Downloading data query android json

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One-to-many relationships enable one object to have many related objects. Finally, many-to-many relationships enable complex relationships among many objects.

First, how many objects are involved in this relationship? In Parse, we can store this data in a single Game object. If the game becomes incredibly successful, each player will store thousands of Game objects in the system.

For circumstances like this, where the number of relationships can be arbitrarily large, Pointers are the best option. Suppose in this game app, we want to make sure that every Game object is associated with a Parse User. We can implement this like so:. We can obtain all of the Game objects created by a Parse User with a query:.

And, if we want to find the Parse User who created a specific Game , that is a lookup on the createdBy key:. Arrays are ideal when we know that the number of objects involved in our one-to-many relationship are going to be small. Arrays will also provide some productivity benefit via the includeKey parameter.

However, the response time will be slower if the number of objects involved in the relationship turns out to be large. Suppose in our game, we enabled players to keep track of all the weapons their character has accumulated as they play, and there can only be a dozen or so weapons. In this example, we know that the number of weapons is not going to be very large.

We also want to enable the player to specify the order in which the weapons will appear on screen. Arrays are ideal here because the size of the array is going to be small and because we also want to preserve the order the user has set each time they play the game:. One trick we could employ is to use the includeKey or include in Android parameter whenever we use a Parse Query to also fetch the array of Weapon objects stored in the weaponsList column along with the Parse User object:.

For example, if we want to find all Parse User objects who also have a given Weapon , we can write a constraint for our query like this:. Suppose we had a book reading app and we wanted to model Book objects and Author objects. As we know, a given author can write many books, and a given book can have multiple authors. This is a many-to-many relationship scenario where you have to choose between Arrays, Parse Relations, or creating your own Join Table.

The decision point here is whether you want to attach any metadata to the relationship between two entities. In general, using arrays will lead to higher performance and require fewer queries. If either side of the many-to-many relationship could lead to an array with more than or so objects, then, for the same reason Pointers were better for one-to-many relationships, Parse Relation or Join Tables will be better alternatives.

Remember, this is information about the relationship , not about the objects on either side of the relationship. Some examples of metadata you may be interested in, which would necessitate a Join Table approach, include:. Using Parse Relations, we can create a relationship between a Book and a few Author objects.

In the Data Browser, you can create a column on the Book object of type relation and name it authors. Perhaps you even want to get a list of all the books to which an author contributed. You can create a slightly different kind of query to get the inverse of the relationship:. There may be certain cases where we want to know more about a relationship. This information could not be contained in a Parse Relation.

In order to keep track of this data, you must create a separate table in which the relationship is tracked. This table, which we will call Follow , would have a from column and a to column, each with a pointer to a Parse User.

Alongside the relationship, you can also add a column with a Date object named date. Now, when you want to save the following relationship between two users, create a row in the Follow table, filling in the from , to , and date keys appropriately:.

If we want to find all of the people we are following, we can execute a query on the Follow table:. Arrays are used in Many-to-Many relationships in much the same way that they are for One-to-Many relationships. All objects on one side of the relationship will have an Array column containing several objects on the other side of the relationship. Suppose we have a book reading app with Book and Author objects. The Book object will contain an Array of Author objects with a key named authors.

We will put the Array in the Book object for this reason. After all, an author could write more than books. Here is how we save a relationship between a Book and an Author. Because the author list is an Array, you should use the includeKey or include on Android parameter when fetching a Book so that Parse returns all the authors when it also returns the book:.

At that point, getting all the Author objects in a given Book is a pretty straightforward call:. Finally, suppose you have an Author and you want to find all the Book objects in which she appears. This is also a pretty straightforward query with an associated constraint:. In Parse, a one-to-one relationship is great for situations where you need to split one object into two objects. These situations should be rare, but two examples include:.

Thank you for reading this far. We apologize for the complexity. Modeling relationships in data is a hard subject, in general. Many of the methods on ParseObject , including save , delete , and get will throw a ParseException on an invalid request, such as deleting or editing an object that no longer exists in the database, or when there is a network failure preventing communication with your Parse Server.

You will need to catch and deal with these exceptions. For more details, look at the Android API. This document explains the ways in which you can secure your apps.

Continue reading for our suggestions for sensible defaults and precautions to take before releasing your app into the wild. These are not secret and by themselves they do not secure an app. These keys are shipped as a part of your app, and anyone can decompile your app or proxy network traffic from their device to find your client key.

This is why Parse has many other security features to help you secure your data. The client key is given out to your users, so anything that can be done with just the client key is doable by the general public, even malicious hackers.

The master key, on the other hand, is definitely a security mechanism. The overall philosophy is to limit the power of your clients using client keys , and to perform any sensitive actions requiring the master key in Cloud Code. The second level of security is at the schema and data level. Enforcing security measures at this level will restrict how and when client applications can access and create data on Parse. When you first begin developing your Parse application, all of the defaults are set so that you can be a more productive developer.

You can configure any of these permissions to apply to everyone, no one, or to specific users or roles in your app. Roles are groups that contain users or other roles, which you can assign to an object to restrict its use. Any permission granted to a role is also granted to any of its children, whether they are users or other roles, enabling you to create an access hierarchy for your apps.

Each of the Parse guides includes a detailed description of employing Roles in your apps. Once you are confident that you have the right classes and relationships between classes in your app, you should begin to lock it down by doing the following:. Almost every class that you create should have these permissions tweaked to some degree. For classes where every object has the same permissions, class-level settings will be most effective.

For example, one common use case entails having a class of static data that can be read by anyone but written by no one. As a start, you can configure your application so that clients cannot create new classes on Parse. See the project Readme for an overview of Configuring your ParseServer.

Once restricted, classes may only be created from the Data Browser or with a the masterKey. This will prevent attackers from filling your database with unlimited, arbitrary new classes.

Parse lets you specify what operations are allowed per class. This lets you restrict the ways in which clients can access or modify your classes. Get : With Get permission, users can fetch objects in this table if they know their objectIds. Any table with public Find permission will be completely readable by the public, unless you put an ACL on each object.

For publicly readable data, such as game levels or assets, you should disable this permission. Create : Like Update, anyone with Create permission can create new objects of a class. All they need is its objectId. Add fields : Parse classes have schemas that are inferred when objects are created.

You should pretty much always turn off this permission for all of your classes when you submit your app to the public. For each of the above actions, you can grant permission to all users which is the default , or lock permissions down to a list of roles and users.

For example, a class that should be available to all users would be set to read-only by only enabling get and find. A logging class could be set to write-only by only allowing creates. You could enable moderation of user-generated content by providing update and delete access to a particular set of users or roles. Parse also supports the notion of anonymous users for those apps that want to store and protect user-specific data without requiring explicit login.

When a user logs into an app, they initiate a session with Parse. The easiest way to control who can access which data is through access control lists, commonly known as ACLs. The idea behind an ACL is that each object has a list of users and roles along with what permissions that user or role has.

Once you have a User, you can start using ACLs. Most apps should do this. To make it super easy to create user-private ACLs for every object, we have a way to set a default ACL that will be used for every new object you create:. You can add a pointer to the private data from the public one. Of course, you can set different read and write permissions on an object. For example, this is how you would create an ACL for a public post by a user, where anyone can read it:.

Roles are a special kind of object that let you create a group of users that can all be assigned to the ACL. The best thing about roles is that you can add and remove users from a role without having to update every single object that is restricted to that role.

To create an object that is writeable only by admins:. This is often reasonable when you have a small set of special roles set up while developing your app. All this is just the beginning. Applications can enforce all sorts of complex access patterns through ACLs and class-level permissions. Pointer permissions are a special type of class-level permission that create a virtual ACL on every object in a class, based on users stored in pointer fields on those objects.

For a class with a sender and a reciever field, a read pointer permission on the receiver field and a read and write pointer permission on the sender field will make each object in the class readable by the user in the sender and receiver field, and writable only by the user in the sender field. Pointer permissions are like virtual ACLs.

In the above example with the sender and receiver , each object will act as if it has an ACL of:. Note that this ACL is not actually created on each object.

Any existing ACLs will not be modified when you add or remove pointer permissions, and any user attempting to interact with an object can only interact with the object if both the virtual ACL created by the pointer permissions, and the real ACL already on the object allow the interaction.

Starting version 2. They actually represent two separate layers of security that each request has to pass through to return the correct information or make the intended change.

These layers, one at the class level, and one at the object level, are shown below. A request must pass through BOTH layers of checks in order to be authorized. Note that despite acting similarly to ACLs, Pointer Permissions are a type of class level permission, so a request must pass the pointer permission check in order to pass the CLP check.

As you can see, whether a user is authorized to make a request can become complicated when you use both CLPs and ACLs. Say we have a Photo class, with an object, photoObject. There are 2 users in our app, user1 and user2. You may expect this will allow both user1 and user2 to Get photoObject , but because the CLP layer of authentication and the ACL layer are both in effect at all times, it actually makes it so neither user1 nor user2 can Get photoObject.

If user1 tries to Get photoObject , it will get through the CLP layer of authentication, but then will be rejected because it does not pass the ACL layer. In the same way, if user2 tries to Get photoObject , it will also be rejected at the CLP layer of authentication. Now lets look at example that uses Pointer Permissions.

Say we have a Post class, with an object, myPost. There are 2 users in our app, poster , and viewer. Lets say we add a pointer permission that gives anyone in the Creator field of the Post class read and write access to the object, and for the myPost object, poster is the user in that field. There is also an ACL on the object that gives read access to viewer. You may expect that this will allow poster to read and edit myPost , and viewer to read it, but viewer will be rejected by the Pointer Permission, and poster will be rejected by the ACL, so again, neither user will be able to access the object.

Often it can be useful to use CLPs only to disable all permissions for a certain request type, and then using Pointer Permissions or ACLs for other request types.

For example, you may want to disable Delete for a Photo class, but then put a Pointer Permission on Photo so the user who created it can edit it, just not delete it. Because of the especially complex way that Pointer Permissions and ACLs interact, we usually recommend only using one of those two types of security mechanisms. Login works just based on username and password, and cannot be disabled using CLPs. Read ACLs do not apply to the logged in user.

For example, if all users have ACLs with Read disabled, then doing a find query over users will still return the logged in user. However, if the Find CLP is disabled, then trying to perform a find on users will still return an error. Create CLPs also apply to signing up. So disabling Create CLPs on the user class also disables people from signing up without the master key. Users can only Update and Delete themselves.

For example, if you disable public Update for the user class, then users cannot edit themselves. But no matter what the write ACL on a user is, that user can still Update or Delete itself, and no other user can Update or Delete that user.

Get requests on installations follow ACLs normally. Find requests without master key is not allowed unless you supply the installationId as a constraint. Update requests on installations do adhere to the ACL defined on the installation, but Delete requests are master-key-only.

For more information about how installations work, check out the installations section of the REST guide. One particularly common use case for Cloud Code is preventing invalid data from being stored. To create validation functions, Cloud Code allows you to implement a beforeSave trigger for your class. These triggers are run whenever an object is saved, and allow you to modify the object or completely reject a save. For example, this is how you create a Cloud Code beforeSave trigger to make sure every user has an email address set:.

Validations can lock down your app so that only certain values are acceptable. You can also use afterSave validations to normalize your data e. You get to retain most of the productivity benefits of accessing Parse data directly from your client applications, but you can also enforce certain invariants for your data on the fly.

While validation often makes sense in Cloud Code, there are likely certain actions that are particularly sensitive, and should be as carefully guarded as possible. In these cases, you can remove permissions or the logic from clients entirely and instead funnel all such operations to Cloud Code functions.

You can do this by having the client call a Cloud Code function instead of modifying the Post itself:. The master key should be used carefully. One very common use case for Cloud Code is sending push notifications to particular users. Instead, you should write Cloud Code functions that validate the data to be pushed and sent before sending a push.

Parse provides a number of ways for you to secure data in your app. As you build your app and evaluate the kinds of data you will be storing, you can make the decision about which implementation to choose. It is worth repeating that that the Parse User object is readable by all other users by default. Most classes in your app will fall into one of a couple of easy-to-secure categories. For fully public data, you can use class-level permissions to lock down the table to put publicly readable and writeable by no one.

For fully private data, you can use ACLs to make sure that only the user who owns the data can read it. Together, we can make the web a safer place. As your app scales, you will want to ensure that it performs well under increased load and usage. Keep in mind that not all suggestions may apply to your app.

Parse objects are stored in a database. A Parse query retrieves objects that you are interested in based on conditions you apply to the query. To avoid looking through all the data present in a particular Parse class for every query, the database can use an index.

An index is a sorted list of items matching a given criteria. Indexes help because they allow the database to do an efficient search and return matching results without looking at all of the data. Indexes are typically smaller in size and available in memory, resulting in faster lookups. You are responsible for managing your database and maintaining indexes when using Parse Server. If your data is not indexed, every query will have to go through the the entire data for a class to return a query result.

On the other hand, if your data is indexed appropriately, the number of documents scanned to return a correct query result should be low. Creating an index query based on the score field would yield a smaller search space in general than creating one on the playerName field. When examining data types, booleans have a very low entropy and and do not make good indexes. Take the following query constraint:. The two possible values for "cheatMode" are true and false.

Writing efficient queries means taking full advantage of indexes. Now say you want to retrieve the scores for all players except a certain one. You could create this query:. The database has to look at all the objects in the "GameScore" class to satisfy the constraint and retrieve the results.

As the number of entries in the class grows, the query takes longer to run. Instead of querying for the absence of values, you ask for values which match the rest of the column values. Doing this allows the database to use an index and your queries will be faster.

Sometimes, you may have to completely rewrite your query. The new query you use depends on your use case. This may sometimes mean a redesign of your data model. This means rewriting your queries accordingly. Your query rewrites will depend on your schema set up. It may mean redoing that schema. Regular expression queries should be avoided due to performance considerations.

MongoDB is not efficient for doing partial string matching except for the special case where you only want a prefix match. Queries that have regular expression constraints are therefore very expensive, especially for classes with over , records. Consider restricting how many such operations can be run on a particular app at any given time.

But I wanna to request to make tutorials on basic components of Android also i. I did not find tutorials on these topics in Beginners section. I am still struggling to get some good tutorial and handson explaining these topics. Kindly consider that. Thanks for your suggestions. It will take sometime to publish these articles as other articles are in queue. You should not take this as a standard or secure coding practice. In production environment, you ideally need to avoid any code that will potentially inject vulnerabilities like MYSQL Injection.

MySQL injection itself is a huge topic and cannot be covered in this single post and that is not the agenda of this post either. This image is for thumbnail purpose. Ravi Tamada.

Notify of. Oldest Newest Most Voted. Inline Feedbacks. How did you get the URL? Reply to Ann. Abhinav Varshney. Amina chermiti. Reply to Amina chermiti. Sicnarf Omsare. Reply to Ravi Tamada. Reply to Sicnarf Omsare. Seems you have php errors. Ht the urls from postman to see the errors php error reporting. Doctype because the response in postman is this: the warning causes the response to throw an error,..

It say Deprecated mysql functions. Kishan Yadav. Reply to Kishan Yadav. Syed Adib. Pau Chittaro. Antigoni Karabillie. Reply to Pau Chittaro. I have the same problem. Did you find the solution? Reply to Antigoni Karabillie. Hello Antigoni, after some google searches i was able to make it work. Thanks again for well written article. Any Idea? Danish Bawany. Hi Mr. Ravi, Actually i wanted to learn database connectivity using php and mysql in android so tried the above code but i am getting errors in the following activities 1.

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About A community driven list of useful Scala libraries, frameworks and software. Topics awesome scala scalajs awesome-list scala-library. Releases No releases published. Packages 0 No packages published. You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. A scala library for connecting to a redis server, or a cluster of redis nodes using consistent hashing on the client side.

Scala Language Integrated Connection Kit. Slick is a modern database query and access library for Scala. Next generation user interface and application development in Scala and Scala. Scala compiler plugin that acts like GNU xgettext command to extract i18n strings in Scala source code files to Gettext. N-dimensional arrays in Scala 3. Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more. A Scala wrapper for Apache Crunch which provides a framework for writing, testing, and running MapReduce pipelines.

RxScala — Reactive Extensions for Scala — a library for composing asynchronous and event-based programs using observable sequences. A distributed tracing extension for Akka. Blindsight is a Scala logging API with DSL based structured logging, fluent logging, semantic logging, flow logging, and context aware logging. A type-safe, reflection-free, powerful enumeration implementation for Scala with exhaustive pattern match warnings and helpful integrations.

Lamma schedule generator for Scala is a professional schedule generation library for periodic schedules like fixed income coupon payment, equity deravitive fixing date generation etc.