My organization has acquired the HERE Navstreets data set. It wishes to update the content while still adhering to the HERE Navstreets data model and relationships.
In this context, it is deemed of value to:
Retain the LINK_ID column as the unique identifier for each street segment.
Make a distinction between the original HERE LINK_ID values and the one added by my organization.
Retain the ability to ingest streets updates from HERE should my organization decide to do so.
In this context, we would like to use a different range of LINK_ID values from the one used by HERE. As an example, if HERE uses values between 10,000,000 and 100,000,000, we would assign only LINK_ID values that are within the range 1,000-9,999,999 (this is only for illustration purposes).
Is this approach already accounted for by HERE for the street data they may get from Map Creator? Is there a specific HERE (for Review or Work in Progress) range of LINK_ID values we should consider?
Based on the HERE KB0015682: Permanent ID concept in HERE Data
Entities with Permanent IDs
Generally, the following feature do have permanent IDs in the HERE Map products:
Lane
Face
Point Features
Administrative Areas (for , Built-up Areas, Districts, and Administrative Areas)
Complex Features (this includes Complex Administrative Area Features as well as Complex Intersections and Complex Roads)
Permanent IDs are globally unique within a specific Object, e.g., a Link ID occurs once globally. However the same Permanent ID can be used among different Object types (e.g., Node, Link, condition, etc.). Note: When a map is upgraded to Intermediate or HERE map, or when a country undergoes administrative restructuring, there may be a change in Permanent IDs.
The following are examples of permanent IDs in the RDF:
Address Point ID
Admin Place ID
Association ID
Building ID
Carto ID
Complex Feature ID
Condition ID
Country ID (which is one of the Admin Place IDs)
Face ID
Feature Point ID
Lane ID
Lane Nav Strand ID
Link ID
Name ID (with some exceptions)
Nav Strand ID
Node ID
POI ID
Road Link ID
Sign ID
Zone ID
Numeric Range of Permanent IDs
Map object IDs (PVIDs) in the extracts use 32-bit integer values to fit in a N(10) scheme. Note: Exception to N(10) scheme can exist. For example, Lane ID is N(12) in length.
The entire range is divided as follows:
Range----------------------------Designation
0000000001 to 0016777215 -> Non-permanent IDs
0016777215 to 2147483647 -> Permanent IDs
The range dedicated to permanent IDs are used for any entity.
The range dedicated to non permanent IDs are used in rare situations where an update is made in a copy of the database instead of in the live database itself and this update results in a new ID. This new ID in the database copy would be in the non-permanent range. The update would also be applied into the live database and this update would receive a permanent ID available in the next scheduled release. A cross-reference is not provided between non-permanent IDs and the eventual permanent ID from the live database.
Related
I am building a small AR data mart for a client which is using Dynamics AX (2012). The data from the mart will feed into a Power BI report. I know almost nothing about AX.
There is a column in the dbo.CUSTTRANS table named DEFAULTDIMENSION. I was told, by the client, that this value can be used to retrieve a location description for the transaction row using the following query:
SELECT
T.DEFAULTDIMENSION
,T3.Name AS Location
FROM dbo.CUSTTRANS T
INNER JOIN dbo.DEFAULTDIMENSIONVIEW T2 ON T2.DEFAULTDIMENSION = T.DEFAULTDIMENSION
INNER JOIN dbo.DIMATTRIBUTEOMBUSINESSUNIT T3 ON T3.RECID = T2.ENTITYINSTANCE
WHERE T.DEFAULTDIMENSION = 5637168346
However, for some values of DEFAULTDIMENSION, like the one above, multiple rows are returned with different descriptions. Is my query incorrect? Or is their data bad? BTW, I would ask the client but the person who would know this won't available until next week.
I think the query is incorrect.
The field DefaultDimension in table CustTrans (as well as others) is used to store a reference to a set of financial dimension and their values (it's a rather complex data structure and logic, which is why I won't go into more detail, but Implementing the Account and Financial Dimensions Framework (White paper) might serve as starting point for more research).
It seems your client interprets the business unit financial dimension as "location" and wants you to report the value of that financial dimension. Note that the term "location" is usually associated with inventory dimensions in Dynamics AX, not financial dimensions.
By filtering T.DEFAULTDIMENSION = 5637168346, you are selecting all CustTrans records that share the exact same set of financial dimensions and values.
By joining to dbo.DimAttributeOMBusinessUnit, each financial dimension in that set is considered the business unit financial dimension.
For DefaultDimension values that reference a set of financial dimensions which only consists of the business unit dimension, the query would only return one (correct) value. But for DefaultDimension values that reference a set with multiple dimensions, the query interprets each dimension as business unit dimension, which produces incorrect results.
If my earlier assumption is correct that your client wants to report only values of the business unit dimension, you need to add an additional filter to the query. It would filter dbo.DefaultDimensionView.BackingEntityType to a value that would correspond with the table id of table dbo.DimAttributeOMBusinessUnit.
I'd like to add that AX already comes with a data mart for BI purposes and contains several BI cubes out of the box, including one for AR. Management Reporter is another solution that can be used to report on financial data and dimensions. A custom built data mart may not be the best fit here.
This is a bit of a weird one. I've got a dataset with thousands of rows. I can't share it. The headers include:
year
reporter ID
reporter name
building ID
building name
controller ID
controller name
latitude (for some)
longitude (for some)
other columns not used for identification
The buildings are my unit of analysis. However, there are problems.
First, the data was entered manually, so name things that should be constant change year to year (eg "Business Inc." and then "Business Incorporated"). And worse, the building ID changes when the controller or the reporter change (which happens when buildings get sold).
For example, in 2015 a building might be called "Big Building", have a building id of "1111" and have a controller called "Tiny Tim". Then in 2016 it is sold, now it appears as "The Big Building", the building id is "4567", and the controller is "Tiny Tim". It is the same building, but this dataset doesn't track that. This is my problem.
What I want: to create a new ID column that actually identifies buildings, and does not change across years or reporters or controllers. This ID could then be used in conjunction with year to lookup the reporter and controller (if desired).
But, I don't know how to do this. I figure there must be something that can look at 'building name' (noting it can have minor changes year on year) as well as the other supporting ID columns and estimate whether to assign a new ID in a new column, or if an ID has already been assigned to this building and then apply that one. Does that make sense?
Can someone please point me in the right direction to get started?
Imagine you have actions setup for when a user is from a certain demographic/market segment. The filters work a bit like a graph, matching for country, region, platform, operating system, and browser.
By default, you will match any value (if you specify US, you match for all users from the US regardless of region, platform, OS, or browser)
If you specify multiple values for any property of the filter it works like an OR (can be any of the values you specified), for the filter to match all the properties must have at least one match or be empty (accept all), essentially an AND operation.
So we can have:
Segment #1:
Countries: United States, Canada
Segment #2:
Countries: United States
Regions: New York
Platform: Tablets
Segment #3
Countries: United States
Browser: Chrome
Segment #4
Countries: United States
Segment #5
Match all (all filters left empty)
Scenario #1
User from Canada on his Tablet
Result: Segment #1
Scenario #2
User from New York, United States visits from Google Chrome on his Tablet.
Result: Segment #2, because the filter more specifically matches the user (matches country, region, and platform)
Scenario #3
User from Texas visits from his desktop
Result: Segment #4, tie with segment #1 is resolved because Segment #4 only matches United States and is therefore more specific
Work so far
I was thinking I could take each segment and load it up into a graph database that looks something like this
Country -> Region -> Platform --> OS -> Browser -> Segment
Each node either has a value (ex: United States, Chrome, Firefox, etc) and relationships that link it to any node below it in the tree (Country -> Browser is okay, Browser -> Country is not) or is null ("match all").
Each relationship (represented by ->) would also store a weight used to resolve ties. Relationships from a catch-all node get the max weight as they will always lose to a more specific filter.
Example database (numbers on the lines are the weight, lower weight becomes the prefered path)
Potential query
So now I need a query (maybe neo4j can do this?) that does the following:
Find the top level country node with the same value as the user or null
Go through each relationship (sorted by weight in ascending order)
Find the longest path, ties go to the node connected by a relationship with the lowest weight (if the tie is between a relationship to a null/catch-all node, the null node loses)
Continue this loop until we find a segment #
I'm sorry for the long post, it's hard to explain what I'm getting at via text.
What I'm looking for
Am I on the right path to solving this problem?
Are there better ways to go about this?
What would be the best way to store these relationships (graph database?)
How can I build a query that does what I want?
tl;dr: Need a way decent/performant way of finding the longest/most specific path in a graph like data structure. Comments requesting clarification or with any related information/documentation/projects/reading are very welcome
With Neo4j, you can store properties in a relationship, example:
(u1:User{name:"foo"})-[:FRIEND_WITH{since : "2015/01/01"}]->(u2:User{name:"bar"})
I think you should store country nodes this way:
(usa:Country{name: "USA", other attributes...})
So you can find every single country by matching with Country label, and then filter with the name property to get the one you're looking for.
Same for the cities, you can do a simple relationship to store every city :
(usa:Country{ name: "USA"})-[:CONTAINS_CITY]->(n:City{name: "New York", other attributes...})
and then you can add platform etc after the city.
To match a segment related to a certain country, you can do this way (example for Scenario #1) :
Match (c:Country{name : "Canada"})-[*1..2]->(p:Platform{name : "Tablet"})-[*1..]->(s:Segment) return s
Then you can create your segment by using nodes and create relations between them, the only problem may be on this case:
User1 has a Tablet in Canada
User2 has a Tablet in Canada using
Chrome
In this case, because of the depth match on the relationship ([*1..]) the User1 can be on the same segment as User2. The solution is to create intermediate nodes with default values, in case you don't have browser informations for example.
Hi all,
I have 3 tables in an access 2010 database:
Crew: CrewID; Name; Adres;...
Voyage: VoyageId; Voyage name; Departure harbour; Arrival harbour
Crewlist: CrewlistId, VoaygeId, CrewId, Rank
The VoaygeId and CrewId from the Crewlist table are linked (relation) to the autonumber ID's from tables 2 and 1.
My first and main question is: Upon boarding everyone has to ‘sign in’ selecting the voyage and there name, and assign them a roll (of to be donde by the responsible officer). How can I make a form that lets the users browse through the voyagenames and crewnames in stead of the ID’s uses in the ‘mother’ table (table 3: Crewlist)
2nd question: how can I make sure that someone isn’t enrolled twice for the same voyage (adding same voyagenumber and same crewId number in crewlist). This would preferably be blocked upon trying to add the same person a second time on a voyage.
To prevent duplicates in Crewlist, add a unique index to the table on both CrewId and VoyageId
It would be a good idea to add relationships and enforce referential integrity
You are now in a position to use the wizards to create a form based on Voyage and a subform based on CrewList with a combobox based on Crew
There are a number of refinements you could add.
Make sure you do not use reserved words like Name and do not put spaces in field names. You will thank yourself later.
See also create form to add records in multiple tables
I am working with the practice repository in preparation for doing upcoming work with a large enterprise client using BQ. The repository link is: google.com:analytics-bigquery:LondonCycleHelmet.ga_sessions_20130910
I have 3 questions to ask in relation to the sample repository & a query that was run (please see the bottom of the link for the query that motivated the question:
1) What is the difference between customDimensions.index, customDimensions.value and hits.customDimensions.index, hits.customDimensions.value?
2) If a single hit has multiple custom dimensions/metrics how is that returned/queried? I only see single dimensions matching at the hit level in the sample data.
3) There are no custom metric values passed in the example data, what will those values look like?
Here is the query that motivated the previous 3 questions:
SELECT hits.page.pagePath AS urls,
hits.time,
customDimensions.index,
customDimensions.value,
hits.customMetrics.index,
hits.customMetrics.value,
trafficSource.medium,
hits.customVariables.index,
hits.customVariables.customVarName,
hits.customVariables.customVarValue
FROM [google.com:analytics-bigquery:LondonCycleHelmet.ga_sessions_20130910]
Every record in that table represents one Google Analytics Session. Big Query has this concept of nested fields and that's how individual hits are defined. They are nested into the hits record.
Answering your questions:
1) customDimensions.index and customDimensions.value are the index and value for user or session scoped custom dimensions. hits.customDimensions.index and hits.customDimensions.value re custom Dimensions set at hit scope level. The scope is defined when you create the custom Dimension through GA interface. indexes are integers from 1 to 20 (as defined in the Admin section) and value is the string passed as the value for that custom Dimension. More info about Custom Dimensions/Metrics
2) Both rows and rows.customDimensions are REPEATED RECORDS in Big Query. So in essence every row in that BQ table looks like this:
|- date
|- (....)
+- hits
|- time
+- customDimensions
|- index
|- value
But when you query the data this should be FLATTEN by default. Because it's flatten if a single hit has multiple custom dimensions and metrics it should show multiple rows, one for each.
3) Should be the same as customDimensions but the values are INTEGER instead of STRINGS.
For a simpler and more educational dataset I suggest that you create a brand new BQ table and load the data provided on this developer document page.
PS: Tell my good friends at Cardinal Path that Eduardo said Hello!