I need to store a complex C# object in SQLite in my mobile app. I know that a complex object can be broken down and stored in multiple tables.
In my particular use case, however, I don't need to query the data. Is there any problem in serializing my complex object and then storing it as a string in my SQLite table?
I only need to store it temporarily as I collect data from the user in multiple screens and there will only be the data I store during the collection process. In other words, once the data collection is completed, I will remove the data from my SQLite table.
I've already tried it and it works fine but want to see if there are some issues that I may run into in the future?
Related
This is my first time using a NOSQL database and I'm really struggling to work out how to structure my data.
I have an app that predicts a users mood and then the user can select if that's right or not. So I need to save both the prediction and the actual result. I want to be able to pull the latest result from firebase and display it on the app.
I understand how I'd do this on an SQL DB and understand how to write an SQL query to get that data back out.
For my Firebase DB I thought of the following structure
the document name is the usersID and store multiple arrays based on the timestamp but I can't seem to user OrderBy on a document only a collection so not sure how to get this back.
The fact that this seems so difficult less me to believe I've implemented the DB wrong to begin with.
Structure of DB is as follows:
I should add that it all works fine for the USER_TABLE as its one document id and a single entry, so I've no problem retrieving that.
Thanks for your help!
orderBy is an instruction to the database to order documents on the server, before it returns them to your app. To store the fields inside the document, you can just do that inside your application code after it receives the document(s).
There is in itself nothing wrong with storing these entries in a single document, Just keep in mind that:
A document can be at most be 1MB in size, so make sure this fits your maximum number of entries.
Firestore only ever returns full documents, so you will either get all entries in a document, or none of them.
You won't be able to order or filter the entries inside a single document. If that is a requirement for you, consider storing each entry in its own document in a subcollection. Note that this will increase the number of documents each user reads though, which will increase the cost.
I am working with a large web application where there can be up to 100,000 objects, populated from a DB, in cache.
There is a table in the database which, given the object ID, will give you a last_updated value which is updated whenever any aspect of that object changes in the DB.
I have read creating an SqlCacheDependency (one row in a table per object) per object, which such high number of objects is a no-go.
I am looking for alternative solutions. One such possible solution I thought of is to cache the "last_updated" table as a datastructure and create a cache dependency to the table it is based on. Then whenever one of the 100,000 objects is requested, I check the cached "last_updated" table and if it is out of date, I fetch the object again from the database and re-cache it. If it is not out of date, I give the cached version. Does this seem like a reasonable solution?
But.. how you can do it for a single row of the table.. In ASP.Net you can create SQl Server dependency which uses a broker Service.. and puts the data into the cache and whenever the table is updated.. the cache will be rejected and new data is taken from db and put into the cache..
i Hope this might give you some idea!
I'm currently developing a mobile application which uses AJAX request to get data from a server.
To enable offline navigation in my application, I need to store all data collected.
My application is quite powerful because there's a section where the user can see charts (powered by highcharts).
I'm asking myself about the best solution to cache the data collected in the JSON format.
Is it light or efficient enough to JSON.stringify the data array into local storage like:
localStorage.setItem("graph_1_datas", JSON.stringify(json_data_array));
Or would it be better to create a database, and a table like that:
TABLE
-----
id
graphId
blockId
x
y
I have 3 graphIds by blockId, and about 10 blockIds...
Storing the JSON strings to local storage should be fairly fast and efficient. Just store a separate file for each request and then it will give you clear simple code for getting the data either from local storage or web service.
If you are likely to want to edit the data offline then you may wish to consider an SQLite database as it will make it easier/more efficient to add code to track changes.
You may also want to consider an SQLite database if your object graph gets more complicated and fits a relational database model.
Background: I am using SQLite database in my flex application. Size of the database is 4 MB and have 5 tables which are
table 1 have 2500 records
table 2 have 8700 records
table 3 have 3000 records
table 4 have 5000 records
table 5 have 2000 records.
Problem: Whenever I run a select query on any table, it takes around (approx 50 seconds) to fetch data from database tables. This has made the application quite slow and unresponsive while it fetches the data from the table.
How can i improve the performance of the SQLite database so that the time taken to fetch the data from the tables is reduced?
Thanks
As I tell you in a comment, without knowing what structures your database consists of, and what queries you run against the data, there is nothing we can infer suggesting why your queries take much time.
However here is an interesting reading about indexes : Use the index, Luke!. It tells you what an index is, how you should design your indexes and what benefits you can harvest.
Also, if you can post the queries and the table schemas and cardinalities (not the contents) maybe it could help.
Are you using asynchronous or synchronous execution modes? The difference between them is that asynchronous execution runs in the background while your application continues to run. Your application will then have to listen for a dispatched event and then carry out any subsequent operations. In synchronous mode, however, the user will not be able to interact with the application until the database operation is complete since those operations run in the same execution sequence as the application. Synchronous mode is conceptually simpler to implement, but asynchronous mode will yield better usability.
The first time SQLStatement.execute() on a SQLStatement instance, the statement is prepared automatically before executing. Subsequent calls will execute faster as long as the SQLStatement.text property has not changed. Using the same SQLStatement instances is better than creating new instances again and again. If you need to change your queries, then consider using parameterized statements.
You can also use techniques such as deferring what data you need at runtime. If you only need a subset of data, pull that back first and then retrieve other data as necessary. This may depend on your application scope and what needs you have to fulfill though.
Specifying the database with the table names will prevent the runtime from checking each database to find a matching table if you have multiple databases. It also helps prevent the runtime will choose the wrong database if this isn't specified. Do SELECT email FROM main.users; instead of SELECT email FROM users; even if you only have one single database. (main is automatically assigned as the database name when you call SQLConnection.open.)
If you happen to be writing lots of changes to the database (multiple INSERT or UPDATE statements), then consider wrapping it in a transaction. Changes will made in memory by the runtime and then written to disk. If you don't use a transaction, each statement will result in multiple disk writes to the database file which can be slow and consume lots of time.
Try to avoid any schema changes. The table definition data is kept at the start of the database file. The runtime loads these definitions when the database connection is opened. Data added to tables is kept after the table definition data in the database file. If changes such as adding columns or tables, the new table definitions will be mixed in with table data in the database file. The effect of this is that the runtime will have to read the table definition data from different parts of the file rather than at the beginning. The SQLConnection.compact() method restructures the table definition data so it is at the the beginning of the file, but its downside is that this method can also consume much time and more so if the database file is large.
Lastly, as Benoit pointed out in his comment, consider improving your own SQL queries and table structure that you're using. It would be helpful to know your database structure and queries are the actual cause of the slow performance or not. My guess is that you're using synchronous execution. If you switch to asynchronous mode, you'll see better performance but that doesn't mean it has to stop there.
The Adobe Flex documentation online has more information on improving database performance and best practices working with local SQL databases.
You could try indexing some of the columns used in the WHERE clause of your SELECT statements. You might also try minimizing usage of the LIKE keyword.
If you are joining your tables together, you might try simplifying the table relationships.
Like others have said, it's hard to get specific without knowing more about your schema and the SQL you are using.
In my web application, I have a dynamic query that returns huge data to datatable, and this query is often recalled with different parameters. So database is exhausted.
I want to get all record with no parameters to an object, and perform queries (may be with linq) on this object. So database will not be exthausted.
Which objects can be used instead of datatable?
This is one of my pet peeves - people who return all the data from the database.
There is absolutely no need for this unless you are doing reporting.
If you are doing reporting, then you need to increase your hardware capability so that the database can cope. This may also include tuning your database, rearranging tables, reindexing, regular rebuilding of indexes, updating statistics, archiving out old data, etc.
If you are NOT doing reporting, then start limiting how much data can be queried at any one time. Users DO NOT need to see massive quantities of data all at once. They need to see discrete amounts of data presented in a manageable and coherent way.
Another rule of thumb i like to observe is: let your database server do the work, it is made to manipulate lots of data, it is what it is good at, and it should have the power to do it. Pulling back loads of data to the client, and then trying to manipulate that data on the client is a foolish thing to do. If your client machines are more powerful than the database server then you have issues.
Never ever perform this(except cache)!!!
You are trying to implement DB mechanisms, like
persistent storage
index search and query strategy
replication
and so on
Spend your time on db optimization(optimal scheme, indexes, query, partitioning).