I'm currently working on a project where I need two different types of non-related datastructures in my Java Android app. One being users, the other being types of food.
Users are set up like this:
users
userid
name
age
gender
weight
height
But, I also need one that looks like this, which must be searchable:
foods
name
carbohydrate
fat
protein
Is it possible to user the same database (preferrable Firebase, as I'm already using that), or do I need to add another database to the app I'm making?
Edit: I ended up exporting the JSON, rewriting it according to the good answers given here, and then importing it again. It works flawlessly. Thanks for your answers!
{
"foods" : {
"name" : {
"carbohydrates" : "5",
"fats" : "5",
"proteins" : "5"
}
},
"users" : {
"FjtMNTcDrOP2wcaPAa0E0Cc1jRz2" : {
"activity" : "Moderate Exercise (3–5 days/week)",
"age" : "40",
"gender" : "Male",
"height" : "180",
"name" : "Flex",
"weight" : "86"
}
}
}
Yes, it is possible to model multiple entity types (such as your users and foods) in the Firebase Realtime Database. While it doesn't have the concept of a table, it's a hierarchy of JSON values and you can model any structure you want in that.
For example, you could express you data model with this JSON:
{
"users": {
"userid": {
"name": "value",
"age": 42,
"gender: "value",
"weight": 190,
"height": 172
}
},
"foods": {
"name": {
"carbohydrate": 42
"fat": 11,
"protein": 8
}
}
}
In relational terms, the above model defines two "tables": users and foods. In Android code you can define separate references to each of these with:
DatabaseReference rootReference = FirebaseDatabase.getInstance().getReference();
DatabaseReference usersReference = rootReference.getChild("users");
DatabaseReference foodsReference = rootReference.getChild("foods");
Yes, you can use the same Firebase Realtime Database to store that data.
The RTDB can be simplified down to being just a JSON tree. So for your desired implementation, you would have two keys at the root of your database (such as "users" and "foods").
{
"users": {
"userid1": {
"name": "somestring",
"age": "somenum",
"gender": "somestring",
"height": "somenum",
"weight": "somenum",
...
},
...
},
"foods": {
"food1": {
"name": "somename",
"carbs": "somenum",
"fat": "somepercent",
"protein": "somepercent",
...
},
...
}
}
You can also add or remove more root keys as you wish and your project takes shape.
However,
As #Tamir Abutbul suggests in their answer, I would use Cloud Firestore for this project over the RTDB.
The reason for this is that based on your data, you are likely going to need to filter results by a number of different values at a time in the future. Cloud Firestore supports these types of queries natively (docs) whereas you'd need to write a custom solution for the RTDB.
Getting Started with Cloud Firestore
You can use Firebase with Cloud Firestore.
Create "users" collections with your wanted data structure and another collection called "foods" with its own data structure.
The next step is just to decide when to use any one of those collections(according to your app logic).
Related
I'm having a diffuculties with aggregations over dynamic templates. I have values stored like this.
[
{
"country": "CZ",
"countryName": {
"en": "Czech Republic",
"es": "Republica checa",
"de": "Tschechische Republik"
},
"ownerName": "..."
},
{
"ownerName": "..."
}
]
Country field is classic keyword, mapping for country name is indexed as dynamic template according to the fact that I want to extend with with another languages when I need to.
{
"dynamic_templates": [
{
"countryName_lsi_object_template": {
"path_match": "countryName.*",
"mapping": {
"type": "keyword"
}
}
}
]
}
countryName and country are not mandatory parameters - when the document is not assigned to any country, I can't have countryName filled either. However I need to do a sorted aggregation over the country names with according to chosen key and also need to include buckets with null countries. Is there any way to do that?
Previously, I used TermsValuesSourceBuilder with order on "country" field, but I need data sorted according to specifix language and name and that can't be done over country codes.
(I'm using elasticsearch 7.7.1 and java 8 and recreation of index / changing data structure is not my option.)
I tried to use missing bucket option, but the response does not include buckets with "countryName" missing at all.
TermsValuesSourceBuilder("countryName").field("countryName.en").missingBucket(true);
How can I query all the objects from a given table in Amazon DynamoDb using sub-object id? I will explain with example:
Orders table data:
{
"id": "76ds6ds76",
"publishDate": "2022-09-20",
"returnDate": null,
"book": {
"bookId": "327a7cdfeececd",
"name": "Hello world"
}
},
{
"id": "838ds990",
"publishDate": "2022-09-30",
"returnDate": null,
"book": {
"bookId": "327a7cdfeececd",
"name": "Hello world"
}
}
I want to get all the Orders with bookId == "327a7cdfeececd". Is there any possibility to query that?
The best way you can achieve that is by making bookid a top level attribute and creating a GSI based on it.
The other option you have is using a Scan and FilterExpression. This will read all the items in the table in order to find the one you need, while it would work well for small tables, it may not be advisable to do it with large tables due to poor performance and cost.
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Scan.html#Scan.FilterExpression
I am working on a spring MVC application. I have a sitaution where i need to check some checkboxes from UI and save the checked values in the form of JSON in the backend and i need to convert that into a string.
The picture shows more.
So i want to save like:
[{
Coast : 'East',
States : [ 'NY', 'MI' ]
},{
Coast : 'Central',
States : [ 'TX', 'OK' ]
}].
Please suggest me how can i implement this.
Your question is quite vague so I'm going to assume because you've used the json tag that you're asking for help on how to model this information in JSON and handle it within your Spring app.
You probably want to restructure your JSON schema to support extra fields being set per state. Instead of States being a list of strings, you could change it to a list of objects which has a name and selected field.
I'd also recommend you change the keys in your JSON to be lower case, this enables more fluent mapping between your JSON and model classes.
For example, MI is selected in the below JSON, whereas NY isn't:
[{
"coast": "East",
"states": [{
"name": "NY",
"selected": true
}, {
"name": "MI",
"selected": false
}]
}, {
...same again for West and Central
}]
You could then have some classes along the lines of and use Jackson to map between them:
public class Region {
String coast;
List<State> states;
}
public class State {
String name;
boolean selected;
}
Considering the below JSON, what would be the best way to store this into SQLite?
I am already parsing this with Gson, but wondering what would be a pain-free way to store this into SQLite and be able to retrieve it with no parsing issues.
I am already storing the desc, deposit objects as a HashMaps. My issue is the lease object. What would be an elegant way to store the leasees array?
Should I just create another Leasee object? And then serialize the ArrayList into a Blob for storage into the database?
{
"name": "1",
"desc": {
"country": "1",
"city": "1",
"postal": "1",
"street": "1",
"substreet": "1",
"year": 1,
"sqm": 1
},
"owner": [
"1"
],
"manager": [
"1"
],
"lease": {
"leasee": [
{
"userId": "1",
"start": {
"$date": 1420070400000
},
"end": {
"$date": 1420070400000
}
}
],
"expire": {
"$date": 1420070400000
},
"percentIncrease": 1,
"dueDate": 1
},
"deposit": {
"bank": "China Construction Bank",
"description": "Personal Bank Account USA"
}
}
Storing everything in a BLOB ignores the benefit that a DB provides.
You have much of a relational database structure already described (however loosely) in the JSON:
Properties table with location and description info.
Persons table with names and contacts.
Roles table relating Properties and Persons (residents, managers, owners, service providers).
Leases table with terms related to Properties and Persons.
Payments table with payment info related to Leases.
You can manually write in the primary keys in your JSON, taking care to match those relationships between tables, then insert the resulting rows by processing that modified JSON. Here's a link to SQLite doc on using INSERT with auto increment.
I have lots of Java objects which have parent child relationships.
These need to be put into Solr.
To do that, we convert the Java object into json as follows:
{
"employee": {
"name" : "John",
"address": {
"apt": 100,
"city": "New York",
"country": "USA"
},
"vehicles": [
{
"name" : "Hyundai",
"color" : "red"
},
{
"name" : "Toyota",
"color" : "black"
}
]
}
}
Now since Solr does not handle this, I am flattening it out as follows:
"employee.name": "John",
"employee.address.apt": 100,
"employee.address.city": "New York",
"employee.address.country": "USA",
"employee.vehicles_0.name": "Hyundai", // Note how arrays are being flattened
"employee.vehicles_0.color": "red",
"employee.vehicles_1.name": "Toyota",
"employee.vehicles_1.color": "black",
It is easy to flatten, but clients of my library do not want the flattened schema when they query.
So I need to de-flatten the above on return from Solr and convert them back to the original Java object.
Does anyone know how this can be done?
I am thinking of somewhat crude way of taking the flattened output from Solr (as shown above) and write a parser to put the fields back to Java objects. But this seems like lot of work. An easy way out or an existing tool would be much appreciated.
I am using Solr 4.5.1
Solr is designed for search, not storing deep object graphs. You might be better off optimizing the Solr records for search and then getting the original objects from the master store by recordID or some such.
Think about what will you be trying to find. For example, will you be searching for individual vehicles? If yes, your current document level should be a vehicle not an employee.
You can index your documents in a Parent->Child structure at first place.
Take a look at this blog post: http://blog.griddynamics.com/2013/09/solr-block-join-support.html