I am generating a table on OSRM, but, in order to help in my route decision I would like to know how many crossroads I have between each point, and if possible what kind of crossroad if it is residential x secondary, tertiary x primary, etc...
Someone had already customized it in order to get this kind of information on osrm_backend, or got any kind of information during process_turn?
Related
I'm facing a bottleneck.
I have a set of pairs (source, destination) for which I need to calculate the durations.
Currently I'm passing all my sources, and all my destinations to the Table Service, which returns a full matrix for all (source, destination) pairs.
But this is way too many pairs compared to what I really need.
Is there a way to solve this better with OSRM?
I know it's possible to send one request per pair but I think this is not going to be fast enough for my use.
I saw that in the General Options there is a radiuses parameter to limit the search, but I'm not sure how to use this with the Table Service.
Any idea or guidance appreciated!
Thanks for this awesome project and any help you could bring!
I am using RdeHat Decision Maker 7.1 (Drools) to create a rule for assigning a case to a department. The rule itself is quite simple, however it requires quite a lot of parameters (~12) like the agent type, working area, case type, customer seniority and more. The result "action" is the department to which the case is assigned.
I tried to place the parameters in a decision table , but the table quickly bloated to over 15,000 rows and will probably get even larger then that. I did, however, notices that in many cases the different between two rows is 1 or two parameters (e.g. same row with the only different is agent type "Local" vs. "Regional") resulting in different assignment.
I am thinking of replacing the table with something else, like a tree structure, so I can group similar rows under the same node and then navigate over the tree to make the decision. To do this I plan to prioritize the parameters and give parameters with higher priority a higher place in the tree.
Does anyone has experience with such a problem ? I looked at decision trees but they focus more on ML and probabilities, so I'm not sure this is what I need.
Is there any other method to deal with bloated tables that become unmanageable ? I cannot go to our customer and ask them to maintain a 15,000 rows excel. They'll shoot me there and then.
Thanks
Alon.
I have a unique problem and I'm not aware of any algorithm that can help me. Maybe someone on here does.
I have a dataset compiled from many different sources (teams). One field in particular is called "type". Here are some example values for type:
aple, apples, appls, ornge, fruits, orange, orange z, pear,
cauliflower, colifower, brocli, brocoli, leeks, veg, vegetables.
What I would like to be able to do is to group them together into e.g. fruits, vegetables, etc.
Put another way I have multiple spellings of various permutations of a parent level variable (fruits or vegetables in this example) and I need to be able to group them as best I can.
The only other potentially relevant feature of the data is the team that entered it, assuming some consistency in the way each team enters their data.
So, I have several million records of multiple spellings and short spellings (e.g. apple, appls) and I want to group them together in some way. In this example by fruits and vegetables.
Clustering would be challenging since each entry is most often 1 or two words, making it tricky to calculate a distance between terms.
Short of creating a massive lookup table created by a human (not likely with millions of rows), is there any approach I can take with this problem?
You will need to first solve the spelling problem, unless you have Google scale data that could allow you to learn fixing spelling with Google scale statistics.
Then you will still have the problem that "Apple" could be a fruit or a computer. Apple and "Granny Smith" will be completely different. You best guess at this second stage is something like word2vec trained on massive data. Then you get high dimensional word vectors, and can finally try to solve the clustering challenge, if you ever get that far with decent results. Good luck.
We were looking for the most suitable database for our innovative “collaboration application”. Sorry, we don’t know how to name it in a way generally understood. In fact, highly complicated relationships among tenants, roles, users, tasks and bills need to be handled effectively.
After reading 5 DBs(Postgrel, Mongo, Couch, Arango and Neo4J), when the words “… relationships among things are more important than things themselves” came to my eyes, I made up my mind to dig into OrientDB. Both the design philosophy and innovative features of OrientDB (multi-models, cluster, OO,native graph, full graph API, SQL-like, LiveQuery, multi-masters, auditing, simple RID and version number ...) keep intensifying my enthusiasm.
OrientDB enlightens me to re-think and try to model from a totally different viewpoint!
We are now designing the data structure based on OrientDB. However, there are some questions puzzling me.
LINK vs. EDGE
Take a case that a CLIENT may place thousands of ORDERs, how to choose between LINKs and EDGEs to store the relationships? I prefer EDGEs, but they seem like to store thousands of RIDs of ORDERs in the CLIENT record.
Embedded records’ Security
Can an embedded record be authorized independently from it’s container record?
Record-level Security
How does activating Record-level Security affect the query performance?
Hope I express clearly. Any words will be truly appreciated.
LINK vs EDGE
If you don't have properties on your arch you can use a link, instead if you have it use edges. You really need edges if you need to traverse the relationship in both directions, while using the linklist you can only in one direction (just like a hyperlink on the web), without the overhead of edges. Edges are the right choice if you need to walk thru a graph.Edges require more storage space than a linklist. Another difference between them it's the fact that if you have two vertices linked each other through a link A --> (link) B if you delete B, the link doesn't disappear it will remain but without pointing something. It is designed this way because when you delete a document, finding all the other documents that link to it would mean doing a full scan of the database, that typically takes ages to complete. The Graph API, with bi-directional links, is specifically designed to resolve this problem, so in general we suggest customers to use that, or to be careful and manage link consistency at application level.
RECORD - LEVEL SECURITY
Using 1 Million vertex and an admin user called Luke, doing a query like: select from where title = ? with an NOT_UNIQUE_HASH_INDEX the execution time it has been 0.027 sec.
OrientDB has the concept of users and roles, as well as Record Level Security. It also supports token based authentication, so it's possible to use OrientDB as your primary means of authorizing/authenticating users.
EMBEDDED RECORD'S SECURITY
I've made this example for trying to answer to your question
I have this structure:
If I want to access to the embedded data, I have to do this command: select prop from User
Because if I try to access it through the class that contains the type of car I won't have any type of result
select from Car
UPDATE
OrientDB supports that kind of authorization/authentication but it's a little bit different from your example. For example: if an user A, without admin permission, inserts a record, another user B can't see the record inserted by user A without admin permission. An User can see only the records that has inserted.
Hope it helps
What I intend to design basically boils down to a list of users, organisations, events, addresses and comments which could quite easily be maintained in a RDBMS such as MySQL. However, if the project takes off I want to add another aspect which is resources - i.e. files, videos, images etc which can belong to either a user, organisation or event. This instantly raises the question of whether to use a RDBMS and store a reference to an external file through a table related to each of the categories previously mentioned or whether to use a Doc/Obj ODBMS such as MongoDB to store these items.
But I also want to be able to link users, organisations and events. i.e. User A owns Org 1 and Org 2. User B owns Org 3 and Org 4. User C owns Org 5. Org 1 has an Event X, held at Addr M on Date R, which Org 3 will also be at. User C intends to attend Event X. Org 2 also has an Event Y at Addr M but on Date T. etc etc. As such, I would suspect that a Graph DBMS such as OrientDB would be the best solution. Either that, or I would have a lot of tables in a RDBMS with a lot of joins, and potentially a lot of queries, or a very strange structure in a Doc/Obj DBMS.
I've looked at InfoGrid, which is a Graph database that can connect to MySQL, which could be a potential way to skin this cat. Has anybody else attempted anything like this? What are your thoughts on how to implement such a system, which needs to be scalable? Suggestions are greatly appreciated.
Your description lends itself to a relational model. RDBMS for this particular setup is the proper way to go.