 15 (15 added to inventory)? Or do I track both in separate tables?
I do not have experience writing inventory control software but I believe with the Snapshot table I mentioned on the question above you would only have to keep track of quantities per day. The Change in product counts could then be calculated from your snapshot table. You could for example have a function that will output the product amount in a given time range as an array. Example: From March 1 to March 7 these were the stock amounts for Product Y [45,40,39,27,22,45,44].
Hope that helps. As I said I am not a product inventory guy but I have worked with Point of Sales Systems and the procedure above should give you a could enough start for what you are trying to do.
This gem could be usefull for tracking changes in models https://github.com/collectiveidea/audited
Keep the data raw. I would personally create a new data entry every day, displaying how much items you have in stock per day. Or you can make the interval much shorter, such as every 12 hours.
For our particular use case:
We had a table called Days, which had a many to many relationship with products, and each "relationship" will have a value called quantity (to keep track of quantity of product per day). Additionally per relationship, we had another value for the relationship with transactions (a one to many relationship) that has the entries for the time of transaction and remaining stocks.
I would personally advise you to use the quantity of stock as the raw data, as it will enable you to gather the data such as how much items were removed during a certain transaction, when the item was out of stock and when it became in stock, all through the data. When you have data in which you need to perform statistical calculations on, it's best to store this data as raw values (quantity of the item).
I am to store quite large amount of boolean values in database used by Rails application - it needs to store 60 boolean values in single record per day. What is best way to do this in Rails?
Queries that I will need to program or execute:
* CRUD
* summing up how many true values are for each day
* possibly (but not nessesarily) other reports like how often true is recorded in each of field
UPDATE: This is to store events that may or may not occur in 5 minute intervals between 9am and 1pm. If it occurs, then I need to set it to true, if not then false. Measurements are done manually and users will be reporting these information using checkboxes on the website. There might be small updates, but most of the time it's just one time entry and then queries as listed above.
UPDATE 2: 60 values per day is per one user, there will be between 1000-2000 users. If there isn't some library that helps with that, I will go for simplest approach and deal with it later if I will get issues with performance. Every day user reports events by checking desired checkboxes on the website, so there is normally a single data entry moment per day (or few if not done on daily basis).
This is dependent on a lot of different things. Do you need callbacks to run? Do you need AR objects instantiated? What is the frequency of these updates? Is it done frequently but not many at a time or rarely but a bunch at once? Could you represent these booleans as a mask instead? We definitely need more context.
Why do these need to be in a single record? Can't you use a 'days' table to tie them all together, then use a day_id column in your 'events' table?
Specify in the Day model that it 'has_many :events' and specify in the Event model file that it 'belongs_to :day'. Then you can find all the events for a day with just the id for the day.
For the third day record, you'd do this:
this_day = Day.find 3
Then you can you use 'this_day.events' to get all the events for that day.
You'll need to decide what you wish to use to identify each day so you query for a day's events using something that you understand. The id column I used above to find it probably won't work.
You could use the timestamp first moment of each day to do that, for example. Or you could rely upon the 'created_at' column of the table to be between the start and end of a day
And you'll want to be sure to thing about what time zone you are using and how this will be stored in the database.
And if your data will be stored close to midnight, daylight savings time could also be an issue. I find it best to use GMT to avoid that issue.
Good luck.
I'm developing a Rails application and I need to save and show some statistics based on the following conditions:
For the current month, display all entries in the database
For the last 8 months, display a cumulative of each month
For the rest, show a cumulative of all values
The thing is that I don't want to save all the data in my database and than apply the condition when showing. Is there a way of keeping my database structured in a way that it also covers the conditions (for example, when the current month changes, apply all the conditions and update the database)?