I'm new to Neo4j so maybe I'm just completely wrong on this, but I'll give it a try!
Our data is mostly composed by reservations, users and facilities stored as nodes.
I need both to count the total reservations that occurred in a specific time frame and the overall income (stored as reservation.income) in this timeframe.
I was thinking to overcome the problem by creating the date as a node, in this way I can assign a relationship [:PURCHASED_ON] to all the reservations that occurred on a specific date.
As far as I've understood, creating the date as a node could give me a few pros:
I could split the date from dd/mm/yyyy and store them as integer properties, in this way I could use mathematical operators such as > and <
I could create a label for the node representing each month as a word
It should be easier to sum() the income on a day or a month
Basicly, I was thinking about doing something like this
CREATE (d:Day {name:01/11/2016 day: TOINT(01), month: TOINT(11), year: TOINT(2016)}
I have seen that a possible solution could be to create a node for every year, every month (1-12) and every day (1-31), but I think that would just complicate terribly the architecture of my Graph since every reservation has an "insert_date" (the day it's created) and then the official "reservation_date" (the day it's due).
Am I onto something here or is it just a waste of time? Thanks!
You may want to look at the GraphAware TimeTree library, as date handling is a complex thing, and this seems to be the logical conclusion of the direction you're going. The TimeTree also has support for finding events attached to your time tree between date ranges, at which point you can perform further operations (counting, summing of income, etc).
There are many date/time functions in the APOC plugin that you should take a look at.
As an example, you can use apoc.date.fields (incorrectly called by the obsolete name apoc.date.fieldsFormatted in the APOC doc) to get the year, month, day to put in your node:
WITH '01/11/2016' AS d
WITH apoc.date.fields(d, 'MM/dd/yyyy') AS f
CREATE (d:Day {name: d, day: f.days, month: f.month, year: f.years});
NOTE: The properties in the returned map have names that are oddly plural. I have submitted an issue requesting that the names be made singluar.
Related
Good day all,
I am trying to filter todays result in SQL table to a collection in powerapps. The column "dt" represents the column in sql of datetime type.
This is my powerapps filter:
ClearCollect(myCollectionName, Filter(myDatasource, Text(dt,"dd/mm/yyyy") = Text(Now(),"dd/mm/yyyy" )));
Seems like the collection is still empty even there is data for today in sql. May I know if my approach is the correct way in filtering?
Short answer: the data is likely being changed based on the client time zone. To fix it, you can update it by applying the time zone offset to the data from the SQL table, something along the lines of:
ClearCollect(
myCollectionName,
Filter(
myDatasource,
Text(DateAdd(dt, TimeZoneOffset(dt), Minutes), "dd/mm/yyyy") =
Text(Now(), "dd/mm/yyyy")))
Long(er) answer: the datetime type in SQL Server represents an absolute value of date and time. For example, the value '2021-12-23 09:30:00' represents 9:30 in the morning of the 23rd day of December, 2021 - at any part of the world. The date/time type in Power Apps, however, represents a point in time, typically referring to the local time where the app is being executed (or created). For example, if I selected that value and I'm in the US Pacific Time Zone (UTC-08:00), that would represent the same value as if someone in London (UTC+00:00) selected 2021-12-23 17:30:00. Since the two types represent different concepts, we may have mismatches like you are facing. To fix this, we can either use a type in SQL Server that has the same semantics as Power Apps (for example, 'datetimeoffset'), or adjust the time when it is being transferred between SQL and Power Apps.
The blog post at https://powerapps.microsoft.com/en-us/blog/working-with-datetime-values-in-sql explains in more details how to work with date/time values in SQL and Power Apps.
I'm new of MDX and I'm trying to calculate a new measure based on two different date dimensions.
I have the Creation Date Dimension (with Year, Trimester, Month, Day) and Resolution Date (with Year, Trimester, Month, Day).As measure I have the number of tickets and I want to calculate two new measures in order to know how many tickets that were resolved this month were actually created last month and how many tickets were resolved in the same month as they were created.
I found this interesting post, but I cannot understand how to use properties..
https://bennyaustin.com/2012/06/05/ssas-mdx-calculated-measures-that-require-date-comparison/
Any ideas or suggests?
Thanks for your help.
This question cannot be answered as asked without knowing the exact definition of your time dimensions.
An approach which might be worth considering if your MDX knowledge is little, but you have some SQL knowledge and if your requirements can be fixed to just the month level as you described, could be the following, which does the main calculations already when loading the cube, and not at query time in MDX:
Add a column 'months_from_creation_to_resolution' to your fact table, possibly just add this as a column in the view you may already use on the fact table. This column would be 0 if the ticket was resolved in the same month where it was created, 1 if it was resolved in the month after creation, 2 if it was resolved e. g. in May and created in March, etc. You do this calculation using SQL date functions. You would then create a new dimension in your cube from this table, which would have the new column as the only attribute. SSAS has no problem using a table as base for both a measure group and a dimension.
Then, in MDX, the number of tickets resolved in the month they were created would just be
([Measures].[TicketCount], [Fact].[months from creation to resolution].[0])
and those resolved in the month after creation would be
([Measures].[TicketCount], [Fact].[months from creation to resolution].[1])
As a side effect, the query run time would be faster, as the main logic is pre-calculated when loading the cube.
I need to create an attendence list showing days in rows and employee names in colums. The list will always cover one full month chosen in parameters.
How can I create a recordset of days of chosen month? I've done it in command section but, due to ERP system limitations, it must done otherways.
Thank you,
Przemek
A good approach is to create a Calendar table (aka Date Dimension in data warehousing lingo). It makes it easy to show days without any attendance. If you don't need that aspect, you can simply create a formula that returns the attendance date month's day, and Group on that formula. The Day() function gets you the day of month. For example,
Day ({Orders.Order Date})
If you search 'creating a data dimension or calendar table' you'll find many helpful sources such as this one: https://www.mssqltips.com/sqlservertip/4054/creating-a-date-dimension-or-calendar-table-in-sql-server/
For your case, I agree with the comments in that post about using date instead of integer as the primary key. Integer PK makes more sense for true data warehousing scenarios as opposed to legacy databases.
Let's say I have a date dimension and from my business requirements I know that the most granular I would need to go is to examine the specific day of the month that an event occurred.
The data I am given provides me with the exact time that an event occurred (YYYY-MM-DD HH:MM:SS). I have two opitons:
Before loading the data into the date dimension, slice the HH:MM:SS from the date.
Create the time attributes in my date dimension and insert the full date time.
The way I see it, I should go with the option 1. This would remove redundant data and save some space. However, if I go with option 2, should the business requirements ever change or if my manager suddenly wants to be more granular I wouldn't need to modify my original design. Which option is more commonly used? Are there more options that I did not consider?
Update - follow up question
I receive new data every month. If I used a pre built date dimension with all the dates would I then need to run my script every month to populate the table with new dates of that month or would I have a continuous process where by every day insert into the table one row, which would be that date?
I would agree with you and avoid option 2. A standard date dimension table is at the individual date level. If you did need to analyse by time of day, you could create an additional time of day dimension at the level of a second in a single day, and link to that from your fact table.
Your date dimension should be created by script automatically, rather than from the dates that events occurred. This allows you to analyse across a range of events from other facts, and on dates where no events occur, using a standard, prebuilt dimension.
I would also include the full date/time stamp as a column in the fact table, along with the 'DateKey' to the dimension table. This would allow you some visibility/analysis of the timestamp, you would not lose the data, and would still allow you to analyse by the date dimension.
Update - follow up question
Your pre-built date dimension (the standard way of doing it) would usually contain some dates in the future. There's no reason not to, for example, include another 5 years of dates in the table. But if you'd like it to gradually grow over time, you could have a script that is run once a day, once a month, or once a year to add new dates. Its totally up to you! There are many example scripts for building date dimensions- just google date dimension script. They exist for the language of your choice, e.g. SQL, C#, Power Query, etc.
I'm an historian of medieval history and I'm trying to code networks between kings, dukes, popes etc. over a period of time of about 50 years (from 1220 to 1270) in medieval Germany. As I'm not a specialist for graph-databases I'm looking for a possibility to handle dates and date-ranges.
Are there any possibilities to handle over a date-range to an edge so that the edges, which represents a relationship, disappears after e.g. 3 years?
Are there any possibility to ask for relationships who have their date-tag in a date-range?
The common way to deal with dates in Neo4j is storing them either as a string representation or as millis since epoch (aka msec passed since Jan 01 1970).
The first approach makes the graph more easily readable the latter allows you to do math e.g. calculate deltas.
In your case I'd store two properties called validFrom and validTo on the relationships. You queries need to make sure you're looking for the correct time interval.
E.g. to find the king(s) in charge of France from Jan 01 1220 to Dec 31st 1221 you do:
MATCH (c:Country{name:'France'})-[r:HAS_KING]->(king)
WHERE r.validFrom >= -23667123600000 and r.validTo <=-23604051600000
RETURN king, r.validFrom, r.validTo
addendum
Since Neo4j 3.0 there's the APOC library which provides couple of functions for converting timestamps to/from human readable date strings.
You can also store the dates in their number representation in the following format: YYYYMMDD
In your case 12200101 would be Jan 1st 1220 and 12701231 would be Dec 31st 1270.
It's a useful and readable format and you can perform range searches like:
MATCH (h:HistoricEvent)
WHERE h.date >= 12200101 AND h.date < 12701231
RETURN h
It would also let you order by dates, if you need to.
As of Neo4J 3.4, the system handles duration and dates, see the official documentation. See more examples here.
An example related to the original question: Retrieve the historical events that happened in the last 30 days from now :
WITH duration({days: 30}) AS duration
MATCH (h:HistoricEvent)
WHERE date() - duration < date(h.date)
RETURN h
Another option for dates that keeps the number of nodes/properties you create fairly low is a linked list years (earliest year of interest - latest year), one of months (1-12), and one of dates in a month (1-31). Then every "event" in your graph can be connected to a year, month, and day. This way you don't have to create a new node for every new combination of a year month and day. You just have a single set of months, one of days, and one year. I scale the numbers to make manipulating them easier like so
Years are yyyy*10000
Months are mm*100
Date are dd
so if you run a query such as
match (event)-[:happened]->(t:time)
with event,sum(t.num) as date
return event.name,date
order by date
You will get a list of all events in chronological order with dates like Janurary 17th, 1904 appearing as 19040117 (yyyymmdd format)
Further, since these are linked lists where, for example,
...-(t0:time {num:19040000})-[:precedes]->(t1:time {num:19050000})-...
ordering is built into the nodes too.
This is, so far, how I have liked to do my event dating