Each user of my system can have contacts. Each contact has details like Name, Address, Email, Phone, etc.
Do you think is a good idea to store this contacts in Azure Tables? I am worried about the following:
How do I search for a specific field (like Email or Phone)?
How do I get only the contacts belonging to a specific user?
How do I sort the contacts by a field?
I think that contacts could be a good candidate for storing in Table Storage - but only if you can partition on the owning person and never really need to search or aggregate across multiple owning users.
One possible design for this is:
store the contacts once with the owning user as partition key and some unique field for row key, but with the fields as columns within each row.
How do I search for a specific field (like Email or Phone)?
You can then ask table storage to search within a partition - it will then do a scan within that partition - which shouldn't be particularly large or slow for any single partition.
How do I get only the contacts belonging to a specific user?
This is just a simple query by partition key only
How do I sort the contacts by a field?
All results from table storage are sorted by (partitionkey, rowkey) so to sort the contacts for a user, you'll need to query for all of them, and then sort them within your web or worker role.
Other designs are, of course, possible -
e.g. you could store each contact in multiple rows in multiple tables - this would then allow you to have pre-formed sort orders within the table storage.
e.g. you could use separate tables instead of separate partitionkeys for each user - this has the advantage that when you delete a user, you can delete the entire table belonging to that user.
Note... while it's possible to use table storage for this... actually I almost always seem to end up back in SQL Azure at the moment - it's just so much more powerful and predictable (IMO). When the team deliver secondary indexing, then I might be tempted to use it for more of my data.
Related
I am building a website with large database, there's 6 types of data, so 6 forms to pass data to database.
Each form has unique parameters, and 4 of 6 forms have the same fields and the fields can contain multiple data: email, address and phone can be multiple on 4 forms.
For the first i wanted to created 4 different tables like: store_contacts, warehouse_contacts, delivery_contacts, etc. to keep different types separated.
so i would have 4 similar tables containing the same fields:
id, phone, email, address, store_id/delivery_id/etc
I have read that better practice to create one table containing them, table Contacts:
id, type, type_id, phone, email, address
from similar questions:
Two tables with same columns or one table with additional column?
https://softwareengineering.stackexchange.com/questions/302573/one-wide-table-or-multiple-themed-tables
https://dba.stackexchange.com/questions/46852/multiple-similar-tables-vs-one-master-table
But i'm not sure if tables will change later and new fields will be added for store only or only for delivery. and apart from contacts i have similar situation for other fields.
Would it be comfortable to make queries with type every time i need to pull data for certain type or when i need to delete them? Won't it get messy when a lot of rows will be inserted? And if a new field will be created for 'store', it is okay that others will contain NULL on that field?
Probably you should read a bit about Relational Entities or Object Orientation - inheritance, depending on the paradigm you are working.
For example, you can get aware about it in articles like this
Usually you should store contacts in a separate and exclusive entity, for a plenty of reasons. Sector-specific fields can be stored in each table, only if you are sure that there would be no use for them in another entities. For example: warehouse_contacts would have an imaginary employee id field to represent an employee in warehouse repsonsible for attending a given contact. Even though, proably the best practice would be to build a third table managing this information.
Nevertheless, if performance is an issue, I mean, if you have millions of records and dozens and dozens of simultaneous access in your website, maybe your Data Base would run faster in fewer tables, not so normalized. But this situation is quite improbable for most enterprises and users. Rather, this situation is kind a common practice in large-scale and legacy systems.
Good luck.
I am working on creating cassandra tables to support various queries my application makes. So far it's great, except I'm having a problem with one particular case:
We have a tinder-like interface where a user can vote "up" or "down" on a photo. I would like to dynamically serve the top 5 photos per query, sorted according to a custom "score", which excludes photos that a user has already voted on.
The pool of photos and the votes per photo are potentially > 10,000 each.
I was thinking of creating a table with a column of "votes: set" containing user ids, but it doesn't help because you can't query by NOT CONTAINS.
Is there a way to perform this query efficiently in Cassandra?
I am working on a self-bi application where users can upload their own datasets which are stored in Cassandra tables that are created dynamically. The data is extracted from files that the user can upload. So, each dataset is written into its own Cassandra table modeled based on column headers in the uploaded file while indexing the dimensions.
Once the data is uploaded, the users are allowed to build reports, analyze, etc., from within the application. I need a way to allow users to merge/join data from two or more datasets/tables based on matching keys and write the result into a new Cassandra table. Once a dataset/table is created, it will stay immutable and data is only read from it.
user table 1
username
email
employee id
user table 2
employee id
manager
I need to merge data in user table 1 and user table 2 on matching employee id and write to new table that is created dynamically.
new table
username
email
employee id
manager
What would be the best way to do this?
The only option that you have is to do the join in your application code. There are just few details to suggest a proper solution.
Please add details about table keys, usage patterns... in general, in cassandra you model from usage point of view, i.e. starting with queries that you'll execute on data.
In order to merge 2 tables on this pattern, you have to do it into application, creating the third table (target table ) and fill it with data from both tables. You have to make sure that you read the data in pages to not OOM, it really depends on size of the data.
Another alternative is to build the joins into Spark, but maybe is too over-engineering in your case.
You can have merge table with primary key of user so that merged data goes in one row and that should be unique since it is one time action.
Than when user clicks you can go through one table in batches with fetch size (for java you can check query options but that is a way to have a fixed window which will be loaded and when reached move to next fetch size of elements). Lets say you have fetch size of 1000 items, iterate over them from one table and find matches in second table, and after 1000 is reached place batch of 1000 inserts to new table.
If that is time consuming you can as suggested use some other tool like Apache Spark or Spring Batch and do that in background informing user that it will take place.
I am creating account data in Cassandra. Accounts are most commonly queried based on an account id. However, often the account is queried by a login name. I have created a user table with primary keys (account_id and login_name). Because of this, I have to "ALLOW FILTERING" on the table to query by the login_name.
Is there a better way to create the table that does not have the impact of a filterable table?
A possible approach is to define a new table that has the exact same elements in the primary key but in the reverse order: (login_name, account_id). You can still keep the table you present as the reference table, which stores all the relevant account data, but this new table would allow you more optimized queries based on login_name. I am not sure how much you would win compared with the query "allowing filtering"... But this kind of "data duplication" for query optimization is a normal procedure in NoSQL DBs.
HTH.
I have two tables which both include a date field. Currently I have two portals, one for each table (occurrence).
Is it was possible to display the results of both of these in one portal, and sort by the date?
Technically a portal can only display records from one table. If you need to join two tables then you have to do this manually or change the design and use one table instead of two (since you want them in the same portal, then the tables are similar to some degree; maybe this similarity can go into its own table).
Sometimes developers use the so-called virtual table technique: they create a table with, say, a field with the record number and a bunch of calculated fields that pick their values from elsewhere, for example, from prefilled global variables. They create a portal to this table, set up the relationship to display the required number of records, and write the code to fill these variables. This way they can show data that isn't stored in any table, combine tables, etc. But it's an arcane technique, I would recommend it only as the last resort.