An open source project by FPL.
Use in Java

Before you get started

Before diving into the FlatBuffers usage in Java, it should be noted that the Tutorial page has a complete guide to general FlatBuffers usage in all of the supported languages (including Java). This page is designed to cover the nuances of FlatBuffers usage, specific to Java.

You should also have read the Building documentation to build flatc and should be familiar with Using the schema compiler and Writing a schema.

FlatBuffers Java code location

The code for the FlatBuffers Java library can be found at flatbuffers/java/com/google/flatbuffers. You can browse the library on the FlatBuffers GitHub page.

Testing the FlatBuffers Java libraries

The code to test the libraries can be found at flatbuffers/tests.

The test code for Java is located in JavaTest.java.

To run the tests, use either JavaTest.sh or JavaTest.bat, depending on your operating system.

Note: These scripts require that Java is installed.

Using the FlatBuffers Java library

Note: See Tutorial for a more in-depth example of how to use FlatBuffers in Java.

FlatBuffers supports reading and writing binary FlatBuffers in Java.

To use FlatBuffers in your own code, first generate Java classes from your schema with the --java option to flatc. Then you can include both FlatBuffers and the generated code to read or write a FlatBuffer.

For example, here is how you would read a FlatBuffer binary file in Java: First, import the library and generated code. Then, you read a FlatBuffer binary file into a byte[]. You then turn the byte[] into a ByteBuffer, which you pass to the getRootAsMyRootType function:

import MyGame.Example.*;
import com.google.flatbuffers.FlatBufferBuilder;
// This snippet ignores exceptions for brevity.
File file = new File("monsterdata_test.mon");
RandomAccessFile f = new RandomAccessFile(file, "r");
byte[] data = new byte[(int)f.length()];
ByteBuffer bb = ByteBuffer.wrap(data);
Monster monster = Monster.getRootAsMonster(bb);

Now you can access the data from the Monster monster:

short hp = monster.hp();
Vec3 pos = monster.pos();

Storing dictionaries in a FlatBuffer

FlatBuffers doesn't support dictionaries natively, but there is support to emulate their behavior with vectors and binary search, which means you can have fast lookups directly from a FlatBuffer without having to unpack your data into a Dictionary or similar.

To use it:

  • Designate one of the fields in a table as the "key" field. You do this by setting the key attribute on this field, e.g. name:string (key). You may only have one key field, and it must be of string or scalar type.
  • Write out tables of this type as usual, collect their offsets in an array.
  • Instead of calling standard generated method, e.g.: Monster.createTestarrayoftablesVector, call createSortedVectorOfTables (from the FlatBufferBuilder object). which will first sort all offsets such that the tables they refer to are sorted by the key field, then serialize it.
  • Now when you're accessing the FlatBuffer, you can use the ByKey accessor to access elements of the vector, e.g.: monster.testarrayoftablesByKey("Frodo"). which returns an object of the corresponding table type, or null if not found. ByKey performs a binary search, so should have a similar speed to Dictionary, though may be faster because of better caching. ByKey only works if the vector has been sorted, it will likely not find elements if it hasn't been sorted.

Text parsing

There currently is no support for parsing text (Schema's and JSON) directly from Java, though you could use the C++ parser through native call interfaces available to each language. Please see the C++ documentation for more on text parsing.