I'm willing to give MongoDB and CouchDB a serious try. So far I've worked a bit with Mongo, but I'm also intrigued by Couch's RESTful approach.
Having worked for years with relational DBs, I still don't get what is the best way to get some things done with non relational databases.
For example, if I have 1000 car shops and 1000 car types, I want to specify what kind of cars each shop sells. Each car has 100 features. Within a relational database i'd make a middle table to link each car shop with the car types it sells via IDs. What is the approach of No-sql? If every car shop sells 50 car types, it means replicating a huge amount of data, if I have to store within the car shop all the features of all the car types it sells!
Any help appreciated.
I can only speak to CouchDB.
The best way to stick your data in the db is to not normalize it at all beyond converting it to JSON. If that data is "cars" then stick all the data about every car in the database.
You then use map/reduce to create a normalized index of the data. So, if you want an index of every car, sorted first by shop, then by car-type you would emit each car with an index of [shop, car-type].
Map reduce seems a little scary at first, but you don't need to understand all the complicated stuff or even btrees, all you need to understand is how the key sorting works.
http://wiki.apache.org/couchdb/View_collation
With that alone you can create amazing normalized indexes over differing documents with the map reduce system in CouchDB.
In MongoDB an often used approach would be store a list of _ids of car types in each car shop. So no separate join table but still basically doing a client-side join.
Embedded documents become more relevant for cases that aren't many-to-many like this.
Coming from a HBase/BigTable point of view, typically you would completely denormalize your data, and use a "list" field, or multidimensional map column (see this link for a better description).
The word "column" is another loaded
word like "table" and "base" which
carries the emotional baggage of years
of RDBMS experience.
Instead, I find it easier to think
about this like a multidimensional map
- a map of maps if you will.
For your example for a many-to-many relationship, you can still create two tables, and use your multidimenstional map column to hold the relationship between the tables.
See the FAQ question 20 in the Hadoop/HBase FAQ:
Q:[Michael Dagaev] How would you
design an Hbase table for many-to-many
association between two entities, for
example Student and Course?
I would
define two tables: Student: student
id student data (name, address, ...)
courses (use course ids as column
qualifiers here) Course: course id
course data (name, syllabus, ...)
students (use student ids as column
qualifiers here) Does it make sense?
A[Jonathan Gray] : Your design does
make sense. As you said, you'd
probably have two column-families in
each of the Student and Course tables.
One for the data, another with a
column per student or course. For
example, a student row might look
like: Student : id/row/key = 1001
data:name = Student Name data:address
= 123 ABC St courses:2001 = (If you need more information about this
association, for example, if they are
on the waiting list) courses:2002 =
... This schema gives you fast access
to the queries, show all classes for a
student (student table, courses
family), or all students for a class
(courses table, students family).
In relational database, the concept is very clear: one table for cars with columns like "car_id, car_type, car_name, car_price", and another table for shops with columns "shop_id, car_id, shop_name, sale_count", the "car_id" links the two table together for data Ops. All the columns must well defined in creating the database.
No SQL database systems do not require you pre-define these columns and tables. You just construct your records in a certain format, say JSon, like:
"{car:[id:1, type:auto, name:ford], shop:[id:100, name:some_shop]}",
"{car:[id:2, type:auto, name:benz], shop:[id:105, name:my_shop]}",
.....
After your system is on-line providing service for your management, you may find there are some flaws in your design of db structure, you hope to add one column "employee" of "shop" for your future records. Then your new records coming is as:
"{car:[id:3, type:auto, name:RR], shop:[id:108, name:other_shop, employee:Bill]}",
No SQL systems allow you to do so, but relational database is impossible for this job.
Related
So in a traditional database I might have 2 tables like users, company
id
username
companyid
email
1
j23
1
something#gmail.com
2
fj222
1
james#aol.com
id
ownerid
company_name
1
1
A Really boring company
This is to say that user 1 and 2 are apart of company 1 (a really boring company) and user 1 is the owner of this company.
I could easily issue an update statement in MySQL or Postgresql to update the company name.
But how could I model the same data from a NoSQL perspective, in something like Dynamodb or Mongodb?
Would each user record (document in NoSQL) contain the same company table data (id, ownerid (or is owner true/false, and company name)? I'm unclear how to update the record for all users containing this data then if the company name needed to be updated.
In case you want to save the company object as JSON in each field (for performance reasons), indeed, you have to update a lot of rows.
But best way to achieve this is to have a similar structure as you have above, in MySQL. NoSql schema depends a lot on the queries you will be making.
For example, the schema above is great for:
Find a particular user by username, along with his company name. First you need to query User by username (you can add an index), get the companyId and do another query on Company to fetch the name.
Let's assume company name changes often
In this case company name update is easy. To execute the read query, you need 2 queries to get your result (but they should execute fast)
Embedded company JSON would work better for:
Find all users from a specific city and show their company name
Let's assume company name changes very rarely
In this case, we can't use the "relational" approach, because we will do 1 query to fetch Users by city and then another query for all users found to fetch the company name
Using embedded approach, we need only 1 query
To update a company name, a full (expensive) scan is needed, but should be ok if done rarely
What if company name changes ofter and I want to get users by city?
This becomes tricky, NoSQL is not a replacement for SQL, it has it's shortcomings. Solution may be a platform dependent feature (from mongo, dynamodb, firestore etc.), an additional layer above (elasticSearch) or no solution at all (consider not using key-value NoSQL)
Depends on the programming language used to handle NoSQL objects/documents you have variety of ORM libraries to model your schema. Eg. for MongoDB plus JS/Typescript I recommend Mongoose and its subdocuments. Here is more about it:
https://mongoosejs.com/docs/subdocs.html
This question already has answers here:
How can you represent inheritance in a database?
(7 answers)
Closed 2 years ago.
I am building a Postgres database which has the following two tables:
Projects (id, startDate, etc...)
and
Employees (id, name, etc...)
I want to keep track of the types of contributions that an employee adds to a project. For example, employee #1 might be an "engineer" on project 1 and a "manager" on project 2. I also don't want to restrict the number of contributions an employee can make to a certain project. So employee #1 could be both a "engineer" and a "manager" for a single project.
My first instinct was just to have a many to many relation between the two titled ProjectEmployees or something and store the projectId, employeeId, and a contributionType as a string which would only take on values from an enum as to not have to deal with misspellings or any related issues.
My main question is just whether or not this is a bad practice. My other thought was to split up each contribution type to its own table. So instead of an EmployeeProjects table, there would be tables such as ProjectEngineers, ProjectManagers, etc... and instead of storing the contributionType as a column, it would be implicit in the table I'm using, and the table only has to store projectId and employeeId. There are many more tables in this database which have a similar sort of relationship where there are many to many relations between different tables, but each relation could be one of many "types" of relations. Is it wiser to split these all into separate tables for each type of relation? Or is it better to just keep track of the relation type in a more general table like my first idea?
My desired result is to just be able to efficiently see which all project contributions (and types) an employee worked on as well as to see all contributors + contributor types for a project.
Use the many to many relation as in your first idea, which in my opinion is a good practice.
Avoid the creation of one table per contribution type as is not scalable and flexible. I.E. if one day you'll have a new contribution type, with the 2nd option you will need each time
to create a new table
to write the new table management logic
proceed with a new deploy of your sw
About the topic of storing the contribution types on a table (with id and description) or as a constraint with contribution types strings enumerated, in my opinion both are valuable solutions.
But if you think to manage contribution types in your software (in a first release or in the future) maybe having a table with contribution types anagraphics can be better. It depends by your design and requirements
Make a table to store contribution types as strings (manager, engineer, etc) and contribution type id (numeric id). This prevents misspellings.
Make a table to store contributions with columns: employee id, project id, contribution type id (you may want other columns there, but it should be unique on the combination of these 3 columns). Do not store contribution types as strings in a table like this, since, as you correctly mentioned, this may allow misspellings. Another reason is to save disk space. An extra join with a small table of contribution types is a small price to pay.
Sorry if this is a relatively easy problem to solve; I read the docs on inheritance and I'm still confused on how I would do this.
Let's say I have the parent table being car_model, which has the name of the car and some of it's features as the columns (e.g. car_name, car_description, car_year, etc). Basically a list of cars.
I have the child table being car_user, which has the column user_id.
Basically, I want to link a car to the car_user, so when I call
SELECT car_name FROM car_user WHERE user_id = "name", I could retrieve the car_name. I would need a linking component that links car_user to the car.
How would I do this?
I was thinking of doing something like having car_name column in car_user, so when I create a new data row in car_user, it could link the 2 together.
What's the best way to solve this problem?
Inheritance is something completely different. You should read about foreign keys and joins.
If one user drives only one car, but many users can drive same car, you need to build one-to-many -relation. Add car_name to your user table and JOIN using that field.
I am currently trying to model a MongoDB database structure where the entities are very complex in relation to each other.
In my current collections, MongoDB queries are difficult or impossible to put into a single aggregation. Incidentally, I'm not a database specialist and have been working with MongoDB for only about half a year.
To keep it as simple as possible but necessary, this is my challenge:
I have newspaper articles that contain simple keywords, works (oevres, books, movies), persons and linked combinations of works and persons. In addition, the same people appear under different names in different articles.
Later, on the person view I want to show the following:
the links of the person with name and work and the respective articles
the articles in which the person appears without a work (by name)
the other keywords that are still in the article
In my structure I want to avoid that entities such as people occur multiple times. So these are my current collections:
Article
id
title
keywordRelations
KeywordRelation
id
type (single or combination)
simpleKeywordId (optional)
personNameConnectionIds (optional)
workIds (optional)
SimpleKeyword
id
value
PersonNameConnection
id
personId
nameInArticleId
Person
id
firstname
lastname
NameInArticle
id
name
type (e.g. abbreviation, synonyme)
Work
id
title
To meet the requirements, I would always have to create queries that range over 3 to 4 tables. Is that possible and useful with MongoDB?
Or is there an easier way and structure to achieve that?
I am trying to come up with a MongoDB document model and would like others opinions. I want to have a Document that represents an Employee. This table will contain all attributes of an employee (I.e. firstName, LastName). Now where I am stuck coming from the relational realm, is the need to store a list of employees an employee can access. In other words lets say Employee A is a Manager. I need to store the direct reports that he manages, in order to use this in various applications. In relational I would have a mapping table that tied an employee to many employees. In mongo not being able join documents, do you think I should utilize an embeded (sub-document) to store the list of accessible employees as part of the Employee document? Any other ideas ?
Unless your using employee groups (Accounting, HR, etc) You'll probably be fine adding the employee name, mongo Object ID, and any other information unique to that manager / employee relationship as a sub document to the managers document.
With that in place you could probably do your reporting on these relationships through a simple aggregation.
This is all IMHO, and begs the question; Is simple aggregation another oxymoron like military intelligence?