We conducted a webinar titled “Backendless Core Concepts” for ex-Parses last week. A recording of the webinar is now available. The video should be helpful not only if you’re coming from Parse, but for anyone who is starting their journey with Backendless. The webinar reviewed the concepts of Backendless User and Data services. Specifically, we focused on:
In my previous post I described how data tables in Backendless map to the client-side classes whose instances contain persisted data objects. However, there are scenarios when the default mapping is undesirable. In that case, Backendless client libraries provide an API to override the mapping. For example, consider the following data table (Restaurant):
Previously I described how to save data objects using REST Console. The same interface allows to save objects with related data – it is strictly a matter of formatting the request body. Consider the following two data table schemas:
Backendless REST Console is a tool capable of driving REST queries against Data Service. It is useful when you need to validate a REST command or for testing and diagnostics purposes. REST Console is available in a dedicated tab on the Data screen of the Backendless Console. Previously I wrote how to load data objects using REST Console and how to save a new data object. In this post I will describe the API to delete a data object.
Previously I wrote about the REST Console, which is a part of the Backendless Console. It is a versatile interface which lets you perform a complete CRUD (Create, Retrieve, Update, Delete) set of operations on your data stored in Backendless using the REST interface. One of my previous articles described how to use the REST Console to perform search queries (that’s the Retrieve part of CRUD). In this post I am going to demonstrate how to save new data objects using the REST Console.
In my previous posts I described how a data object may have a related geopoint (or a collection of). One of the benefits of the data-to-geo relationships is search by distance. That means Backendless can search for data objects using the location of the related geopoints. Consider an example from a taxi-reservation system. There may be several cabs-for-hire in the area. Your app needs to locate all available cars within the specified distance from where the customer is located.
The class representing a cab may look like this:
public class Car
public String make;
public String model;
public boolean available;
public GeoPoint location;
In my previous two posts I described:
Of course both of the operations above can also be accomplished with the API. However, in this post I am going to show how to retrieve a data object which has a related geopoint. Consider the following object:
The Address table has the location column of the GEOPOINT RELATIONSHIP type. There are three data objects in the table and one of them has a related geopoint. The geopoint is shown in the screenshot below.
Notice the geopoint’s metadata ( city: NEW YORK CITY ):
In my post yesterday I described how to declare a relationship in a data table schema with a geopoint. Now that you know how to create a table column which contains one or more geo points, I am going to show how to populate it with data.
Data objects in Backendless may have related properties not only with other tables, but also with Geopoints. These relationships may be declared programmatically or using Backendless Console. In this post I review the process of declaring a Data-to-Geo relationship in a data table schema.
Once a relationship is declared, you can do the following: