I have a simple application to store Contacts. This application uses a simple relational database to store Contact information, like Name, Address and other data fields.
While designing it, I question came to my mind:
When designing programs that uses databases, should I retrieve all database records and store them in objects in my program, so I have a very fast performance or I should always gather data only when required?
Of course, retrieving all data can only be done if it`s not too many, but do you use this approach when you make sure that the database will be small (< 300 records for example)?
I have designed once a similar application that fetches data only when needed, but that was slow (using a Access database).
Thanks for all help.
This depends a lot on the type of data, the state your application works in, transactions, multiple users, etc.
Generally you don't want to pull everything and operate on the data within your application because almost all of the above conditions will cause data to become non-synchronized. Imagine a user updating a contact while someone else is viewing that information from a cached version inside their application.
In your application, you should design the database queries such that they retrieve what is going to be displayed on the current screen. If the user is viewing a list of contacts, then the query would retrieve the entire contact table, or a portion of it if you are doing a paginated view. When they click on a contact, for example, for more information, then a new query would request the full details of that contact.
For strings and small pieces of data like what a contact list involves, you shouldn't have any speed issues working with a relational database like SQL, MySql or Oracle.
I think it will be best to retrieve data when needed , retrieving all the records and storing it in object can be an overhead. And when you say you have a small database , retrieving the records when needed should not be an issue at all.
Related
I am now working on a project which requires to show the transaction history of one customer and if the product customer buys is under warranty or not. I need to use the data from the current system, the system can provide Web API, which is a .csv file. So how can I make use of the current system data?
A solution I think of is to download all the .csv files and write scripts to insert every record into the database I built which contains the necessary tables and relations to hold the data I retrieve. Then I can have a new database which I want. because I never done this before so I want know if it is feasible?
And one more question would be, if I should store the data locally or use a cloud database like Firebase?
High-end databases like SQL Server and Oracle come with utilities that allow you to read directly from a csv file. Check the docs. Having done this many times, the best procedure I found was to read the file into one holding table. This gives you the chance to examine the data and find any unexpected quirks or missing fields. This allows you to correct the data, where possible.
Then write the scripts to move the data from the holding table into the proper tables you have designed. This must be done in a logical manner. For example, move the customer data before the buy transactions. Thus any error messages you get will not be because you tried to store a transaction before you stored the customer. (You will have referential integrity set up, yes?) This gives you more chances to correct or adjust the data or just identify problems more or less at your leisure.
Whether or not to store the data in the cloud is strictly according to the preferences of your employer.
Coming from a RDBMS background and trying to wrap my head around ElasticSearch data storage patterns...
Currently in SQL Server, we have a star schema data mart, RecordData. Rows are organized by user ID, geographic location that pertains to the rest of the searchable record, title and description (which are free text search fields).
I would like to move this over to ElasticSearch, and have read about creating a separate index per user. If I understand this correctly, with this suggestion, I would be creating a RecordData type in each user index, correct? What is a recommended naming convention for user indices that will be simple for Kibana analysis?
One issue I have with this recommendation is, how would you organize multiple web applications on the ES server? You wouldn't want to have all those user indices all over the place?
Is it so bad to have one index per application, and type per SQL Server table?
Since in SQL Server, we have other tables for user configuration, based on user ID's, I take it that I could then create new ES types in user indices for configuration. Is this a recommended pattern? I would rather not have two data base systems for this web application.
Suggestions welcome, thank you.
I went through the same thing, and there are a few things to take into account.
Data Modeling
You say you use a star schema today. Elasticsearch is typically appropriate for denormalized data where the totality of the information resides in each document unlike with a star schema. If you can live with denormalized, that is fine but I assume that since you already have star schema, denormalized data is not an option because you don't want to go and update millions of documents each time the location name change for example(if i understand the use case). At least in my use case that wasn't an option.
What are Elasticsearch options for normalized data?
This leads us to think of how to put star schema like data in a system like Elasticsearch. There are a few options in the documentation, the main ones i focused were
Nested Objects - more details at https://www.elastic.co/guide/en/elasticsearch/guide/current/nested-objects.html . In nested objects the entire information is kept in a single document, meaning one location and its related users would be in a single document. That may make it not optimal becasue the document will be huge and again, a change in the location name will require to update the entire document. So this is better but still not optimal.
Parent - Child Relationship - more details at https://www.elastic.co/guide/en/elasticsearch/guide/current/parent-child.html . In this case the location and the User records would be kepts in separate indices similarly to a relational database. This seems to be the right modeling for what we need. The only major issue with this option is the fact that Kibana 4 does not provide ways to manipulate/aggregate documents based on parent/child relationship as of this writing. So if you main driver for using Elasticsearch is Kibana(this was mine), that kind of eliminates the option. If you want to benefit from the elasticsearch speed as an engine this seems to be the desired option for your use case.
In my opinion once you got right the data modeling all of your questions will be easier to answer.
Regarding the organization of the servers themselves, the way we organize that is by having a separate cluster of 3 elasticsearch nodes behind a Load Balancer(all of that is hosted on a cloud) and then have all your Web Applications connect to that cluster using the Elasticsearch API.
Hope that helps.
We would like to give some of our customers the option to read data from our central database. The data is live and new records are being added every few seconds. Our database is MySQL running on Amazon RDS.
I was wondering what is the common practice for doing so.
One option would be to give them select right from specific tables, in that case they would be able to access other customers' data as well.
I have tried searching for database, interface, and API key words and some other key words, but I couldn't find a good answer.
Thanks!
Use REST for exposing specific tables to do CRUD operations. You can control the access on it too.
The project I have been given is to store and retrieve unstructured data from a third-party. This could be HR information – User, Pictures, CV, Voice mail etc or factory related stuff – Work items, parts lists, time sheets etc. Basically almost any type of data.
Some of these items may be linked so a User many have a picture for example. I don’t need to examine the content of the data as my storage solution will receive the data as XML and send it out as XML. It’s down to the recipient to convert the XML back into a picture or sound file etc. The recipient may request all Users so I need to be able to find User records and their related “child” items such as pictures etc, or the recipient may just want pictures etc.
My database is MS SQL and I have to stick with that. My question is, are there any patterns or existing solutions for handling unstructured data in this way.
I’ve done a bit of Googling and have found some sites that talk about this kind of problem but they are more interested in drilling into the data to allow searches on their content. I don’t need to know the content just what type it is (picture, User, Job Sheet etc).
To those who have given their comments:
The problem I face is the linking of objects together. A User object may be added to the data store then at a later date the users picture may be added. When the User is requested I will need to return the both the User object and it associated Picture. The user may update their picture so you can see I need to keep relationships between objects. That is what I was trying to get across in the second paragraph. The problem I have is that my solution must be very generic as I should be able to store anything and link these objects by the end users requirements. EG: User, Pictures and emails or Work items, Parts list etc. I see that Microsoft has developed ZEntity which looks like it may be useful but I don’t need to drill into the data contents so it’s probably over kill for what I need.
I have been using Microsoft Zentity since version 1, and whilst it is excellent a storing huge amounts of structured data and allowing (relatively) simple access to the data, if your data structure is likely to change then recreating the 'data model' (and the regression testing) would probably remove the benefits of using such a system.
Another point worth noting is that Zentity requires filestream storage so you would need to have the correct version of SQL Server installed (2008 I think) and filestream storage enabled.
Since you deal with XML, it's not an unstructured data. Microsoft SQL Server 2005 or later has XML column type that you can use.
Now, if you don't need to access XML nodes and you think you will never need to, go with the plain varbinary(max). For your information, storing XML content in an XML-type column let you not only to retrieve XML nodes directly through database queries, but also validate XML data against schemas, which may be useful to ensure that the content you store is valid.
Don't forget to use FILESTREAMs (SQL Server 2008 or later), if your XML data grows in size (2MB+). This is probably your case, since voice-mail or pictures can easily be larger than 2 MB, especially when they are Base64-encoded inside an XML file.
Since your data is quite freeform and changable, your best bet is to put it on a plain old file system not a relational database. By all means store some meta-information in SQL where it makes sense to search through structed data relationships but if your main data content is not structured with data relationships then you're doing yourself a disservice using an SQL database.
The filesystem is blindingly fast to lookup files and stream them, especially if this is an intranet application. All you need to do is share a folder and apply sensible file permissions and a large chunk of unnecessary development disappears. If you need to deliver this over the web, consider using WebDAV with IIS.
A reasonably clever file and directory naming convension with a small piece of software you write to help people get to the right path will hands down, always beat any SQL database for both access speed and sequential data streaming. Filesystem paths and file names will always beat any clever SQL index for data location speed. And plain old files are the ultimate unstructured, flexible data store.
Use SQL for what it's good for. Use files for what they are good for. Best tools for the job and all that...
You don't really need any pattern for this implementation. Store all your data in a BLOB entry. Read from it when required and then send it out again.
Yo would probably need to investigate other infrastructure aspects like periodically cleaning up the db to remove expired entries.
Maybe i'm not understanding the problem clearly.
So am I right if I say that all you need to store is a blob of xml with whatever binary information contained within? Why can't you have a users table and then a linked(foreign key) table with userobjects in, linked by userId?
I have a database that has lots of data and is all "neat", normalized (within reason - using EAV), and I have stored procedures to access and modify the data.
I also have a WinForms application that users download to search and view this data (no inserts). To make things handy for use and updates, I've been using SQLite to store this data and it works really well.
I'm working on updating the entire process and I was wondering if I should use a denormalized view of the data to ship out to the users, ala the 1 table with all the properties as columns, or continue to use the same schema as the master database?
My initial thoughts are along the lines of :
Denormalized View:
Benefits...
Provides a simple method of querying the data (since I'm not doing a lot of joins, just a bunch of column searching.
Cons...
I'd have to manage a second data access layer. Granted I don't think it will be difficult, but it is still a bit more work.
If a new property is added, I'd have to modify the schema again and accomodate for the changes. Wheras I can simply query the property bag and work form there.
Same Schema:
Pros...
Same layout as master database, so updates are minimal, and I can even use the same queries when building my Data Access Layer since SQLite doesn't support stored procedures.
Cons...
There is a lot of small tables for lookup codes and the like, so I could start running into issues when building the queries and managing it in the DAL.
How should I proceed?
If you develop your application to query views of the data rather than the underlying data itself, you will be able to keep the same database for both scenarios without concern or the need to alter your DAL.